Dr Grant Trewartha PhD, BSc (Hons), FHEA

Dr Grant Trewartha

School of Sport, Exercise and Rehabilitation Sciences
Associate Professor in Sport Data Science

Contact details

Address
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Grant works on health and sport performance technology that's built to travel — remote patient/athlete monitoring, wearable sensing and AI decision support carried from the lab and clinic into the hands of real people.

Qualifications

  • Agile Project Management (Foundation & Practitioner), APMG, 2016
  • Fellow, Higher Education Academy (UK), 2015
  • PhD Sport and Exercise Sciences – Biomechanics, Loughborough University, 2001
  • BSc (Hons.) Sport and Exercise Science, Loughborough University, 1997

Biography

Grant gained his PhD in Biomechanics/Computer Vision from Loughborough University (2001), supervised by Prof Fred Yeadon, before joining the University of Bath (2001–16), where he co-directed the "Rugby Science" research group and led national and international projects on player welfare and injury prevention for the sport's governing bodies. He then spent seven years (2016–23) as Head of Biomechanics at wearable technology start-up NURVV Ltd, before returning to academia as Professor of Digital Healthcare Interventions at Teesside University. He holds an Honorary Reader position at the University of Bath and Emeritus Professor position at Teesside. He has published over 90 peer-reviewed papers (H-index 34) and attracted research funding from NIHR, EPSRC, World Rugby and the Academy of Medical Sciences.

Grant’s commercial background includes seven years spent as Head of Biomechanics at NURVV Ltd, leading end-to-end R&D for a consumer wearable running platform — from sensor and algorithm design through to app feature logic and product roadmap. He has also conducted academic consultancy projects for a range of organisations, including Visiba Ltd (AI-Triage), Digital Vitality Ltd (healthcare technologies), Impact Tech Labs (sport technology), Rugby Football Union (catastrophic injury surveillance), and as an expert witness for a sport injury case.

Teaching

  • Grant primarily teaches on the MSc Sport Data Science and AI programme.
  • Module Leader for “Sports Data Management & Visualisation”

Postgraduate supervision

Grant has successfully supervised 13 PhD to completion. He is interested in supervising Masters and PhD students in the following areas:
• Technology-informed movement rehabilitation
• Multisource AI-informed modelling for clinical decision support such as triage and injury prediction
• Biomechanics of balance recovery and fall prevention
• Data science approaches to athlete monitoring

Research

Multisource AI for risk stratification and decision support; wearable and sensor-based monitoring of human movement; digital health technologies for remote patient and athlete monitoring; and the translation of algorithms from controlled research settings into real-world products and services, in both sport and healthcare.

Current Projects

  • Multimodal AI-informed triage combining contextual and physiological data, with Visiba Ltd (Academy of Medical Sciences Cross-Sector Experience Award)
  • AI risk-stratification and remote monitoring for frailty virtual wards (EPSRC NortHFutures)
  • Novel sensor technologies for remote balance and gait monitoring applications (with Digital Vitality Ltd and EPSRC NortHFutures)
  • Including social and community integration measures in evaluating hip fracture recovery (NIHR Team Science)
  • Deep learning and wearable-sensor prediction of running biomechanics and ground reaction forces (with University of Bath)

Publications

Recent publications

Article

Rivadulla, AR, Chen, X, Cazzola, D, Trewartha, G & Preatoni, E 2026, 'A Small network of Consumer-Based wearable sensors Enables The identification of The neutral- and Tilted-Pelvis running techniques', Journal of Biomechanics, vol. 206, 113481. https://doi.org/10.1016/j.jbiomech.2026.113481

Rivadulla, AR, Chen, X, Cazzola, D, Trewartha, G & Preatoni, E 2026, 'Clustering analysis across different speeds reveals two distinct running techniques with no differences in running economy', Sports biomechanics, vol. 25, no. 1, pp. 22-45. https://doi.org/10.1080/14763141.2024.2372608

Rivadulla, AR, Sheehy, Z, Chen, X, Cazzola, D, Trewartha, G & Preatoni, E 2026, 'Does preferred technique influence how kinematics change during a run to exhaustion?—A cluster based approach', PeerJ, vol. 14, e20673. https://doi.org/10.7717/peerj.20673

Carter, J, Chen, X, Cazzola, D, Trewartha, G & Preatoni, E 2026, 'Estimation of lower limb joint moments using consumer realistic wearable sensor locations and deep learning–finding the balance between accuracy and consumer viability', Sports biomechanics, vol. 25, no. 4, pp. 516-531. https://doi.org/10.1080/14763141.2025.2526702

Cordero-Sánchez, J, Sheehy, Z, Serrancolí, G, Preatoni, E, Trewartha, G & Cazzola, D 2026, 'Prediction of on-field rugby scrummaging contact forces from videos using artificial neural networks', PLOS One, vol. 21, no. 4, e0330097. https://doi.org/10.1371/journal.pone.0330097

Review article

Trewartha, G, Janssens, L & Harrison, S 2026, 'Digital exclusion faced by people living with chronic respiratory disease: Challenges, implications and solutions', Chronic Respiratory Disease, vol. 23, 14799731261441307. https://doi.org/10.1177/14799731261441307

View all publications in research portal