Classification of Facial Expressions for Intended Display of Emotions Using Brain-Computer Interfaces

Publication date

2020-09-01

Authors

Salari, E.
Freudenburg, Zachary VORCID 0000-0002-2790-0020
Vansteensel, Mariska JORCID 0000-0002-9252-5116ISNI 0000000392447362
Ramsey, NickORCID 0000-0002-7136-259XISNI 0000000399572879

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Abstract

Facial expressions are important for intentional display of emotions in social interaction. For people with severe paralysis, the ability to display emotions intentionally can be impaired. Current brain-computer interfaces (BCIs) allow for linguistic communication but are cumbersome for expressing emotions. Here, we investigated the feasibility of a BCI to display emotions by decoding facial expressions. We used electrocorticographic recordings from the sensorimotor cortex of people with refractory epilepsy and classified five facial expressions, based on neural activity. The mean classification accuracy was 72%. This approach could be a promising avenue for development of BCI-based solutions for fast communication of emotions. ANN NEUROL 2020;88:631-636.

Keywords

Neurology, Clinical Neurology

Citation

Salari, E, Freudenburg, Z V, Vansteensel, M J & Ramsey, N F 2020, 'Classification of Facial Expressions for Intended Display of Emotions Using Brain-Computer Interfaces', Annals of Neurology, vol. 88, no. 3, pp. 631-636. https://doi.org/10.1002/ana.25821