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, 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.
Medical Technology Research Group has particular interests in the research, development and evaluation of novel medical procedures, techniques and devices for various healthcare applications (illustration of our fundamental research approach - .pdf download).
Preterm labor which occurs in approximately 10% of pregnant women is a leading cause of neonatal mortality and morbidity. However, unsatisfactory and inaccurate prediction and diagnosis of preterm labor is an immense clinical challenge to the obstetricians. The reported measurement techniques or devices potentially for predicting preterm labor include tocodynamometer, fetal fibronectin and transvaginal ultrasonography. They are either operator-dependent or suffer from an inherent lack of accuracy. Guidelines of ‘Management of Preterm Labor’ from the American College of Obstetricians and Gynecologists have reviewed these techniques, and concluded that there is currently no reliable preterm prediction technique for routine clinical practice. Therefore, there is an urgent clinical need to develop alternatives which can improve diagnosis and achieve satisfactory accuracy for routine clinical use.
Respiratory rate is recognised as an important prognostic marker in acute illness and it is an important component of clinical scoring systems. This means that the need for reliable methods of respiratory rate monitoring has increased. Automated respiratory rate measurement is routinely performed in critical care settings such as intensive care units. However in acute care settings such as emergency departments and acute medical assessment units, measurement and monitoring of respiratory rate are still often undertaken manually. Errors are commonly encountered in manual measurement and may have an adverse effect on patient care. The aim of this project is to develop and assess innovative devices for monitoring respiratory rate of patients in acute care settings.
Our society is facing major healthcare challenges as many people are currently struggling to get easy access to medical care. Remote healthcare monitoring relying on wearable technologies have demonstrated the capacity to improve patient access to all levels (primary, secondary and tertiary). However, there are significant challenges ahead before such a system can be utilized on a large scale in practice. There is therefore urgent need to comprehensively summarise currently available wearable sensors and systems, summarise the major clinical applications of wearable technologies for daily use or frequent monitoring, understand the technical barriers of wearable technology development on sensing, communication and data analysis, understand the major challenges and obstacles of implementing wearable technologies for daily use and into the healthcare system, and finally establish best-practice solutions of implementing wearable technologies that can be easily integrated and used by healthcare professionals considering the existing constraints.
This interdisciplinary project develops an innovative and low cost hearing aid and a big-data-centric hearing rehabilitation solution for millions of older people in China with hearing impairment. Through our core technical skills and published and patented achievements in the areas of hearing aid, bio-signal processing technology, remote monitoring, medical device manufacture and healthcare technology assessment, a novel hearing aid tailored for the Chinese tonal language and a portable hearing screener for home use will be developed. In addition, a Chinese language cloud-based software platform will be developed to implement online hearing screening technology and protocol and to monitor hearing impairment at home, allowing regular calibration of hearing aid to optimize the effectiveness of hearing rehabilitation, as well as utilising behaviour change techniques to overcome resistance to using the hearing aid. The novel hearing aid and its rehabilitation solution will also create an IoT cloud platform that could be used by a range of innovative suppliers to provide novel management pathways for other chronic diseases.
Manual blood pressure (BP) measurement is regarded as the gold standard clinical BP technique. It depends heavily on obtaining good quality sound signals from a stethoscope. In addition, skills are required to determine BPs from the stethoscope sounds. There is potential for inaccurate measurement due to noise in the sounds heard, as well as loss of confidence, poor training or hearing. Consequently many clinical staff are moving to automated devices simply because they no longer have the necessary skills for traditional manual technique. Although automated devices have the advantage of being easy to use, they do not detect systole and diastole directly but use an indirect method for estimating BPs. This is known to be less accurate, as recognised by device Standards which allow up to 5% of measurements to have an error of >16 mmHg compared to the ‘gold standard’. There is a need for devices which are capable of providing accurate measurements in a clinical or domestic environment. We have developed patented technologies to address the current limitations of manual and automated techniques. The first technology allows the quality of a BP measurement to be determined and communicated to the user. It can be directly incorporated in existing devices or can be a ‘add on’ to the device. The second can measure BPs by detection of unique signal changes in the cuff. This is fundamentally as accurate as the ‘gold standard’ method. The two technologies are compatible and could be incorporated into a single device.
