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

@article{Keshavarz:2020:10.1039/c9nh00590k,
author = {Keshavarz, M and Kassanos, P and Tan, B and Venkatakrishnan, K},
doi = {10.1039/c9nh00590k},
journal = {NANOSCALE HORIZONS},
pages = {294--307},
title = {Metal-oxide surface-enhanced Raman biosensor template towards point-of-care EGFR detection and cancer diagnostics},
url = {http://dx.doi.org/10.1039/c9nh00590k},
volume = {5},
year = {2020}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AU - Keshavarz,M
AU - Kassanos,P
AU - Tan,B
AU - Venkatakrishnan,K
DO - 10.1039/c9nh00590k
EP - 307
PY - 2020///
SN - 2055-6756
SP - 294
TI - Metal-oxide surface-enhanced Raman biosensor template towards point-of-care EGFR detection and cancer diagnostics
T2 - NANOSCALE HORIZONS
UR - http://dx.doi.org/10.1039/c9nh00590k
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000511441800006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
VL - 5
ER -