IN DEGREE PROJECT ELECTRICAL ENGINEERING,SECOND CYCLE, 30 CREDITS

, STOCKHOLM SWEDEN 2016

Healthcare Transformation Based on ICTA Study on Open Platforms For Wearable Healthcare Systems

RACHAEN MAHFUZ HUQ

KTH ROYAL INSTITUTE OF TECHNOLOGYSCHOOL OF INFORMATION AND COMMUNICATION TECHNOLOGY

Healthcare Transformation Based on ICT

A Study on Open Platforms for Wearable Healthcare Systems

Author:

Rachaen Mahfuz Huq

Erasmus Mundus – Master of Research on Information and Communication Technologies (MERIT)

Supervisor:

Andres Laya Romero

Department of Communication Systems, KTH

Industrial Supervisor:

Dina Titkova

Biosync Technology AB, Stockholm, Sweden.

Examiner

Anders Västberg

Associate Professor, Department of Communication Systems, KTH

School of Information and Communication Technology

KTH Royal Institute of Technology

Stockholm, Sweden

2016

i

Abstract

Personalized digital healthcare and wellbeing with the use of wearable devices and

accompanying mobile apps is a recently evolved phenomenon. This technology architecture

has given birth to a number of actors who make a complex network and work together

closely to make things work. At the early stage of this industry, little work has been done

focusing on understanding these complex business relationships among the actors in the

wearable health ecosystem and also critically analyzing the current nature of the industry’s

growth. This thesis contributes in filling this gap. It breaks down the complexity of actors by

classifying them into distinguishable components according to their roles in the ecosystem,

and identifies their inter-relationships by developing a framework based on the “matters of

exchange” among them. The thesis also pinpoints some upcoming challenges in the industry

based on the observation made on the current nature of growth among the present actors.

Analyzing the cases of the present actors using the tools developed in this thesis, it is

concluded that the major challenge lies within the application development frontier of the

ecosystems, which is the gateway of innovation in this industry. We have observed that the

fragmented growth of ecosystems is individually benefiting the platforms, but not benefiting

the innovation in app development as a whole. It is concluded that collaboration among

actors in managing and utilizing health data generated from wearable devices, such as a

standardization has become essential to control the consequences of this fragmented growth

and to enabling a device independent app-innovation environment.

ii

Acknowledgement

I would like to thank my academic supervisor Andrés Laya Romero for his constant support

in improving my research skills, skills to organizing ideas in a systematic structure, and in

particular, for teaching me “how to write”. Without his constructive feedback, I could hardly

realize what it takes to say more with less words, and to properly explain when necessary.

I would also like to thank my external supervisor Dina Titkova, Business Development

Director at Biosync Technology AB, for all the support, information and inspiration I got from

her during the times at Biosync. With this I would also appreciate Björn de Jounge, CEO,

Biosync Technology AB for all the discussions we had related to topic of the thesis. It was a

great time of learning being involved with Biosync.

I am thankful to Anders Västberg, Associate Professor, Communication Systems Department

at KTH for accepting the role as my examiner for the thesis. I would also like to thank Jan

Markendahl, Associate Professor, Communication Systems Department at KTH for

stimulating a great interest for me in this field of research through the course “Wireless

Infrastructure Deployment and Economics” at KTH.

I would like to thank Mats Bengtsson, School of Electrical Engineering, KTH, and the

coordinator of my Master’s Program for the all the support , and answering to all my queries

throughout my time at KTH. I would also like to thank Marco Massaro, Program Coordinator

of Erasmus Mundus MERIT at Politecnico di Torino, Italy for all the logistic support at PoliTo.

I would like to thank the European Commission, and the Erasmus Mundus MERIT selection

committee for selecting me for the Erasmus Mundus Scholarship. It has been a life-changing

experience of studying at two of the very best schools in the world, PoliTo and KTH.

Rachaen M. Huq.

iii

Table of Contents

Abstract…………………………………………………………………………………………………………. i Acknowledgement………………………………………………………………………………………….. ii Table of Contents…………………………………………………………………………………………… iii List of Figures………………………………………………………………………………………………… v List of Tables………………………………………………………………………………………………….. vi List of Abbreviations ……………………………………………………………………………………… vii

1. Chapter 1 : Introduction ……………………..…………………………………………………………. 1 1.1 Background……………………..……………………………………………………………………. 1 1.2 Major Definitions……………………..……………………………………………………………. 2 1.3 Problem Area……………………..…………………………………………………………………. 4 1.4 Research Question……………………..………………………………………………………….. 6 1.5 Research Method……………………..……………………………………………………………. 6 1.6 Related Works……………………..……………………………………………………………….. 7 1.7 Research Gap and Outcome of the thesis……………………..…………………………. 8

1.8 Outline of the thesis……………………..……………………………………………………….. 9 2. Chapter 2: Theoretical Frameworks ...……………………………………………………………... 10 2.1 The Design Pattern Based Approach ……………………..………………………………. 11

3. Chapter 3: Methodology ……………………..………………………………………………………….. 14 3.1 Data Collection…………..…………………………………………………………………………. 14 3.2 Data Analysis………………..………………………………………………………………………. 16 4. Chapter 4: Analysis……………………………………………………………………………………….... 18

4.1 An overview of the players…………….……………………………………………………...... 18 4.2 Classifying the players in a “Layered Approach”………………………………………. 21 4.3 Identifying EMKIS and Design Patterns in the Wearable Market………………. 28 4.3.1 Among the Complete Solution Providers…..…………………………………. 28 The Case of Microsoft Band…………..…………………………………………….. 28 The Case of Empatica………………………………………………………………….. 31 4.3.2 Among the Device Manufacturers ………………………………………………. 33 The Case of Angel……………………………………………………………………….. 33 4.3.3 Among the Platform Providers……………………………………………………. 36

The Case of Oceanleap………………………………………………………………… 36 The Case of Samsung Simband & SAMI………………………………………… 38 4.3.4 Among the Application Developers …………………………………………….. 40

The Case of Runtastic…………………………………………………..……………… 41 4.3.5 Summary of the Identified Design Patterns………………………………….. 43

iv

4.4 Understanding the Challenges in the Current Scenario…………………………….. 45 4.4.1 Fragmentation, device dependency and absence of standards……… 45 4.4.2 Challenge in developing the business model design pattern………… 48 4.4.3 How the challenges are overcome when a standardization and

device independency is implemented…………………………………………..

50

5 Conclusions and Future Works……………………………………………………………………….. 52 5.1 Summary of Findings and Concluding Remarks……………………………………….. 52 5.2 Future Works …..……………………………………………………………………………………. 54 Bibliography………………….……………………………………………………………………………….. 55

List of Figures

Fig. 1 A conceptual overview of the wearable devices based e-health setting………. 4

Fig. 2 The research areas related to wearable healthcare and the research gap…… 7

Fig. 3 Multi-sided design pattern for e-health…………………………………………………….. 13

Fig. 4 Outline of the adopted methodology………………………………………………………… 17

Fig. 5 Flow of data and computational feedback for wearable health systems – a technical outline………………………………………………………………………………………

22

Fig. 6 Flow of data, software requests and responses in a cloud based wearable heath system……………………………………………………………………………………………

23

Fig. 7 Exchange of Money, Information, Knowledge and Service among the players in a typical wearable health ecosystem (the EMKIS Framework)……

25

Fig. 8 Major players mapped according to span of their businesses……………………. 27

Fig. 9 Exchange of money, information, knowledge, and service around Microsoft Health……………………………………………………………………………………………………..

30

Fig. 10 EMKIS model for the case of Empatica……………………………………………………… 33

Fig. 11 EMKIS for the case of Angel……………………………………………………………………… 35

Fig. 12 EMKIS model for Oceanleap……………………………………………………………………... 37

Fig. 13 EMKIS for the case of Samsung Simband and SAMI…………………………………… 39

Fig. 14 EMKIS model for Runtastic………………………………………………………………………. 42

Fig. 15 Illustrating the challenge of running a same application using the data from multiple cloud platforms…………………………………………………………………………..

47

Fig. 16 Razor & Blade and Inverter Razor & Blade approach for initial market entry for a newcomer wearable health app developer firm under the present scenario………………………………………………………………………………………

49

Fig. 17 Inverted Freemium – Razor & Blade – Dual design pattern for wearable health application developers’ business model………………………………………….

50

vi

List of Tables

Table 2.1 Design-Patterns for E-health Business Models…………………………................. 11

Table 4.1 Summary of Design Patterns found from the studies……………………………. 44

vii

List of Abbreviations

API Application Program Interface

App (Smartphone) Application

B2B Business-to-Business

CEO Chief Executive Officer

e-health Electronic Health

EMKIS Exchange of Money, Knowledge, Information and Service

FDA Food and Drug Administration

GPS Global Positioning System

GSR Galvanic Skin Response

H/W Hardware

HIS Health Information System

HR Heart Rate

IEEE Institute of Electrical and Electronics Engineers.

IoT Internet of Things

IS Information Systems

IT Information technology

m-health Mobile Health

MIT Massachusetts Institute of technology

OS Operating System

PaaS Platform as a Service

S/W Software

SaaS Software as a Service

SAMI Samsung Multimodal Architecture Interaction

SDK Software Development Kit

UI User Interface

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Chapter1:Introduction

1.1Background

Newtechnologiesandbusinessmodelconceptsareevolvingaroundpersonalizedhealthcareandwellbeingbasedonwearabledevicesat recent timeswith the riseof the InternetofThings(IoT),m‐healthande‐healthservices.Currentlywitharound700millionUSdollarindustry in the form of sports and activity trackers [1], wearable devices and theirapplicationsareoneofthemostdiscussedissuesovertheinternet[2].Itisestimatedin[3]thattheglobalwearable‐devicesmarketwillcontinuetogrowintermsofdevicesshippedannually,from33millionin2015to148millionattheendofthenext5years.

Thewearable devicesmarket became popularwith simple fitness bandswith three axisaccelerometers todetectbodymovements toprovide feedbackonphysicalexercisesanddailyactivities.FitbitClassicwasthefirstofthiskindwhichwasreleasedlate2008[4]andlaterJawboneUPandFitbitUltrawerereleasedinlate2011[5].Thedeviceswerepocket‐hold‐typetillearly2012whenthewearablesstartedtotaketheshapeofwristbandsandsmart‐watches with Nike Fuelband and Sony Smart‐watch (Figure‐The evolution ofwearablesin[5]).WiththereleaseofPebble,FitbitFlexandSamsungGalaxyGearoneaftertheother in2013,wearables forwellbeingandexercisesgotmuchmarketattentionandseveralnewerupdateswereaddedintheyear2014.Itwaslate2014andearly2015(tilltoday)thatwearabledevicesarebeingwidelydiscussedabouttheirpotentialinelectronicandmobilehealthcare.ThisstartedwiththereleaseofIntelBasis,Microsoftband,SamsungSimband,FitbitPurepulseandafewothernewcomerse.g.SeraphimSense(AngelSensor),EmpaticaEmbrace. 2014/15 is the yearwhen thesedevices are actually taking shape tobecomehealthcaredeviceswithsophisticatedmulti‐modalsensorswhichwillpotentiallyaddanewdimensiontothem‐healthande‐healthsectoringeneral.

Thereisahighlevelofconsumerinterestonwearabledevices,speciallysmart‐watchesandfitness wristbands [2]. Studying the recent literature on wearable m‐health, andconsequentlyobservingthemarketreleasesofanumberofwearablehealthcaredevicesanddataanalyticsinfrastructure,wehaveobservedthatthetrendoffitnesstrackinghasstartedto shift towards healthmonitoring deviceswith advanced bio‐sensors integratedwithinthem.Their increasedpopularity is transforming theway the futureofdigitalhealthhadbeenpicturedevenafewyearsback.Thishasmadethissocalled“nextbigthing”amajorfieldofinterestbothintheacademiaandtheindustry.

Thisthesisisfocusedonbreakingdownthecomplexityofthewearablehealthcareindustry’scomplex multi‐actor relationships using easily understandable frameworks. It pinpointssomecrucialchallengesthatneedtobeaddressedinordertoensureasustainablegrowthoftheindustryfromaninnovationmanagementperspective.

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1.2MajorDefinitions

Beforegoingintothespecificproblemareaofthisthesis,itisbeneficialtothereadertobeclarifiedaboutafewmajortermsandtheirdefinitionswhichwillbeusedthroughoutthisthesis, such aswearable devices, Internet‐of‐Things, e‐health,m‐health, cloud computingandcloudplatforms.

Wearable Devices: Wearable devices, also known as “wearables” refer to “electronictechnologiesorcomputersthatareincorporatedintoitemsofclothingandaccessorieswhichcancomfortablybewornonthebody”[6].Ingeneralterms,wearablescoverawiderangeofdevices and sensors including smart‐watches, smart‐glass, smart‐textiles, head‐bands,smart‐jewelry, hearing aids etc. In the digital health domain, the term mainly refers todevices such aswristbands,whichmeasure,with its sophisticated sensors, differentbio‐signalsandvitalsignsfromtheplaceitisattachedtothehumanbody.Typicallytheuserisfed backwith a processed statistical overview of activity, sleep, vital signs etc. via theirsmartphone or a web interface. The importance of wearable devices has been on thespotlight originating from the medical need to monitor patients from a distance for anextensiveamountoftime.Sincethen,notonlyresearchhasbeendoneonhowtomakethesedevices“medical‐quality”butalsocompanieshasinvestedindevelopingwearabledevicesforclinicalpurposes[7].

InternetofThings(IoT):[9]definedIoTas“aglobalnetworkandserviceinfrastructureofvariable density and connectivitywith self‐configuring capabilities based on standard andinteroperable protocols and formats [which] consists of heterogeneous things that haveidentities,physicalandvirtualattributes,andareseamlesslyandsecurelyintegratedintotheInternet”.Insimplewords,IoTreferstophenomenawherephysicalobjects,integratedwithsmartsensorsaregiventheconnectivitytoseamlesslysendandreceivedataobtainedfromthephysicalworldtoandfromtheinternettofacilitatevarioussmart‐livingconceptslikesmart‐homeandsmart‐citiesetc.

CloudComputing:Oxforddictionarydefines cloudcomputingas “thepracticeofusinganetworkofremoteservershostedontheInternettostore,manage,andprocessdata,ratherthanalocalserverorapersonalcomputer”[10].Insimpleterms,whenadeviceoutsourcesitscomputingtask(e.g.logicaloperations,signalprocessingetc.)totheinternet,keepingforitselfonlythetaskofsensing(datacollection)andinternetconnectivitythroughagateway,canbecalledcloudcomputing.

CloudPlatform:[11]definesCloudPlatformas“asystemwheresoftwareapplicationsmaybe run in an environment composed of utility cloud services in a logically abstractenvironment.”Cloudplatformisthemostintegralpartofcloudcomputingwhichfacilitatesthedevelopmentanddeploymentofsoftwareapplicationswherethedeveloperoutsourcesthecomplexityofowning,managing,maintainingandrisksofthehardwareandsoftwarelayers.

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E‐Health andm‐Health: According to [12], e‐Health (electronic health) refers to “thehealthcare practices assisted by communication systems and electronic processes. Variousformsofe‐Healthsystemsandservicesmayinclude:ElectronicHealthRecords(EHR),MobileHealth(m‐Health),HealthcareInformationSystems(HIS),telemedicine,andconsumerhealthinformatics”; andm‐Health (mobile health) refers to “thepractice of e‐Health assistedbysmartphones, which are used to capture, analyze, process, and transmit health‐basedinformationfromsensorsandotherbiomedicalsystems.”Therefore,m‐healthisessentiallyasubsetofe‐health.Sotheconceptofwearabletechnologybasedhealthcareismoreinclinedtom‐healthdomainrathere‐health.

Smart wearables send the health data to a secured storage via internet where they areprocessed.Theusersandthephysiciansarefedbackwith(orhaveon‐demandaccessto)theprocessedinformationinordertohavethestatisticaloverviewoftheuser’sactivityorvitalsigndata.SmartwearablehealthdeviceswillbeapartoftheenvisionedInternet‐of‐Thingsecosystemwhichiswhytheseconceptsarerelatedtoeachother.

