An early force prediction control scheme using multimodal sensing of electromyography and digit force signals.

ABSTRACT: Different grasping gestures result in the change of muscular activity of the forearm muscles. Similarly, the muscular activity changes with a change in grip force while grasping the object. This change in muscular activity, measured by a technique called Electromyography (EMG) is used in the upper limb bionic devices to select the grasping gesture. Previous research studies have shown gesture classification using pattern recognition control schemes. However, the use of EMG signals for force manipulation is less focused, especially during precision grasping. In this study, an early predictive control scheme is designed for the efficient determination of grip force using EMG signals from forearm muscles and digit force signals. The optimal pattern recognition (PR) control schemes are investi

SUBMITTER: Khan SM 

PROVIDER: S-EPMC11019178 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature