Dr Mark Elliott MEng, PhD, FIMA, FHEA

Dr Mark Elliott

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

Contact details

Email
m.elliott.3@bham.ac.uk
Twitter
@dr_mte
View my research portal

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, Kempton, C, Ryan, K, Grinbergs, P & Elliott, M 2024, 'Exploring Older Adults' Perceptions of Using Digital Health Platforms for Self-Managing Musculoskeletal Health Conditions: Focus Group Study', JMIR Aging, vol. 7, e55693. https://doi.org/10.2196/55693

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

Hamilton, RI, Garcia, AA, Bowd, J, Hamilton, D, Mason, D, Elliott, M & Holt, C 2024, 'Utilising electrodermal activity sensor signals to quantify nociceptive response during movement activities', BMC Research Notes, vol. 17, no. 1, 36. https://doi.org/10.1186/s13104-024-06689-9

Perello-March, J, Burns, CG, Woodman, R, Birrell, S & Elliott, MT 2023, 'How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study', Human Factors. https://doi.org/10.1177/00187208231185705

Perello-March, JR, Burns, CG, Woodman, R, Elliott, MT & Birrell, SA 2023, 'Using fNIRS to Verify Trust in Highly Automated Driving', IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 1, pp. 739-751. https://doi.org/10.1109/TITS.2022.3211089

Evans, J, Hamilton, RI, Biggs, P, Holt, C & Elliott, MT 2022, 'Data sharing across osteoarthritis research groups and disciplines: Opportunities and challenges', Osteoarthritis and Cartilage Open, vol. 4, no. 1, 100236. https://doi.org/10.1016/j.ocarto.2022.100236

Perello-March, JR, Burns, CG, Woodman, R, Elliott, MT & Birrell, SA 2022, 'Driver State Monitoring: Manipulating Reliability Expectations in Simulated Automated Driving Scenarios', IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 6, pp. 5187-5197. https://doi.org/10.1109/TITS.2021.3050518

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

Perello-March, JR, Burns, CG, Birrell, SA, Woodman, R & Elliott, MT 2022, 'Physiological Measures of Risk Perception in Highly Automated Driving', IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 5, pp. 4811-4822. https://doi.org/10.1109/TITS.2022.3146793

Vayalapra, S, Wang, X, Qureshi, A, Vepa, A, Rahman, U, Palit, A, Williams, MA, King, R & Elliott, MT 2022, 'Repeatability of Inertial Measurement Units for Measuring Pelvic Mobility in Patients Undergoing Total Hip Arthroplasty', Sensors, vol. 23, no. 1, 377. https://doi.org/10.3390/s23010377

Eshelby, V, Sogut, M, Jolly, K, Vlaev, I & Elliott, MT 2022, 'Stay home and stay active? The impact of stay-at-home restrictions on physical activity routines in the UK during the COVID-19 pandemic', Journal of Sports Sciences, vol. 40, no. 3, pp. 310-322. https://doi.org/10.1080/02640414.2021.1992885

Lemola, S, Gkiouleka, A, Read, B, Realo, A, Walasek, L, Tang, NKY & Elliott, MT 2021, 'Can a ‘rewards-for-exercise app’ increase physical activity, subjective well-being and sleep quality? An open-label single-arm trial among university staff with low to moderate physical activity levels', BMC Public Health, vol. 21, no. 1, 782. https://doi.org/10.1186/s12889-021-10794-w

Wang, X, Qureshi, A, Vepa, A, Rahman, U, Palit, A, Williams, MA, King, R & Elliott, MT 2020, 'A Sensor-Based Screening Tool for Identifying High Pelvic Mobility in Patients Due to Undergo Total Hip Arthroplasty', Sensors. https://doi.org/10.3390/s20216182

Conference contribution

Sharma, S, Woodman, R & Elliott, MT 2023, Exploring the Impact of Autonomous Taxis on People with Disabilities. in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)., 10421862, IEEE Conference on Intelligent Transportation Systems, Institute of Electrical and Electronics Engineers (IEEE), pp. 5210-5215, 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, 24/09/23. https://doi.org/10.1109/ITSC57777.2023.10421862

Review article

Su, Z, Woodman, R, Smyth, J & Elliott, M 2023, 'The relationship between aggressive driving and driver performance: A systematic review with meta-analysis', Accident Analysis and Prevention, vol. 183, 106972. https://doi.org/10.1016/j.aap.2023.106972

View all publications in research portal