A multiple session dataset of NIRS recordings from stroke patients controlling brain–computer interface

This paper presents an open dataset of over 50 hours of near infrared spectroscopy (NIRS) recordings. Fifteen stroke patients completed a total of 237 motor imagery brain–computer interface (BCI) sessions. The BCI was controlled by imagined hand movements; visual feedback was presented based on the...

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Bibliographic Details
Published in:Scientific data 2024-10, Vol.11 (1), p.1168-7, Article 1168
Main Authors: Isaev, Mikhail R., Mokienko, Olesya A., Lyukmanov, Roman Kh, Ikonnikova, Ekaterina S., Cherkasova, Anastasiia N., Suponeva, Natalia A., Piradov, Michael A., Bobrov, Pavel D.
Format: Article
Language:English
Subjects:
631/378/1689/534
631/378/2632/2634
692/617/375/1370/534
Aged
Algorithms
Artificial intelligence
Biochips
Brain
Brain research
Brain-Computer Interfaces
Classification
Computer applications
Data Descriptor
Datasets
Female
Hemodynamics
Hemoglobin
Humanities and Social Sciences
Humans
Imagination
Implants
Infrared spectroscopy
Interfaces
Male
Mental task performance
Middle Aged
multidisciplinary
Open access
Patients
Physical therapists
Rehabilitation
Science
Science (multidisciplinary)
Signal processing
Spectroscopy, Near-Infrared
Spectrum analysis
Stroke
Stroke - physiopathology
Visual perception
Visual system
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Summary:This paper presents an open dataset of over 50 hours of near infrared spectroscopy (NIRS) recordings. Fifteen stroke patients completed a total of 237 motor imagery brain–computer interface (BCI) sessions. The BCI was controlled by imagined hand movements; visual feedback was presented based on the real–time data classification results. We provide the experimental records, patient demographic profiles, clinical scores (including ARAT and Fugl–Meyer), online BCI performance, and a simple analysis of hemodynamic response. We assume that this dataset can be useful for evaluating the effectiveness of various near–infrared spectroscopy signal processing and analysis techniques in patients with cerebrovascular accidents.
ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-024-04012-6