A Deep Classifier for Upper-Limbs Motor Anticipation Tasks in an Online BCI Setting

Valenti, Andrea and Barsotti, Michele and Bacciu, Davide and Ascari, Luca (2021) A Deep Classifier for Upper-Limbs Motor Anticipation Tasks in an Online BCI Setting. Bioengineering, 8 (2). p. 21. ISSN 2306-5354

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Abstract

Decoding motor intentions from non-invasive brain activity monitoring is one of the most challenging aspects in the Brain Computer Interface (BCI) field. This is especially true in online settings, where classification must be performed in real-time, contextually with the user’s movements. In this work, we use a topology-preserving input representation, which is fed to a novel combination of 3D-convolutional and recurrent deep neural networks, capable of performing multi-class continual classification of subjects’ movement intentions. Our model is able to achieve a higher accuracy than a related state-of-the-art model from literature, despite being trained in a much more restrictive setting and using only a simple form of input signal preprocessing. The results suggest that deep learning models are well suited for deployment in challenging real-time BCI applications such as movement intention recognition.

Item Type: Article
Subjects: Science Repository > Engineering
Depositing User: Managing Editor
Date Deposited: 07 Feb 2023 06:32
Last Modified: 05 Jul 2024 09:25
URI: http://research.manuscritpub.com/id/eprint/631

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