A primary motivation of our research is the monitoring of physical, physiological, and biochemical parameters - in any environment and without activity restriction and behaviour modification - through using miniaturised, wireless Body Sensor Networks (BSN). Key research issues that are currently being addressed include novel sensor designs, ultra-low power microprocessor and wireless platforms, energy scavenging, biocompatibility, system integration and miniaturisation, processing-on-node technologies combined with novel ASIC design, autonomic sensor networks and light-weight communication protocols. Our research is aimed at addressing the future needs of life-long health, wellbeing and healthcare, particularly those related to demographic changes associated with an ageing population and patients with chronic illnesses. This research theme is therefore closely aligned with the IGHI’s vision of providing safe, effective and accessible technologies for both developed and developing countries.

Some of our latest works were exhibited at the 2015 Royal Society Summer Science Exhibition.


Citation

BibTex format

@inproceedings{Pansiot:2007,
author = {Pansiot, J and Stoyanov, D and McIlwraith, D and Lo, BPL and Yang, GZ},
pages = {208--+},
publisher = {SPRINGER},
title = {Ambient and wearable sensor fusion for activity recognition in healthcare monitoring systems},
url = {https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000246511700036&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202},
year = {2007}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AU - Pansiot,J
AU - Stoyanov,D
AU - McIlwraith,D
AU - Lo,BPL
AU - Yang,GZ
EP - 208
PB - SPRINGER
PY - 2007///
SN - 1680-0737
SP - 208
TI - Ambient and wearable sensor fusion for activity recognition in healthcare monitoring systems
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000246511700036&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
ER -