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 = {Gao, A and Lo, P and Lo, B},
publisher = {IEEE},
title = {Food volume estimation for quantifying dietary intake with a wearable camera},
url = {http://hdl.handle.net/10044/1/57659},
year = {2018}

RIS format (EndNote, RefMan)

AB - A novel food volume measurement technique isproposed in this paper for accurate quantification of the dailydietary intake of the user. The technique is based on simul-taneous localisation and mapping (SLAM), a modified versionof convex hull algorithm, and a 3D mesh object reconstructiontechnique. This paper explores the feasibility of applying SLAMtechniques for continuous food volume measurement with amonocular wearable camera. A sparse map will be generatedby SLAM after capturing the images of the food item withthe camera and the multiple convex hull algorithm is appliedto form a 3D mesh object. The volume of the target objectcan then be computed based on the mesh object. Comparedto previous volume measurement techniques, the proposedmethod can measure the food volume continuously with no priorinformation such as pre-defined food shape model. Experimentshave been carried out to evaluate this new technique andshowed the feasibility and accuracy of the proposed algorithmin measuring food volume.
AU - Gao,A
AU - Lo,P
AU - Lo,B
PY - 2018///
TI - Food volume estimation for quantifying dietary intake with a wearable camera
UR - http://hdl.handle.net/10044/1/57659
ER -