Arteries are vital for human life. Arteries are naturally elastic and become stiff and less able to respond to different clinical and physiological factors. There is currently a significant interest in assessing health and in screening. Various assessment techniques have been developed to quantify arterial properties non-invasively and indirectly, including the analysis of arterial pulse characteristics and measurement of pulse wave velocity. Arterial volume distensibility, giving the relative change in blood volume with a known change in arterial pressure, provides direct quantification of the mechanical properties of the arterial wall. Our novel device to measure arterial volume distensibility uses a long air-filled pressure cuff fitted on a limb, along with the non-invasive measurement of the velocity of the pulse wave radiating from the heart down the peripheral limb. This work has been awarded the Institute of Physics and Engineering in Medicine (IPEM) Martin Black annual Prize for the best article published in ‘Physiological Measurement’ in 2011.
Gao P, Hao DM, Qiu Q, An Y, Wang Y, Yang L, Yang YM, Zhang S, Li XW, Zheng D. Comparison of electrohysterogram signal measured by surface electrodes with different designs: A computational study with dipole band and abdomen models. Scientific Report 2017; 7:17282. doi: 10.1038/s41598-017-17109-3.
Chen M, Chen A, Si X, Ji M, Zheng D. Peripheral arterial volume distensibility changes with applied external pressure: significant difference between arteries with different compliance. Scientific Report 2017; Article Number: 40545; Doi:10.1038/srep40545.
Zhang M, Zhang XM, Chen F, Chen A, Dong B, Zheng D. Effects of room environment and nursing experience on clinical BP measurement: an observational study. Blood Press Monit 2017; 22: 79-85.
Wang Y, Cao L, Hao DM, Rong Y, Yang L, Zhang S, Chen F, Zheng D. Effects of force load, muscle fatigue and extremely low frequency magnetic stimulation on EEG signals during side arm lateral raise task. Physiol Meas 2017; 38:745-758.
Cao L, Wang Y, Hao DM, Rong Y, Yang L, Zhang S, Zheng D. Effects of force load, muscle fatigue, and magnetic stimulation on surface electromyography during side arm lateral raise task: A preliminary study with healthy subjects. BioMed Research International 2017; Article ID 8943850, Doi: 10.1155/2017/8943850
Wang A, Yang L, Wen W, Zhang S, Gu G, Zheng D. Gaussian modelling characteristics changes derived from finger photoplethysmographic pulses during exercise and recovery. Microvasc Res 2017 Mar 24. pii: S0026-2862(16)30234-5. doi: 10.1016/j.mvr.2017.03.008
Yang FW, Chen F, Zhu MP, Chen A, Zheng D. Significantly reduced blood pressure measurement variability for both normotensive and hypertensive subjects: effect of polynomial curve fitting of oscillometric pulses. BioMed Research International 2017; Article ID 5201069; doi:10.1155/2017/5201069
Herakova N, Nzeribe NHN, Wang Y, Chen F, Zheng D. Effect of respiratory pattern on automated clinical blood pressure measurement: an observational study with normotensive subjects. Clinical Hypertension 2017; 23:15; DOI 10.1186/s40885-017-0071-3
Chen F, Zheng D, Tsao Y. Effects of noise suppression and envelope dynamic range compression on the intelligibility of vocoded sentences for a tonal language. Acoustical Society of America 2017; 142: 1157-1166.
Jiang X, Wei SS, Zheng D, Liu FF, Zhang S, Zhang Z, Liu CY. Change of bilateral difference in radial artery pulse morphology with one-side arm movement. Artery Research 2017; 19: 1-8.
Xia Y, Yang L, Mao X, Zheng D, Liu CY. Quantification of vascular function changes under different emotion states: A pilot study. Technol Health Care 2017; 25: 447-456.
Fan P, PY He, Lu CY, Murray A, Zheng D. Validation of Korotkoff stethoscope sounds during blood pressure measurement: Analysis using a convolutional neural network. IEEE J Biomed Health Inform 2017, 21(6):1593-1598.
Gao Y, Xia L, Gong YL, Zheng D. ECG patterns of left anterior fascicular block and conduction impairment in ventricular myocardium: a whole-heart model-based simulation study. Journal of Zhejiang University-SCIENCE B; 2017; 19(1):49-56.
Chi XL, Li M, Zhan X, Man HH, Xu SL, Zheng D, Bi J, Wang YC, Liu C. Relationship between carotid artery sclerosis and blood pressure variability in essential hypertension patients. Computers in Biology and Medicine; 2017; 92:73-77.
