Development of a Portable Robot and Graphical User Interface forHaptic Rehabilitation Exercise

Rajibul Huq, Elaine Lu, Rosalie Wang and Alex Mihailidis

Abstract— This paper presents progress in the developmentof a robotic system for post-stroke upper limb rehabilitation.It is a portable, lower cost, actuated upper limb roboticrehabilitation device, which is being developed to meet the needsof stroke therapists and their patients. The developed systemprovides force feedback for haptic rehabilitation, applying bothresistive and assistive forces for more targeted exercises for post-stroke patients. The proposed system includes a graphical userinterface with both manual and automatic control of the roboticdevice for upper limb exercise. The automatic control makesuse of artificially intelligent systems to adapt the treatmentwith minimal interventions of therapists. It also provides virtualrehabilitation games for stroke patients. A focus group studywith therapists was conducted to assess the developed system.Additionally, individual therapist sessions are in progress tofurther develop the graphical user interface and virtual realitygames. These and other planned studies will offer valuableinsights of therapists and stroke survivors for the furtherdevelopment and commercialization of the robotic system.

I. INTRODUCTION

Every year stroke affects 16.3 million people worldwide.It is the leading cause of permanent disability in adults [1].Among those who have experienced a stroke, there are anestimated 64.5 million stroke survivors who live with varyinglevels of disability and need assistance for activities of dailyliving (ADL) [1]. Approximately 80% of these have motordeficits, resulting in serious disability [2]. The burden of carefor stroke survivors is high for the healthcare system andfamily members or caregivers [1], [3].

Often the upper limb is impaired as the brain arteryresponsible for blood flow to areas controlling the upperlimb is frequently involved in a stroke [4]. Therefore it isimportant for the upper limb to be supported and rehabilitatedto perform ADLs, such as eating, bathing, and dressing.

Rehabilitation robots have been developed to alleviate theburden on therapists and healthcare systems, while simulta-neously increasing patient access to rehabilitation. Severalstudies have shown similar improvement in stroke survivoroutcomes with the use of rehabilitation robotic devices(RRD) when compared with conventional therapy [5], [6],[7]. RRDs are able to offer treatment features that wouldbe difficult to achieve with conventional therapy [8], [9].Features such as exact repetitive movements, programmableresistance levels, objective evaluation, and movement sensingcapabilities could increase the value of RRD and hence

This work was supported by an NSERC-CIHR Collaborative HealthResearch Program grant and Quanser Consulting Inc.

The authors are with the Intelligent Assistive Technology and SystemsLab (IATSL), University of Toronto, and affiliated with the Toronto Reha-bilitation Institute, Toronto, Ontario, Canada

clinical acceptance. Although robots will likely never replacetherapists, they may be useful in aiding therapists or extend-ing rehabilitation to remote locations or to the home.

There exist several robotic devices for upper limb post-stroke rehabilitation [7], however, most of the systems arenot portable enough for home use or high costs restrictthem to specialized clinics. As a result, the concept ofextending rehabilitation to a remote location by optimizingthe engineering design of the robot still remains an ongoingresearch topic in rehabilitation engineering. Hence, the mainchallenge is in determining the best clinical efficacy for theleast amount of robotic complexity and functionality.

There are several control approaches to robotic ther-apy [10]. For example, a self-adaptive robot training methodis described in [11] where the system assists a user tocomplete a tracking task using a minimal assistance strategy.A decision theoretic approach is described in [12] where anintelligent system autonomously controls the resistive forceand target position to improve forward reaching capabilityof a stroke patient. The robotic therapy also employs virtualreality (VR) to engage the patients in repetitive motionexercise using 2D or 3D games [13]. Hence, the roboticsystems make use of VR games to engage and motivateusers with fun and meaningful activities [7]. The effectiverehabilitation games are adapted to accommodate disabilities,gradable for improving abilities and provide appropriatefeedback to enhance performance and encouragement.

