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
    He C, Chang J, Hu Q, Wang J, Antonello J, He H, Liu S, Lin J, Dai B, Elson DS, Xi P, Ma H, Booth MJet al., 2019,

    Complex vectorial optics through gradient index lens cascades

    , Nature Communications, Vol: 10, Pages: 1-8, ISSN: 2041-1723

    Graded index (GRIN) lenses are commonly used for compact imaging systems. It is not widely appreciated that the ion-exchange process that creates the rotationally symmetric GRIN lens index profile also causes a symmetric birefringence variation. This property is usually considered a nuisance, such that manufacturing processes are optimized to keep it to a minimum. Here, rather than avoiding this birefringence, we understand and harness it by using GRIN lenses in cascade with other optical components to enable extra functionality in commonplace GRIN lens systems. We show how birefringence in the GRIN cascades can generate vector vortex beams and foci, and how it can be used advantageously to improve axial resolution. Through using the birefringence for analysis, we show that the GRIN cascades form the basis of a new single-shot Müller matrix polarimeter with potential for endoscopic label-free cancer diagnostics. The versatility of these cascades opens up new technological directions.

  • Journal article
    Chen C-M, Kwasnicki RM, Curto VF, Yang G-Z, Lo BPLet al., 2019,

    Tissue oxygenation sensor and an active in vitro phantom for sensor Validation

    , IEEE Sensors Journal, Vol: 19, Pages: 8233-8240, ISSN: 1530-437X

    A free flap is a tissue reconstruction procedure where healthy tissue is harvested to cover up vital structures after wound debridement. Microvascular anastomoses are carried out to join the arteries and veins of the flap with recipient vessels near the target site. Continuous monitoring is required to identify the flap failure and enable early intervention to salvage the flap. Although there are medical instruments that can assist surgeons in monitoring flap viability, high upfront costs and time-consuming data interpretation have hindered the use of such technologies in practice. Surgeons still rely largely on the clinical examination to monitor flaps after operations. This paper presents a low-cost, low-power (6.6 mW), and miniaturized Hamlyn StO 2 (tissue oxygen saturation) sensor that can be embodied as a plaster and attached to a flap for real-time monitoring. Similar to the design of oxygen saturation (SpO 2 /SaO 2 ) sensors, the Hamlyn StO 2 sensor was designed based on photoplethysmography (PPG), but with a different target of quantifying tissue perfusion rather than capturing pulsatile flow. To understand the spectral response to oxygenation/deoxygenation and vascular flow, an active in vitro silicone phantom was developed. The new sensor was validated using the silicone phantom and compared with a commercially available photospectroscopy and laser Doppler machine (O2C, LEA, Germany). In addition, in vivo experiments were conducted using a brachial pressure cuff forearm ischemia model. The experiment results have shown a high correlation between the proposed sensor and the O2C machine (r = 0.672 and p <; 0.001), demonstrating the potential value of the of the proposed low-cost sensor in post-operative free flap monitoring.

  • Conference paper
    Qiu J, Lo FPW, Sun Y, Wang S, Lo Bet al., 2019,

    Mining discriminative food regions for accurate food recognition

    , BMVC 2019, Publisher: British Machine Vision Conference

    Automatic food recognition is the very first step towards passive dietary monitoring. In this paper, we address the problem of food recognition by mining discriminative food regions. Taking inspiration from Adversarial Erasing, a strategy that progressively discovers discriminative object regions for weakly supervised semantic segmentation, we propose a novel network architecture in which a primary network maintains the base accuracy of classifying an input image, an auxiliary network adversarially mines discriminative food regions, and a region network classifies the resulting mined regions. The global (the original input image) and the local (the mined regions) representations are then integrated for the final prediction. The proposed architecture denoted as PAR-Net is end-to-end trainable, and highlights discriminative regions in an online fashion. In addition, we introduce a new fine-grained food dataset named as Sushi-50, which consists of 50 different sushi categories. Extensive experiments have been conducted to evaluate the proposed approach. On three food datasets chosen (Food-101, Vireo-172, andSushi-50), our approach performs consistently and achieves state-of-the-art results (top-1 testing accuracy of 90:4%, 90:2%, 92:0%, respectively) compared with other existing approaches.

  • Journal article
    Chabloz N, Wenzel M, Perry H, Yoon I, Molisso S, Stasiuk G, Elson D, Cass A, Wilton-Ely Jet al., 2019,

    Polyfunctionalised nanoparticles bearing robust gadolinium surface units for high relaxivity performance in MRI

    , Chemistry - A European Journal, Vol: 25, Pages: 10895-10906, ISSN: 0947-6539

    The first example of an octadentate gadolinium unit based on DO3A (hydration number q = 1) with a dithiocarbamate tether has been designed and attached to the surface of gold nanoparticles (around 4.4 nm in diameter). In addition to the superior robustness of this attachment, the restricted rotation of the Gd complex on the nanoparticle surface leads to a dramatic increase in relaxivity (r1) from 4.0 mM‐1 s‐1 in unbound form to 34.3 mM‐1 s‐1 (at 10 MHz, 37 °C) and 22 ± 2 mM‐1s‐1 (at 63.87 MHz, 25 °C) when immobilised on the surface. The ‘one‐pot’ synthetic route provides a straightforward and versatile way of preparing a range of multifunctional gold nanoparticles. The incorporation of additional surface units improving biocompatibility (PEG and thioglucose units) and targeting (folic acid) lead to little detrimental effect on the high relaxivity observed for these non‐toxic multifunctional materials. In addition to the passive targeting attributed to gold nanoparticles, the inclusion of a unit capable of targeting the folate receptors overexpressed by cancer cells, such as HeLa cells, illustrates the potential of these assemblies.

  • Conference paper
    Guo Y, Sun M, Lo FPW, Lo Bet al., 2019,

    Visual guidance and automatic control for robotic personalized stent graft manufacturing

    , 2019 International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 8740-8746

    Personalized stent graft is designed to treat Abdominal Aortic Aneurysms (AAA). Due to the individual difference in arterial structures, stent graft has to be custom made for each AAA patient. Robotic platforms for autonomous personalized stent graft manufacturing have been proposed in recently which rely upon stereo vision systems for coordinating multiple robots for fabricating customized stent grafts. This paper proposes a novel hybrid vision system for real-time visual-sevoing for personalized stent-graft manufacturing. To coordinate the robotic arms, this system is based on projecting a dynamic stereo microscope coordinate system onto a static wide angle view stereo webcam coordinate system. The multiple stereo camera configuration enables accurate localization of the needle in 3D during the sewing process. The scale-invariant feature transform (SIFT) method and color filtering are implemented for stereo matching and feature identifications for object localization. To maintain the clear view of the sewing process, a visual-servoing system is developed for guiding the stereo microscopes for tracking the needle movements. The deep deterministic policy gradient (DDPG) reinforcement learning algorithm is developed for real-time intelligent robotic control. Experimental results have shown that the robotic arm can learn to reach the desired targets autonomously.

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