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NUS-ISS Learning Day 2018- Integrating IoT and AI for urban health solutions
1. Integrating IoT and Artificial
Intelligence for Health
Solutions
Smarter Health Solutions for a better tomorrow
#ISSLearningDay2018
Dr. Matthew Chua, NUS-ISS
13 July 2018
2. About Me…
• PhD, Biomedical Engineering from
NUS Faculty of Engineering
• Faculty at NUS Institute of Systems
Science
• Research Interests: Medical
Device, Robotics and Artificial
Intelligence.
• Heading Research in ISS and
Principal Investigator of over S$1
million grant funding
#ISSLearningDay2018
3. Agenda
• Introduction
• Case 1: Home-based mHealth Cardiac Rehabilitation
• Case 2: m-Health Fine-motor Skills Rehabilitation for
Stroke
• Case 3: Chatbot for Clinical Processes
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6. Problem Statements
• Coronary heart disease accounts for 30% of all worldwide
deaths
• Not all patients attend centre-based Cardiac
Rehabilitation programmes after discharge
• High drop out rates and non-adherence
#ISSLearningDay2018
7. Summary of Project
• Develop an integrated home-based mobile Health
(mHealth) cardiac rehabilitation (CR) programme
• Utilizes wireless sensor technologies like pedometer, heart
rate tracker, gyroscopes and sleep tracker
• In-built artificial intelligence help to remind, feedback and
track patients’ progress
• Monitored by clinicians at NUH
#ISSLearningDay2018
9. Case 2: m-Health Fine-motor Skills
Rehabilitation for Stroke
#ISSLearningDay2018
10. Problem Statements
• The first 6 months post stroke is critical in aiding patients
regain motor skills
• Most patients cannot afford time or money for daily
rehabilitation at centres
• Fine-motor skills of hands cannot yet be tracked
consistently in most gamification systems
#ISSLearningDay2018
11. Summary of Project
• Development of a m-Health Hand Rehabilitation System for Stroke
Patient Recovery
• Integration of Infrared-based camera tracking system, machine
learning, gamification elements and virtual instructor-led training.
• A system that can be taken home and has fun, easy-to-use, and
interactive training programmes. Adherence to programme and
recovery can be tracked remotely by a healthcare provider.
• To pilot the system in the community partners, primarily in Stroke
Support Station (S3), supported by secondary partners such as Lion’s
befrienders and Disabled People’s Association Singapore.
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12. Overview
• An Intelligent Hand Tracking System with Therapist-Designed Game-
based Rehabilitation Programmes for Stroke Patient Recovery
• Ability to capture the fine motor skills and joints of the hand
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15. Problem Statements
• According to the Ministry of Health Website, average
waiting time of 92 minutes for both registration and
general consultation in local polyclinics and hospitals
• Bottleneck caused by the rate at which patients can be
seen by doctors.
• This long waiting time contributes to a poor quality of
healthcare experience
#ISSLearningDay2018
16. Summary of Project
• Develop a medical chatbot application system with
integrated A.I. and medical knowledge base to assist in
clinical consultation.
• Reducing registration, waiting and consultation time,
improving patient’s satisfaction of the healthcare service.
#ISSLearningDay2018