With consideration of existing robotic systems and controltechniques, this work has three objectives:

1) To develop a portable robotic system with a hapticinterface that facilitates the concept of rehabilitation ata remote location, e.g., at a home.

2) To develop a graphical user interface (GUI) that in-tegrates different control techniques and VR games inthe same screen, and allows therapists to easily interactwith the system.

3) To evaluate the current system with therapists in afocus group study.

This work addresses all three objectives mentioned above anddevelops a portable 2D haptic robotics system for upper limbstroke rehabilitation. It also develops a GUI that includesmanual and automated haptic exercise as well as VR gamesfor rehabilitation. Furthermore, a focus group and individ-ual sessions are conducted to obtain therapist feedback onpossible future improvements to the robotic system.

The rest of the paper is organized as follows. SectionsII and III describe the robotic device and GUI. Section IVpresents therapist feedback on the developed system. Section

The Fourth IEEE RAS/EMBS International Conferenceon Biomedical Robotics and BiomechatronicsRoma, Italy. June 24-27, 2012

978-1-4577-1198-5/12/$26.00 ©2012 IEEE 1451

V outlines the future work directions and finally, Section VIsummarizes this work.

II. ROBOTIC SYSTEM

A. MethodThe robot has been developed using a user-centred ap-

proach [14] which includes an international survey of thera-pists [15] to identify the design requirements of the roboticdevice. The development process also included our expe-riences with a previous prototype [16]. The detailed robotdevelopment steps can be found in [17]. The robotic devicehas been manufactured by Quanser Inc., a robotics companyin Markham, Canada.

B. Device DescriptionThe upper limb stroke rehabilitation robot prototype is a

two degrees of freedom (2DOF) impedance controlled planarhaptic robotic device (see Fig. 1(a)). The robot’s casingdimensions are approximately 32x14x39cm and its weight isabout 17.3kg. Two DC motors attached with optical encoders

(a) 2DOF robot (b) Two link manipula-tor model of the robot

Fig. 1. Robotic device

drive the robotic arm through a capstan. The robotic arm isconnected to a plastic end-effector, which is controlled by apatient during a rehabilitation exercise. The maximum forcethat can be applied through the end-effector using a motor ofthe robot is 52.8N. The optical resolution at the end effectoris 0.013 mm/count at home position. This end effector iscustomizable for different patient requirements.

The robot is equipped with a tethered and movable externalemergency stop to shut off power for safety purposes. Therobot has a USB interface with a computer which makes itpossible to operate the robot with a laptop or tablet device.

The robot is operated by QuaRC (Quanser’s Rapid ControlPrototyping) software and it can be used with other program-ming languages using standard communication protocols,e.g., TCP/IP and shared memory.

C. Forward Kinematic ModelThe forward kinematic model (FKM) of the robot is

described using the two link manipulator model shown inFig. 1(b), where the arm (link) lengths are defined as L1=254mm and L2=266.7 mm. The link angles with x-axis aredefined as θ1 and θ2. The geometric design criteria of therobot body imposed the following constraints on θ1 and θ2.

θ1 > θ2 (1)140◦ ≥ θ1 − θ2 ≥ 40◦ (2)90◦ ≥ θ1 ≥ −50◦ (3)50◦ ≥ θ2 ≥ −90◦ (4)

Eqns. 5-6 describe the FKM of the robot and Eqn. 7 showsthe Jacobian matrix.

x = L1 cos θ1 + L2 cos θ2 (5)y = L1 sin θ1 + L2 sin θ2 (6)

J =

[−L1 sin θ1 −L2 sin θ2−L1 cos θ1 −L2 cos θ2

](7)

The kinematic equations result in the robot workspace shownin Fig. 2.

Fig. 2. The workspace of the robot

D. Haptic Effect

The haptic effect is applied using Eqn. 8, where the force,F = [Fx Fy]

T to be applied on the end-effector is convertedinto torque, τ = [τx τy]

T and then the corresponding current,I = [Ix Iy]

T is applied on the motors. The torque amplifyingfactor of the capstan is denoted as Ka=30 and the torqueconstant of the motor is found Kt=0.115 N-m/A from themotor specification.

