Lionel Tarassenko
Professor of Engineering Science
President, Reuben College
Tel: 01865 283452
College: Reuben College
Location: Department of Engineering Science, Parks Road, Oxford OX1 3PJ

Professor Lionel Tarassenko is a world-leading expert in the application of signal processing and machine learning in healthcare, with a strong track record in translation to clinical medicine. His work has had a major impact on the identification of deterioration in acute care and on the self-management of long-term conditions using smartphone apps. He has been a pioneer in developing early warning systems for acutely-ill patients. The machine learning system which he designed for patient monitoring in critical care was the first such system to gain FDA approval. It has led to improved patient outcomes documented in clinical trials (Crit. Care Med. 2011), with more than 1 billion hours of monitoring in hospitals worldwide.

Lionel has been an academic in the Department since April 1988 and he was elected to the Chair of Electrical Engineering in 1997.  He was the driving force behind the Institute of Biomedical Engineering (IBME) which he directed from its opening in April, 2008 to October, 2012. He also established an £8m Centre of Excellence in Medical Engineering within the IBME, and he has led the Technology and Digital Health theme in the NIHR Oxford Biomedical Research Centre since its inception in 2007. Under his leadership, the IBME grew from 110 to 220 academic researchers, and it was awarded a Queen’s Anniversary Prize for Higher Education in 2015 for “new collaborations between engineering and medicine delivering benefit to patients”.

Lionel was elected to a Fellowship of the Institute of Electrical Engineers in 1996, when he was also awarded the IEE Mather Premium for his work on neural networks, to a Fellowship of the Royal Academy of Engineering in 2000, and to a Fellowship of the Academy of Medical Sciences in 2013. He received a British Computer Society Medal in 1996 for his work on neural network analysis of sleep disorders. His research on jet engine health monitoring was awarded the Rolls-Royce Chairman’s Award for Technical Innovation in 2001 and the Sir Henry Royce High Value Patent Award in 2008. His work on mobile phones for healthcare was awarded the E-health 2005 Innovation Award for “best device to empower patients”. He received the 2006 Silver Medal of the Royal Academy of Engineering for his contribution to British engineering leading to market exploitation and he won the Institute of Engineering & Technology IT Award, also in 2006. In 2010, he gave the prestigious Vodafone lecture on m-health at the Royal Academy of Engineering and the Centenary Lecture on Biomedical Engineering at the Indian Institute of Science in Bangalore. He received the 2015 Martin Black Prize from the Institute of Physics for the best paper in Physiological Measurement. He was the Editor-in-Chief of the Topol Review of NHS Technology and its impact on the workforce, which reported in 2019. In September of that year, he was given the Oxford Trust’s Outstanding Achievement Award for his contribution to biomedical engineering and translational innovation in healthcare.

He is the author of 230 journal papers, 210 conference papers, 3 books and 32 granted patents. He has been a founder director of four University spin-out companies, the latest being Oxehealth in September 2012. He is the R&D Director of Sensyne Health, an AIM listed company, and is a director of the University’s wholly-owned Technology Transfer company, Oxford University Innovation. Lionel was the Head of the Department of Engineering Science (Dean of Engineering) from 2014 to 2019, and is now the founding President of Reuben College, the University of Oxford’s newest college. He was made a CBE in the 2012 New Year’s Honours List.

Signal processing and machine learning applied to medical signals and data is the main focus of the Biomedical Signal Processing & m-health group run by Prof. Lionel Tarassenko; the Computational Health Informatics Laboratory, run by Prof. David Clifton; and the Computational Intelligence in Biomedical Monitoring (CIBIM) Laboratory run by Prof. Maarten De Vos.

Prof. Tarassenko’s group has historically focused on signal processing and machine learning for early warning of patient deterioration in hospital, as well as digital health for self-management of chronic diseases such as diabetes. Prof. Clifton’s group focuses on (i) very-large scale data fusion, from genomics to patient-worn sensors, and (ii) extensions for affordable healthcare in developing countries. Prof. De Vos’ research focus is on (i) tensor decompositions in biomedical applications and (ii) neuroscience and mental health monitoring.

All three groups collaborate closely and have several joint projects. If you are interested in biomedical signal processing research, please feel free to approach these members of faculty.

Supporting people with type 2 diabetes in effective use of their medicine through mobile health technology integrated with clinical care (SuMMiT-D pilot): results of a feasibility randomised trial
Farmer AJ,  Allen J,  Bartlett YK,  Bower P,  Chi Y,  French DP,  Gudgin B,  Holmes E,  Horne R,  Hughes DA,  Jones L,  Kenning C,  Locock L,  McSharry J,  Miles L,  Newhouse N,  Rea R,  Robinson S,  Tarassenko L,  Velardo C,  Williams N,  Yu L-M,  et al. (2024)
Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care Unit
Villarroel M,  Chaichulee S,  Jorge J,  Davis S,  Green G,  Arteta C,  Zisserman A,  McCormick K,  Watkinson P,  Tarassenko L,  et al. (2023)
Wearables for continuous patient monitoring on COVID-19 isolation wards
Roman C,  Vollam S,  Watkinson P,  Tarassenko L,  et al. (2023)
Sleep staging using wearables and deep neural networks
Davidson S,  Harford M,  Tarassenko L,  Carter J,  Roman C,  et al. (2023)
Identification of motor progression in Parkinson's disease using wearable sensors and machine learning
Sotirakis C,  Su Z,  Brzezicki MA,  Conway N,  Tarassenko L,  FitzGerald JJ,  Antoniades CA,  et al. (2023)
Using a novel ambulatory monitoring system to support patient safety on an acute infectious disease ward during an unfolding pandemic
Buss A,  Areia C,  Biggs C,  Edmundson H,  Young L,  Roman C,  Santos M,  Tarassenko L,  Watkinson P,  Vollam S,  et al. (2023)
Using a novel ambulatory monitoring system to support patient safety on an acute infectious disease ward during an unfolding pandemic.
Buss A,  Areia C,  Biggs C,  Edmundson H,  Young L,  Roman C,  Santos M,  Tarassenko L,  Watkinson P,  Vollam S,  et al. (2023)
Mobile messaging support versus usual care for people with type 2 diabetes in sub-Saharan Africa: a protocol for a multicentre randomized controlled trial (StAR2D) (Preprint)
Farmer A,  Bobrow K,  Leon N,  Williams N,  Phiri E,  Namadingo H,  Cooper S,  Prince J,  Crampin A,  Besada D,  Daviaud E,  Yu L-M,  N'goma J,  Springer D,  Bruno P,  Tarassenko L,  Nyirenda M,  Levitt N,  et al. (2022)
A new method to measure inter-breath intervals in infants for the assessment of apnoea and respiratory dynamics
Adjei T,  Purdy R,  Jorge J,  Adams E,  Buckle M,  Fry RE,  Green G,  Patel C,  Rogers R,  Slater R,  Tarassenko L,  Villarroel Montoya M,  Hartley C,  et al. (2022)
Non-contact physiological monitoring of post-operative patients in the Intensive Care Unit
Jorge J,  Villarroel M,  Tomlinson H,  Gibson O,  Darbyshire J,  Ede J,  Harford M,  Young JD,  Tarassenko L,  Watkinson P,  et al. (2022)