Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis.

Mohan, Dhanya Menoth; Khandoker, Ahsan Habib; Wasti, Sabahat Asim; Ismail Ibrahim Ismail Alali, Sarah; Jelinek, Herbert F; Khalaf, Kinda

Mohan, Dhanya Menoth; Khandoker, Ahsan Habib; Wasti, Sabahat Asim; Ismail Ibrahim Ismail Alali, Sarah; Jelinek, Herbert F; Khalaf, Kinda.

Afiliação

Mohan DM; Department of Biomedical Engineering, Health Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
Khandoker AH; Department of Biomedical Engineering, Health Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
Wasti SA; Neurological Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates.
Ismail Ibrahim Ismail Alali S; Department of Biomedical Engineering, Health Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
Jelinek HF; Department of Biomedical Engineering, Health Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
Khalaf K; Department of Biomedical Engineering, Health Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.

Front Neurol ; 12: 650024, 2021.

Article em En | MEDLINE | ID: mdl-34168608

Palavras-chave

artificial intelligence; dynamics; gait; hemiplegia; machine learning; post-stroke; spatiotemporal; statistical tools

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research / Systematic_reviews Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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