τ = −JTF (8)

I =τ

KaKt(9)

The following force model is used to create the haptic effect.

F = Fg − Fd + Fs

= Fg −KdV +KsP (10)

Here, Fg = [Fx,g Fy,g]T is a constant global force, Fd =

[Fx,d Fy,d]T is the damping force which is proportional to the

end-effector velocity (V = [Vx Vy]T ), and Fs = [Fx,s Fy,s]

T

is the stiffness effect which is proportional to the positionvector of the target (P = [Px Py]

T ) with respect to the end-effector. The proportional constants Kd and Ks denote thedamping and stiffness coefficients, respectively.

III. GRAPHICAL USER INTERFACE (GUI)

Fig. 3 shows the GUI developed for the robotic system.Fig. 3(a) depicts the control interface for the therapists andFig. 3(b) shows the resizable visual feedback interface fortheir patients. The visual feedback interface shows real-time positions of the robot end-effector and target usinga circle and rectangle, respectively. As the patients mayhave vision impairment, the feedback window also providesoptions for changing colors of the end-effector, target, and

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(a) (b)Fig. 3. GUI for the robotic system

background to match patients’ visual capability. The overallexercise duration is also shown in the bottom-right cornerof the visual-feedback interface. The GUI includes therapistinterfaces for both manual and automatic haptic exercises.For each exercise it shows exercise information for perfor-mance evaluation. It also provides games that employ VRfor encouraging the patients to be engaged in the repetitivemotion exercises. A preliminary version of the GUI and VRgames were evaluated by an experienced neurorehabilitationtherapist (Dr. Debbie Hebert, Toronto Rehabilitation Insti-tute). Changes were implemented as a result and presentedhere as follows.

A. Haptic

Fig. 4 shows the haptic interface, where therapists canselect different force control parameters of the robot. A

Fig. 4. Haptic control interface

patient can perform an exercise with or without force feed-back which is set by the Haptic (touch) feedback panel. Anexercise with force feedback can further set force type, whichis either resistive or assistive. The Resistance panel specifiesdifferent resistance levels equivalent to pushing differentobjects in real life, e.g., resistance equivalent to pushing ahard cover book is set approximately to 5N. Resistance isimplemented as damping force which is proportional to end-effector speed and directed opposite to its velocity, i.e., Eqn.10 uses Fg = [0 0]T , Fs = [0 0]T , and Kd > 0. Hence,the Resistance panel sets a different damping coefficient Kd

(N.s/m) corresponding to pushing each object.The Assistance panel specifies three discrete levels of

assistance, namely, Low, Medium, and High, for helping apatient to perform exercises. The robotic device generatesan attractive force proportional to the distance between theend-effector and the target position for assisting the patientto reach the target points, i.e., Eqn. 10 uses Fg = [0 0]T ,Fd = [0 0]T , and Ks > 0. The magnitude of the attractiveforce is clipped to three different levels, 3N, 7N, and 12N,corresponding to Low, Medium, and High spring constantKs (N/m) options in the Assistance panel.

B. WorkspaceFig. 5 shows the robot workspace in white. It also shows

the current end-effector position as a red circle. The gray

Fig. 5. Workspace interface

region inside the workspace denotes user-space, which showsthe maximum distance from workspace-center at any di-rection covered by the patient in an exercise session. Thisinterface is also used to set a target position to be reachedby the patient. The button shown below the Set Target panelis used to start an exercise.

