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多会话数据集的近红外光谱记录从中风患者控制脑机接口。

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

机构信息

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Butlerova St., 5A, Moscow, 117485, Russia.

Research Center of Neurology, Volokolamskoe shosse, 80, Moscow, 125367, Russia.

出版信息

Sci Data. 2024 Oct 25;11(1):1168. doi: 10.1038/s41597-024-04012-6.

DOI:10.1038/s41597-024-04012-6
PMID:39455586
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11512011/
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.

摘要

本文提供了一个超过 50 小时的近红外光谱（NIRS）记录的开放数据集。15 名中风患者共完成了 237 次运动想象脑机接口（BCI）的训练。BCI 由想象中的手部运动控制；视觉反馈是根据实时数据分类结果呈现的。我们提供了实验记录、患者人口统计学资料、临床评分（包括 ARAT 和 Fugl-Meyer）、在线 BCI 性能以及对血液动力学反应的简单分析。我们假设这个数据集可用于评估各种近红外光谱信号处理和分析技术在脑血管意外患者中的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/9116a59d8b75/41597_2024_4012_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/92ee30cac1ab/41597_2024_4012_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/2ddce3e11b72/41597_2024_4012_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/88fdea1364e8/41597_2024_4012_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/ad234e621250/41597_2024_4012_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/9116a59d8b75/41597_2024_4012_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/92ee30cac1ab/41597_2024_4012_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/2ddce3e11b72/41597_2024_4012_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/88fdea1364e8/41597_2024_4012_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/ad234e621250/41597_2024_4012_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/11512011/9116a59d8b75/41597_2024_4012_Fig5_HTML.jpg

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Medicine (Baltimore). 2023 Jun 30;102(26):e34148. doi: 10.1097/MD.0000000000034148.
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Sensorimotor Rhythm-Based Brain-Computer Interfaces for Motor Tasks Used in Hand Upper Extremity Rehabilitation after Stroke: A Systematic Review.基于感觉运动节律的脑机接口在中风后手上肢康复运动任务中的应用：一项系统综述。
Brain Sci. 2022 Dec 28;13(1):56. doi: 10.3390/brainsci13010056.
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Brain-machine interface-based training for improving upper extremity function after stroke: A meta-analysis of randomized controlled trials.
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The Application of Brain-Computer Interface in Upper Limb Dysfunction After Stroke: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.脑机接口在脑卒中后上肢功能障碍中的应用：随机对照试验的系统评价和荟萃分析
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