November 5, 2025

EMG pattern recognition by neural networks for multi fingers control

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Experiments demonstrate recognition of finger movement and joint angles with EMG signals, indicating advances in neural networks for robotics.

Recognition of finger movement and joint angles was achieved using EMG signals and neural networks, enhancing robotic control.
Key metrics include classification of movements, integrating data from 5 fingers and 10 joints into a robotic hand design.
Assessment involved online simulations and experiments focused on real-time interpretations of EMG patterns.
This implies potential improvements in the design of intuitive robotic systems; further applications may follow.

Uchida et al. (1992) studied this question.

View Full Paper

Ask AI

Bookmark

Experiments demonstrate recognition of finger movement and joint angles with EMG signals, indicating advances in neural networks for robotics.