Projects per year
Personal profile
Academic Biography
Grant Trewartha is Professor of Digital Healthcare Interventions within the School of Health and Life Sciences, joining Teesside University in August 2023.
He graduated from Loughborough University in 1997 with a BSc in Sports Science and from the same institution in 2001 with a PhD in Biomechanics / Computer Vision. His PhD project on "Three-dimensional automatic tracking of human movement" was conducted under the supervision of Prof Fred Yeadon and won awards at national and international scientific congresses.
From 2001-16, Grant was a member of academic staff in the Department for Health at the University of Bath, where he taught on sport-related degree programmes and carried out research in human biomechanics with sport and health applications and sport injury prevention. He co-directed the "Rugby Science" research group and led numerous projects on behalf of the sport's governing bodies relating to player welfare and injury prevention.
From 2016-23, he was Head of Biomechanics at NURVV Ltd, a wearable technology start-up who specialised in developing wearable technology products for sport and health markets.
Summary of Research Interests
Grant's primary research interests are in digital mobility monitoring. This includes: remote monitoring of gait and balance, self-management of gait rehabilitation, use of digital health tools for injury risk factor analyses, and wearable technology approaches for rehabilitation of sport injuries.
Enterprise Interest and Activities
Having spent 7 years in industry with NURVV Ltd, Grant has a keen interest and expertise in the deployment of wearable technology products for human motion monitoring 'in the wild'.
At NURVV, Grant had close involvement in the end-to-end product development process, including idea generation, product proposition, market research, sensor design & testing, algorithm development for firmware (metrics from raw data) and app features (insights), hardware testing, metrics validations, product roadmap.
External Research Collaborations
Dr Ezio Preatoni, University of Bath - Wearable technology and Machine Learning analyses for human motion applications
Dr Dario Cazzola, University of Bath - Computational musculoskeletal modelling applied to injury prevention
Dr Alex Atack, St Mary's University - Wearable technology applied to sport injury rehabilitation
Education/Academic qualification
PhD, Three-dimensional automatic tracking of human movement, Loughborough University
1 Jan 1998 → 12 Jul 2001
Award Date: 12 Jul 2001
Bachelor, Sports Science, Loughborough University
15 Sept 1994 → 10 Jul 2001
Award Date: 10 Jul 1997
External positions
Honorary Reader, University of Bath
1 Oct 2016 → …
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Collaborations and top research areas from the last five years
Projects
- 1 Finished
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AI-empowered Mobile Application System for Amputee Gait Training and Assessment
Trewartha, G. (PI)
1/09/23 → 31/03/24
Project: Research
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Balance assessment in cardio-respiratory conditions
Harrison, S. L., Craig, C. E., Loughran, K. & Trewartha, G., 1 Jan 2025, Gait, Balance, and Mobility Analysis: Theoretical, Technical, and Clinical Applications. Stuart, S. & Morris, R. (eds.). Academic Press, p. 435-466 32 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter
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Persistent pain is associated with poorer balance and gait performance for people with Chronic Obstructive Pulmonary Disease
Loughran, K. J., Trewartha, G., Martin, D., Fernandes-James, C., Shea, R., Dixon, J., Tough, D. & Harrison, S. L., 1 Jul 2025, In: Respiratory Medicine. 243, p. 108133 108133.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Downloads (Pure) -
Clustering analysis across different speeds reveals two distinct running techniques with no differences in running economy
Rivadulla, A. R., Chen, X., Cazzola, D., Trewartha, G. & Preatoni, E., 11 Jul 2024, In: Sports Biomechanics.Research output: Contribution to journal › Article › peer-review
Open Access -
Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions
Carter, J., Chen, X., Cazzola, D., Trewartha, G. & Preatoni, E., 29 Aug 2024, In: PeerJ. 12, 8, 21 p., e17896.Research output: Contribution to journal › Article › peer-review
Open AccessFile7 Downloads (Pure) -
Data should be made as simple as possible but not simpler: The method chosen for dimensionality reduction and its parameters can affect the clustering of runners based on their kinematics
Rivadulla, A. R., Chen, X., Cazzola, D., Trewartha, G. & Preatoni, E., 1 Dec 2024, In: Journal of Biomechanics. 177, 16 p., 112433.Research output: Contribution to journal › Article › peer-review
Open AccessFile5 Downloads (Pure)
Datasets
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Full Body Kinematics and Ground Reaction Forces of Fifty Heterogeneous Runners Completing Treadmill Running at Various Speeds and Gradients
Carter, J. (Creator), Chen, X. (Creator), Cazzola, D. (Creator), Trewartha, G. (Creator), Preatoni, E. (Creator), Carter, J. (Contributor), Preatoni, E. (Contributor), Chen, X. (Contributor), Cazzola, D. (Contributor) & Trewartha, G. (Contributor), University of Bath, 30 May 2024
DOI: 10.15125/bath-01341, https://researchdata.bath.ac.uk/id/eprint/1341
Dataset