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 = {Di, Camillo B and Nicosia, G and Buffa, F and Lo, B},
doi = {10.1109/JBHI.2020.3028398},
journal = {IEEE Journal of Biomedical and Health Informatics},
pages = {3041--3043},
title = {Guest editorial data science in smart healthcare: Challenges and opportunities},
url = {http://dx.doi.org/10.1109/JBHI.2020.3028398},
volume = {24},
year = {2020}

RIS format (EndNote, RefMan)

AB - The fifteen articles in this special section focus on data science used in smart healthcare applications. A shift toward a data-driven socio-economic health model is occurring. This is the result of the increased volume, velocity and variety of data collected from the public and private sector in healthcare, and biology in general. In the past five-years, there has been an impressive development of computational intelligence and informatics methods for application to health and biomedical science. However, the effective use of data to address the scale and scope of human health problems has yet to realize its full potential. The barriers limiting the impact of practical application of standard data mining and machine learning methods have been inherent to the characteristics of health data. Besides the volume of the data (‘big data’), these are challenging due to their heterogeneity, complexity, variability and dynamic nature. Finally, data management and interpretability of the results have been limited by practical challenges in implementing new and also existing standards across the different health providers and research institutions. The scope of this Special issue is to discuss some of these challenges and opportunities in health and biological data science, with particular focus on the infrastructure, software, methods and algorithms needed to analyze large datasets in biological and clinical research.
AU - Di,Camillo B
AU - Nicosia,G
AU - Buffa,F
AU - Lo,B
DO - 10.1109/JBHI.2020.3028398
EP - 3043
PY - 2020///
SN - 2168-2194
SP - 3041
TI - Guest editorial data science in smart healthcare: Challenges and opportunities
T2 - IEEE Journal of Biomedical and Health Informatics
UR - http://dx.doi.org/10.1109/JBHI.2020.3028398
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000587913300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/89095
VL - 24
ER -