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
    Gao A, Liu N, Shen M, Abdelaziz MEMK, Temelkuran B, Yang G-Zet al., 2020,

    Laser-profiled continuum robot with integrated tension sensing for simultaneous shape and tip force estimation

    , Soft Robotics, Pages: 1-23, ISSN: 2169-5172

    The development of miniaturized continuum robots has a wide range of applications in minimally invasive endoluminal interventions. To navigate inside tortuous lumens without impinging on the vessel wall and causing tissue damage or the risk of perforation, it is necessary to have simultaneous shape sensing of the continuum robot and its tip contact force sensing with the surrounding environment. Miniaturization and size constraint of the device have precluded the use of conventional sensing hardware and embodiment schemes. In this study, we propose the use of optical fibers for both actuation and tension/shape/force sensing. It uses a model-based method with structural compensation, allowing direct measurement of the cable tension near the base of the manipulator without increasing the dimensions. It further structurally filters out disturbances from the flexible shaft. In addition, a model is built by considering segment differences, cable interactions/cross talks, and external forces. The proposed model-based method can simultaneously estimate the shape of the manipulator and external force applied onto the robot tip. Detailed modeling and validation results demonstrate the accuracy and reliability of the proposed method for the miniaturized continuum robot for endoluminal intervention.

  • Conference paper
    He C, Chang J, He H, Liu S, Elson DS, Ma H, Booth MJet al., 2020,

    GRIN lens based polarization endoscope – from conception to application

    , Label-free Biomedical Imaging and Sensing (LBIS) 2020, Publisher: SPIE

    Graded index (GRIN) lenses focus light through a radially symmetric refractive index profile. It is not widely appreciated that the ion-exchange process that creates the index profile also causes a radially symmetric birefringence variation. This property is usually considered a nuisance, such that manufacturing processes are optimized to keep it to a minimum. Here, a new Mueller matrix (MM) polarimeter based on a spatially engineered polarization state generating array and GRIN lens cascade for measuring the MM of a region of a sample in a single-shot is presented. We explore using the GRIN lens cascade for a functional analyzer to calculate multiple Stokes vectors and the MM of the target in a snapshot. A designed validation sample is used to test the reliability of this polarimeter. To understand more potential biomedical applications, human breast ductal carcinoma slides at two pathological progression stages are detected by this polarimeter. The MM polar decomposition parameters then can be calculated from the measured MMs, and quantitatively compared with the equivalent data sampled by a MM microscope. The results indicate that the polarimeter and the measured polarization parameters are capable of differentiating the healthy and carcinoma status of human breast tissue efficiently. It has potential to act as a polarization detected fiber-based probe to assist further minimally invasive clinical diagnosis.

  • Conference paper
    Dryden S, Anastasova S, Satta G, Thompson AJ, Leff DR, Darzi AWet al., 2020,

    Toward point-of-care uropathogen detection using SERS active filters

    , Optical Diagnostics and Sensing XX: Toward Point-of-Care Diagnostics, Publisher: SPIE, Pages: 1124705-1-1124705-7

    150 million people worldwide suffer one or more urinary tract infections (UTIs) annually. UTIs are a significant health burden: societal costs of UTI exceed $3.5 billion in the U.S. alone; 5% of sepsis cases arise from a urinary source; and UTIs are a prominent contributor toward antimicrobial resistance (AMR). Current diagnostic frameworks exacerbate this burden by providing inaccurate and delayed diagnosis. Rapid point-of-care bacterial identification will allow for early precision treatment, fundamentally altering the UTI paradigm. Raman spectroscopy has a proven ability to provide rapid bacterial identification but is limited by weak bacterial signal and a susceptibility to background fluorescence. These limitations may be overcome using surface enhanced Raman spectroscopy (SERS), provided close and consistent application of bacteria to the SERS-active surface can be achieved. Physical filtration provides a means of capturing uropathogens, separating them from the background solution and acting as SERS-active surface. This work demonstrates that filters can provide a means of aggregating bacteria, thereby allowing subsequent enhancement of the acquired Raman signal using metallic nanoparticles. 60 bacterial suspensions of common uropathogens were vacuum filtered onto commercial polyvinylidene fluoride membrane filters and Raman signals were enhanced by the addition of silver nanoparticles directly onto the filter surface. SERS spectra were acquired using a commercial Raman spectrometer (Ocean Optics, Inc.). Principal Component – Linear Discriminant Analysis provided discrimination of infected from control samples (accuracy: 88.75%, 95% CI: 79.22-94.59%, p-value <0.05). Amongst infected samples uropathogens were classified with 80% accuracy. This study has demonstrated that combining Raman spectroscopy with membrane filtration and SERS can provide identification of infected samples and rapid bacterial classification.

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

    Metal-oxide surface-enhanced Raman biosensor template towards point-of-care EGFR detection and cancer diagnostics

    , NANOSCALE HORIZONS, Vol: 5, Pages: 294-307, ISSN: 2055-6756
  • Journal article
    Zhang Y, Guo Y, Yang P, Chen W, Lo Bet al., 2020,

    Epilepsy Seizure Prediction on EEG Using Common Spatial Pattern and Convolutional Neural Network


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