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arXiv · 1809.03300

Classification of grasping tasks based on EEG-EMG coherence

Giulia Cisotto·Anna V. Guglielmi·Leonardo Badia·Andrea Zanella
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Abstract

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.

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Giulia Cisotto, Anna V. Guglielmi, Leonardo Badia, Andrea Zanella. 2018-09-10. Classification of grasping tasks based on EEG-EMG coherence. https://doi.org/10.1109/healthcom.2018.8531140

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