A cross-subject decoding algorithm for patients with disorder of consciousness based on P300 brain computer interface

Brain computer interface (BCI) technology may provide a new way of communication for some patients with disorder of consciousness (DOC), which can directly connect the brain and external devices. However, the DOC patients' EEG differ significantly from that of the normal person and are difficul...

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Bibliographic Details
Published in:Frontiers in neuroscience Vol. 17; p. 1167125
Main Authors: Wang, Fei, Wan, Yinxing, Li, Zhuorong, Qi, Feifei, Li, Jingcong
Format: Journal Article
Language:English
Published: Switzerland Frontiers Research Foundation 20.07.2023
Frontiers Media S.A
Subjects:
Accuracy
Algorithms
Behavior
Brain
brain computer interface
Coma
Computer applications
Consciousness
cross-subject
Data collection
Diagnosis
disorder of consciousness
EEG
Experiments
Implants
Localization
Neuroscience
P300
Patients
disorder of consciousness
brain computer interface
cross-subject
EEG
P300
ISSN:1662-453X, 1662-4548, 1662-453X
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Summary:Brain computer interface (BCI) technology may provide a new way of communication for some patients with disorder of consciousness (DOC), which can directly connect the brain and external devices. However, the DOC patients' EEG differ significantly from that of the normal person and are difficult to collected, the decoding algorithm currently only is trained based on a small amount of the patient's own data and performs poorly. In this study, a decoding algorithm called WD-ADSTCN based on domain adaptation is proposed to improve the DOC patients' P300 signal detection. We used the Wasserstein distance to filter the normal population data to increase the training data. Furthermore, an adversarial approach is adopted to resolve the differences between the normal and patient data. The results showed that in the cross-subject P300 detection of DOC patients, 7 of 11 patients achieved an average accuracy of over 70%. Furthermore, their clinical diagnosis changed and CRS-R scores improved three months after the experiment. These results demonstrated that the proposed method could be employed in the P300 BCI system for the DOC patients, which has important implications for the clinical diagnosis and prognosis of these patients.
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Edited by: Yang Bai, The First Affiliated Hospital of Nanchang University, China
Reviewed by: Marina Raguz, Dubrava Clinical Hospital, Croatia; Fang Peng, University of Electronic Science and Technology of China, China
These authors have contributed equally to this work and share first authorship
ISSN:1662-453X
1662-4548
1662-453X
DOI:10.3389/fnins.2023.1167125