Whenitcomestocloudcomputing,wearablehealthcaredevicesmostlyusecloudcomputingtofunction.Theytakethebio‐datafromthebody,sendthemtotheuser’ssmartphonesviaBluetooth, the smartphone sends the data to the “cloud” over the internetwhere all theprocessingtakesplace.Thentheprocessedinformationissentbacktophoneandalsoawebportalfortheusertohavethefeedback.

Thecloudplatformis typicallysignificant in thewearable technologydomain.This is thevirtualspacewheredeveloperscanaccessthedatageneratedbythedevicesanddevelopapplications for those devices. Cloud platform is often provided as a service by serviceproviders(Platform‐as‐a‐Service‐PaaS)wheretheproviderhasnoactiveinterestonwhatpurpose it is actually serving to the end user. In PaaS framework, the service providerprovideshardwareandsoftwaredevelopmenttoolse.g.API‐ApplicationProgramInterface,SDK –Software Development Kit to the developers as a service and uses its owninfrastructuretohandleallthesesoftware.Inthisway,theyfreethedevelopertothinkaboutowningandmanagingtheinfrastructureandenvironmentforapplicationdevelopment.

Inordertounderstandhowthewholesystemofthewearabledeviceswork,thediagramonFig.1canbeusedtogetageneraloverview.Thesensorsinthewearabledevicesrecordthebio‐signalsinitsowninternalbuffermemory.ThesedataaretransferredviaBluetoothtothe smartphone,which is used as the internet gateway. Sometimes the smartphonemayshowtherawdatainrealtimeinthephone’sscreen.However,thedataarethensyncedwiththeusersaccountinthecloudwhereitcanbeaccessedbyotherappsthattheuserwishestouse.Thesecloudbasedappsthentransfertheprocessedinformationinagraphicaluserinterfaceinthemobilescreenviatheapps,andalsoasadesktopwebappifaccessedthroughacomputer.Inane‐healthsetup,thesehealthdatacouldalsobeaccessedbythedesignatedphysicianwheres/hewillbeabletoseethedetailhistoricaldataeitherinrealtimeorasarecord.Theusergets theself‐feedback fromhisowndevicesandalsocanreceiveexpertfeedbackfromthephysician.

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Fig.1Aconceptualoverviewofwearabledevicesbasede‐healthsetting.

1.3ProblemArea

Wearablehealthcareisnotjusta“product”or“service”butmoreofanetworkofresourcesandsystemswhoworktogetherfromdataacquisitiontillservicedelivery.Thisisthereasonwhytherealreadyexistsacomplexecosystemofactorsinvolvedinthemarket.Wearabletechnology based future m‐health scenario is becoming even more complex as the keyplayersintheindustryaregrowinginascatteredwaybytryingtodeveloptheirownappdevelopmentplatformsaroundtheirhardware[13],whileeachofthemisatsimilarstagesinthemarket.Notonlythelargefirms,butalsostart‐upsarepartneringwiththirdpartiestomakeappsfortheirdevices.Thismakesthesituationharderforindependentthirdpartydeveloperstochoosethedevicetheywanttomakeapplicationsfor.Inanycase,theriskofreachingonlyasmallportionofthemarketprevailsamongthedevelopercommunity.

Thefuturewearablehealthcaremarketanditspotentialgrowtharenotverysimilartootherproductsormarkets(e.g.smartphones)becauseofthismulti‐actorsetupandtheextentofsoftware innovation required to make wearable devices really useful. Involvement ofmultiplebusinessentitiesisrequiredtodeliveralltheservicesthatanenduserrequires.Asingle company cannotpossiblyhave the resources toprovide its customerswith all thedifferentservicestheywishtogetoutoftheirwearables.

Thewearabletechnologymarketisagreen‐fieldcomparedtothesmartphonemarketandthemajorplayersintheindustryarestillstrugglingandcompetingtoaccumulatealarge

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user base by proposing their best offerings. What will happen in the wearable healthindustryinthenext5yearsisstillhardtopredict;however,unlikethesmartphonemarket,thewearablemarketisgettingmuchfragmentedwithalotofbigplayersdevelopingtheirownappdevelopmentenvironmentsaroundtheirdevices.[14]Currently,thelargerfirmsaredevelopingwearableswithappstosupportgeneralfitnessandwellbeing(e.g.stepcount,calorie,activity,sleepetc.offeredbybothIntelBasis[15]andMicrosoftband[16]),whilesome smaller firms are focusing on specific health problems (e.g. Epilepsy and seizuredetection for Empatica device [8]). The app development field based on the health datagatheredbythesedevicesbeingasubstantialgroundfor innovation,mostof thedevices’softwareplatformsareopenforthirdpartydevelopers.Butitisdifficultfordeveloperstochoosewhichdevices tomake applications for, sincenoparticular smart‐wrist‐bandhasstoodoutinthemarketsignificantlysofar.

Ononehand,adefragmentationoftheappmarketmightbehelpfulforappdevelopersandleading platformproviders. On the other hand, toomuchmarket concentrationwill alsobring its own challenges for the firms relying on income from the app (e.g. will createmonopolyoroligopoly).Itisnecessarytoadoptaframeworkthatwillbenefitallthepartiesintheecosystem,especiallythedevelopers,sothatsoftwareinnovationcanbefacilitated.Thekeyplayersarepossiblyfailingtorealizethattosustaininthemarketinthelongrun,the“application‐support”frontiershouldbekeptopen‐ended,possiblydevice‐independent,readyfordevelopment,andeasyaccessible.Thereasonis,thebio‐datapoolthatwearabledeviceswillgenerate,opensupnewpossibilities inappinnovationbythirdparties.Aftersome timeof using adevice, theusersmight not be satisfiedwith the “specific needs” ahealthcarewearableprovidesandmightwishtomaximizetheuseofthedevices/hebought.

Understandingthechallengesandshowingthewaytoanoptimalsolutionwouldrequiresystematicanalysisofthepresentscenarioandtherelationshipsofthesevariousactorswhoare involved. The industry has a set of heterogeneous business relationships. Hence,technological compatibility and interoperability among the players are needed fordeveloperstoinnovate,andtheuserstotakethefullpotentialoftheproductsbyusingtheapp‐services. In‐depth studies on thebusiness and InformationTechnologymodel of thewearablehealthcarecase,theirchallengesandpossiblewaysoftransformationhasnotbeendiscussedspecificallyinthisfieldbasedonrecentmarkethappenings.Properanalysisandmanagementofthistechnologycanleadtomaximizingthebenefitsthatuserscangetoutoftheir healthwearables. Analysis of business and Information Technologymodels in thisindustrycanleadustofindthekeychallengesandloopholesintheexistingscenario.

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1.4ResearchQuestion

Inthisthesis,wewillinvestigatethefollowingresearchquestion:

Howtosystematicallydescribethecomplexrelationshipsamongactorsofthewearablehealthecosystem,andwhatchallengesthiscomplexityhasbroughtinhealthcareapp‐innovation?

Theresearchquestioncanbeansweredbyillustratingthefollowingkeypoints:

Describingthetechnologicalorganismofinthecurrentset‐up. Classifyingthefirms,theirrolesintheecosystem,theirtechnicaldependenceoneach

other,andhowtheyinteract. Analyzingthebusinessmodelsoffirmsofdifferentlayersinthewearableecosystem

usingacommonframeworktounderstandtheirbusinessrelationships. Observingthewaytheactors,ecosystems,andbusinessrelationshipsaregrowing,

identifyingtheupcomingchallenges,andshowingthewaytowardsthesolution.

1.5ResearchMethod

Thefirststepwastoillustratethetechnologicalorganismofthewearablehealthecosystemsandunderstandhowdifferenttypesofactorsworktogetherinthewholeprocess,i.e.fromobtaining bio‐data from the users’ bodies till the feedback they get in theirsmartphones/web‐apps.Thisstepwasparticularlyimportanttoclassifytheactorsonthebasisofwhatrolestheyplayintheirownbusinessnetworks.

A“layeredapproach”wasdevelopedinthesecondstep,inordertoclassifytheactorsbasedontheirtechnicalroles.Thisapproachenablesmappinganyexistingornewcomerplayerinthemarketgivingaclearpictureofwhereitstandsintheecosystem.Itisimportanttonotethatthepurposeofthisthesisisnottomapalltheplayersintheindustry,buttounderstandthedifferent“types”ofthemintheindustrywhoplaytechnologicallysimilarroleoradoptsimilarbusinessmodels.Hence,inthecaseanalyses,firmswithsimilarbusinessmodelswillbe analyzed once and will not be repeated if another firm is adopting the exact sameapproach.

In thethirdstepwedevelopedanewframeworkthatenablesdescribingtherelationshipamongtheactorsinthemulti‐actordigitalbusinessofwearablehealth.Thismodelisbasedon“exchanges”amongtheactors.ThemodelisnamedtobetheEMKISModel,whereEMKISstandsforExchangeofMoney,Knowledge,InformationandService.Weevaluatedtheactorsofdifferentlayers(asclassifiedinthesecondstep)andtheiractivities,offersandservicesinthe EMKIS framework and defined their relationships clearly with other actors in theecosystembasedonthesefourcommonfactorsofexchange.Inparalleltoanalyzingcasesoftheactorsindifferentlayers,wehavealsousedthetheoreticalmodelofMettler&Eurich[17]tofindoutthe“designpatterns”oftheire‐healthbusinessmodelsandhaveexemplifiedhowthesefirmsaresimilaranddifferenttoeachotherintermsofbusinessmodels.

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Asfinalstep,inlightoftheanalysesdone,wepinpointedthecrucialfactorsthatwillariseasmajorchallengesinhealthcareapp‐innovationbasedonwearabledevices,consideringthewaytheactors,theirroles,relationships,ecosystemsandbusinessmodelsaregrowingatpresent.Weconcludedwithshowingawayhowthesechallengescanbeovercome.

1.6RelatedWorks

Existingresearchworksrelatedtowearabledevicesinelectronicandmobilehealthcarehasbeenmulti‐folded.One fold is related to the technologyandconnectivityarchitecture forwearabledevices,whichfallsundertheumbrellaofInternet‐of‐Thingsanditsapplicationsin healthcare. The other fold is related to the business models for IoT and healthcareapplications,whichfallsunderthecategoryofbusinessmodelrelatedresearchinabroadersense. This includesmodels for two ormultisidedmarkets and platformbased businessmodels which are related to the recent trends in wearable healthcare market. Fig. 2illustratestherelatedfieldsofresearchandthegapwhichisfocusedinthisthesis.

Fig.2Theresearchareasrelatedtowearablehealthcareandtheresearchgap

JosephWei,in[18]identifiesafewconsiderationsforthemanufacturersofwearablese.g.connectivity,cloud,securityandmanufacturingdesign.Thisarticleoverviewsthemarketscenario andmentions that to achieve the predicted growth in the industry,we need toexaminethe“underlyingtechnologies,usagesandbusinessmodels”.Healsoclaimsthatmostofthefuturedevelopmentworkforwearablesisonthesoftwareapplicationsideratherthan

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pushing the hardware sophistication.Wei’swork gives us themotivation to explore thebusinessmodels in the industry and also to focus on the coming challenges in softwareapplicationdevelopmentforwearabledevices.

Mazhelisetal.in[19]makesanattempttoillustratetheunderstandingofIoTdomainfromabusinessperspective,initiallybydefiningtheecosystemandrolesofthefirmsconstitutingit. The paper has listed the potential IoT firms’ roles explained with some real worldexampleslikethechipmanufacturingindustry.

Martsonetal.in[14]hasrecognizedAmazon,Apache,Google,IBM,SalesforceandMicrosoftaskeyplayersofthewearableindustrywhoarestrivingtobuildupanecosystemaroundtheir platforms. He also mentions, projecting this trend to the IoT domain, platformprovidersaredrivingthegrowthofthecloudcomputingmarket.Theseplatformproviderswilleventuallycreatemostoftheend‐valueintheIoTecosystem.

Leminenetal.in[20]identifiesandfocusesonacriticalresearchgapinstudyingbusinessmodelsinanIoTcontextandbuildsaframeworkforanalyzingdifferentIoTbusinessmodels.This is a comprehensive paper which broadly describes the theoretical foundations inbusiness model concepts. It classifies the current scholarly attempts to describe theemerging IoT business models as “Structural”, “Methodology” and “Design‐based”approaches. It also establishes a framework to analyze different IoT business modelsinspiredbytheOsterwalder’s[21]“Canvasthinking”.

Themostrelevantworkwhichcoversaportionofthefocusedresearchgapofthisthesis,isthearticlebyMettlerandEurichin[17]wheretheauthorsadoptedadesign‐patternbasedapproachforanalyzinge‐healthbusinessmodels.Thearticleclaimstoprovidethee‐healthmarketerswitha“setoftools”todevelopmoresustainablebusinessmodels.

Two more works provided some more relevant concepts which apply in the wearableindustries’businessmodels;oneisbyEisenmannetal.[22]andtheotherbySmedlundandFaghankhani[23].[22]Presentsthestrategiesfortwosidedmarketsandhowthebusinesslogicintwosidedmarketrevolvesaroundthe“broker”.Thisarticleisparticularlyhelpfultounderstandthelogicandbusinessmodelsadoptedbysomeleadingplayers(e.g.Microsoft,Intel)inthewearableindustryandtheirbehavior(SeeSection4.3.1)

[23]Talksabout“PlatformOrchestrationforEfficiency,DevelopmentandInnovation”wherethe authors highlight different key characteristics of platform based businesses andtwo/multisidedmarkets,andfactorsthatmakeaplatformbusinessasuccess.

1.7ResearchGapandOutcomeofthethesis

The notion of using wearable devices for wellbeing and distant healthcare, and openplatformsforhealthcareappinnovationisveryrecentandthemarketscenarioisrapidlychanging with quick technological updates. There had been academic works under the

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umbrellaof Internet‐of‐Things forhealthcareandwellbeing in general and in conceptualwaysbutthereisanecessitytoapplythetheoriesinthepracticalscenariostounderstandthemarketsituationbetterandtobeabletologicallyfindoutthecomingchallengesinapp‐innovation.

Thisthesisproposesaframeworktounderstandthecomplexityofbusinessrelationshipsinthewearablehealthdomain.Italsousesanexistinge‐healthbusinessmodelframeworktofind patterns among the business models adopted by the major players. It applies theoutcomesofboththeanalysestocomprehendtheinherentfacts,issuesandchallengesinthecurrentscenarioandguidestopossiblesolutions.

Attheendthisthesis,wewouldhavethefollowingoutcome:

Description of the technological organism of the current wearable healthcareecosystem,howitworks,whoareinvolved.

Alayeredclassificationoftheactorsintheecosystemandunderstandtheirroles. Aframeworktodescribetherelationshipamongtheactorsinanecosystem,what

dothey“give”totheotheractorsandwhatdothey“get”. Howthebusinessmodelsoftheseactorsaresimilarordifferenttotheotheractors

whoplaysimilarroles. Usingtheinsightscomingfromtheanalysis,wewouldpinpointthemajorissuesto

ariseintermsofinnovationinhealthcareappdevelopmentandwhatisnecessarytosolvethem.

1.8OutlineoftheThesis

InChapter2,thetheoreticalframeworksusedinthisthesisisdescribedindetails.

In Chapter 3, the methodological structure of this research is illustrated with elaboratedescriptions of data collection, data analysis, quality and reliability of the work andlimitations.

Chapter4isdedicatedtothemainanalysis.Itproposesthenewframework,andusesboththenewandtheexistingbusinessmodelframeworkdescribedinChapter2toidentifythechallengestoariseintermsofinnovationinappdevelopmentusingthedatageneratingfromwearabledevices.

Chapter5 closes thediscussionwith thesummaryof findingsandscopeandnecessityoffutureresearchinextensiontothiswork.

