Medical Device and Technology Research Group

Medical Device and Technology Research Group at ARU focuses on the research and development of innovative medical technologies and devices with scientific and socioeconomic impacts to address unmet healthcare needs.

The group works across multidisciplinary areas with electronic engineers, medical physicists, computer scientists, clinical consultants, industrial partners, guideline makers, and allied professionals at different stages along the pathway of medical device development and commercialization.

We have earned international reputation in developing novel blood pressure and arterial stiffness measurement techniques, and recent developments on wearable devices and monitoring system for pre-term labour, pregnancy induced hypertension, stroke, pneumonia, sleep apnoea and personalised hearing impairment rehabilitation solutions.

Our group has established close research and clinical partnership with Essex Partnership University NHS Foundation Trust, and industry partners to combine academic research with commercial exploitation. We have also been well recognized for promoting knowledge and technology exchanges internationally, building up educational and research collaborations, and facilitating technology adoption in developing countries, including China and countries in Africa, with the aims to promote the adoption of healthcare technologies in these partner countries.

Key members of staff

Dr Stephen Hughes

Selected publications

Al-Halhouli AA, Al-Ghussain L, El Bouri S, Habash F, Liu H, Zheng D. Clinical Evaluation of Stretchable and Wearable Inkjet-Printed Strain Gauge Sensor for Respiratory Rate Monitoring at Different Body Postures. Applied Sciences. 2020 Jan;10(2):480. Doi: 10.3390/app10020480

Chen Z, Liu H, Zheng D. Research and application of photobiomodulation of rod cells for diabetic retinopathy. International Review of Ophthalmology, 2019, 43(6): 373-376. Doi: 10.3760/cma.j.issn.1673-5803.2019.06.003

Peng J, Hao D, Liu H, Liu J, Zhou X, Zheng D. Preliminary Study on the Efficient Electrohysterogram Segments for Recognizing Uterine Contractions with Convolutional Neural Networks. BioMed research international. 2019; Article ID 3168541. Doi: 10.1155/2019/3168541

Al-Halhouli AA, Al-Ghussain L, El Bouri S, Liu H, Zheng D. Fabrication and Evaluation of a Novel Non-Invasive Stretchable and Wearable Respiratory Rate Sensor Based on Silver Nanoparticles Using Inkjet Printing Technology. Polymers. 2019 Sep;11(9):1518. Doi: 10.3390/polym11091518

Liu H, Leung T, Wong A, Chen F, Zheng D. The Geometric Effects on the Stress of Arterial Atherosclerotic Plaques: a Computational Study. In2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019 Jul 23 (pp. 6948-6951). IEEE. Doi: 10.1109/EMBC.2019.8857885

Liu H, Wang L, Chan K, Xiong L, Leng L, Shi L, Leung TW, Chen F, Zheng D. The Application of Non-linear Flow Resistance in Cerebral Artery: Compared with Windkessel Model based on Genetic Algorithm. In2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019 Jul 23 (pp. 2285-2288). IEEE. Doi: 10.1109/EMBC.2019.8857963

Hartmann V, Liu H, Chen F, Hong W, Hughes S, Zheng D. Towards Accurate Extraction of Respiratory Frequency from the Photoplethysmogram: Effect of Measurement Site. Frontiers in physiology. 2019;10:732. Doi: 10.3389/fphys.2019.00732

Contact us

Dr Haipeng Liu
Phone: +44 (0) 1245 684941