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 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.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2024-10-25
DOI
https://doi.org/10.1038/s41597-024-04012-6
Citations
6
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
2.06

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

М. Р. Исаев, R. Kh. Lyukmanov, Pavel Bobrov, Ekaterina S. Ikonnikova et al.
6 citations
Scientific Data
EEG and Brain-Computer Interfaces
2.06
article

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

М. Р. Исаев, R. Kh. Lyukmanov, Pavel Bobrov, Ekaterina S. Ikonnikova, М. А. Пирадов, Н. А. Супонева, О. А. Мокиенко, Anastasiia N. Cherkasova
article en
6 citations

Abstract

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.

Scientific DataVol. 11(1)
Institute of Higher Nervous Activity and Neurophysiology (RU), Research Center of Neurology (RU)
Ministry of Science and Higher Education of the Russian Federation
Good health and well-being
Openalex Percentile: Top 13%
EEG and Brain-Computer Interfaces
2.06
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.