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Chapter2:TheoreticalFrameworks

“Businessmodel”isacommonlyusedtermtodefineawiderangeofactivitiesandbusinessrelationshipsinsideandoutsideafirm.Coinedasaterminthe90’s,researchonbusinessmodelshaveboomedsincethen.LiteratureonBusinessModelscommonlyexplaindifferentcharacteristics, identifiablemodels, analyzing factors, case studies and perspectives of abusiness entity or an industry. [24] Defines business models as “the process how theorganizationoperates inthemarketandwhatisthebasisofitsvaluecreation”.Twoofthemostpopularbusinessmodel frameworkswerebyOsterwalder’s “canvasapproach” [21]and Chesbrough and Rosembloom’s [25] six‐point approach (market segment, valueproposition,valuechain,costandprofit,valuenetwork,andcompetitivestrategy).

Due to thecomplexityof relationshipsamong firms in the IoTbusinesses, the traditionalbusinessmodelconceptswerefurtherpolished,refinedandmademoredetail‐orientedinthe literature related to IoT business models. In this respect, Leminen et al. in [20]constructed a framework derived from Osterwalder’s canvas thinking, for analyzingdifferentIoTbusinessmodels.However,thismodelismoresuitableformappingdifferentplayers under a formatted characteristic plot than understanding business inter‐relationshipsinanIoTecosystem.Moreover,theIoTbusinessmodel isalsoverygeneral,takingeveryinternetandsensorbasedbusinessunderitsshed.DifferentIoTbusinessesmayincorporatedifferent kindsof business relationships and the roles of actorsmay alsobedifferent.

Finding a suitable theoretical framework for business model analysis for wearablehealthcareindustrywaschallenging.Withclosestrelevancetoe‐healthbusinessmodels,thedesign‐patternbasedapproachforanalyzinge‐healthbusinessmodelsbyMettlerandEurich[17]servedasamajortheoreticalresourceforthiswork.Heaimedtoprovidea“setoftoolstoanalyzeandexplainthegenericlogicsbehindabusinessmodel”inthecontextofe‐healthserviceprovisions.Accordingto[26],“businesslogicisonewayoflookingatabusinesstogeta feel forwhat thebusiness is trying todoandhowit is trying todo it,asbusiness”.Businesslogicistobeseenfromastrategiclevelthanoperational.TheauthorsaddressedacriticalmixtureofbusinessmodelandInformationTechnology(IT)/InformationSystem(IS)todescribee‐healthbusinessmodels,whichisparticularlyusefulinanalyzingindustrieslike the one in our focus. Using this model, that inherent technological and businessinteractionsamongdifferentparticipatingbusinessentitiesbecomesclearinthecontextofan e‐health service ecosystem. The design pattern based approach is a classification ofvarious business logics incorporatedwith the e‐health services. This framework focusesmoreonhowservicesaredeliveredandhowe‐healthservicesarelogicallyputtowork.Thismodelhoweveractedasaguidelinetobuildtheframeworkofanalysisforthisthesisbecauseit describes a few businessmodel design patternswhich can be closely related to somecommonapproachesofwearablehealthindustryactors.

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2.1The“Design‐Pattern”–basedapproach

MettlerandEurichin[17]classifiedthefollowingbusinessmodeldesignpatternsapplicablein the e‐health businesses. According to them, the business model design patterns are“formalmeansofdocumentinggenericlogicsbehindabusinessmodelinaparticularcontextorproblemsituation.”Descriptionandexamplesareasfollows:(derivedfrom[17]–Table‐I,moreexamplesadded,quoteddescriptionsobtainedfromthereference)

PatternName

ShortDescription Example

“Freemium” “Basic services are offered for free, while apremiumischargedforanadvancedservice”

Skype

“Multi‐sided” “The value creation is based on the interactionamongparties”.Whenonepartyhasasignificantinteresttogivesubsidizedoreasierserviceaccesstoanotherparty.

FacebookDevelopers

“Crowd‐sourcing/Open”

“Commitment of motivated individuals producevaluefortheorganizationforfree”,orinexchangeofknowledgeorinformation.

Wikipedia,tripadvisor

“InvertedFreemium”

“Customerspayapremiumfeeforbeingentitledtoconsumefreeservices”

Insurance

“Razor andBlades”

Acquisition of primary product or servicegeneratesalock‐ineffectforcomplementarygoods

Printers and InkCartridge

“Inverted RazorandBlades”

“Complementary goods attract the customer andmakeherbuythecoreproduct”

Apple iPhone andApps

“Asaservice” “Only theusageof service is chargedbutnot theproductitself”

Rolls Royce’s“Power by thehour”.Airbnb

Table:2.1Design‐PatternsforE‐healthBusinessModels(derivedfrom[17])

Thedesignpatternsdescribedinthispaperareexplainedinthecontextofe‐heathingeneral.However, fewofthesesevendesign‐patternsfore‐healthbusinessmodelareparticularlyrelevantforthecasesofwearablehealthcaresystems,whichareshortlybriefedbelowwithrelevant examples from this particular market of interest. This relevance makes thisframeworkinterestingforustousethemodelinanalyzingwearablehealthbusinessmodels.Abriefdescriptionofthe“relevance”ofthismodelinthewearabledomainisexplainedasfollows:

1)E‐healthasmultisidedmarket:Thisdesignpatterncanberelatedtotherecenthappeningsin the wearable market. Smart‐watch manufacturers of recent times often partner with

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health andwellbeing application developer companies for complimentary apps for theirdevices.Forexample, Intel recentlyannouncedpartnershipwith “SMSAudio” todevelop“BioSport biometric ear buds” tomonitor heart rate continuously and synchronizewith“Runkeeper”apptotrackburntcalories,distancecoveredetc.[27].

2)Crowd‐sourcing/Open:Althoughdescribedinagenericwayintheliterature,thisdesignpatternrelatestothemostpopularapproachamongagroupoffirmsinthewearablehealthindustry.Thereasonis‐theindustryrequiressoftwareinnovationwithrespecttothebio‐datathatthewearabledevicesgenerate.ThispatternistracedinthewearabledomainasmostofthedevicemanufacturersarekeepingtheapplicationdevelopmentsideopentothirdpartyappdevelopersbygivingthemtheaccesstotheanonymousdatapoolthroughtheirAPIs.Theideaistopromoteinnovationindigitalhealthtofindnewalgorithmsinwhichthebiodatacanbeturnedintomeaningfulinsightsaboutthebody.

3) As a service: Platform‐as‐a‐Service (PaaS) has recently emerged as a new scope forbusiness, not only in wearable health sector, but IoT based businesses in general. Forexample,Salesforceintroducedtheir“Salesforce1”platformforanumberoflatestwearabledevices(e.g.Applewatch,AndroidWearetc.)wherethecompanychargesthedevelopersinreturn of sample codes for easier cross‐device development [28]. A leading Nordictelecommunications company “Telenor” introducedTelenorConnexion cloudplatform toenablenewIoTbasedcompanieslaunchtheirbusinessesfasterwithaB2Bpartnershipwiththem.“Oceanleap”,astartup,providescloudservicestowearabledevicemanufacturersonausage‐basedpricingpolicy.(SeeSection4.3.3).

Most of thewearablehealth industry frontrunners likeMicrosoft band, are adopting thesameapproach,whichisamixtureof“multi‐sided”and“open”approach.Here,dedicatedapp developers provide the default applications for their devices, and third parties candevelopapplicationsbyaccessinghistoricalandreal‐timedatageneratedbytheuserswhicharestoredinthecloudplatforms.ThesecompaniesprovideopensourceanddownloadableSDKsandfreeAPIstoanydeveloperwhowanttomakeappsfortheirdevices.

Themulti‐sideddeignpattern isparticularlyrelevantamong theplayers in thewearablehealthindustry,becausesomefundamentalfeaturesofthismatchwiththepresentmarkethappenings. This pattern clearly illustrates how the health‐service provider and healthservice consumer is connected with the “broker” or “information portal” in an e‐healthsetting.(SeeSection4.3.1,thecaseofMicrosoft)

MettlerandEurichprovidein[17],ablueprintofthisdesign‐patternasdepictedinfig.4.

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Fig.3Multi‐SidedDesignPatternfore‐health(Obtainedfrom[17]).

FromFig.3wecanseehowMettlerandEurichcreatedasampleframeworkillustratingthegenericelementsoftransferamongthepartiesinamulti‐sidede‐healthsetup.Forexample,serviceandservicedevelopmenttools,moneyandconsumerinfoareexchangedbetweenthe service provider and the broker. On the other hand,money and consumer info, andserviceisexchangedbetweentheconsumerandthebroker.

Theyalsostatethat“themainactorinthisscenarioisabrokersuchasahealthinformationportal”.Theyindicatethatthekeymarketsegmentsinthispatternscenarioarethehealthservice providers like the hospitals or doctors, and health service consumers (patients,wearable health device users) and the major value objects are the information aboutconsumers,primarye‐healthservicesetc.

Akeycharacteristicofthemulti‐sidedmarketine‐health,asdescribedin[17](page82ofthereference)isasfollows:

“Thebusinesslogic iscenteredaroundthebroker,onceadedicatedquantityofloyalserviceconsumersisreached,otherserviceprovidersmightgetattractedbythelargecustomerbaseandmaybewillingtooffertheirservicesviathebroker.”

Particularrelevanceofthemulti‐sideddesignpatterninthecurrentwearableindustrywillbefurtherexploredinChapter4.

 

 

 

 

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Chapter3:Methodology

This thesiswork isexploratory innatureand investigates thebusinessrelationships inacomplex network of actors. In order to draw conclusions, the current scenariomust beanalyzedfirst,andthenthemotivesbehindtheactors'businesslogicsmustbeexploredtofindout the challenges, andpropose thepossible solutions.Hence, the research involvesunderstandingofthecurrentsituationintheindustry,analyzethemusingtheoreticaltools,developingframeworksspecifictothecontextofthisindustry,andconcludewithproposingwaystoovercomethechallenges.Therefore,theresearchismore“qualitative”innaturethan“quantitative”.

Anne Hakansson’s research methodology guideline in [29] was used while forming themethodologyofthisresearchwork.Accordingto[29],

“TheQualitativeResearchmethodconcernsunderstandingmeaning,opinionsandbehaviorstoreachtentativehypothesisandtheoriesordevelopcomputersystems,artifactsandinventions.Themethod commonly uses smaller data sets that are sufficient enough to reach reliableresults,wherethedatacollectioncontinuesuntilsaturationisreached.”

Inthisresearch,weconsideredderivingthedesignpatternsinthebusinessmodelsofthefirms under consideration within the industry of focus. We studied the existing designpatterns and business models and found out the key challenges to arise in the presentsystem.Aframeworkwasalsodevelopedwhichhelpsunderstandingthesituationbetter.Data collection fromvarious sources continued untilwe could clearly identify themajorissuesintheindustrythoseneedattention.Thesaturationindatacollectionwasidentifiedwhensufficientnumberoffirmswerestudiedwhoindividuallyrepresentdifferentdesignpatterns,andacleartrendinthemarketcouldbeseen.Basedonthetrends,thesolutionframeworkwasbuilt.

3.1DataCollection:

Thescopeofthisstudyisrelativelynewandtheavailableacademicliteratureinthisareastilldonotcoversufficientstudiesandanalysisoftherecentmarketscenario.Hence,themajority of the data are collected from secondary sources, e.g. recently publishedwhitepapers related towearable technologymarket research, officialwebsites of the industryplayers, newspapers and periodicals, popular technology blogs, online magazines andproduct and service reviews.Quality and reliabilityof the secondary sourcesweregivenproperattentionwhilecollectingthedataforanalysis. Informationfromofficialwebsites,reliablemarketresearchese.g.pwcandwell‐knownmagazines(BusinessInsider,Forbes)were mainly used. Detail information about recent product offerings also came fromrecorded talks from different conferences and product launch talks; e.g. developers’

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conferenceofSamsungSimbandretrievedfromtheirofficialYouTubechannel.Overall,theworkinvolvedrelevantdatacollectionfromascatteredpoolofinformationfromdifferentonlinesourcesandwereorganizedtoproducemeaningfulresults.

Theworkalsoinvolvesanextensiveliteraturestudyspanningoverawiderangeoffields,whichemergedondifferentdomainofstudies,buthelpedbuildthefoundationofthiswork.Literatureinthefieldofbusinessmodels,multi‐sidedmarkets,openinnovation,InternetofThings(IoT),e‐healthandm‐health,etc.werestudiedtobuildupsuitableframeworkstoanalyzethetopicofinterestinthisthesis.

Theprimarydatausedinthisresearchcamefromtwointerviewsandtwoconferences.Theinterviewsweresemi‐structuredandacommonframeworkofthemeswereexplored.TheframeworkwasdesignedbasedonChesbroughandRosenbloom’s[25]sixbuildingblocksofabusinessmodelandtheintervieweeswereaskedopenendedquestionsabouteachofthebuilding blocks in relation to their companies. The questions were themed on – valuepropositionof the company, competitive strategy,market segment, value chain, cost andprofit structure, and position of the firm in the value network. Questions for both theinterviews followed thesamesetof themes,however, theyslightlydifferedbasedon theknowncontextualbackgroundofeachcompany.

According to [30] , “Semi‐structured interviewsallow informants the freedomtoexpresstheirviewsintheirownterms”,andtheycanalso“providereliable,comparablequalitativedata”.Thesemi‐structurednatureoftheinterviewsallowedtheinterviewertoaskfurtherexplanationwhenevernecessary,basedontheanswerstothestructuredquestionsasked.

Listoftheintervieweesandtheconferences/meet‐upsarelistedbelow:

Interviewee1:Mr.EugeneJorov,Co‐founderofSeraphimSense(Angelsensor),anewcomercompany providing hardware and app‐development platform for health and fitness. ThecompanyisbasedinIsrael.Hewasinterviewedovervideoconferenceinordertounderstandthe business logics behind their product and to understand how a newcomer companydesigns its businessmodel to enter themarket, where other big companies are alreadycompetingwitheachother.Theideawasalsotounderstandhowtheyplantotacklethelevelofcompetitionwiththeirofferings.

Interviewee 2: Mr. Fredrik Östbye, Vice President ‐Business Development at TelenorConnexion (in Sweden), a Telenorwing providing new IoT based companieswith cloudservicesinordertofacilitatefasterlaunchoftheirbusinesses.Thisinterviewgaveusanideaaboutseeingthebusinessandmarketscenariofromtheperspectiveofaplatformprovider,whoempowerIoTfirmsbyprovidingtheirPlatformasaService.Theinterviewwassemi‐structuredinnature.

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This thesiswasdeveloped insideBiosyncTechnologyAB, a technology spin‐off companyfromSwedishInstituteofComputerScience(SICS).ThecompanyisbasedinSwedenandfocusesonapplicationdevelopmentforstressmeasurement,visualizationofbio‐feedback,andgeneralwellbeingtobeusedwithwearabledevices.Hence,insightsweregatheredfromDina Titkova, Business Development Director, and Björn de Jounge, CEO at BiosyncTechnologyAB

Apartfromtheinterviews,the“Quantified‐Self(QS)Stockholm ‐CauseandEffectMeet‐up”[31] was attended. The meet‐up was held in Stockholm on March 2, 2015 where QSvisionaries, enthusiasts, and a few start‐ups shared their company profiles and personalexperienceswithhealth‐trackingdevices.Themeet‐upgaveageneralimpressiononhowdigitalhealthenthusiastsperceive the integrationofwearable technologies in theirdailylives.

Anothereventwasattendednamed“InternetofEverything(IOE)ForReal–2015”heldon17June2015inStockholm[32].Inthisevent,personnelfromleadingtechnologycompaniesandpromisingstart‐upssharedtheirvision,ideasandchallengesintheIoTdomainandhowtheyareapproachingthemarket.SpeakersintheeventincludedRamiAvidan,CommercialDirector(M2M)atTele2,DarenMowry,HeadofAmazonWebServicesNordicsandBalticsThe event also included a panel discussionon IoTwherepersonnel from severalmobileoperatorsinEurope(Telefonica,Mobistar,Tele2,BT,andKPN)participated.

3.2DataAnalysis:

Thecollectedqualitativedatawereanalyzedaccording to the theoreticalbusinessmodelframeworks of Mettler and Eurich (Design Pattern approach) and the EMKIS modeldevelopedduringthethesiswork.