C. Performance dataFig. 6 describes the performance data shown in the GUI.

Fig. 6(a) shows the real-time exercise data which includeinstantaneous speed of the end-effector, error (deviation)from the optimal path towards the target, and smoothnessof the end-effector trajectory. Smoothness of the trajectoryis calculated as a function of change in the end-effector’s mo-tion direction. Frequent changes in motion direction result inlower smoothness values. The GUI provides plots of average

(a) Exercise data

(b) Exercise data plot (c) Workspace of the robotFig. 6. Performance data

statistics of exercise data. It includes a pie chart of targetsreached and missed in an exercise, average velocity, root-mean-square (RMS) error, and trajectory smoothness to reacheach target in an exercise. The exercise data can be saved assession data where speed, error, and smoothness are averagedover all targets used in an exercise. This session data canbe compared with future data for performance analysis overtime. For example, Fig. 6(c) shows a comparison of averagespeed obtained from three different sessions for a patient.

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D. Manual exercise

The GUI provides a manual mode of exercise whichindicates direct supervision of movement exercise by atherapist. In this mode, the therapist sets the force parametersand target locations, and decides when to stop an exercise.There are two options available for performing a supervisedexercise: 1) Interactive and 2) Waypoint. These options aredescribed below.

1) Interactive exercise: This mode of exercise can beperformed with or without a target position. In the absence oftargets, the patient randomly moves the end-effector insidethe robot workspace. The user-space is also updated withthis movement. Different haptic effects can be applied onthe end-effector during the movement. For example, Fig. 7(a)shows an instance where the exercise is performed withoutany target and a resistance equivalent to pushing 5 hardcover books is applied on the end-effector. In the case ofassistance without a target, the system applies force towardsthe current motion direction of the end-effector, i.e., Eqn.10 uses Fg = [0 0]T , Fs = [0 0]T , and Kd < 0. Fig. 7(b)

(a) Without target (b) With targetFig. 7. Interactive exercise

shows an example of goal directed exercise where a targetposition is specified (green rectangle) in the workspace tobe reached by the patient. In this example, Low assistance isalso applied to help the patient to reach the target position.Note that the user-space (gray region), which is updatedwith the robot movement, can play an important role ina supervised exercise. A therapist can assign a new targetposition outside the user-space to extend upper limb mobilityof a patient.

2) Waypoint exercise: In this mode of exercise, a therapistcan define a set of target positions (or waypoints) to bereached by a patient following a predefined sequence. Thetherapist also sets a resistive or assistive type of force anda time constraint to reach each target location. The Haptic(touch) feedback panel is used to specify the force type andthe Set Target panel is used to define the waypoint position(blue rectangle) and the time constraint (see Fig. 8(a)).Fig. 8(b) shows a result of a waypoint exercise where fourwaypoints are specified at four corners (green rectangles).The patient started from the workspace-center and followedan anti-clockwise sequence from the top right waypoint andfinally returned to the starting waypoint. Waypoint exercise

(a) Setting a new waypoint (b) End-effector trajectoryFig. 8. Waypoint exercise

can play an important role in some cases where a therapistinitially helps the patient to follow a trajectory for very lowlevel recovery of the affected post-stroke upper limb.

E. Automated exercise

In this mode of exercise a therapist only defines a setof target locations and their associated time constraints.An intelligent system autonomously applies assistance orresistance to the end-effector and repeats the same targetlocations until the patient becomes fatigued. Unlike manualmode of exercise, the intelligent system decides when to stopan exercise based on patient fatigue. Fatigue is estimated as afunction of end-effector speed and error to reach each targetlocation. Fig. 9(a) shows an example of an automated for-ward reaching exercise. Fig. 9(a) shows the target locations

(a) User-space (b) Fatigue

(c) Speed (d) ErrorFig. 9. Automated exercise

(blue rectangles) and the updated user-space generated by theend-effector movement. Fig. 9(b) shows the estimated fatigueto reach the successive target locations. Fig. 9(c) and 9(d)depict corresponding mean speed and RMS error to reachthe target locations. Overall, fatigue is high if velocity orerror is high. The intelligent system autonomously appliesresistance or assistance to match patient performance andstops the exercise when fatigue reaches its maximum limit,which is set to 10 in this example. The main motivationof the automated system is that a therapist needs not to bealways present with a patient; rather an intelligent systemcan guide the patient through simple reaching exercises andthis may help to extend rehabilitation to a remote location.Our future work will improve the intelligent system in that

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target locations and time constraints can also be set by theintelligent controller.

