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.
2 column colour block - Research areas
2 column colour block - Research areas 2
- Showing results for:
- Reset all filters
Journal articleZheng Y, Ghovanloo M, Lo BPL, et al., 2019,
Introduction to the special issue on wearable and flexible integrated sensors for screening, diagnostics, and treatment, IEEE Transactions on Biomedical Circuits and Systems, Vol: 13, Pages: 1300-1303, ISSN: 1932-4545
The papers in this special issue present a selection of high quality research papers on wearable and flexible integrated sensors for screening, diagnostics, and treatment. Emerging flexible and wearable physical sensing devices create huge potential for many vital healthcare and biomedical applications including artificial electronic skins, physiological monitoring and assessment systems, therapeutic and drug delivery platforms, etc. Monitoring of vital physiological parameters in hospital and/or home environments has been of tremendous interests to healthcare practitioners for a long time. Robust and reliable sensors with excellent flexibility and stretchability are essential in the development of pervasive health monitoring systems with the capability of continuously tracking physiological signals of human body without conspicuous discomfort and invasiveness.
Journal articleRosa BMG, Anastasova-Ivanova S, Yang GZ, 2019,
Journal articleLo B, Zhang Y, Inan OT, et al., 2019,
The seven papers included in this special section focus on machine learning applications for the mental health industry. Mental health is one of the major global health issues affecting substantially more people than other noncommunicable diseases. Much research has been focused on developing novel technologies for tackling this global health challenge, including the development of advanced analytical techniques based on extensive datasets and multimodal acquisition for early detection and treatment of mental illnesses. The papers in this issue are dedicated to cover the related topics on technological advancements for mental health care and diagnosis with a focus on pervasive sensing and machine learning.
Journal articleBerthelot M, Ashcroft J, Boshier P, et al., 2019,
Use of near infrared spectroscopy and implantable Doppler for postoperative monitoring of free tissue transfer for breast reconstruction: a systematic review and meta-analysis, Plastic and Reconstructive Surgery Global Open, Vol: 7, Pages: 1-8, ISSN: 2169-7574
Background: Failure to accurately assess the perfusion of free tissue transfer (FTT) in the early postoperative periodmay contribute to failure, which is a source of major patient morbidity and healthcare costs.Goal: This systematic review and meta-analysis aims to evaluate and appraise current evidence for the use of nearinfrared spectroscopy (NIRS) and/or implantable Doppler (ID) devices compared with conventional clinicalassessment (CCA) for postoperative monitoring of FTT in reconstructive breast surgery.Methods: A systematic literature search was performed in accordance with the PRISMA guidelines. Studies in humansubjects published within the last decade relevant to the review question were identified. Meta-analysis using randomeffects models of FTT failure rate and STARD scoring were then performed on the retrieved publications.Results: 19 studies met the inclusions criteria. For NIRS and ID, the mean sensitivity for the detection of FTT failure is99.36% and 100% respectively, with average specificity of 99.36% and 97.63% respectively. From studies withsufficient reported data, meta-analysis results demonstrated that both NIRS (OR = 0.09 [0.02, 0.36], P < 0.001) and ID(OR = 0.39 [0.27, 0.95], P = 0.04) were associated with significant reduction of FTT failure rates compared to CCA.Conclusion: The use of ID and NIRS provide equivalent outcomes in detecting FTT failure and were superior to CCA.The ability to acquire continuous objective physiological data regarding tissue perfusion is a perceived advantage ofthese techniques. Reduced clinical staff workload and minimised hospital costs are also perceived as positiveconsequences of their use.
Journal articleLi B, Gil B, Power M, et al., 2019,
Flexible electronic materials combined with micro-3D fabrication present new opportunities for wearable biosensors and medical devices. This Research Article introduces a novel carbon-nanotube-coated force sensor, successfully combining the advantages of flexible conductive nanomaterials and the versatility of two photon polymerization technologies for creating functional 3D microstructures. The device employs carbon-nanotube-coated microsprings with varying configurations and geometries for real-time force sensing. To demonstrate its practical value, the device has first been embodied as a patch sensor for transcutaneous monitoring of human arterial pulses, followed by the development of a multiple-point force-sensitive catheter for real-time noninvasive intraluminal intervention. The results illustrate the potential of leveraging advanced nanomaterials and micro-3D-printing for developing new medical devices.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.