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Privacy and personalisation: predicting Parkinson’s disease severity from real-world gait with federated learning.

Lookup NU author(s): Dr Chloe Hinchliffe, Dr Hugo Hiden, Dr Lisa AlcockORCiD, Dr Rachael LawsonORCiD, Professor Alison YarnallORCiD, Professor Lynn RochesterORCiD, Dr Silvia Del DinORCiD, Professor Paul WatsonORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Publication metadata

Author(s): Hinchliffe C, Hiden H, Alcock L, Lawson RA, Yarnall AJ, Rochester L, Del Din S, Watson P

Publication type: Article

Publication status: Published

Journal: Frontiers in Aging Neuroscience

Year: 2026

Volume: 18

Online publication date: 09/03/2026

Acceptance date: 17/02/2026

Date deposited: 09/03/2026

ISSN (electronic): 1663-4365

Publisher: Frontiers Research Foundation

URL: https://doi.org/10.3389/fnagi.2026.1766599

DOI: 10.3389/fnagi.2026.1766599

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Funding

Funder referenceFunder name
EPSRC-funded TORUS research programmeEPSRC-funded TORUS research programme (EP/X036146/1)
Lockhart Parkinson’s Disease Research Fund
Parkinson’s UK (J-0802, G-1301, G-1507)
the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre (BRC)
The EU Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 853981
the NIHR/Wellcome Trust Clinical Research Facility (CRF) infrastructure at Newcastle upon Tyne Hospitals NHS Foundation Trust
the UK Research and Innovation (UKRI) Engineering and Physical Sciences Research Council (EPSRC) (Grant Ref: EP/W031590/1, Grant Ref: EP/X031012/1 and Grant Ref: EP/X036146/1)

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