The EMKIS framework was developed particularly in the context of wearable devicesmarket.Themodelvisualizesthecomplexnatureof“exchange”relationshipsamongactorsinanecosysteminthecurrenttechnologicalsetupoftheindustry.A“LayeredApproach”wasdevelopedtoclassifytheplayersinthebusinesslandscapebasedontheirtechnologicalrolesin theecosystem, theirofferingsandspanacrossplayers.Thedatacollected fromawiderangeofsourcesweresystematicallyorganized inthese two frameworks(designpatternandEMKIS)tounderstandtheoverallscenarioclearlyandconcisely.

Thetheoreticalmodelswereappliedtostudythecasesofdifferentfirmsindifferentlayersasclassifiedinthelayeredapproach

TheadoptedmethodologyforthisstudyisillustratedinFig.4:

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Fig.4:Outlineoftheadoptedmethodology

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Chapter4:Analysis

4.1Anoverviewoftheplayers

Thefollowingcompanieswillbementionedinthecomingsectionsasrelevantexamplesandcasestudies.Shortdescriptionsaboutthesecompaniesareprovidedbelow:

MicrosoftBand[33]

MicrosoftBandisasmart‐bandwithsmart‐watchfeaturesandfitnessandhealthtrackingcapabilities.It isdevelopedbyMicrosoftandwasreleasedon30October2014.ThebandintegrateswithWindowsPhone,AndroidandiOSthroughaBluetoothconnection.Thebandhas optical heart rate monitor, three‐axis accelerometer, gyro‐meter, GPS, ambient lightsensor, Galvanic Skin Response–GSR (Skin conductivity), UV sensor, Skin temperaturesensorandcapacitivesensor.“MicrosoftBand,thefirstdevicepoweredbyMicrosoftHealth,helpsyouachieveyourwellnessgoalsbytrackingyourheartrate,steps,calorieburn,andsleepquality”–asdescribedinitsofficialwebsite[16].MicrosoftbandhasMicrosoftHealthcloudplatform in the backendwhich collects data from the band and also from other partnerdevices, andprovides theuserswith “actionable insights” about theirhealth through thesmartphoneinterface.ThebuiltinappinMicrosoftHealththatcomeswiththebandincludestrackingheartrate,steps,calorieburnt,andsleepquality.

IntelBasis[34]

BasisPeakwasastartupfirmmakingwearablehealthdevicesforfitnessandsleeptracking.ThecompanywaslaterboughtbyIntel.Basisisasmart‐watchtypedevicewithfitnessandhealthtrackingcapabilities.Thedevicehasopticalheartratesensor,3‐axisaccelerometer,Skin temperature sensor andGalvanic skin response sensor.On the softwareapplicationside,BasisoffersadvancedanddetailsleeptrackingfeaturesdevelopedinpartnershipwithafewleadingacademicinstitutionsinSanFrancisco[15].

AppleWatch[35]

AppleWatch is the smart‐watch fromApple Incwhich incorporates fitness tracking andhealth‐tracking capabilities. It has heart rate sensor, a 3 axis accelerometer, GPS and itintegrateswithiOSandotherAppleproductsandservices,withAppleHealthplatforminthebackend.

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SamsungSimband[36]

Samsung’sSimband isnotanend‐userproduct, ratheran“openhardware‐opensoftware‐open‐mechanical” platform for digital health entrepreneurs and researchers to use, withSAMI(SamsungArchitectureforMultimodalInteraction)platformsupportingthebackendcloud.ThesensorsintheSimbandincludePPG(photo‐plethysmogram),heartrate(ECG),bio‐impedance,GalvanicSkinResponse,andskintemperature.

Empatica[37]

EmpaticaissmallscalecompanybasedinMilanandCambridge(USA)withonly19teammembersandanumberofacademicpartnerships.Their“Embrace”watchis“designedtosave lives” and targeted towards people living with epilepsy and the device detectsconvulsive seizure in epilepsy. Their latest Empatica E4 wristband targets mainlyresearchersbyensuring“clinicalqualityobservation”andreliablephysiologicaldata.Thedataareaccessiblefromtheirownsecurecloudplatformandtheplatformletsusersbuildtheirownappsbasedonthedatafromtheband.

Polar[38]

Foundedin1977inFinland,polarisoriginallyaheartratemonitoringequipmentandsportstraining computer manufacturer firm. Currently the company offers a wide range ofwearablewristbandsforfitnesstrackingusingheartratesensorsandaccelerometers.PolardevicesareattachedtoGoogleFitandApplehealthplatformstoenabledevelopersbuildapps based on Polar’s data. Polar also has their proprietary API “Polar Access Link” forinsurancecompanies,wellnessinstitutesandapplicationdeveloperswithmorespecificdataneeds.

Angel[39]

AngelisdesignedbySeraphimSenseLtd.,astartupbasedinIsrael.It isawristbandtypewearabletargetedtowardsdigitalhealthenterprisesandresearchers.Thewristbandhousesheartratesensor,activitysensorsandtemperaturesensor.AngelclaimstoallowitsusersuseanyapplicationoftheirchoicetoanalyzeandvisualizethedatacollectedbyAngel.Angelpromotes innovation by inviting enterprises, developers and researchers to take theadvantageoftheiropensourceSDK.

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FitbitandJawbone[40],[41]

FitbitandJawbonetwocompaniesbasedinSanFrancisco,California.Boththefirmsgainedpopularityaswearablefitnesstrackersintheearlywearablemarket.Bothofthemproducedsimple wristbands with accelerometers, however their latest models (Fitbit Surge andJawboneUP3) includes heart rate sensors and corresponding app‐features based on theheartratedata.

Salesforce[42]

Salesforce.comisacloudcomputingcompanybasedinSanFrancisco,California.Theirmajorbusiness focus isonCustomerRelationshipManagement (CRM)products;however,withtheir release of “Salesforce Wear” in mid‐2014 [37] they entered the wearable marketecosystem.Salesforcewearisanapplicationdevelopmentplatformforsixmajorwearabledevicesofthattime(Pebble,SamsungGear,GoogleGlass,AndroidWear,MYOandNYMI).This created a “meeting‐place” where developers can create apps for these popularwearables.

TelenorConnexion[43]

TelenorConnexionisacloudandconnectivityservicewingorTelenor(ANorwegianmobileoperator) and is based in Sweden. The company offers cloud services to growing IoTenterprisesandenablethemlaunchfasterbyprovidingconnectivitysolutions(software)andapplicationdevelopmentplatform.

Oceanleap[44]

Oceanleapoffersacloudbasedapplicationdevelopmentplatformspecificallyforwearablesinhealthcareandfitness.“Oceanleapplatformisdesignedtobehighlyflexibletosupportallkindsofwearabledeviceuse casesandapplications.Theplatformenableswearabledevicemakers and app builders to bring their products tomarket quickly and inexpensively. Allplatform functions are provided to developers and Oceanleap handles all the underlyingplumbingandbackendinfrastructure”,asdescribedintheirofficialwebsite.

GoogleFitandAppleHealth[45],[46]

GoogleFitisahealthandfitnesstrackingcloudplatformfromGooglefortheAndroidOS.Itblendsdatafrommultipleappsanddevices.GoogleFitusessmartphonesensorsandsensorsoftheactivitytrackerstodetectandrecordfitnessactivities(walking,running,cycling),andgives theuseranoverviewwith respect tohis set goals.Nike,HTC,LG,Motorola,Noom,

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Runtastic,RunKeeperandPolarareconfirmedpartnersofGoogleFitsofar.Therearealsoanumber of apps those will be usable with Google Fit, e.g. Runkeeper, Runtastic,Mapmyfitness.

Apple Health is the counterpart platform of Google Fit, developed by Apple for iOSsmartphones. Apple health is an application platformwhich collects data fromwearabledevicesandsmartphonesensorsanditdisplaysadashboardofallthefitnessandhealthdataoftheuser,includingtheheartrate,caloriesburned,bloodpressure,bloodsugar,etc.ThereisanumberofpopularwearabletrackerscompatiblewithAppleHealthincludingFitbitandJawbone,andalistofpopularappse.g.Runtastic,Runkeeper,Myfitnesspal.

MyFitnessPal,RuntasticandRunkeeper[47],[48],[49]

Runkeeper, launched in 2008, is a GPS based fitness‐tracking app for iOS and Android.RunKeeperallowsuserstotrackfitnessactivitiese.g.walking,runningandcyclingusingGPSdata.

MyFitnessPal is also a smartphone app running on iOS and Android, and also on awebinterface. It tracks diet, exercise, activities and determine suitable nutrients and calorieintakewithrespecttotheusers'setgoals.

Runtastic is amobile fitness application companybased inAustria. Runtastic develops anumberofactivitytrackerapps,hardwareproducts(RuntasticMomentfitnesstracker),andservicese.g.onlinetrainingplans,detaileddataanalysis.

4.2ClassifyingthePlayersina“LayeredApproach”

Wehave classified theplayers in thewearable health ecosystem into threemajor layersaccordingtothetechnologicalactivitiestheyperform.

1)HardwareorDeviceLayer:Thefirmsthatsellthehardware.

2)CloudPlatformorInfrastructureLayer:FirmsthatprovidecloudcomputingsupporttotheDeviceLayerfirms.

3) Software or Application Layer: The firms whomake applications on the platforms togeneraterevenuesfromthoseapps.

Thislayeredapproachinclassifyingthefirmsismotivatedfromthewaydifferentpiecesoftheecosystemaroundwearablehealthacttogether.Toillustrate,atypicalscenariocanbeassumedforasimplifiedunderstanding.Awearabledevicesendsitssensordatatothecloudthroughagateway(smartphone),andthedevelopersaccessthedataandcreatecloudbasedapplication services for the device using the cloud service’s API (Application ProgramInterface)andSDK(SoftwareDevelopmentKit).Thecomputationaltasksareperformedin

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the cloud and the results are sent back the smartphone’s user interface and thecorrespondingwebportal.AconceptualdiagramisshowninFig.5,wheretheflowofinputdata fromdeviceto thecloudandthe feedback fromthecloudafter thecomputationareshown.TheAPIismarkedasanedgewherethirdpartiescaninteractwiththedata.

ThetechnicalsynopsisoftheorganismasillustratedinFig.5usestheoverviewofawearablehealthtechnologysetupandhelpsexplainthebusinessactivitiesandpositionofafirm.Thissynopsis,combinedwiththelayeredclassificationofplayers,servetodevelopaframeworkwhichwoulddescribetheecosystemaroundwearablehealth.

ThefollowingcolorcodesareusedinFig.5.

BLUE:theflowofinputdatafromdevicetothecloud.

GREEN:thefeedbackfromthecloudafterthecomputation.

Fig.5.Flowofdataandcomputationalfeedbackforwearablehealthsystems–atechnicaloutline

ThetechnicaloutlinecanbefurtherillustratedasinFig.6.ItistobenotedthatanAPIisnothingbuta“key”thatallowsanapplicationtoaccessandusethedatathatisstoredinthehealth‐informationcloud. InFig.6,wecansee thatwhenaclientstartsanapplication, itsendstheapplicationserverarequest(whetheritismobileorwebbased).Iftheparticulartaskrequiresthehealthinformationwhichisstoredinthededicatedcloud,theappusestheAPIasa“key”bysendingtheAPIrequest.Afterauthentication,theapplicationservercanaccessthedata,furtherprocessintheapplicationserver,andthenfeedsbacktotheuserathis smartphone or web interface. An “open platform” necessarilymeans that the API isroyaltyfree,anddeveloperscanaccessthedatawithoutanycostattachedtoitfortheapp

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developer’s side.We have found out studying the cases of popular firmswith an “openplatform”approach,e.g. fromtheirdeveloperagreements (Seesection4.3.1–Microsoft),thatanopenplatformdoesnotmeanthat“storing”thedatafromthedevicemanufacturer’ssideisfree,justtheaccesstothatdata,touseittobuildapps,isfree.Fig.6distinguishestheflowofdatafromwearabledevicetothecloudthroughthesmartphone;theflowofsoftwarerequests(applicationrequest,APIrequests),andfeedbackinformationtotheuserthroughamobileorwebportal.

ThefollowingcolorcodesareusesinFig.6

Blue–Flowofgenerateddata

Red–Flowofsoftwarerequests

Green–Responsesfromthecloud

Fig.6.Flowofdata,softwarerequestsandresponsesinacloudbasedwearablehealthsystem.

Threemajortypes(layers)ofplayersoftheecosystemcanbeidentifieddependingonwhattechnologicalrolestheyplay.Thedevicelayerconsistsofplayerswhichmanufactureandsellthewearabledevices,integratingnecessarysensorsforhealthandfitnesstracking,e.g.IntelBasis,MicrosoftBand,NikeFuelBand,Empatica,AngelSensor,Pebble,Apple,andPolar.

Theinfrastructurelayerconsistsoftheplayersprovidingcloudplatformservices(PlatformasaService)tostorethedatageneratedfromthedevices,andgivesthedevelopersaccesstothose data for developing applications. These companies provide the necessary SDK

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(SoftwareDevelopmentKit)tothedevelopersforfree(open)orwithfinancialagreement(Closed).Wehavefoundoutthatthereexistsatrendamongcompaniestobeonly intheinfrastructurelayerandprovideplatformandconnectivityservicesonly(e.g.Salesforce,IBMCloud,TelenorConnexion.).Itisalsoseenthatinsomecasesthedevicelayerplayersownand provide in‐house cloud services. The PaaS concept inwearable IoT industry targetsnewcomer companies in thedevice layer to facilitate their quick launching and reducinginfrastructuralcostsrelatedtocloud.

Theapplication layerconsistsofappdevelopmentcompaniesandindividualswhocreateappsforaspecificdeviceorplatform.Therehadbeenanumberofplayersofthiskindinthesmartphoneplatformsevenbeforethewearableboom(Runtastic,Runkeeper)whofocusedonfitnessappsbasedonthesmartphones’accelerometerdata.However,withtheincreasedadoptionoffitnesswearables(Fitbit,Jawbone),theappswerefurthermadecompatibletoworkwiththesensorsofthosewearables.Withtheincreasedadoptionofmoresophisticateddevices (Microsoft band, Intel Basis), the scope of application development found a newfrontierofbusinessinthemobilehealthcaresector.Atpresent,thereisscopeforhealthcareapplicationdevelopmentbasedonthesedeviceswhichhaveembeddedsophisticatedmulti‐modalbio‐sensors.

InlightofthetechnologicaloutlineofthewearablehealthsystemasillustratedinFig.5andFig.6,wepropose a simplified framework for analyzing thebusiness relationships in thewearablemarket.Thisframeworkisbasedonthefollowingkeystones:

1)Theframeworkclassifiestheactorsoftheecosystembasedonwhattechnologicalroletheyplay. In thisanalysis, the layeredapproachofclassifying theplayerswillbeused todetermine the actors. The end‐users of wearable devices and apps are in the serviceconsumingsideoftheecosystemwhereallothersareserviceprovidersorkey‐enablers.

2) The framework focuses on exchange. It uses the exchange of money, knowledge,information,innovationandserviceamongtheplayersintheecosystemtounderstandtheirinter‐relationships. The framework is based on the assumption that complexmulti‐actordigitalbusinessescanbeunderstoodandexplainedeasilyiftheirrolesareclassifiedbasedon the exchange of these four major elements that flow among the actors around theecosystem.

3)Inatypicalanalysiswiththisframework,firstoneneedtoidentifytheactorswhichareinvolvedintheparticularmulti‐actorbusinessecosystem,ifnottheentireecosystem,atleasttheactorsaroundaparticularfocalpointneedtobeidentified.Afterthis,foreachparticularactor,thefollowingtwoquestionsneedtobeanswered.

a)Whattheactoris“giving”tootheractorsaroundit?

b)Whatthatactoris“taking”or“getting”inreturn?

The “things” which are exchanged between actors should be related to the four majorelementsasdescribedin(2).

