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.


BibTex format

author = {Zhao, T and Deng, L and Wang, W and Elson, DS and Su, L},
doi = {10.1364/OE.26.020368},
journal = {Optics Express},
pages = {20368--20378},
title = {Bayes' theorem-based binary algorithm for fast reference-less calibration of a multimode fiber},
url = {http://dx.doi.org/10.1364/OE.26.020368},
volume = {26},
year = {2018}

RIS format (EndNote, RefMan)

AB - In this paper, we present a Bayes’ theorem-based high-speed algorithm, to measure the binary transmission matrix of a multimode fiber using a digital micromirror device, in a reference-less multimode fiber imaging system. Based on conditional probability, we define a preset threshold to locate those digital-micromirror-device pixels that can be switched ‘ON’ to form a focused spot at the output. This leads to a binary transmission matrix consisting of ‘0’ and ‘1’ elements. High-enhancement-factor light focusing and raster-scanning at the distal end of the fiber are demonstrated experimentally. The key advantage of our algorithm is its capability for fast calibration of a MMF to form a tightly focused spot. In our experiment, for 5000 input-output pairs, we only need 0.26 s to calibrate one row of the transmission matrix to achieve a focused spot with an enhancement factor of 28. This is more than 10 times faster than the prVBEM algorithm. The proposed Bayes’ theorem-based binary algorithm can be applied not only in multimode optical fiber focusing but also to other disordered media. Particularly, it will be valuable in fast multimode fiber calibration for endoscopic imaging.
AU - Zhao,T
AU - Deng,L
AU - Wang,W
AU - Elson,DS
AU - Su,L
DO - 10.1364/OE.26.020368
EP - 20378
PY - 2018///
SN - 1094-4087
SP - 20368
TI - Bayes' theorem-based binary algorithm for fast reference-less calibration of a multimode fiber
T2 - Optics Express
UR - http://dx.doi.org/10.1364/OE.26.020368
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000440803600055&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/62605
VL - 26
ER -