F. Video gamesThe GUI also includes video games to encourage the

patient to perform repetitive motion exercises. Fig. 10(a)shows an example of a game called, Bouncing Ball. The

(a) Bouncing ballgame

(b) Decoration game (c) Car driving game

Fig. 10. Video games

patient controls a bat position with the robot end-effector toprevent a bouncing ball from hitting the ground. There areseveral parameters that can be varied to change the difficultylevel of the game. The speed of the ball and haptic effect(resistance or assistance) can be changed to improve controlaccuracy and muscle activity. The game GUI provides scores,which show the numbers of balls returned and missed, asfeedback to the patient and therapist. This game also includesan AI system that automatically changes ball speed andhaptic effect to match user performance.

Fig. 10(b) shows another example which is a strategic typeof game. The game GUI includes some objects common to aliving room. The objects are initially placed randomly in theenvironment. The patient can control a cursor with the end-effector to select and reposition an object in the environment.The overall goal of the game is to rearrange all the objectsso that the environment looks like a familiar living roomenvironment. It is believed that the tasks of selection andrepositioning of an object will increase a patient’s controlaccuracy. This game also includes different haptic effects.For example, the patient will feel resistance while goingthrough an object or the boundary. It can apply differentresistance levels to different objects. The system can alsoapply assistance to help the patient to reach a particularobject position in the environment.

Fig. 10(c) shows a car driving game. The main goal ofthe game is to control the speed and position of the car toavoid collisions with the obstacles placed on the road. Theforward motion of the end-effector controls the speed of thecar and sideways movement controls left/right position ofthe car. The game GUI provides several options to changethe difficulty level of the game. For example, the obstaclesize and position can be randomly changed to improvecontrol accuracy. Different haptic effects can also be includedto improve muscle activity. For example, the game GUIprovides options for applying road resistance and collisioneffects. This GUI also provides scores so that the patient isencouraged to play the game for longer duration.

IV. THERAPIST FEEDBACK

A group of stroke therapists was consulted to get theirfeedback on the features of the robotic prototype. The

purpose of the focus group was to refine the features,specifications, and user interfaces of the developed roboticdevice.

A. Methods

The participants included therapists (physiotherapists andoccupational therapists) from a local rehabilitation hospitaland members from the design team, and the moderator for thesessions was a professional moderator. Therapists includedin the study had to have at least two years of experienceworking in upper limb rehabilitation with stroke patients.

The session was 80 minutes and conducted in three steps:1) general discussion on the current state of upper limb strokerehabilitation technology; 2) description of and interactionwith the developed robotic system; and 3) feedback on thesystem. This section will mainly focus on the feedback step.Most of the therapists tested the robot with and withouthaptic effect (force feedback). The haptic effect was set toprovide maximum 10N of force feedback to ensure safety ofthe users.

B. Results

Seven therapists participated in the focus group. Therewere three physiotherapists and four occupational therapists.All had Master’s degrees in their fields. Four had 2-5 yearsof experience in stroke therapy, two had 6-10 years ofexperience, and one had more than 10 years of experience.They had all treated populations of adults (18-64 years old)and older adults (65 years old and over). One had experiencein treating youth (11-18 years old). They had experienceworking in a rehab hospital setting, with two in acute caresettings. In addition, two had worked in long-term care, threehad worked in outpatient clinics, two had worked in homecare, and one had worked in a home-based private practice.The following sections briefly describe their feedback on therobotic device and GUI for stroke therapy.

C. Robotic device

System size & safety: Most therapists felt that the devicewas too heavy and large for home use. They found that thedevice is unsafe for clients to use alone, because of visibleelectrical wiring, but predominantly because patients may nothave sufficient trunk support. The device would need to havemore rounded edges to prevent injury. They also suggesteda longer forearm support end-effector for user safety.

