The Internet of Things for Health Care

Dr. Songpol Ongwattanakul

Acting Director

The Center for Biomedical and Robotic Technology Loboratory (BART LAB)

Faculty of Engineering

Overview

• Introduction

• IoT for Healthcare Trends

• Services and Applications

• Data -> Big Data

• What do we do?

• Obstacles

• Conclusions

Introduction

IoT for Healthcare Trends

• Forbes: • $117 Billion Market For Internet of Things In Healthcare

By 2020

• Business Insider:

IoT for Healthcare Trends

• Potential applications: • Remote health monitoring

• Fitness program

• Chronic diseases and elderly care

• IoT-based healthcare services are expected to • Reduce costs

• Saving on energy, labor, and time.

• Increase the quality of life (QOL) • QOL = The individual’s perception of their position in life in the

context of the culture and value systems in which they live and in relation to their goals. [WHO]

• Enrich the user’s experience (UX) • UX = A person's perceptions and responses that result from the

use or anticipated use of a product, system or service. [The

international standard on ergonomics of human system interaction, ISO 9241-210]

Services and Applications

• IoT Healthcare Services: • Ambient Assisted Living (AAL)

• The Internet of m-Health Things (m-IoT)

• Adverse Drug Reaction (ADR)

• Community of Healthcare (CH)

• Children Health Information (CHI)

• Wearable Device Access (WDA)

• Semantic Medical Access (SMA)

• Indirect Emergency Healthcare (IEH)

• Embedded Gateway Configuration (EGC)

• Embedded Context Prediction (ECP)

Services and Applications

• IoT Healthcare Applications: • Glucose Level Sensing

• Electrocardiogram Monitoring

• Blood Pressure Monitoring

• Body Temperature Monitoring

• Oxygen Saturation Monitoring

• Rehabilitation System

• Medication Management

• Wheelchair Management

• Imminent Healthcare Solutions

• Healthcare Solutions using Smartphones

Data

• Data = Data + Metadata

• Metadata = Data about the data

• What to do with Data? • Statistics: Hypothesis, Modeling, Forecasting, etc.

• Data mining: Decision tree, Classification/Clustering, Association, etc.

• Goal = Knowledge about your services • What are the factors contributed to effectiveness?

• Know your customer.

What do we do?

• At BARTLAB, we do medical robots.

• Medical robot => Professional Service Robot

• Example 1: Medical Device

Monofilament Project

AGV Project

• Example 2: Hospital Logistics

• Monofilament Project • Under clinical trials phase.

• Expect to be in service by the end of 2017.

• AGV Project • 3rd Generation platform

• ISO 13482 compliance

• Limited vertical transportation (require IoT elevator interface)

• Note: all communications are encrypted with an asymmetric pair of keys as a baseline for security.

Obstacles of IoT for Healthcare R&D

• For medical/wellness device and system, • Ethic issues

• Animal and human testing

• Data collected from human subject

• Clinical trials • Normally expensive and take long time

• FDA Certification • Tons of documents

• HL7 (medical device only) • HL7 Standards provide a framework for the exchange,

integration, sharing, and retrieval of electronic health information.

Conclusions

• Opportunity for IoT Healthcare in Thailand • Novelty Healthcare Devices/Systems

• Healthcare Applications for better QOL

• Medical Hub

• At BARTLAB, Mahidol University, we would like to help good ideas become good benefits of mankind. Therefore, we offer, • Consultation services

• Prototyping services

• Testing services

for various kinds of medical devices both standalone and IOT. Please visit www.bartlab.org for more information.