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We propose this framework’s name to the EMKIS framework, i.e. Exchange of Money,Knowledge,Information,InnovationandService.Fig.7illustratesatypicalnetworkofactorsin the wearable health business network. This framework is developed based on thetechnicalsynopsisofthecloudbasedwearablehealthsystemandconsequentlythelayeredapproachasdescribedintheprevioussections.Thisframeworkwillbeusedinthefollowingsectionswhile studying the casesofdifferentactors.Uniformity in illustrationse.g. colorcodeswillbemaintainedfortheanalysisonwards.

ThefollowingcolorcodesareusedinFig.7.

Green:Flowofinformation/knowledge

Red:Flowofmoney

Blue:Flowofservice/provision.

Fig.7Exchangeofmoney,information/knowledge,andserviceamongtheplayersinatypicalwearablehealthecosystem(TheEMKISFramework)

TodescribethewearablehealthsystemundertheEMKISframeworkatypicalscenariocanbe taken with respect to generalized actors. The infrastructure layer players (Platformproviders)ononesideprovideasecurehealthdatastorageandcomputationplatformandchargesthepartnerdevicelayerfirmsinexchangeofbackendsupportforthehealthdatageneratedbythedevices.Ontheotherside,theygivethedataandcomputationplatform’saccess to the applicationdevelopers inexchangeof innovationwith thedata.Thedevicemanufacturerschargetheendusersforpurchasingofthedevices,andtheseendusersalsopaythesmartphoneappstoreforhealthcareapppurchases.Ashareofthisrevenueiskept

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bythesmartphoneappstore(30%oftheappcostforAndroidand99USDyearlyforiOS)andtherestgoestotheappdeveloper.Theappdeveloperprovidesitsservicetotheendusers through the user interface based on the smartphone OS platform, combining theprocessedinformationfromthecloudplatformviainternet.Theinformationcombinedwithvisualinterface,createstheknowledge(bio‐feedback)theenduserpaysfor.

Thepointtonotehereisthatthe"apps"willneedtobepublishedinthesmartphoneappstorese.g.androidoriOS,orwindowsphoneOS,notthehealthinformationcloud(platform).Thehealthclouddoesnothaveaseparateappstoretopublishanyapp,ratheritisaseparateentity just to store accessible data.What the open platform providersmean by an openplatform is that the data stored in their cloud can be accessed by an app for freewhenrequestedunderaroyaltyfreelicensemechanism.The"key"toaccessthedataisan"API".

Theappspublishedinthosesmartphoneappstoreshavetheirownmechanismofpaymentagreementswiththeirdevelopers(e.g.30%onpaidappsforandroid,yearlychargeforiOS).However,whatopencloudplatformsareprovidinghereisthe“access”tothecloudi.e.theAPI.

Thecurvedarrowthatisgoinginsidethesmartphoneappstoreisthemoneytheappstoreistakingoutmidwayofatransactionfromtheusertothedeveloper.Themoneyiscominginadifferentwaythanthatofthedevicemanufacturesandappdevelopers.Theappstoreistakingasharemidwayofatransactionfromusertothedeveloper,thereforeitisrepresentedinadifferentway.Fortherevenuesthedevicemanufacturersandothersareearningarerepresentedbytheredarrowsthosegoinginsidetheboxescorrespondingtoeachactor.

ForthecasesofcurrentincumbentsintheITmarket(Intel,Microsoft),thebusinessesspanacrossthelayersasthesecompaniesoffera“completesolution”.Theirpresencestartfromthe device manufacturing, through cloud infrastructure, till the application layer.Interestingly,anumberofthesecompanieshavekepttheapplicationdevelopmentsideopenforthirdpartiesbyprovidingfreeSDKsandAPIstothedevelopers.

Differently than Intel and Microsoft, Samsung had adopted an “open hardware – opensoftware –open mechanical” approach [50] as they announced their Simband healthwearable onMay 28, 2014 [51] alongwith its SAMI (SamsungMultimodal ArchitectureInteraction)cloudplatform.Aspertheannouncement,this“Simband”willnotbeaproduct,butareferencedesignforotherdigitalhealthentrepreneursandmedicalresearcherstouse.

Fewmajor players and newcomers aremapped in Fig. 8 classified in different layers ofbusiness,withspecialremarksontheirmarketpositionandtype/spanofoffering.

Fig. 8 is constituted using the information collected from the official websites of thecorresponding devices. In Fig. 8, we can observe that the leadingmarket players (Intel,Microsoft,Apple,Fitbit, Jawbone)arecompletesolutionproviders; i.e. theyspannedtheirbusinessacrossallthethreelayers.ExceptBasis,alltheotherleadingfirmshavekepttheirdevice’splatformopenforthirdpartydevelopment.Empaticaisasmallerfirminthemarketwhoisalsoacompletesolutionprovider,buttheyhaveamedicalfocusandaspecifictarget

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marketwhoare inmedicalneed for thedevice.Angel is anewcomer company spanningacrossonlythedeviceand infrastructure layer.Salesforce,TelenorConnexion,Oceanleapare only in the infrastructure layer. Runkeeper, Runtastic, MyFitnessPal are only in theapplication layer. Samsung, with their “open hardware‐open software‐open‐mechanical”approach inenablingthirdpartyhardwareandsoftwaredevelopmentplatforms,will fallunderthedeviceandinfrastructurelayer.

Fig.8.Majorplayersmappedaccordingtospanoftheirbusinesses

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4.3IdentifyingEMKISandDesignPatternsintheWearableMarket

Among thecompletesolutionproviders,wewillpresent thecasesofMicrosoftBandandEmpatica in detail. Among the device manufacturers we will present the case of Angel.AmongtheplatformproviderswewillstudySamsungSimbandandOceanleapinparticulardetails.Intheapplicationlayer,wewillstudythecaseofRuntastic.

4.3.1AmongtheCompleteSolutionProviders

From fig.8wecan furtherderive that the leadingmarketplayers in thewearablehealthindustryare“CompleteSolutionProviders”;i.e.theseplayersspantheirbusinessesacrossthe layersfromdevicemanufacturing, in‐housecloudplatformandbuilt‐inappsfortheirdevices.TheseplayersincludeMicrosoftBand,IntelBasis,Applewatch,Fitbit,Jawbone.IntelBasis still did not provide a timeline when they will release the SDK for third partyintegration,buttheymentionthatitisapriorityforthem[52].Fromtheperspectiveofthesefirms,weappreciatea“Multi‐sided”and“Open”patternfromtheMettlerandEurich’sdesignpatterns in e‐healthbusinessmodels in [17] (see table1).Themulti‐sided framework isadoptedinrelationtopartnershipwiththedevicemanufacturerstobuildtheirbusinessesaround the centeredcompany’s infrastructure, and theopen framework isused to inviteapplication developers to make the software resources rich with apps. This is furtherillustratedwithacasestudyonMicrosoftBand.

TheCaseofMicrosoftBand

OnOctober30,2015,Microsoftreleaseditsfirstwearable“Microsoftband”whichincludesa number of sensors for health tracking, e.g. heart rate, skin conductance (Galvanic SkinResponse–GSR),threeaxisaccelerometer.TheannouncementofMicrosoftHealthplatformforadvanceddataanalyticsusingthesensordatafollowedthedeviceannouncementatthesametime.

Microsofthadalimitednumberofthesedevices,whichwere“soldout”withinthefirsttwoweeksofitsrelease.ThepricewassettoUSD199.[53]Inadditiontothat,whileFitbitisasubstituteproductforMicrosoftBand,Microsoftactuallypromoted“FitbitFlex”(anactivitytrackerdevice),i.e.freewithpurchaseofthenewMicrosoftLumia830phone.ThishappenedjustoveraweekbeforethereleaseofMicrosoftBand.[54]

The releasewebsite ofMicrosoft Health [55] (The Official Microsoft Blog)mentions thefollowingstatement:

“MicrosoftHealthisdesignedtobenefitourpartnersinmanyways.Fornewentrantsandstartupswehaveacompleteofferingthatincludesourapp,andAPIsaswellascloudstoragefortheirdata.ExistingservicescanuploadtheirdatatoMicrosoftHealthandtakeadvantageofouradvancedalgorithmsandthepowerfulmachinelearning

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fromourIntelligenceEnginetogivetheircustomersinsights.Newdevicescanlicenseour10wrist‐wornsensormodulestogatherrobustdataincludingactiveheartrate,sleepandGPS.”

Microsoftannouncedcollaborationswith Jawbone(Devicemanufacturer),MapMyFitness,MyFitnessPal and RunKeeper (App developers), and also announced partnerships withStarbucksandGold’sGym.[53](PaymentusingMicrosoftBandwithpre‐loadedStarbuckscard;goal‐orientedworkoutsatGold’sGymspeciallydesignedforthebandowners)

Lastly,theMicrosoftHealthCloudAPIdeveloperagreementin[56] says,

"SubjecttoyourcompliancewiththisAgreement,Microsoftgrantsyouanonexclusive,revocable,non‐sub‐licensable,non‐transferable,royaltyfreelicensetousetheMicrosoftAPIs solely during the Term and solely to develop, reproduce and distribute anApplication(s)."

Theseobservationscanbeexplainedinthefollowingway:

The limited production of Microsoft band is not motivated by creating an artificialappearanceofhighdemandoftheproduct,but itwasrathera“demonstrationdevice”toactuallypromoteMicrosoftHealthPlatform.

The idea ofMicrosoft Band andMicrosoft health is not to competewith otherwearabledevicemanufacturers e.g. Fitbit, but to bring these devices under the shed of MicrosoftHealth Platform and Microsoft wants them to collaborate with Microsoft, just the waydifferentPCmanufacturersuseMicrosoftWindowsasanOperatingSystem.

Microsoftwantsnewdevicestolicensetheircutting‐edgetechnologywithMicrosoftoratleastsharethedatawiththeMicrosoftHealthPlatform.Forexample,Microsoftdoesn’tseemtopushawayFitbitfromthemarket,ratherwantsthenextFitbittousethesensorset‐upoftheMicrosoftBand,andtheMicrosoftHealthPlatform.

ThetruecompetitionofMicrosoftinthisfieldisnotFitbit,JawboneorBasis,ratherGoogleFit,AppleHealth,AndroidWearPlatform,Salesforceetc.

The revenue stream for Microsoft will come from multiple sources in the MicrosoftEcosystem, e.g.Microsoft Band sales, the other devicemanufacturers (Sensor licensing),devicesusingMicrosoftHealthCloudforbackendsupport.TherevenuemechanismcanbeoverviewedusingtheEMKISmodelinFig.9.

WhentheinformationstoredintheMShealthcloudisrequested,theappusestheAPItoaccess and use that data. If the API license is free, MS has no other way to charge thedevelopers, neither they mean to do it. However, the platform may impose advertisingregulationse.g. touseadcontents fromtheiradnetwork intheapps,butMicrosoftbanddoesn’tevenimposeanythinglikethatintheiragreement.

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Theopencloudplatformisonlychargingthe"devices"whichusesthecloudtostorethedatageneratedbytheirdevices.

Fig.9Exchangeofmoney,information,knowledge,andservicearoundMicrosoftHealth

ThedesignpatterninthebusinessmodelofMicrosoftbandishasmultiplefolds.

Firstly,inthehardwareside,Microsoft’sapproachis“multi‐sided”,invitingdifferentleadingequipmentmanufacturersontolicensingtheircuttingedgedevicesensors,andcollaboratingwiththeMicrosoftHealthPlatformforthehealthdata.

Secondly, in the software side, there is mixture of “multi‐sided” and “open” approaches.Towardstheestablishedappcompanies(Runkeeper),theapproachispartnershipbasedandmulti‐sided.Tothenewcomerappdevelopers,theirapproachisopen,allowingthemtobuildappsforthedevice,ontheirplatform,byprovidingfreeaccess(API)tohealthcloud.

FromthedesignpatternsadoptedbyMicrosoft,itisevidentthatthecompany’smajorfocusand longtermgoal is that thereshouldbea largeecosystemofplayersaroundMicrosoftHealth.On thehardwareside, thereshouldbeotherpopulardevicemanufacturersapartfromMicrosoftband(currentlythereisonlyJawbone).Onthesoftwaresidethereshouldbepopular fitness apps (Runkeeper, Myfitnesspal), and a number of new innovative appdevelopercompanieswhohasbuilttheirappsontheMicrosoftHealthPlatformforMicrosoftbandandthepartnerdevices.

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TheCaseofEmpatica

Sincethe1990sRosalindPicardatMITMediaLabhadbeenresearchinghowtobestmeasureemotionthoughsensors.In2007,shedevelopedawearabledevice(iCalm)thatmeasuredskinconductivity(GalvanicSkinResponse)toseeitscorrelationwithstress.Withextensivesetofexperiments,Dr.PicardconcludedthatunusualspikesintheGSRresponsecorrelateto flattening of brain waves that happens after epilepsy seizures. After patenting thetechnologyandpublishingtheresultsinrenownedmedicalandengineeringjournals,Picardpartnered with Matteo Lai, co‐founder of Empatica to commercialize the technology.Foundedin2011,Empaticaoffersarangeofdevices,suchas‐“EmpaticaEmbrace”targetedtowards end users, corporates (for corporate wellness program) and “Empatica E4” formedicalresearchers.Allthedevicescomewiththeirtrademarkappforstressmonitoringandseizuredetection.Thefollowingfactsareobservedstudyingtheirofferingsfromtheirofficialwebsitesandotherpressreleases.

Accordingto[57],EmpaticaCEOMatteoLaisaysaboutEmpaticaE3:

“Itisavery,verywell‐receivedsensorandithasenabledprojectsthataredifficulttodowithlabequipment,becauseit’sclinicallyvaluabledatathatyoucangetinthefield.Soyou can give it to patients so you can get data and you can study everything fromAlzheimer’s toParkinson’s,Schizophrenia,depression,stress,anxiety,andalsoepilepsyandautism.”

Empatica Devices are being used by medical and research institutes including BostonChildren’s Hospital, Microsoft Research, Intel, Stanford, Yale, and NASA. [58].  [57] addsfurther:

“thetechnologyhasan initialprimary focusonepilepsy,but isalsousable foractivity,stressandsleeptrackinginhealthyindividualsandwillgraduallyaddusecasesforotherchronicconditionsincludinganxiety,depression,andautism”;

“Embrace, the forthcoming consumer device based on the E3, measures monitorphysiologicalstress,emotionalarousal,sleepandphysicalactivity,and forpeoplewithepilepsy,itdetectsaseizureasitbeginsandautomaticallyinformsaparent,caregiver,orfriendsotheycancallforhelp”.

Accordingto[57],CEOMatteoLaisays“thecompanydecidedtotransitionintoaconsumerdevicebecausetheneedissogreat.”

AboutEmpaticaEmbrace,thelatestconsumerdevicefromEmpatica,CEOMatteoLaisays“It’sthefirsttimeamedicaldevicelooksbeautifulandissomethingthatyouwanttowear.Notsomethingtobeashamedoforapatchthatyouhavetohideonyourbodybecauseit’suglytolookat.”[57]

[59](22January2015)statesthat“EmpaticaiscurrentlyseekingfortheFDA’sclearanceforEmbrace,andisalreadyintheprocessofdevelopingadditionalappstoexpandtheusesofthewearabledevice.”

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Wecanderivethefollowingpointsfromthestatedfacts:

Empaticahasawell‐definedtargetmarket.Ononehand,theyhaveanavailableE3andE4wristbandtargetingmedicalandacademicresearchers(autism,epilepsy);ontheotherhandtheyarereleasingaconsumerendmodel“Embrace”forpatientsfightingautismandepilepsyconsideringcustomerneedsondesignandformfactors.

Empatica highlights their expertise on the quality and reliability of the bio‐data thatEmpatica collects from the users’ body and want to become a “research‐platform” forwearablehealthcareinnovatorswiththeirhighqualitysensingcapabilities.

WhatcreatesthemostvalueforEmpaticadevicesistheresearchinvolvedinthesoftwareand data analytics end, rather than hardware form factors or open‐cloud‐platformapproaches. Inotherwords, thoughthe“visible”coreproduct is thedevice,yet thevaluecreatingfactoristheirproprietarysignalprocessingalgorithmthatrunsinthebackendattheircloud.Theapplicationhowevercomesfreetotheuserthroughtheirsmartphones’appstore,andthewebportalfromtheirinternetbrowsers.

