Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks.

Murray, Rosemarie; Mendez, Joel; Gabert, Lukas; Fey, Nicholas P; Liu, Honghai; Lenzi, Tommaso

Murray, Rosemarie; Mendez, Joel; Gabert, Lukas; Fey, Nicholas P; Liu, Honghai; Lenzi, Tommaso.

Afiliação

Murray R; Department of Mechanical Engineering, and Robotics Center, The University of Utah, Salt Lake City, UT 84112, USA.
Mendez J; Department of Mechanical Engineering, and Robotics Center, The University of Utah, Salt Lake City, UT 84112, USA.
Gabert L; Department of Mechanical Engineering, and Robotics Center, The University of Utah, Salt Lake City, UT 84112, USA.
Fey NP; Rocky Mountain Center for Occupational and Environmental Health, Salt Lake City, UT 84111, USA.
Liu H; Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Lenzi T; State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Shenzhen 518055, China.

Sensors (Basel) ; 22(23)2022 Dec 01.

Article em En | MEDLINE | ID: mdl-36502055

Assuntos

Amputados; Membros Artificiais; Humanos; Reprodutibilidade dos Testes; Caminhada/fisiologia; Marcha/fisiologia; Fenômenos Biomecânicos; Redes Neurais de Computação

Palavras-chave

A-mode ultrasound; above-knee amputee; ambulation mode classification; lower-limb powered prosthesis; neural signals; sonomyography; transfemoral amputee; user intent recognition

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Membros Artificiais / Amputados Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

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