3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.RO2023★ 1 cited
Predicting Continuous Locomotion Modes via Multidimensional Feature Learning from sEMG
Peiwen Fu, Wenjuan Zhong, Yuyang Zhang +5
Walking-assistive devices require adaptive control methods to ensure smooth transitions between various modes of locomotion. For this purpose, detecting human locomotion modes (e.g…
cs.RO2023★ 3 cited
Gait Cycle-Inspired Learning Strategy for Continuous Prediction of Knee Joint Trajectory from sEMG
Xueming Fu, Hao Zheng, Luyan Liu +9
Predicting lower limb motion intent is vital for controlling exoskeleton robots and prosthetic limbs. Surface electromyography (sEMG) attracts increasing attention in recent years…