Fromtheabovediscussion,itcanbederivedthatthecorevalueofEmpaticalieswithinthedata analytics application for the device than the device itself which provides the datarequiredforanalysis.However,theapplicationcomesfreefromthesmartphoneapp‐storeandthedevicecomeswithaprice.Sincetheapplicationisnotusablewithanyotherdevice,andcomesfreetotheuserfromtheapp‐store,thedevicecanbeclassifiedasthecoreproductandtheappasacomplimentarygood.Inthiscase,thevaluelieswithinthecomplimentarygoodwhichattractsthetargetcustomersandmakethembuythecoreproduct(thedevice).Thisisan“InvertedRazorandBlade”designpattern.TherevenuemechanismcanbefurtherunderstoodfromtheEMKISillustrationinFig.10,wherewecanseethattherevenuestreamof Empatica comes from the device purchase, and the service come from the mobileapplicationandwebportalsidehandledandmanagedbythesamecompany.

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Fig.10EMKISmodelforthecaseofEmpatica.

4.3.2AmongtheDeviceManufacturers

TheCaseofAngel

Angel,developedbySeraphimSenseLtd.which isco‐foundedbyEugene JorovandAmirShlomovichandbased in Israel, isawearablewristbandwithhealthtrackingcapabilities(heart rate, activity, blood oxygen, and skin temperature). The following key points areobservedfromthewebandpressreleasesrelatedtoAngel.

According to the officialwebsite [39], Angel is “the first trulyopen sensor forhealthandfitness”,and“engineeredtobeopen”.Italsosays:“Mosttrackersforfitnessandhealtharebuiltforusebyasingleproprietaryapp.Angelintroducesanopentechnologymeanttobreakthisparadigm.Angelcanbeusedwithmanyexistingappsandweb‐platforms,andhopefully,willinspireanabundanceofnewones.”

[39]addsfurtherthatAngelis“abuildingblockforDigitalHealthenterprises.Itisdesignedfor full integration inDigitalHealthproductsandservices.ItsOpenSDKanddriversenableEnterprisePartnerstoentertheDigitalHealthmarketplacewithastateoftheartsolution.”;and also “Angel isopen inordertosupportResearch. Angel’scapabilitiesandopennessaregreat tools forResearchers.”  It also highlights that “Angel is the firstdevicedesignedwithdevelopmentopportunityinmind.Weareopeningupcommunicationprotocols,API/SDK,andsensordatastreams.EnterprisesandDeveloperswillbeabletouseAngeltocreateappsforiPhone,Android,andotherdevicesthatsupportBluetoothLowEnergy.”

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Accordingto[60],EugeneJorovsays:

“Wewantedtocreatetherighthardwareforthefutureofhealth.Rightnowdigitalhealthsolutionsare started from scratch bybuildinga sensor.Mostdevices endupwith verylimitedfunctionality.Whatevertheproduct,itsusersaretypicallylockedintousingtheonlyappthatcomeswithit.Healthisjusttooimportanttoremainclosedtomassinnovationandwebelieveinanopenfutureforthehealtheco‐system.”

Accordingto[61], Jorovalsosays“Angelwillbeinitiallymarketedasaconsumerdevicewhilethe company awaits an FDA review.Once approved, the device could bemarketed to anynumberofhealthcareresources.”

Fromthe interviewconductedwithEugene Jorov,we foundout thatAngel,asabuildingblock,istargetingmainlysmallenterprisesandresearchersatthismomentandiswillingtocollaboratewithbeginners.HedidnotdiscloseAngel’scurrentpartnerincloudplatformatthemoment,buthintedthatAngelwillpartnerwithpopularhealthplatforms(SAMI,AppleHealth)andeventuallyplantobuildtheirowncloudinfrastructure.

Fromthe interviewwealsocame toknowthatAngel isnotseeing thebigplayers in themarket (Samsung, Microsoft) as a competition considering how big and immature thewearablehealthmarketisandhoweverycompanyhasasubsetofpotentialcustomersandpartnerenterprises.

Thefollowingcanbederivedfromthefactsstatedabove:

Angelcreatesthevaluefromtheiropenness(inhardwareandsoftware)andreachabilityofsmall scale digital health newcomer players. Angel wants to build a rich ecosystem ofhealthcareapplicationsfromthedevelopercrowd,basedonAngelandAngel‐baseddevices.ImportantpointtonoteisthatAngelisnotinthecloudplatformbusiness,hencethemainproductisthehardware.Angeldoesnothaveanyparticularhealthapplicationdevelopedbythecompany,rathertheyprovideSDKsandsampleapps(forAndroidandiOS)andAPIstoaccesstheirsensors.

SinceAngelisnotinthecloudinfrastructurebusiness,andnotintheapplicationmarketaswell, therevenuemechanismfor thecompanyhas tobe fromdevicesalesand fromB2Bpartnershipwithotherdigitalhealthentrepreneurs.Also,sinceAngel isnotknowntobepartneringwithanyothercloudinfrastructure,thepartnerenterprisesusingdevicesbuiltoverAngelwillpresumablybeattachedtothesamecloudwhichAngelislinked.Basedontheinformationgathered,therevenuemechanismforAngelaccordingtoEMKISmodelcanbeillustratedinFig.11.

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Fig.11EMKISforthecaseofAngel

FromthediscussionabovewecansummarizethatAngel’stargetistoestablishitselfasthe“righthardware”inthewearablehealthdomain.Theyarekeentodrawtheattentionofthebusiness community in this area by promoting their openness and reachability by otherparties,e.g.Angelbasedhardwaremakers,mobile/webapplicationdevelopersforAngelandAngel based devices etc. Angel seems to create a situation where it can approach thepotentialend‐userswithalargesetofmobileapplicationssupportedbythedevice,andthepotentialB2Bcustomerswithapackageofhardware,software,anddataplatformsupport.

FromFig. 11,we can see that the flowof revenues forAngelwill be from the end‐users(usabledevicepurchase),andB2Bcustomers(hardwarebulkpurchase).Towardstheendusers,thedesignpatternis“InvertedRazorandBlade”,sinceAngelseemstohighlightthenotionthatasingleproprietaryappisnotenoughforasinglewearable;andonceagoodnumberofthirdpartyappsisreached,themorelucrativeAngeldeviceswouldbefortheendusers. In general, Angel’s businessmodel design pattern is “Multi‐sided”. It bridges newcompanieswithacommoncloudplatformprovider,whicheventuallyconnectsittoasetofapplication developers. In the enterprise side, the company takes money for hardwaresupport,andintheinfrastructuresideitgivesmoneyforcloudsupport.

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4.3.3AmongthePlatformProviders

TheCaseofOceanleap

Oceanleapisagoodexampleofacloudplatformproviderforwearablehealthcaredevices;thoseoperateonlyintheinfrastructurelayer.ThefollowingfeaturesofOceanleapmakeitinterestingforustoanalyzethecompanyinmoredetails:

TheofficialwebsiteofOceanleap[44]statesthattheyare“thefirstcompanytoofferacloudplatform,builtspecificallyforwearables”,andtheirplatform“enableswearabledevicemakersandappbuilderstobringtheirproductstomarketquicklyandinexpensively”.

Totheappdevelopers,OceanleapwillprovideafullsetofAPIs,samplecodes,andbuilt‐infunctionstodevelopappsforhealthandfitness.Oceanleaphaspre‐categorizedtypicalusecasesofawearablehealthappi.e.activities,measuringunitsandattributes,andorganizedtheir app‐development tools accordingly [62]. Apart from a development environment,Oceanleapprovidessoftwaredevelopmentserviceondemandwithintheir“BuildyourownorPartnerwithus”schemes.[63].HavingOceanleaptodevelopappsforanenterpriseisaseparateservicethanthecloudinfrastructureitself.

To the wearable device makers, Oceanleap provides all the backend support for thegenerateddatae.g.storage,accessibility,anddevelopmentplatformusingthedata.[62].

Oceanleap has partnered with Sensoplex (http://www.sensoplex.com/) and Invensense(http://www.invensense.com/) – twowearable sensormanufacturers and invitingmorepartners.Withthesepartnercompanies,Oceanleap“pre‐integrates”theirplatformAPI(ormake compatible) with the sensor data outputs. In simple terms, Oceanleap is fullycompatibleandtechnicallypreparedtosupporttheback‐endsofthewearablesthosehaveSensoplexorInvensensehardwareinside.

Oceanleap’spricingpolicyisusagebasedasmentionedin[64].TheychargetheirpartnerdevelopersmonthlybasedonAPIrequestspersecondforplatformusage.The“usagetiers”havearesolutionof10APIrequests/second.Forancillaryservicese.g.datastorage,transfer,pushnotifications,thepricingpolicyisbundlebased.Forexample,20GBofdatastorageisincludedineach“usagetier”bundle,and200USDischargedforeachadditional10GB.

ThefollowingpointsrelatedtoOceanleap’sbusinesscanbederivedfromtheobservationsabove:

Oceanleap’sintendedrevenuemechanismismulti‐folded.Firstly,theywillchargethemobileapplicationdevelopersfortheplatformbasedonAPIrequests.Theyalsohavea30dayfreetrialoffer.ThismakesOceanleapasafechoiceforthenewcomerhealthandfitnessappstohandlethebackendanddatausagefortheapps.Secondly,Oceanleapsellspre‐builtappstoenterprises who want to market their product quickly. In addition to that, they takecustomizedorders tobuildapps forenterprisesaccording toanyparticularrequirement.

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Software‐as‐a‐Service(SaaS)isanadditionalrevenuemechanismhereoverPlatform‐as‐a‐Service(PaaS).

Regardingpartnerships,theCompanyispartneringdirectlywithsensormakersinordertoproperlybridgethehardwareandsoftwaresidesofthesystem.Thatmeans,theirSDKsandplatform APIs are pre‐integrated with the two partnering sensor‐makers’ sensor dataoutputs.Thecompanyistakingintoaccountthepossiblecomplexitythatmightarisewiththe difference in data formats coming from different sensor manufacturers. This pre‐integration should help reduce the complexity from the software development side. Thecompanyiskeepingitsimplebykeepingitlimitedandcontrolled.

The exchange of money, knowledge, information and service for the ecosystem aroundOceanleapcanbeillustratedinFig.12.FromFig.12itwillbefurtherclearhowtherevenuemechanismworksforOceanleap.TheplatformproviderchargesthedevicemakersforPaaSand the app developers for usage of the platform and SaaS (pre‐built app or build‐on‐demand).Clearlythecompanyadoptsthe“asaservice” designpatternbringingtogetheralltheactorsaroundtheplatformecosystemandearningrevenuesisdifferentpossiblewaysbynotsellinganyproduct,ratherprovidingnecessaryservice.

Fig.12EMKISmodelforOceanleap

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TheCaseofSamsung(SIMBAND–SAMI)

In addition to Oceanleap, it is also worth understanding Samsung’s approach towardswearablehealthduetoitsnotabledifferenceinpromotingitselfnotasaproduct,butasanopenplatformintermsofbothhardwareandsoftware.OnMay28,2014,attheir“VoiceoftheBody”eventinSanFrancisco,Samsunglaunchedtheirdigitalhealthinitiativewiththeannouncementofthefollowingofferstodigitalhealthinnovatorsandentrepreneurs.

Simband: Samsung had launched Simband as an “open reference design platform” forwearablehealthdevices.ThoughSimbandexistsasawearabledevice,butitisnotlaunchedas a consumer device, rather a research and development platform for enterprises andinnovators.AccordingtoSamsung[65],Simbandis:

a)“Amodulardevice”,whichmeans,thatthemodules(display,sensormoduleetc.)canbeadded,modified,replacedwithoutaffectingthewholesystem.Forexample,Simsense isSamsung’sreference implementation[66]ofasensormodulewhich ismodularly housed inside Simband. This can be modified or replaced using themechanicalandelectricaldesignconsiderationsasmade“open”bySamsung.

b)“Open”,whichmeans,informationregardingSimbandhardwaremodulewouldbeavailabletothedeveloperssothattheycanreproduceordeveloptheirhardwareinSimband’sblueprint.

SAMICloudPlatform:SamsungArchitectureforMultimodalInteractions(SAMI)isacloudbasedsoftwareplatformforsecurelystoringandprocessingthedatageneratedbySimbandandSimbandbaseddevices.AccordingtoSamsung[67],SAMIis“adataexchangeplatformthatenablesanydeviceorsensortopushitsdatatothecloud.Applications,servicesanddevicescanthenusethatdatathroughsimpleAPIs.”SAMIisanopensoftwarearchitecture[65],withopenAPI[68],thatmeans,applicationswillbeabletorequestaccesstothedata(viaAPI)inSAMIfreeofcharge.

ThefollowingcanbederivedfromSamsung’sofferingstounderstandtheirbusinessdesignpatterns.

Samsungunderstandsthecomplexityofactorsinwearableecosystem,andwantstogetholdontotheindustrywithade‐fragmentationapproach,thatmeans,gettingasmanyaspossiblenew actors (enterprises) under the umbrella of Samsung, i.e. Simband’s blueprint in thehardware, and SAMI cloud in thebackend infrastructure.As [65] states, Samsung’s opensoftware‐hardware approach is “intended to lead to the creation of a hardware andalgorithmsecosystemthatwillenablenewtechnologyand innovationtobeeasilybuilt intofinishedproducts”.

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Atthismoment,Samsung’srevenuemechanismisnotcommerciallyend‐usercentric,ratherintendedtoflocktogetheranumberofdevicemakersandsoftwaredevelopersundertheshedoftheirecosystem.Since,theSimbanddeviceisnotavailableforend–userstobuyandonly available for researchers and enterprises to work on, revenue is not meant to begeneratedfromdevicesales.Thedesignofthehardwareisopenandlicensefree,andtheplatformisalsoopenAPI.Therefore,theonlyrevenuestreamwouldbefromtheSimbandbaseddevicemakerenterprises,whowilluseSAMItostoretheirdataforfurtherprocessinginthecloud.Theexchangeofmoney,knowledge,informationandservicefortheecosystemaroundSAMIandSimbandisshowninFig.13.

Fig.13EMKISforthecaseofSamsungSimbandandSAMI

SamsungdiffersfromOceanleapinanumberofwaysintermsofthebusinessmodeldesignpatterns in wearable health. To the application developers, the major difference is inplatformaccessinexchangeofmoney.Samsungwillnotchargethirdpartyapplicationsforaccesstodata(APIrequest),asOceanleapwill.Salesoftheendproduct(Simband),oritsdesign is not meant to makemoney as per Samsung announcements. Samsung will notprovideanydirectSaaS(appdevelopmentasaservice),theenterprisesneedto“doittheirown”withthetoolsandenvironmentSamsungprovidesasanecosystem.Byprovidingthehardwareandsoftwareplatformforbothhardwareandsoftwaredevelopersinthefuturedigitalhealthmarket,Samsungismorefocusedonbringingtheenterprisesunderasame

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umbrellathatusesametechnicalstandardsinhardwareandsoftwarewhenitcomestotheiroperations. Hence, it can be concluded that Samsung’s design pattern ismore similar toMicrosoftinthisregardsthanOceanleaporotherplatformproviders.SamsungdifferswithMicrosoftinthewaythatitdidnotbringanyenduserdeviceyetasMicrosoftdidwiththeirMicrosoftBand.SamsungismoreexplicitwiththeirbusinessintensionsthanMicrosoftinthisregard,withthesametargettosustaininthemarket.

Therefore,Samsung’sdesignpatternis“Multi‐sided“towardsthedevicemanufacturers,and“open“toapplicationdevelopers,similartoMicrosoft.

