An Adversarial Learning Framework for Reliable Myoelectric Force Estimation Under Fatigue
Electromyography (EMG) signals are widely used as control inputs for myoelectric exoskeletons. However, muscle fatigue, which can result from prolonged use or heavy loads, significantly affects muscle activation patterns, leading to reduced estimation accuracy. To address this challenge, we propose