ePrints

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases.

Lookup NU author(s): Dr Lisa AlcockORCiD, Philip Brown, Dr Alma CantuORCiD, Dr Silvia Del DinORCiD, Dr Cameron KirkORCiD, Professor Lynn RochesterORCiD, Dr Kirsty ScottORCiD

Downloads

• Published version [.pdf]

Licence

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

Publication metadata

Author(s): Romijnders R, Salis F, Hansen C, Küderle K, Paraschiv-Ionescu A, Cereatti A, Alcock L, Aminian K, Becker C, Bertuletti S, Bonci T, Brown P, Buckley E, Cantu A, Carsin A, Caruso M, Caulfield B, Chiari L, D'Ascanio I, Del Din S, Eskofier BM, Fernstad S, Fröhlich M, Garcia-Aymerich J, Gazit E, Hausdorff JM, Hiden H, Hume E, Keogh A, Kirk C, Kluge F, Koch S, Mazza C, Megaritis D, Micó-Amigo E, Müller A, Palmerini L, Rochester L, Schwickert L, Scott K, Sharrack B, Singleton D, Soltani A, Ullrich M, Vereijken B, Vogiatzis I, Yarnall A, Schmidt G, Maetzler W

Publication type: Article

Publication status: Published

Journal: Frontiers in Neurology

Year: 2023

Volume: 14

Online publication date: 16/10/2023

Acceptance date: 18/09/2023

Date deposited: 19/10/2023

ISSN (electronic): 1664-2295

Publisher: Frontiers Research Foundation

URL: https://doi.org/10.3389/fneur.2023.1247532

DOI: 10.3389/fneur.2023.1247532

Data Access Statement: The data analyzed in this study is subject to the following licenses/restrictions: The Mobilise-D consortium are planning to make representative data available through online repositories (Zenodo & GitHub) in the near future. All scripts that were designed for the current analysis are available online and can be found at: GitHub, https://github.com/neurogeriatricskiel/ mobilised. Requests to access these datasets should be directed to RR, r.romijnders@neurologie.uni-kiel.de.

Altmetrics

Funding

Share