4.3.4AmongtheApplicationDevelopers

Theapplicationlayerinthewearablehealthdomainisnotatthesamelevelofmomentumthedevicesandplatformsareatthemoment.Itisanticipatedwithoutreservationthatthehealthcareappsaregoingtorevolutionizem‐healthsector inthecomingyears,however,only a few actors (for example Empatica) in this domain has come forwardwith a finalproductoraBetaversion.Themainfocusandkeyfactorofcompetitionintherecentmarketisbuildingtherightenvironmente.g.hardwareandsoftware,toaccommodateandfacilitatethe potential application layer players. In other words, the players in the device andinfrastructure layers are laying the foundation for advanced health‐data analytics, byestablishing health‐data generation, storage and management infrastructure, where theactualdataanalyticsplayersarestilltogrow.Manyofthemarestillintheresearchphase,orawaitingmedicalqualityapproval.

Atthispoint,itisimportanttoclassifytheapplicationlayerplayersintotwomajortypes:

1)Thefitnessandwellbeingappmakers(Runtastic,Runkeeper,Myfitnesspal);

2)Healthcare/medicalappmakers(Basis,Empatica,Biosync).

Thepresentthirdpartyapplicationmarketforwearabledevicesmainlycomprisesoffitnessapplicationsthosewerealreadythereforsmartphones(usingsmartphone’ssensors),andlatermadecompatiblewithselectwearables.Runtastic,Runkeeper,MyFitnessPalaresuchexamples.Inthislimitedsubsetofplayers,mostcomewithacompletepackagewithdevice,cloud and proprietary application (Intel Basis, Empatica). These are the early players ofwearablem‐healthandtheylaunchedatatimewhentheconceptsofopenplatformsandthirdpartyappintegrationwasstillbuildingupabusinessecosystem.

Inthesecircumstances,itisnotpossibletoidentifythebusinessmodeldesignpatternsofsuchacompanybystudyingitscase.However,itisrelevanttostudythecaseofafitnessappmakercompanyand identify itsdesignpatterns,as thebusiness relationships fromtheirperspectivewillbesimilartosuchfuturecompaniesofourinterest.Later,acaseofsuchahypotheticalcompanycanbedevelopedandpossibledesignpatternoptionsbemodeled.

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Theapplicationlayerplayershaveacomparativelylesscomplexrevenuemechanismthantheplayersoftheinfrastructurelayerandcompletesolutionproviders.Companiesinthislayerdealdirectlywithend‐users,andfromdevelopmenttodelivery,thesecompaniesareend‐usercentric.Therevenuestreamforthemisalsodirectlyorindirectlyuni‐directional,i.e.fromtheendusersoftheapps.Therefore,popularfitnessappcompaniesfollowsomehowsimilar business model design patterns. For example, Runkeeper, Runtastic have twoversionsoftheirapps,thefirstisfreeandanother“pro”versionforwhichtheusershavetopay.Theseappsalsohavein‐apppurchasesforparticularfeaturesasrequiredbytheusers.Forthefreeversions,therevenuesourceisadvertisingintheapp.Tohaveaclearview,wewillanalyzethecaseofRuntastic.

TheCaseofRuntastic

Runtasticstartedin2009asafitnessappdevelopmentcompanyinAustria.Thecompanydevelops apps for fitness and activity tracking and supplementary hardware products(wearable devices) and online services, e.g. fitness data analysis, training log, socialnetworking.Recently,onAugust52015AdidasboughtRuntasticfor240MillionUSDollars.[69]. The following facts should provide an overview of the revenue mechanism of thecompany.

The basic Runtastic app is freewhere Runtastic Pro is an ad‐free paid application withadvancedfeatures.Thereareatotalof18othermobileappsinadditiontothebasicRuntasticProfordifferenttypeofwork‐outsandtrainings.10ofthemareavailableinproversions.[70].

Runtasticalsosellssupplementaryhardwareandaccessoriesrelatedtotrainingandfitness,such as: the Runtastic heart ratemonitor, Runtastic’s Orbit Activity Tracker, fashionableactivitytrackerwristwatchesetc.

Runtasticprovidesonlinetrainingservicestotheirprousersfordifferentspecificpurposes,e.g.weightlossplan.UserscanlogintotheiraccountsatRuntastic.comtoviewtheiractivitylog. All thework‐out data fromuser’s smartphone andRuntastic devices are stored andmanagedintheRuntasticplatform.

ThefollowingcanbederivedabouttherevenuemechanismofRuntastic’sbusinessactivities.

From the free versions of the apps, the company receives advertising revenues from adnetworks.Fromthepro‐versions,therevenuescomedirectlyfromtheend‐users.Thesamemechanismappliesforin‐apppurchases.

Additionalrevenuestreamisdesignedtobecomefromsalesofsupplementaryhardwareorsoftware services for training (Heart Rate monitors, weight loss app). The hardwarewearablesprovideenhancedappexperiencewitheasyintegrationwiththewearables.

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TherevenuemechanismcanbefurtherillustratedwiththeEMKISmodelofforRuntasticasshowninFig.14.Inthispart,thecenterofdiscussionistheappdevelopercompanies,hencetheEMKIS is relevantlykeptmoredetailed.Wecansee that the incoming flowofmoneycomesfromappsales(pro‐versions)orin‐apppurchases,supplementarypurchases,andfromadvertisingnetworks.Inexchangeofadrevenues,theappsprovidetheadnetworkswithspacesintheirappscreen;andinexchangeofthepro‐versioncharges,theusersenjoyadvanced features from the app. The developers have to pay the smartphone app storeaccording to their app sales policies (30% revenue share for Android, and a yearlysubscriptionof99USDforiOS).Adrevenuesarealsosharedwiththesmartphoneappstore.Runtastic’scloudplatformproviderisundisclosed.Ifitisnotownedbythesamecompany,then B2B expenses would be added. The dotted red lines indicate how the developercompaniesneedtopaythesmartphoneOS(orappstore)indirectly,byrevenuesharingfromapppurchasesandadvertising.

Fromtheabovediscussion,itisclearthatthedesignpatternsforRuntasticisamixtureof“Freemium”and“RazorandBlades”.For themobileappbusiness,a simplisticFreemiummodel is used; at the same time, an extensive range of complementary devices andaccessoriesareofferedtothecustomers,relyingonthelock‐ineffectsduetotheuseoftheapplication,whichis“RazorandBlades”.

ItistobenotedthatRuntasticdoesnotworkaspartofanyopenplatformecosystem;henceitsrelationshipwithitsundisclosedcloudpartnerisbasedonclosedpartnership.IfithadbeenwithanaplatformasOceanleap,therewouldUsageChargeandSaaSmoneychannelsfromdevelopertoplatformandAccessandSaaSservicechannelsfromtheotherwayaround.

Fig.14EMKISmodelforRuntastic

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The case of Empatica described in section 4.3.1 (complete solution provider) should berevisitedforthecaseofahealthcaretypeapplicationdeveloper,however,itshouldbenotedthattheyexistasacompletesolutionprovider,notasanapplicationdeveloperonly.Sincethereisnocompanyinthemarketyetwhichresidesonlyintheapplicationlayeranddealswithanopenplatform,afuturescenarioofsuchcanbedevelopedtofindoutitspossibledesignpatterns.

4.3.5Summaryoftheidentifieddesignpatterns

Summaryoftheobserveddesignpatternsindifferentplayers’businessmodelscanbeputtogetherasinTable4.1

DesignPattern

Firm TypeofFirm Comments

Multi‐sidedMulti‐sided

MicrosoftBand

Complete SolutionProvider

Partnership with devicemakers

Angel DeviceMaker Partnershipcallstodevicemakersandappdevelopers

Samsung‐SAMI PlatformProvider–HardwareandSoftware

Partnershipcallstodevicemakerstouse“Simband”designandSAMIascloud;callstoappdeveloperstoinnovate

Open

MicrosoftBand

Complete SolutionProvider

Towards the applicationdevelopers, free access tohealthcloud.

Samsung‐SAMI PlatformProvider–HardwareandSoftware

Towards the applicationdevelopers, free access tohealthcloud.

InvertedRazor andBlade

Empatica

Complete SolutionProvider, Specialpurposedevice

The core value lies withinthedataanalytics.

Angel DeviceMake FocusesmoreontheappsthatwillgrowaroundAngel(byothers).

Razor andBlade

Runtastic Fitnessappdeveloper

Sales of complementaryhardware.

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AsaService

Oceanleap

PlatformProvider SaaSandPaaS

Freemium

Runtastic Fitnessappdeveloper

Pro versions and in apppurchases.

Table4.1.SummaryofDesignPatternsfoundfromthestudies.

Fromtheabovediscussionsonthebusinessmodeldesignpatternsoftheexistingfirmsandtheir corresponding EMKIS models, we can derive the following concluding remarksregardingtheexistingwearablehealthindustry.

Duetotheimmaturenatureofthewearabletechnologybasedhealthapplicationmarket,theITindustryfrontrunnerse.g.Microsoft,Samsunghaveatendencytoadoptamulti‐sidedandopenapproach.Theyunderstandthepotentialofinnovationinthismarketandthatisthereasonwhytheymainlyofferanecosystemaroundwhichapplicationswouldbedeveloped.Theyunderstandthenecessityandscarcityofahealthcare‐specializedcloudinfrastructurewhichwouldmake it easy for developers to implement their innovation andmarket thehealth‐appsordevicesquicklyandinexpensively.Themulti‐sidedapproachisbasedontheassumptionthattherewillbeanumberoffirmswillingtoenterthewearabledevicesmarketandtheywillneedacloudinfrastructuretostoretheirdataandmakethemaccessiblebytheapplications that the end –userswill eventuallywish to use. The desired role of a cloudplatform is to bridge the device makers and application developers and make all thebusinessesaround it successfulandmaking theend‐users satisfiedbyallowing themthefreedomtouseanyservicetheyoptfor.Thatmeans,thatapplication‐servicemarketshouldbeindependentofthedevicemarket.Theflowofmoneyisthereforedesignedinawaythatthetwosidesoftheplatformcancomplementeachother.Thatmeans,openaccesstodatawouldmakeiteasyfordeveloperstomaketheirapplicationscompatiblewiththeplatform,andagreaternumberofcompatibleapplicationswouldmakemoredevicemakersinterestedinchoosingtheplatform.Itisalsoobservedfromthechoiceofthedesignpatternsofthesecompaniesthattheyunderstandtheimportanceofapplicationsinthewholescenario.Itisthe apps that provide the service to the end users, and creating an ecosystem for theapplicationdeveloperstoworkwiththedataandfocusoninnovation,isaconcernfortheplatform providers and the devicemakers. After all, it is the apps that give the devicesmeaningtoexist.Itisanecosystemofneeds–usersneedgoodapps,appsneedaccesstodataforanalytics,dataneedswearabledevices,anddevicesneedtostoredatainthecloud.AplatformisactuallyatthecenteroftheneedsandhencethemostimportantplacetobefromtheperspectiveofanestablishedITcompanylikeSamsungorMicrosoft.

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Thewearabletechnologybasedhealthcareapplicationmarketisatayoungstageandnottoomanyapplicationsaretherewhichdirectlyfocusonhealthproblems.FromthecaseofEmpaticawecanseethatthecompany,beingfullyfocusedonpreventionandearlydetectionofahealthproblem,havingtheexpertiseonhealthdataanalytics,hadtocometothemarketasa complete solutionproviderwithan InvertedRazorandBladedesignpattern. In thecontextofawearablehealthecosystem,companieslikeEmpaticacouldriseandevolveonlyin the application layer. However, in the current situation does not reflect that it couldhappen that way. For a health application company to emerge as a complete solutionprovider does not go with the notion of a role‐distributed and layeredwearable healthecosystem.

Itislesscomplexforfitnessappmakerstorelyonafreemiummodelfortheirappsbecausemost of their services do not require data analytics from a wearable device. For moreadvancedappservices,theyoffertheirowndevices,whichisaRazorandBladepattern.Thissituationisaresultoftheprevailingcomplexityinthehardware‐softwareintegrationinsideecosystems,wheretheappsaremadedevicespecifictoreducecomplexity.Thissituationresultsinafurtherlock‐inwhereusershavenooptionbuttobuytheirdevicesaccordingtotheirusageneeds.

PaaSandSaaSareelementaryservicestowardsnewdigitalhealthentrepreneurswhowishtoenterthemarketasacompletesolutionprovider.ThenatureoftheserviceofOcealeapleads us to conclude that its target customers are enterprises who need PaaS for theirdevices’data,andSaaSforapplicationdevelopment.Theendresultofthiswouldbea(setof) specific health application(s) compatiblewith aparticulardevice, bothownedby thesamecompany,andtheofferistosolveaparticularhealthproblem.Inshort,Oceanleap’sserviceistoenablenewcompanies,expertindataanalytics,toquicklymarketaproduct(oraproduct‐service‐combination)asEmpatica.

4.4Understandingthechallengesinthecurrentscenario

4.4.1Fragmentation,devicedependency,andabsenceofstandards

It is clear from the case analyses that the wearable m‐health platform providers areanticipatinglargevolumeofhealthapplicationsaroundtheirecosystems.Wherecompaniesare providing the developerswith open access to their health data bank in exchange ofinnovation, thesmallercompaniesarechargingthedevelopers inexchangeofaccessandSaaSwithdedicatedsupporttotheirclientdevelopers.However,themajorconcernfromtheappdevelopmentperspectiveisthefragmentedgrowthofecosystems.Thereareagrowingnumber of open platforms who are individually developing ecosystems around theirplatforms. The app development ecosystem is still not conducive to a standalone andhardware independent app development environment. From the case analyses, we canobservethatthewearablehealthmarketisgrowinginscattereddirectionsandnotfocusingon interoperability of apps across devices. Hardware and cloud infrastructure aremade

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compatibleatthefirstplacebefore launchinganapplication,e.g.EmpaticaandRuntastic.Empaticahasemergedasacompletesolutionproviderfortheirmedicalapp,andRuntasticsells compatible wearable hardware to support their apps. This fragmentation leads todevicedependencywhichwillbecrucialinthegrowthofhealthcareapplications.Iftheappdevelopmentecosystemscontinuetogrowinthisfashion,therewillbeasituationwhereitwillbenecessaryforend‐userstobuydifferentwearabledevicestobeabletousedifferenthealthcareapplications.Forexample,ifanovelapplicationisdevelopedforMicrosoftbanddevicesusingthedataintheMicrosoftHealthplatform(sayheartratedata),Empaticauserswillnotable tousethatapplicationdespite the fact thatEmpaticadevicesarecapableofmeasuringtheheartratedataoftheuser.ThisisnotonlyachallengefortheperspectiveofcompanieslikeEmpaticathattheusersarelimitedtoonlyafewapps,butitalsoappliestoMicrosoftBand,becausetheBandusersarealsonotbeingabletousespecializedhealthappswhichEmpaticahasdeveloped.Inadditiontothat,absenceofastandard inthehealthdataformatsindifferentcloudplatformprovidersiscomingonthewayofadeviceindependentand interoperableandstandaloneappdevelopmentenvironment, thereforeholdingbackthegrowthininnovation.Thefragmentedgrowthofecosystemsisindividuallybenefitingtheplatforms,butnotbenefitingtheinnovationinappdevelopmentasawhole.

The issuecanbebetterrealizedbyconsideringasituationwheretwodifferentwearabledeviceuserswanttouseanapp.Bothgeneratethesamedata,buttheyusedifferentopencloudplatformstostorethem.Therefore,tousetheapptheybothsendrequeststothesameapplication server. As illustrated in Fig. 15, the server then sends API requests to twodifferentplatformstoaccessthedata.Hereitisnoteworthythattheapplicationneedstwodifferentserversidecodestohandleasameapplicationfor twodifferentusers.Withtheincreasingnumberofthesedevicesandplatforms,thecomplexitywouldbeevenmore.Tosolve the problem, the application developer would probably require updating theapplication asmore devices enter themarket, or develop different versions of the sameapplicationforeachdevice.

