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 articleAnastasova S, Crewther B, Bembnowicz P, et al., 2017,
Conference paperPower M, Seneci CA, Thompson AJ, et al., 2017,
The development of microscale surgical tools could pave the way for truly minimally invasive microsurgical procedures. This work demonstrates the application of direct laser writing (DLW) using two-photon polymerization (TPP), a rapid prototyping microfabrication technique, to create a tethered, passively actuated three-dimensional gripper with potential applications in microbiopsy. A microgripper design was devised, modelled and optimized. The gripper was then fabricated and characterized for validation of the theoretical model. The results demonstrate that modelling the behavior of compliant microtools provides a useful approximation for the observed trends and, thus, can be utilized in the design of TPP tools. Future work on the incorporation of viscoelastic material into the model will further improve agreement between the predicted and experimental performance.
Conference paperPower M, Anastasova S, Shanel S, et al., 2017,
Towards hybrid microrobots using pH- and photo-responsive hydrogels for cancer targeting and drug delivery, 2017 IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 6002-6007, ISSN: 1050-4729
This work is towards targeted drug delivery using microrobots functionalized to navigate towards naturally occurring pH gradients caused by cancer cells, and to release a payload in response to a light stimulus. Stimuli-responsive microrobots for the localization of specific cell types and targeted drug delivery could provide a new and promising therapy to prevent and treat the spread of cancer. In this work, we present two novel biocompatible photoresists for the fabrication of hybrid microrobots using two-photon polymerization (TPP) for medical applications. One biomarker for cancerous cells is that they exhibit lower pH compared to surrounding healthy tissue. In this work, a pH-responsive resist was developed and demonstrated to automatically seek a low-pH solid in a microfluidic channel, simulating metastatic cells within a vessel. The second resist, a hydrogel-based photoresist, was created to contract in response to light. The two resists were combined together in a two-step printing process to create a microswimmer with potential for tumor localization and drug release capabilities in the human circulatory system.
Conference paperVarghese RJ, Berthet-Rayne P, Giataganas P, et al., 2017,
A framework for sensorless and autonomous probe-tissue contact management in robotic endomicroscopic scanning, 2017 IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 1738-1745, ISSN: 1050-4729
Advances in optical imaging, and probe-based Confocal Laser Endomicroscopy (pCLE) in particular, offer real-time cellular level information for in-vivo tissue characterization. However for large area coverage, the limited field-of-view necessitates the use of a technique known as mosaicking to generate usable information from the incoming image stream. Mosaicking also needs a continuous stream of good quality images, but this is challenging as the probe needs to be maintained within an optimal working range and the contact force controlled to minimize tissue deformation. Robotic manipulation presents a potential solution to these challenges, but the lack of haptic feedback in current surgical robot systems hinders the technology's clinical adoption. This paper proposes a sensorless alternative based on processing the incoming image stream and deriving a quantitative measure representative of the image quality. This measure is then used by a controller, designed using model-free reinforcement learning techniques, to maintain optimal contact autonomously. The developed controller has shown near real-time performance in overcoming typical loss-of-contact and excess-deformation scenarios experienced during endomicroscopy scanning procedures.
Conference paperSun Y, Wong C, Yang GZ, et al., 2017,
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.
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