Lower Limb Joint Torque Prediction Using Long Short-Term Memory Network and Gaussian Process Regression
Mengsi Wang,
Zhenlei Chen,
Haoran Zhan
et al.
Abstract:The accurate prediction of joint torque is required in various applications. Some traditional methods, such as the inverse dynamics model and the electromyography (EMG)-driven neuromusculoskeletal (NMS) model, depend on ground reaction force (GRF) measurements and involve complex optimization solution processes, respectively. Recently, machine learning methods have been popularly used to predict joint torque with surface electromyography (sEMG) signals and kinematic information as inputs. This study aims to pr… Show more
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