EveniftheappsaremadecompatiblewithdifferentplatformsintermsofAPIs,i.e.theapp’scodewillcontainAPIsofmultipleplatformsandusethemwheneverrequired,thebiggerchallengeistomaptheapp’sdataanalyticsalgorithmworkwiththedifferentformatsandunitsofthedatastored.Sofar,thereexistsnostandardforthewearable‐generatedhealthdata.Eventhoughtheplatformsareopenaccess,thecompaniesareusingtheirproprietarydataformatsfortheirplatformswhichbecomesabarriertointeroperabilityacrossdevicesandplatforms.Thismeans, thechallenge isnotonlyabout integratingdifferentAPIs inasingleapp,butalsoinanalyzingdataindifferentformats.Hence,astandardizationofthewearablehealthdataintermsofformats,units,qualityetc.isimmediatelyrequired.Forthedesiredgrowthofwearableappinnovation,anopenstandardforhealthdataisrequiredontopofopenplatforms.Thesestandardswouldbefollowedbyallthedevicesandplatformspresentinthemarket.

Relatedtostandardizationofhealthdataacquisition,processingandformats,theContinuaCertificationProgram[71]hasrecentlyemergedasapotentialsolutionaddressingtheissue

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prevailing in the personal health monitoring devices. Continua focuses not only on theinteroperabilitybutalsothequalityofacquireddatafromtheelectronichealthdevices.Inthis framework, the “Continua Certified” devices are interoperable. Healthcare devicemakerse.g.Intel,Samsung,Phillipshavealreadyjoinedtheframework.However,untilnowtheContinuaCertifieddevicesare limited tovital signsmonitoringdevices tobeusedathome. A list of certified products can be found in [72]. A similar approach has becomeessential at present in the wearable industry, considering the fragmented growth ofwearableecosystemswithlittleornoprovisionforinteroperability.

Fig.15:Illustratingthechallengeofrunningasameapplicationusingthedatafrommultiplecloudplatforms

AninitialadvancementinthisfieldwastheIEEE11073StandardforPersonalHealthDevices[73],whichisstillanactiveworkinggroupdevelopingmorestandardsfordifferenthealthmonitoringdevices.AnotherrecentadvancementinforwearabledevicesistheIEEE1708‐2014Standard[74],whichoutlinesthetechnicalaspectsanddatarepresentationformatsforwearablecuff‐lessbloodpressuremeasuringdevices.However,itshouldbenotedthatthe industry has grownmust faster than the standardization initiatives, and hence it isimportantatthemomentthatatleasttheend‐formatsofvarioushealth‐datafromdifferentwearabledevicesarestandardizedsoon.

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4.4.2 Challenge in developing the business model design pattern from the appdevelopers’perspective

Theideaofanapplicationdevelopercompanyisbasedontheassumptionthattheywillhaveexpertiseintheanalyticsofhealthdatathatthewearableswouldgenerate.Inageneralcase,theywouldhost their applications in their application serversandwouldaccess/use thehealth data freely though the open APIs of different platforms. However, too muchfragmentation, device dependency and absence of standardization of health data fromwearablesmake it difficult for application developers to emerge as an application layerplayeronly,rathertheyemergeascompletesolutionproviders.Thesechallengeseventuallymakeitdifficulttodesigntheirbusinessmodels.

Thepotentialapplicationdevelopersforwearablehealthwhopresumablydonotspantheirbusinesses in other layers (device and infrastructure) will face the biggest challenge todevelop their business model design pattern in this fragmented market. Algorithmdevelopmentusinglargesetsofhealthdataisalreadycomplex,ontopofthis,tomaketheirapplication available to everyone who wish to use it, the software development wouldintroduceextracomplexityjusttocopewithmultipleplatformsandun‐standardizeddata.Asaresult,theapplicationswouldcometomarketwithlimitedcompatibilities.Thedesignpatternchallengescanbebrokendownintothefollowing:

InvertedRazorandBladeapproachasEmpaticacannotbeadoptedbasedontheassumptionthatthecompanydoesnothaveahardwarewingorpartner(s).

Freemium approach would be unsuitable, unlike fitness apps, since this is a healthcareapplicationanditwouldbedifficulttodifferentiatebetweenfreeandpaidservices.However,if one companyhasmultiplehealth apps in themarket, fewgeneric apps couldbemadeavailableforfree,whilekeepingthespecificmedicalneedbasedappspaid.Evenifthismodelis adopted, the device dependency of applications would still remain as a challenge bynarrowingthemarketreach,limitingtheuserbasebyoneorafewbrandsofdeviceusers.

Ifthecompanypartnerswithanydevicemaker(whohasapartnercloudplatformprovider),InvertedRazorandBladetypemodelsneedtoclearlydefinetherevenuesharingmechanismbetweenthetwocompanies(Fig.16)

Similarly,toadoptanInvertedFreemiumapproachonly,itwillbenecessarytohavetheappwork across devices and platforms, based on the assumption that the users buy (orsubscribesto)theirdeviceandapplicationsseparately.

However, to tackle the challenges in short run under the present circumstances, thefollowingissuesareneededtobeconsidered

Tostartwith,theappneedstobedevelopedtobecompatiblewithaplatformwhichhasabiggermarketshareintermsofdeviceownersandagreatervolumeofavailableappsforthedevices.Invertedfreemiumdesignpatternwillbetheapproachinthisrespect.Theproblemwiththisapproachisthattheappdeveloperwillnothavedirectcontroloverhowmuchthe

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enduserswouldpayintotaltobeabletousetheapp,becauseaportionofthetotalcostisthedevicewhichisthepropertyofanothercompany.Thiswillcreateextracomplexityforthecompanytoattracttheirtargetcustomerswhoarepotentiallyinmedicalneedofthatapplication.Ontopofthat,thisapproachwillcreateavalueforthedevicemanufacturerandwillnotaddanybenefit to theappdevelopercompany inreturn.Partnershipagreementmightbedifficulttoachieveatthebeginningconsideringthemarketposition‐gapbetweentheincumbentdevicemakerandnewcomerappdeveloper.

Thecompanymayadoptasmallscaleapproachbypartneringwithothergrowinghardwaremanufacturersandcloudplatformproviders.Thepartnerhardwaremanufacturershouldhavethenecessarysensorsandreliabledatafromthatsensor.Inthisapproachthedeviceitselfwillbeconsideredasamedicaldeviceandcanbeprescribedbygeneralphysiciansorhealth‐consultants.

Twodesignpatternsareadvisabletobeadoptedtofacilitatethisapproach.First,RazorandBlade,wherethedevicewillbeprescribedtobeboughtbytheusersandtheappwillcomeforfree.Inthiswaythedevicemanufacturerwillpayapercentageofthesalesrevenuetothedevelopercompany.TheotherisInvertedRazorandBladewheretheuserswillbuytheapplication(asperprescription)andadevice(manufacturedbythepartner)willcomeforfreewith similar agreements on revenue sharing. These two approaches can be furtherillustratedinfig.16.

Fig.16.Razor&BladeandInverterRazor&Bladeapproachforinitialmarketentryforanewcomerwearablehealthappdeveloperfirmunderthepresentscenario.

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4.4.3 How the challenges are overcome when a standardization and device‐independencyisimplemented

Thechallengespresentedintheprevioussectionsarebasedontheideathatthehealthcareapplicationsshouldbeusableindependentofdevicebrandsusingthedataaccessibleacrossplatforms.Onlyhavinganumberofopenplatformswillnotsolvetheissue,rathertheopenplatforms need to follow a standard format of the data, so that the applications canimplementtheirdataanalyticsalgorithmsirrespectiveofwhatplatformtheyaregettingthedata from.The consumers shouldhave the freedom to buy anypopularwearable healthdeviceoftheirchoices,andtheyshouldbeabletobuyandusethehealthapplicationtheyrequireifthewearablehastherequiredsensorsthattheapplicationneeds.Inanidealcaselikethis,theRazorandBlade(orinvertedrazorandblade)designpatterncanbemaintainedasapartofthebusinessmodellocally,targetingthecustomerswhowillonlybuythedeviceorappfortheirparticularmedicalneeds;atthesametimeenablingtheexistingusersofadifferent device to just purchase the app (or purchase subscription to the service) in anInvertedFreemiummodel.Fig.17illustratesthisdual‐design‐patternframework.

Fig.17.InvertedFreemium–Razor&Blade–Dualdesignpatternforwearablehealthapplicationdevelopers’businessmodel.

Inthisframework,iftheuseralreadyownsacompatibledevice,hecanjustbuytheappfromhisapp‐storewithaflatpriceorsubscription,andiftheuserwishes,hecanoptforbuying

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thepartneringdevicewheretheappwillcomeforfree,orbuytheappitselfandthedevicecomesfree.Revenuesharingwillbeanimportantaspectforthepartneringcompanies.

Ononehand,inthepresentscenariowhereanapplicationdevelopercompanyneedstohaveatleastonedevicemakerasapartner,aRazorandBladeoranInvertedRazorandBladedesign,withclearagreementsonrevenuesharingwiththepartnerwouldbeessential.Ontheotherhand,iftheecosystemisattunedunderastandardizationframeworkintermsofdata,deviceindependentapplicationswouldbepossibletodevelop.Inthatcase,anInvertedFreemiumpattern can be adoptedwhere no revenue sharingwould be required, and inparallel, a Razor and Blade (or an Inverted Razor and Blade) designmay exist betweendevice‐applicationpartners.

 

 

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Chapter5:ConclusionsandFutureWorks

5.1.SummaryofFindingsandConcludingRemarks

Theresearchquestionofthethesiswas:

“Howtosystematicallydescribethecomplexrelationshipsamongactorsofthewearablehealthecosystem,andwhatchallengesthiscomplexityhasbroughtinhealthcareapp‐innovation?”

In this thesiswehavebrokendown thecomplex technologicalorganismof thewearablehealthecosystemintounderstandableanddistinguishablecomponents.Thisbreakdownhasenabledclassifyingtheindustryplayersinalayeredapproachdefiningwhatrolestheyplayintheecosystemandhowtheycollaboratewitheachother.WehavedevelopedtheEMKISframeworkbasedonthe“mattersofexchange”amongtheactors.Thisframeworkgivesaclearpictureofwhatanactor“gives”toothersinanecosystemandwhatdothey“get”inreturn.Wehavestudiedcasesofactors fromdifferent layersandrolesandstudiedthemunder this common framework to understand the differences and similarities in theirrevenuemechanisms.Inparalleltothis,wehavealsousedanexistingframeworkfromtheliteraturetocomparethebusinessmodel“designpatterns”ofthesamefirms.Intheend,wehavediscussedsomemajortechnicalandbusinessmodelchallengesforthehealth‐careapp‐innovators.

We have seen that players are emerging in all three (device, infrastructure, application)layers of thewearable ecosystem. Established IT companies such asMicrosoft, Samsunghighlighttheirpresenceistheinfrastructurelayereventhoughtheyarepresentinallthethree layers; we have therefore called them the “complete solution providers”. TheinfrastructurelayerisparticularlyanimportantplacetobefortheestablishedITcompaniesbecausethislayerisatthecenteroftheecosystemwhichconnectsboththedevicemakersandapplicationdevelopers.Ononehand, these companieshavea “multi‐sided”businessmodeldesignpatterntowardsemergingdevicemakers,providingthemthecloudservicestostoreandmanagethedataobtainedfromtheirdevicesinexchangeofmoney.Ontheotherhand,theirbusinessmodeldesignpatternis“open”towardstheapplicationdevelopers,i.e.theappdevelopersaregivenaccess(openAPI)tothedatatomakeinnovativeapplicationsfor the deviceswhich use their infrastructure/platform. In return of the access given todevelopers,thedevelopersaddvaluetotheplatformandmakeitmoreinterestingforthedevicemakerstochoosetheplatform.ThistrendiscommonamongtheleadingITcompanieswhosteppedintothewearablemarketandstillcompetingtogetagoodholdinit.Thistrendis based on the understanding of these companies about the potential of third partyinnovationinhealthcareappdevelopmentinthissector.

Asaresultofthecurrentmarkettrendsinthisindustry,wehaveanumberofopenplatformseachwillingtodevelopenrichedecosystemsaroundthem,withatargettoenclosealotof

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device makers on one side, and a lot of supported applications on the other. Thisphenomenonleadstoafragmentedgrowthofecosystemswithnoorlittleconveniencesforcross‐platformappdevelopment.This leadstoaseriousproblemfromtheperspectiveofend‐usersaswell,thatisthedevicedependencyoftheapps.Iftheecosystemscontinuetogrowinthisfragmentedwayracingtobetheplatform‐leader,itwillbeahindrancetotheoverall growth of the market, both for the end users, and also to the innovators. Theapplicationmarketneedstobedevice‐independent,andanyusershouldbeabletouseanyapp,ifhiswearablehasthesensorstheapprequires.Atpresent,thesituationisnotsuch.EvenifthedevelopershavetheopenAPIaccesstomostoftheplatforms,thereisnostandarddataformatthatalltheplatformsuse.Thisisarecurringchallengefordeveloperstomakehealthdataanalyticsappsformultipleplatforms.Thefragmentedgrowthofecosystemsisindividuallybenefitingtheplatforms,butnotbenefitinginnovationinappdevelopmentasawhole.Standardizationforthewearablehealthdataintermsofformats,unit,qualityetc.isimmediatelyrequiredinadditiontoopenplatforms.

Thesechallengeshavetheirimpactsonthebusinessmodeldesignpatternsofthenewcomercompaniesinhealthcareappdevelopmentaswell.Duetothedevicedependencyoftheapps,itisdifficultforappdeveloperstoemergeasanapplicationlayerplayeronly,andhence,theyhave to come up as a complete solution provider such as Empatica or Runtastic. If anewcomercompanystartstodevelopforapopularplatform,thereareotherchallenges,suchastheirmarketreachwouldbenarroweddowntoonlytheusersofthosedeviceswhichusethatparticularplatform.Inadditiontothat,thecompanywillhavenocontroloverwhattheusershavetopayintotaltobeabletousetheirapp,becausethatwoulddependonthepriceof the device. A solution could be to partner with another device maker and adopt anInvertedRazorandBladeapproachwithacleardefinitionregardingrevenuesharing.Inthatcase,thetargetcustomerswouldbenarroweddowntothosewhowouldbuythedevicesonlyformedicalneeds.

However,ifthedatawerestandardized,thesecompanieswouldhavetheflexibilitytoadoptanInvertedFreemiumapproachwheretheywillsell theapponly,andanyuserwiththerequiredsensorswouldbeabletousetheapp.Norevenuesharingwouldberequiredinthiscase.However,theycaninadditiontohis,partnerwithadevicemakerandadoptaRazorandBladeapproachtargetingthosecustomerswhoonlyneedadevicetobeabletousethatapp.Inthisway,thepotentialcustomerreachfortheseappswouldbroadenbyusingamixeddesignpattern.

In conclusion, we can affirm that collaboration among actor to take steps such asstandardizing the health data from wearables, has become essential to control theconsequencesofthefragmentedgrowthofecosystemsintheindustry.Sincenoplayerinthisnewindustryissufficientlydominanttoinitiateandcontrolthestandards,theplayersneedtoco‐operateeachotherinestablishing,developing,andsupportingaproperstandardforthehealthdatawhichalltheplatformswouldfollow.Onlyinthisway,thenotionofopeninnovation in wearable healthcare would be meaningful and the development of thisindustrywouldbesustainable.

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5.2.FutureWorks

Inthis thesiswehaveconcludedthat there isan immediateneedofcollaborationamongactors towards standardization for the physiological data generated from wearablehealthcare devices in order to achieve an interoperable, device‐independent appdevelopmentecosystem.Thiswouldenablesustainablebusinessmodelsforalltypeofactorsinthewearablehealthdomain,especiallytheappdevelopers.

In terms of research, the future works would be on developing the standards for thesevarious types of health data. The various kinds of physiological data that the differentwearablesinthemarketgeneratecanbeenlisted.Astandardframeworkneedtobeworkedoutintermsofdataformats,units,qualityetc.Theacademiacancontributeinthisregard.

Intheindustry,theleadingITcompanieswhoareinthewearablemarketaswell,needtoagreeonastandardizingbody.TheContinuaCertificationprogramasmentionedinChapter4couldbeextendedforwearabledevices.TheycanalsocollaboratewithIEEEindevelopingthese standards for wearables. The app developers should draw the attention of theinfrastructurelayerplayersaddressingtheissuesidentifiedinthisworktoformasolutionthatwouldbenefiteverymemberoftheecosystem.

 

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