Chen D, Chen F, Murray A, Zheng D. Respiratory modulation of oscillometric cuff pressure pulses and Korotkoff sounds during clinical blood pressure measurement in healthy adults. BioMedical Engineering OnLine 2016; 15:53. DOI: 10.1186/s12938-016-0169-y
Yao Y, Xu LS, Sun YX, Fu Q, Zhou SR, He DN, Zhang YH, Guo Li, Zheng D. Validation of an adaptive transfer function method to estimate the aortic pressure waveform. IEEE J Biomed Health Inform 2016; 99: DOI: 10.1109/JBHI.2016.2636223.
Wang A, Yang L, Wen W, Zhang S, Hao D, Liu Y, Khalid SG, Zheng D. Quantification of radial arterial pulse characteristics changes during exercise and recovery. J Physiol Sci. 2016 Dec 27. doi: 10.1007/s12576-016-0515-7.
Liu CY, Griffiths C, Murray A, Zheng D. Comparison of stethoscope bell and diaphragm, and of stethoscope tube length, for clinical blood pressure measurement. Blood Press Monit 2016; 21:178-83.
Wang Y, Hao DM, Jin L, Zhang S, Yang YM, Bin GY, Zheng D. Regression models for near-infrared measurement of subcutaneous adipose tissue thickness. Physiol Meas 2016; 37: 1024-1034.
Zhang Y, Hao DM, Lv XH, Li SW, Tian YQ, Zheng D, Zeng Y. Quantification of MRI and MRS characteristics changes in a rat model at different stage of cerebral ischemia. Neurological Research 2016; May 23: 1-7. DOI: 10.1080/01616412.2016.1181345
Zhang J, Liu CY, Pan CL, Bai M, Zhang J, Peng Y, Zheng D, Zhang Z. Effect of multiple clinical factors on recurrent angina after percutaneous coronary intervention: a retrospective study from 398 ST-segment elevation myocardial infarction patients: an observational study. Medicine (Baltimore). 2016; 95: e5015. DIO: 10.1097/MD.0000000000005015
Xie Y, Breen L, Cherrett T, Zheng D, Allen C. An exploratory study of the reverse exchange system of medical devices in the NHS. Supply Chain Manag Journal 2016; 21:194-215.
Li P, Li K, Liu CY, Zheng D, Liu CC. Detection of coupling in short physiological series by a joint distribution entropy method. IEEE TBME 2016; 99: doi: 10.1109/TBME.2016.2515543
Dai L, Zhang Y, Zheng D, Xia L, Gong Y. Role of CaMKII and PKA in early afterdepolarization of human ventricular myocardium cell: A Computational model study. Comput Math Methods Med 2016; Article ID 4576313. doi:10.1155/2016/4576313
Liu CY, Zheng D, Murray A. Arteries stiffen with age, but can retain an ability to become more elastic with applied external cuff pressure. Medicine 2015; 94: e1831.
Wang A, Yang L, Liu C, Cui J, Li Y, Yang X, Zhang S, Zheng D. Athletic differences in the characteristics of the photoplethysmographic pulse shape: Effect of maximal oxygen uptake and maximal muscular voluntary contraction. BioMed Res Int 2015; Article ID 752470. doi:10.1155/2014/752470
Lara J, Ogbonmwan I, Oggioni C, Zheng D, Qadir O, Brandt K, Mathers J, Siervo M. Effects of handgrip exercise or beetroot juice on blood pressure, peripheral arterial function and ADMA in overweight older adults: a pilot RCT. Maturitas 2015; 82: 228-235.
Li P, Liu CY, Sun X, Zheng D, Wang XP, Liu CC. Assessing the complexity of short-term heart beat interval series by distance distribution entropy. Med Biol Eng Comput 2015; 53: 77-87.
Gong Y, GaoY, Lu Z, Zheng D, Deng D, Xia L. Preliminary simulation study of atrial fibrillation ablation procedure based on a detailed human atrial model. J Clin Trials in Cardio 2015; 2: 1-9.
Prof Dingchang Zheng
Professor of Medical Technology Innovation, Department of Medical Science and Public Health
Faculty of Medical Science, Anglia Ruskin University
Phone: +44 (0) 1245 684941