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{Kwasnicki:2018:10.1186/s40001-018-0326-9,
author = {Kwasnicki, RM and Cross, GW and Geoghegan, L and Zhang, Z and Reilly, P and Darzi, A and Yang, GZ and Emery, R},
doi = {10.1186/s40001-018-0326-9},
journal = {EUROPEAN JOURNAL OF MEDICAL RESEARCH},
title = {A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study},
url = {http://dx.doi.org/10.1186/s40001-018-0326-9},
volume = {23},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - BackgroundThe prevalence of self-reported shoulder pain in the UK has been estimated at 16%. This has been linked with significant sleep disturbance. It is possible that this relationship is bidirectional, with both symptoms capable of causing the other. Within the field of sleep monitoring, there is a requirement for a mobile and unobtrusive device capable of monitoring sleep posture and quality. This study investigates the feasibility of a wearable sleep system (WSS) in accurately detecting sleeping posture and physical activity.MethodsSixteen healthy subjects were recruited and fitted with three wearable inertial sensors on the trunk and forearms. Ten participants were entered into a ‘Posture’ protocol; assuming a series of common sleeping postures in a simulated bedroom. Five participants completed an ‘Activity’ protocol, in which a triphasic simulated sleep was performed including awake, sleep and REM phases. A combined sleep posture and activity protocol was then conducted as a ‘Proof of Concept’ model. Data were used to train a posture detection algorithm, and added to activity to predict sleep phase. Classification accuracy of the WSS was measured during the simulations.ResultsThe WSS was found to have an overall accuracy of 99.5% in detection of four major postures, and 92.5% in the detection of eight minor postures. Prediction of sleep phase using activity measurements was accurate in 97.3% of the simulations. The ability of the system to accurately detect both posture and activity enabled the design of a conceptual layout for a user-friendly tablet application.ConclusionsThe study presents a pervasive wearable sensor platform, which can accurately detect both sleeping posture and activity in non-specialised environments. The extent and accuracy of sleep metrics available advances the current state-of-the-art technology. This has potential diagnostic implications in musculoskeletal pathology and with the addition of aler
AU - Kwasnicki,RM
AU - Cross,GW
AU - Geoghegan,L
AU - Zhang,Z
AU - Reilly,P
AU - Darzi,A
AU - Yang,GZ
AU - Emery,R
DO - 10.1186/s40001-018-0326-9
PY - 2018///
SN - 0949-2321
TI - A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study
T2 - EUROPEAN JOURNAL OF MEDICAL RESEARCH
UR - http://dx.doi.org/10.1186/s40001-018-0326-9
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000433969500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/60722
VL - 23
ER -