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The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

Gait Analysis with Wearables can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders

Lookup NU author(s): Dr Rana RehmanORCiD, Dr Silvia Del DinORCiD, Dr Lisa AlcockORCiD, Dr Yu GuanORCiD, Professor Lynn RochesterORCiD

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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): Rehman RZU, Zhou Y, Del Din S, Alcock L, Hansen C, Guan Y, Hortobágyi T, Maetzler W, Rochester L, Lamoth CJC

Publication type: Article

Publication status: Published

Journal: Sensors

Year: 2020

Volume: 20

Issue: 23

Online publication date: 07/12/2020

Acceptance date: 04/12/2020

Date deposited: 09/12/2020

ISSN (print): 1424-8239

ISSN (electronic): 1424-8220

Publisher: MDPI AG

URL: https://doi.org/10.3390/s20236992

DOI: 10.3390/s20236992

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Funding

Funder referenceFunder name
721577

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