Degree of freedom: The current system can mimic onlyplanar types of exercise, which was felt to be insufficient.Therapists would ideally like to see a 3DOF system, however,considering cost trade-offs of a 3DOF system and haptics,they opted for haptics.

Range of motion: Most of the therapists felt that thefull range of motion (ROM) of the robot workspace is notadequate for different planar exercises. One therapist, how-ever, mentioned that this could be solved by repositioningthe patients’s seat position for a different exercise.

Monitoring postural compensation: All felt that therobotic system needed to be equipped with additional sensors

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to detect compensatory postural movement while performingthe exercises with the robot.

Haptic effect/Force feedback: Some therapists felt thatthe main feature of the device was adequate force feedback interms of resistance. The therapists, however, also mentionedthat they would prefer assistance over resistance in a hapticrehabilitation device. The therapists also expected that therobotic device would measure the force applied by a patienton the robot end-effector, which is not available in the currentsystem.

Biofeedback: Biofeedback was seen as a desired featureby some therapists to allow therapists and their patients tohave information relating to joint position, muscle use andactivation. The current system, however, does not provideany biofeedback

Cost: The therapists suggested that the device cost shouldnot exceed $5000 for clinical use. One of the therapists alsosuggested that she could recommend her patients using thisdevice for home use on a rental basis for $50 a month.

D. GUI

The therapists did not have a long time given time restric-tions for the focus group to test the exercise modes and videogames. As a result, individual feedback sessions are beingarranged to evaluate the GUI with the same therapists whoparticipated in the focus group study. The following sectionsinclude some of the feedback from the focus group and fromtwo individual sessions.

Haptic interface: Most of the therapists felt that thecurrent haptic interface is satisfactory to control resistanceand assistance. They also emphasized adding more real worldobjects for resistance control. It was also discussed that theforce applied for assistance should be moderate enough sothat the patients can keep up with the end-effector motion.

Performance analysis: The therapists felt that the numeri-cal performance data shown in the GUI was not good enoughfeedback, as sometimes these numbers were not intuitive.They also expected data feedback in report format, e.g.current ROM of the patient, which can be printed for furtheranalysis. Some of them suggested having a randomizedthree minute video recording with timeline information tounderstand how the patient was using the device.

Exercise: The therapists seemed to be interested in thedifferent modes of exercises provided with the GUI. Someof them argued that the fixed planar exercise is usuallyapplied for the first stage recovery of post-stroke patients.The other stages require the exercise plane to be oriented atdifferent angles. The developed robotic device, however, canbe positioned either vertically or laterally and thus it providesonly two planes of exercise. Overall, they think the exercisewill be convincing if it can be shown to improve recoveryof stroke patients.

Video games: Most of the therapists felt that video gameswould be an important part to a rehabilitation robotic system.They mentioned that the games provided with the GUIwere visually motivating and would help their patients bemore compliant with exercise programs. Some of them also

mentioned that the games could be cognitively challengingfor their patients. Cognitively challenging games, however,could have both positive or negative effects depending onthe patient’s needs. Some of the games may require a certaindegree of cognitive ability, and thus restricting some patientsfrom using them. Alternatively some therapists may like toincorporate some cognitive exercise in the games so that theyare stimulating cognitive skills as well as motor recovery. Ourproject consultant therapist, Dr. Debbie Hebert commentedthat different games could have different activities for differ-ent treatments. For example, clients with apraxia could useactivities that require sequencing in ’real life’ tasks - likedressing, making a meal, etc.; clients with attention problemscould use activities that require scanning - like the drivinggame.

Human robot interaction: The therapists mentioned thatthe current system lacks the human robot interaction feature.They suggested modeling a virtual therapist/coach avatar us-ing the picture or voice of a therapist to guide and encouragea patient throughout the therapy. An avatar could also be apart of the postural compensation monitoring system to alertpatients if their body positions deviated from the prescribedprogram.

