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, Crewther B, Bembnowicz P, Curto V, Ip HMD, Rosa B, Yang G-Zet al., 2017,

    A wearable multisensing patch for continuous sweat monitoring

    , BIOSENSORS & BIOELECTRONICS, Vol: 93, Pages: 139-145, ISSN: 0956-5663
  • JOURNAL ARTICLE
    Ravi D, Wong C, Deligianni F, Berthelot M, Andreu-Perez J, Lo B, Yang G-Zet al., 2017,

    Deep Learning for Health Informatics

    , IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, Vol: 21, Pages: 4-21, ISSN: 2168-2194
  • JOURNAL ARTICLE
    Ravi D, Wong C, Lo B, Yang G-Zet al., 2017,

    A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices

    , IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, Vol: 21, Pages: 56-64, ISSN: 2168-2194
  • CONFERENCE PAPER
    Sun Y, Wong C, Yang GZ, Lo Bet al., 2017,

    Secure key generation using gait features for Body Sensor Networks

    , Pages: 206-210

    © 2017 IEEE. With increasing popularity of wearable and Body Sensor Networks technologies, there is a growing concern on the security and data protection of such low-power pervasive devices. With very limited computational power, BSN sensors often cannot provide the necessary data protection to collect and process sensitive personal information. Since conventional network security schemes are too computationally demanding for miniaturized BSN sensors, new methods of securing BSNs have proposed, in which Biometric Cryptosystem (BCS) appears to be an effective solution. With regards to BCS security solutions, physiological traits, such as an individual's face, iris, fingerprint, electrocardiogram (ECG), and photoplethysmogram (PPG) have been widely exploited. However, behavioural traits such as gait are rarely studied. In this paper, a novel lightweight symmetric key generation scheme based on the timing information of gait is proposed. By extracting similar timing information from gait acceleration signals simultaneously from body worn sensors, symmetric keys can be generated on all the sensor nodes at the same time. Based on the characteristics of generated keys and BSNs, a fuzzy commitment based key distribution scheme is also developed to distribute the keys amongst the sensor nodes.

  • JOURNAL ARTICLE
    Akay M, Coatrieux G, Hao Y, Fotiadis DI, Laine A, Lo B, Nikita KS, Noury N, Rodrigues J, Wang MDet al., 2016,

    Guest Editorial MobiHealth 2014, IEEE HealthCom 2014, and IEEE BHI 2014

    , IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, Vol: 20, Pages: 731-732, ISSN: 2168-2194

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