A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal.

Baygin, Mehmet; Barua, Prabal Datta; Dogan, Sengul; Tuncer, Turker; Key, Sefa; Acharya, U Rajendra; Cheong, Kang Hao

Baygin, Mehmet; Barua, Prabal Datta; Dogan, Sengul; Tuncer, Turker; Key, Sefa; Acharya, U Rajendra; Cheong, Kang Hao.

Afiliación

Baygin M; Department of Computer Engineering, College of Engineering, Ardahan University, Ardahan 75000, Turkey.
Barua PD; School of Business (Information System), University of Southern Queensland, Toowoomba, QLD 4350, Australia.
Dogan S; Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia.
Tuncer T; Cogninet Brain Team, Cogninet Australia, Sydney, NSW 2010, Australia.
Key S; Department of Digital Forensics Engineering, College of Technology, Firat University, Elazig 23119, Turkey.
Acharya UR; Department of Digital Forensics Engineering, College of Technology, Firat University, Elazig 23119, Turkey.
Cheong KH; Department of Orthopedics and Traumatology, Bingöl State Hospital, Ministry of Health, Bingöl 12000, Turkey.

Sensors (Basel) ; 22(5)2022 Mar 04.

Article en En | MEDLINE | ID: mdl-35271154

Asunto(s)

Algoritmos; Análisis de Ondículas; Mano; Fuerza de la Mano; Movimiento

Palabras clave

Frustum154; frustum pattern; grasp detection; sEMG signal classification

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Análisis de Ondículas Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Turquía

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