E. Discussion

The current system is at a developmental stage and thera-pist feedback shows an overall conceptual acceptance of thedeveloped system. There exist several scopes of improvementrequired for the robotic device and GUI. It should benoted that none of the therapists had prior experience withrehabilitation robotics and it may have been hard for themto discuss the device without having a reference with whichto compare. In addition, they had limited time to try theprototype during the focus group. Not having this referenceand not testing all the features of the robot themselves, maylimit the extent to which they can give detailed feedbackon the current prototype. Nevertheless, these therapists haveexperience in neurorehabilitation and in working directlywith stroke survivors, so their feedback is valuable to helpguide design.

Therapists who do not have experience with robotic re-habilitation may have a certain standard in mind beforebeing open to using robotic therapy with their patients. Toovercome this problem, as one therapist suggested, clinicscould be set up with robotic devices which would allowtherapists to experience using the device.

Overall, the therapists seemed enthusiastic about devel-oping a RRD. Many felt that one of the advantages of theprototype was that it could help those with more physicalimpairment, as there is a lack of treatment options to aidthese individuals. The therapists saw the potential in theproject and would like to participate further and see theclinical trials.

V. FUTURE WORK

The focus group study shows that the current system canbe improved in many ways. Our future work will be directed

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towards fulfilling the therapists’ suggestions and conductingmore studies with therapists and stroke survivors to furtherimprove the design. Hence, we define the following futuregoals to be achieved.

A. Robotic system

The device needs to be improved in safety, workspace,portability, and usability. We note that the device also re-quires a better method of securing it to a table. The end-effector should be better designed to support and secure theparetic hand.

B. GUI

The haptic interface needs to be improved by adding morereal-world resistance levels realizable by the patients andtherapists. The assistance force levels also need to be tunedwith respect to real clinical treatments. The 3D viewer forreal-time visual feedback needs to be improved to meet eachpatient’s visual perception capability. In case of poor visualperceptual skills, the system needs to incorporate audio feed-back for assisting the patients. The GUI also needs to provideexercise data in useful report format for further analysis. Itshould include different games with different activities tomatch requirements of different patients. Finally, it shouldincorporate a virtual therapist/coach avatar to encourage thepatient throughout the therapy.

C. Ongoing and future studies

A study that is currently in progress involves individualtherapist trials of the GUI and VR games to gain their feed-back to improve the therapist and stroke survivor interfaces,explore how therapists think a RRD can be integrated intoclinical practice and better define the clients who mightbenefit from robotic therapy. Feedback from patients isequally important and recruitment is underway for a strokesurvivor focus group to evaluate the RRD. Additionally,a clinic for upper limb rehabilitation is planned so thattherapists and their patients will have the opportunity inthe future to work with improved versions of the RRD ina cutting-edge treatment development and evaluation clinicsetting.

VI. CONCLUSION

This work presents preliminary developments of a portablerehabilitation robot for upper limb post-stroke patients. Therobot also provides haptic feedback for targeted treatment ofthe paretic upper limb. The system also provides a GUI thatincludes both supervised and automated reaching exercisesusing the developed robotic device. The GUI also includesvideo games to motivate the stroke survivors to be engagedin the movement training.

This work has also included a focus group study where ex-perienced therapists expressed their views on the developedsystem. The therapists were enthusiastic about the developedrobotic system; however they felt that there were manyscopes for improvements.

Our future work will address the therapists’ feedback tomake this portable upper limb RRD a step towards the

development of an appropriate tool for therapists to use instroke therapy.

ACKNOWLEDGEMENTS

The authors would like acknowledge Quanser Inc. for theirin-kind support in manufacturing the device.

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[17] E. Lu, R. Wang, R. Huq, D. Gardner, P. Karam, K. Zabjek, D. Hebert,J. Boger, and A. Mihailidis, “Development of a robotic device forupper limb stroke rehabilitation: A user-centered design approach,”accepted in Paladyn. Journal of Behavioral Robotics.

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