Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 22; p. 7359
• Main Authors: Chen, Juntao, Zhang, Zhiqing, Guan, Wei, Cao, Xinxin, Liang, Ke
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18.11.2024; MDPI
• Subjects: Accuracy; Algorithms; Analysis; control accuracy; Decomposition; Deep Learning; EEMD-IWOA-LSTM; Hand - physiology; Humans; Mathematical models; Neural networks; Neural Networks, Computer; Optimization algorithms; physiological tremor; Physiology; Remote control; Robotics - methods; Robots; teleoperated robot; Time series; Tremor - physiopathology; EEMD-IWOA-LSTM; physiological tremor; teleoperated robot; control accuracy

Currently, teleoperated robots, with the operator’s input, can fully perceive unknown factors in a complex environment and have strong environmental interaction and perception abilities. However, physiological tremors in the human hand can seriously affect the accuracy of processes that require high...