OVERVIEW

This area of research seeks to leverage the technological advancements in Internet of Things (IOT) to facilitate and enable the effective and efficient delivery of safe, quality healthcare service. Through researched solutions on the implementation, use, and impact of health information systems (cloud-based IOT systems), we seek to improve the quality of life of patients by enabling their independence and self-reliance, facilitating individualized healthcare delivery, slowing down the health decline of chronic patients by ensuring their compliance to treatment programs, and improving the physiological well-being of the general population. This theme of research brings together academic researchers from different disciplines as well as healthcare professionals, industry partners, policymakers, and the broader population, to advance research in healthcare.

The projects under this theme are supported by the following grants:

• EMPOWERing Patients with Chronic Disease, NUS Principal Investigator, $2,050,274.40, (National Health Innovation Challenge Programme Office) in collaboration with Singhealth Regional Health System and Singhealth Polyclinics [2019-2022]
• Next Generation of Digital Nudging Design for Active Aging, Principal Investigator, $20,000, University of Sydney-NUS Partnership Collaboration Awards (PCA) [2019-2020]
• Health Informatics Internet of Things (IoT) Platform, $1,100,000 (Dean’s Start-up Strategic Initiative Fund) [2017-2019]

PROJECTS

• iMovin' Intervention Platform[Read More]

  One of our current projects involves the development and testing of iMovin’, a smartphone application paired with a wrist-worn fitness activity tracker to offer customized services to various user groups depending on individual preferences. Insufficient physical activity is widely recognized as a pressing health issue, particularly in Singapore. iMovin’ aims to promote physical activity by taking into consideration a user’s personality and habits before determining the services and notifications that should be displayed to the user upfront. Using an adaptive algorithm, these users are profiled periodically by the app through regularly administered in-app questionnaires and activity trackers that passively track and collect daily activity data. This non-invasive technology gives individuals easy access to services that enables monitoring of their own physical activity routines.

  iMovin’ is available for use on both iOS and Android. To use the app, users pair it with a fitness activity tracker to provide their daily activity data. This information is then sent to a secure backend service that provides real-time analysis and regularly determines the most appropriate services for each group of users using our proprietary algorithm.

  Currently, we have successfully conducted a pre-trial test with 30 participants for Version 1.0 of iMovin’ and we are quickly moving on the next stage to release Version 1.1. In the upcoming version, we have incorporated new features and architecture overhauls while addressing issues based on feedback from the pilot. This new version will be tested on a sample population of 100 participants in a controlled trial, to assess the efficacy of the algorithm for different identified user groups.

  While iMovin’ is inexpensive, portable and easy to use, the key to success of this project would be assessing if individuals will be motivated to use the mobile app over the long term. In future iterations of the project, we plan to not only add new modular features to iMovin’s suite of accessible services but also deploy the iMovin’ service to other target populations in Singapore.

• Digital Processing Speed Test[Read More]

  This study aims to develop a digitalised cognitive impairment screening application that allows health practitioners to efficiently conduct cognitive impairment assessment for participants and to assist the early detection of cognitive impairment (CI), particularly in a community-based setting. The literature shows that while cognitive screening tests are used to detect CI, there is no measure of processing speed, which is prevalent in patients with vascular cognitive impairment (VCI) and the screening is mostly conducted in a hospital setting which prevents the efficient screening of individuals who do frequent hospitals.

  Our application combines two research streams. First, the development of a cognitive screening test that incorporates artificial intelligence pattern recognition algorithm with automated voice instructions in 3 languages (English, Malay and Mandarin) for the assessment to be carried out with minimal human intervention. Second, we developed an improved screening test based on a paper-pencil cognitive screening test that has been demonstrated to accurately classify VCI. This test includes a symbol based test which requires participants to input the corresponding digits into the device with a stylus. While this test can be scored manually, it is time consuming and does not detect the processing speed of the participant.

  We have built a prototype application that combines both aspects and is able to provide nuanced insights based on the processing speed captured. The technology developed in this study may be implemented in large-scale research studies of ageing- particularly dementia, and have the potential to provide novel insights into the early stages of memory decline.

  Work is still in progress to further gather non-identifiable data on individuals with or without chronic diseases, dementia other diseases in order to refine the automated predictive technology and conduct machine learning. We strive to work with collaborators interested in testing our technology to ensure digitalized screening applications become widespread and practical for practitioner use.

PEOPLE

• PRINCIPAL INVESTIGATORS / CO-PRINCIPAL INVESTIGATORS / COLLABORATORS

  Teo Hock Hai

  Stanley Kok

  Tan Swee Lin, Sharon

• RESEARCH ASSISTANTS / RESEARCH ENGINEERS

  Ma Pengfei

  Munirah Bashir

  Wang Chen

• PhD STUDENTS

  Ong Zhi Quan

• STUDENT ASSISTANTS

  Dylan Tan Hong Tai