Dr Mark Elliott MEng, PhD, FIMA, FHEA

Dr Mark Elliott

School of Sport, Exercise and Rehabilitation Sciences
Associate Professor of Human Movement Analytics

Dr Elliott’s research is centred on data-driven and digital health focussed approaches to infer people’s health and behaviour, through the measure of human movement and physiology. He applies state-of-the-art methods to monitor, measure and model movement and physiology using data from wearable sensors, motion capture systems and smartphones. He has particular interests in using technologies to capture objective measures of physical function, detect early onset of osteoarthritis and analyse physical activity related behaviour.

Qualifications

MEng Electronic Systems Engineering (Aston University)

PhD Biomedical Engineering (Aston University)

Biography

Before completing his PhD, Mark qualified with an MEng in Electronic Systems Engineering (Aston University) and worked for 3 years as a Design Engineer in the telecommunications industry. He completed his PhD at Aston University, developing machine learning methods to discriminate between different walking patterns. He subsequently went on to complete two post-doctoral Research Fellow positions in the Sensory Motor Neuroscience (SyMoN) lab at the University of Birmingham, modelling the timing of human movement. He gained the post of Assistant Professor and subsequently, Associate Professor at the Institute of Digital Healthcare, WMG, University of Warwick in 2015, establishing his current research interests combining digital health and human movement analysis. He took up his current post in the School of Sport Exercise and Rehabilitation Sciences in 2024.

Postgraduate supervision

Dr Elliott is interested in supervising Masters and PhD students in the following areas:

  • Early detection of osteoarthritis and other musculoskeletal conditions using objective measures of movement, physiology and other variables.
  • Modelling and predicting health outcomes using smartphone/wearable based measures of physical activity, sleep and other variables.
  • Technologies to support self-management of physiotherapy (inc. virtual/augmented realities, smartphone apps)
  • Integration and standardisation of large human movement datasets.
  • Investigating the role of incentives for increasing physical activity using digital platforms.

Research

  • Applying analysis, modelling and machine learning methods to movement and physiology data to infer health and behaviour.
  • Developing and applying technology to support and monitor self-management of musculoskeletal (MSK) conditions.
  • Evaluation and validation of novel sensor technologies for quantifying movement related behaviour.
  • Investigating the role of digital incentives platforms for increasing physical activity.
  • Understanding the barriers to health technology adoption and health inequalities in MSK medicine.

Other activities

Fellow of the Institute of Mathematics and its Applications (FIMA)

Topic Driver for the AI 4 MSK Medicine Topic Group (TG-MSK), part of the WHO/ITU AI4Health Global Initiative.

Publications

Recent publications

Article

Clohessy, S, Arvanitis, TN, Rashid, U, Craddock, C, Evans, M, Toro, CT & Elliott, MT 2024, 'Using digital tools in clinical, health and social care research: a mixed-methods study of UK stakeholders', BMJ open, vol. 14, no. 4, e076613. https://doi.org/10.1136/bmjopen-2023-076613

Simpson, O, Elliott, M, Muller, C, Jones, T, Hentsch, P, Rooney, D, Cowell, N, Bloss, W & Bartington, S 2022, 'Evaluating actions to improve air quality at University Hospitals Birmingham NHS Foundation Trust', Sustainability, vol. 14, no. 18, 11128. https://doi.org/10.3390/su141811128

Elliott, M, Chua, WL & Wing, A 2016, 'Modelling single-person and multi-person event-based synchronisation', Current Opinion in Behavioral Sciences, vol. 8, pp. 167-174. https://doi.org/10.1016/j.cobeha.2016.01.015

View all publications in research portal