This work presents an innovative application of the well-known concept of cortico-muscular coherence for the classification of various motor tasks, i.e., grasps of different kinds of objects. Our approach can classify objects with different weights (motor-related features) and different surface frictions (haptics-related features) with high accuracy (over 0:8). The outcomes presented here provide information about the synchronization existing between the brain and the muscles during specific activities; thus, this may represent a new effective way to perform activity recognition.
Cite
@article{arxiv.1809.03300,
title = {Classification of grasping tasks based on EEG-EMG coherence},
author = {Giulia Cisotto and Anna V. Guglielmi and Leonardo Badia and Andrea Zanella},
journal= {arXiv preprint arXiv:1809.03300},
year = {2020}
}