Lower-Limb Joint Torque Prediction Using LSTM Neural Networks and Transfer Learning

• Published in: IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING Vol. 30; pp. 600 - 609
• Main Authors: Zhang, Longbin, Soselia, Davit, Wang, Ruoli, Gutierrez-Farewik, Elena M.
• Format: Journal Article Publication
• Language: English
• Published: United States IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ankle; Ankle Joint; Athletes; Biomechanical Phenomena; Electromyography; generalizability; Humans; inverse dynamics; Joints (anatomy); Knee Joint; Learning; Long short-term memory; Lower Extremity; LSTM; Machine Learning; Mean square errors; Muscle strength; Muscles; Neural networks; Neural Networks, Computer; Performance prediction; Plantar flexion; Predictive models; Root-mean-square errors; Task analysis; time series; Torque; Training; Transfer learning

Estimation of joint torque during movement provides important information in several settings, such as effect of athletes' training or of a medical intervention, or analysis of the remaining muscle strength in a wearer of an assistive device. The ability to estimate joint torque during daily ac...