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.


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  • Journal article
    Anastasova S, SpeharDélèze A, Kwasnicki RM, Yang G, Vadgama Pet al., 2020,

    Electrochemical monitoring of subcutaneous tissue pO2 fluctuations during exercise using a semi‐implantable needle electrode

    , Electroanalysis, Vol: 32, Pages: 2393-2403, ISSN: 1040-0397

    Semi‐implantable needle oxygen electrodes were used for forearm subcutaneous monitoring in human subjects undertaking high intensity cycling and fist clenching exercise. pO2 variations in the range between 40 and 100 mm Hg oxygen were seen. Superimposed on these were paradoxical rises in subcutaneous pO2, of up to 100 mm Hg which paralleled the scale of the exercise. This was indicative of increased blood flow through skin. Triton X‐100 incorporated into the sensor polyurethane membranes helped to give faster responses and reduced the possibility of biofouling and drift. The sterilizable system, free from internal electrolyte film appears promising for future clinical monitoring.

  • Journal article
    Di Camillo B, Nicosia G, Buffa F, Lo Bet al., 2020,

    Guest editorial data science in smart healthcare: Challenges and opportunities

    , IEEE Journal of Biomedical and Health Informatics, Vol: 24, Pages: 3041-3043, ISSN: 2168-2194

    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.

  • Journal article
    Keshavarz M, Chowdhury AKMRH, Kassanos P, Tan B, Venkatakrishnan Ket al., 2020,

    Self-assembled N-doped Q-dot carbon nanostructures as a SERS-active biosensor with selective therapeutic functionality

    , Sensors and Actuators B: Chemical, Vol: 323, Pages: 128703-128703, ISSN: 0925-4005
  • Journal article
    Li B, Tan H, Jenkins D, Srinivasa Raghavan V, Gil Rosa B, Guder F, Pan G, Yeatman E, Sharp Det al., 2020,

    Clinical detection of neurodegenerative blood biomarkers using graphene immunosensor

    , Carbon, Vol: 168, Pages: 144-162, ISSN: 0008-6223

    Accurate detection of blood biomarkers related to neurodegenerative diseases could provide a shortcut to identifying early stage patients before the onset of symptoms. The specificity, selectivity and operational requirements of the current technologies, however, preclude their use in the primary clinical setting for early detection. Graphene, an emerging 2D nanomaterial, is a promising candidate for biosensing which has the potential to meet the performance requirements and enable cost-effective, portable and rapid diagnosis. In this review, we compare graphene-based immunosensing technologies with conventional enzyme-linked immunosorbent assays and cutting-edge single molecule array techniques for the detection of blood-based neurodegenerative biomarkers. We cover the progress in electrical, electrochemical and optical graphene-based immunosensors and outline the barriers that slow or prevent the adoption of this emerging technology in primary clinical settings. We also highlight the possible solutions to overcome these barriers with an outlook on the future of the promising, graphene immunosensor technology.

  • Journal article
    Kassanos P, 2020,

    Analog-digital computing let robots go through the motions

    , SCIENCE ROBOTICS, Vol: 5, ISSN: 2470-9476

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