Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots.

Yang, Sibo; Garg, Neha P; Gao, Ruobin; Yuan, Meng; Noronha, Bernardo; Ang, Wei Tech; Accoto, Dino

Yang, Sibo; Garg, Neha P; Gao, Ruobin; Yuan, Meng; Noronha, Bernardo; Ang, Wei Tech; Accoto, Dino.

Afiliação

Yang S; School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Garg NP; Rehabilitation Research Institute of Singapore (RRIS), Nanyang Technological University, Singapore 308232, Singapore.
Gao R; School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Yuan M; Rehabilitation Research Institute of Singapore (RRIS), Nanyang Technological University, Singapore 308232, Singapore.
Noronha B; School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Ang WT; School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Accoto D; Rehabilitation Research Institute of Singapore (RRIS), Nanyang Technological University, Singapore 308232, Singapore.

Sensors (Basel) ; 23(6)2023 Mar 10.

Article em En | MEDLINE | ID: mdl-36991709

Assuntos

Robótica; Humanos; Intenção; Eletromiografia/métodos; Extremidade Superior/fisiologia; Movimento (Física)

Palavras-chave

humanrobot interaction; machine learning; motion intention detection; sensory fusion; upper limb assistive robots; wearable sensors

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Robótica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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