Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system-Reference-Cited by-同舟云学术

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

Published:2021-06 Issue: Volume:122 Page:110414
ISSN:0021-9290
Container-title:Journal of Biomechanics
language:en
Short-container-title:Journal of Biomechanics

Author:

Kanko Robert M.^ORCID,Laende Elise K.^ORCID,Strutzenberger Gerda,Brown Marcus,Selbie W. Scott^ORCID,DePaul Vincent^ORCID,Scott Stephen H.,Deluzio Kevin J.^ORCID

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Rehabilitation,Biomedical Engineering,Orthopedics and Sports Medicine,Biophysics

Reference30 articles.

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4. Bland, J.M., Altman, Douglas, G., 1986. Statistical methods for assessing agreement between two methods of clinical measurement, The Lancet, Originally published as Volume 1, Issue 8476 327, 307–310. https://doi.org/10.1016/S0140-6736(86)90837-8.

5. Concurrent validity of the GAITRite electronic walkway and the 10-m walk test for measurement of walking speed after stroke;Cleland;Gait Posture,2019

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