Health Internet of Things

Qing Zhang
Team Leader
Health Internet of Things

The Health Internet of Things (HIoT) team have expertise in data extraction from internet connected sensor and health monitoring devices to perform data mining and data analytics using machine learning, artificial intelligence to develop new or translate metrics to better determine health monitoring and management of home-based care for age-related and mental health conditions.

Our Science
As our population ages thanks to advances in medicine, therapeutics and devices, there’s a pressing need to support older people to live independently in their own homes for longer. The cost and lack of residential care placements are additional factors that will influence families to look and adopt assistive technologies to support their parents at home. As health and lifestyle monitoring technologies are becoming embedded in our daily life and internet connectivity is becoming pervasive, the baby boomers who are readily adopting these technologies wanare you at their homes to be smart to prolong a healthy lifestyle.

With recent advances in wireless sensor monitoring technologies, and mobile devices being lifestyle orientated, easily deployable and interoperable, integration towards a smart home becomes more feasible. For smart home integration to effectively support the elderly in their own homes, it needs to be able to determine if functional ability and independence, together with health, are maintained. A few smart home-like products are emerging in the marketplace employing motion and movement sensors to detect daily activity and the possibility of detecting falls. There are also some telehealth products that support health monitoring. These products, however, are more specialised for those with severe chronic illness and are costly for general health monitoring of older people who remain functionally independent.

Our Solutions
The Smarter Safer Homes (SSH) is the underlying platform developed and used by the HIoT team, and was designed to capture data from wireless communication technologies of home and health monitoring sensors to establish smart homes. It features a consumer design interface to self-manage and support the older community, and enable them to engage informal (eg. family) and formal (aged care and clinical) support services. The SSH platform employs novel analytics to determine functional independence through an objective and personalised measure of an individual’s functional independence.

Impact on the Health System
Our Smarter Safer Homes platform is designed to provide the very support at which Consumer Directed Care (CDC) is aimed. The platform enables an ageing person to allow their family/carer or aged care support access to their daily health and wellbeing status. Through a wealth of up-to-date information of the person’s progress, functional measures of independence and health status via the SSH platform, care and support can be enabled in a preventative and timely manner, and in accordance with their individual profile.

 

Case Studies

 

Team Members

Qing Zhang

Son Tran

Vanessa Smallbon

 

 

 

 

 

 

Qing Zhang
Senior Research Scientist, focusing on applying IoT and AI techniques in healthcare.
CSIRO Profile

Son Tran
Postdoctoral Researcher, applying data mining techniques to understand activity recognition, human identification in smart homes.

Vanessa Smallbon
Software Engineer, developing and implementing IoT techniques on Smart Home platform.