Accelerometry-based digital gait characteristics for classification of Parkinson's disease: What counts?

Rehman, R.Z.U., Buckley, C., Mico-Amigo, M.E. et al. (7 more authors) (2020) Accelerometry-based digital gait characteristics for classification of Parkinson's disease: What counts? IEEE Open Journal of Engineering in Medicine and Biology, 1. pp. 65-73. ISSN 2644-1276

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/
Keywords: Classification; Machine Learning; Digital Gait; Parkinson's disease; Partial least square-discriminant analysis (PLS-DA)
Dates:
  • Accepted: 20 December 2019
  • Published (online): 21 January 2020
  • Published: 14 February 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 09 Jun 2020 14:08
Last Modified: 09 Jun 2020 14:14
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: https://doi.org/10.1109/ojemb.2020.2966295

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