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

Mobile Health (mhealth) (2939) Cognitive and Neurorehabilitation (262) Fitness Trackers and Smart Pedometers/Accelerometers (561) mHealth for Rehabilitation (263)

Published on in Vol 19, No 5 (2017): May

Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting

Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting

Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting

Authors of this article:

Megan K O'Brien1, 2 Author Orcid Image ;   Nicholas Shawen1 Author Orcid Image ;   Chaithanya K Mummidisetty1 Author Orcid Image ;   Saninder Kaur1 Author Orcid Image ;   Xiao Bo3 Author Orcid Image ;   Christian Poellabauer3 Author Orcid Image ;   Konrad Kording2 Author Orcid Image ;   Arun Jayaraman1, 2 Author Orcid Image
Article Authors Cited by (50) Tweetations (15) Metrics

Journals

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  20. Botonis O, Harari Y, Embry K, Mummidisetty C, Riopelle D, Giffhorn M, Albert M, Heike V, Jayaraman A. Wearable airbag technology and machine learned models to mitigate falls after stroke. Journal of NeuroEngineering and Rehabilitation 2022;19(1) View
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Books/Policy Documents

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  2. Xiao T, Albert M. Artificial Intelligence in Brain and Mental Health: Philosophical, Ethical & Policy Issues. View