Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model.

Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse

Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse.

Afiliação

Lambrecht S; Division PMA, Department of Mechanical Engineering, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. stefan.lambrecht@kuleuven.be.
Harutyunyan A; Department of Biomedical Kinesiology, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. stefan.lambrecht@kuleuven.be.
Tanghe K; AI Laboratory, Vrije Universiteit Brussel, 1050 Ixelles, Belgium. anna.harutyunyan@vub.ac.be.
Afschrift M; Division PMA, Department of Mechanical Engineering, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. kevin.tanghe@kuleuven.be.
De Schutter J; Department of Biomedical Kinesiology, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. Maarten.afschrift@kuleuven.be.
Jonkers I; Division PMA, Department of Mechanical Engineering, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. joris.deschutter@kuleuven.be.

Sensors (Basel) ; 17(4)2017 03 24.

Article em En | MEDLINE | ID: mdl-28338618

Assuntos

Marcha; Algoritmos; Fenômenos Biomecânicos; Pé; Humanos

Palavras-chave

adaptive thresholds; gait segmentation; kinematics; modeling; neuroprostheses; neurorobotics; real-time event detection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Marcha Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Bélgica País de publicação: Suíça

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