This paper is in the following e-collection/theme issue:

mHealth for Data Collection and Research (673) Mobile Health (mhealth) (1917) Portable and Mobile Technologies for Rehabilitation (119) Cognitive and Neurorehabilitation (198) Fitness Trackers and Smart Pedometers/Accelerometers (492) mHealth for Rehabilitation (178)

Published on in Vol 6 , No 1 (2018) :January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/8815, first published .
Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

Authors of this article:

Brad Manor 1 Author Orcid Image ;   Wanting Yu 1 Author Orcid Image ;   Hao Zhu 1 Author Orcid Image ;   Rachel Harrison 1 Author Orcid Image ;   On-Yee Lo 1 Author Orcid Image ;   Lewis Lipsitz 1 Author Orcid Image ;   Thomas Travison 1 Author Orcid Image ;   Alvaro Pascual-Leone 2 Author Orcid Image ;   Junhong Zhou 1 Author Orcid Image
Article Authors Cited by (50) Tweetations (6) Metrics

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  2. Bunker M, Sher A, Akpokodje V, Villagra F, Parthaláin N, Akanyeti O. Advances in Computational Intelligence Systems. View