Work

Exploring the contribution of joint angles and sEMG signals on joint torque prediction accuracy using LSTM-based deep learning techniques

Year: 2024

Type: article

Source: Computer Methods in Biomechanics & Biomedical Engineering

DOI: 10.1080/10255842.2024.2400318

Authors: Engin Kaya, Hande Argunsah

Institution: Acıbadem University

Language: English

Topic: Muscle activation and electromyography studies

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4402270704

FWCI: 1.065

Cites: 49

Cited by: 10

Related to: 10