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主观问卷能否用作脑机接口性能预测指标?

Can a Subjective Questionnaire Be Used as Brain-Computer Interface Performance Predictor?

作者信息

Rimbert Sébastien, Gayraud Nathalie, Bougrain Laurent, Clerc Maureen, Fleck Stéphanie

机构信息

Université de Lorraine, Inria, LORIA, Neurosys Team, Nancy, France.

Université Côte d'Azur, Inria, Sophia-Antipolis Mditerrannée, Athena Team, Valbonne, France.

出版信息

Front Hum Neurosci. 2019 Jan 23;12:529. doi: 10.3389/fnhum.2018.00529. eCollection 2018.

DOI:10.3389/fnhum.2018.00529
PMID:30728772
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6352609/
Abstract

Predicting a subject's ability to use a Brain Computer Interface (BCI) is one of the major issues in the BCI domain. Relevant applications of forecasting BCI performance include the ability to adapt the BCI to the needs and expectations of the user, assessing the efficiency of BCI use in stroke rehabilitation, and finally, homogenizing a research population. A limited number of recent studies have proposed the use of subjective questionnaires, such as the Motor Imagery Questionnaire Revised-Second Edition (MIQ-RS). However, further research is necessary to confirm the effectiveness of this type of subjective questionnaire as a BCI performance estimation tool. In this study we aim to answer the following questions: can the MIQ-RS be used to estimate the performance of an MI-based BCI? If not, can we identify different markers that could be used as performance estimators? To answer these questions, we recorded EEG signals from 35 healthy volunteers during BCI use. The subjects had previously completed the MIQ-RS questionnaire. We conducted an offline analysis to assess the correlation between the questionnaire scores related to Kinesthetic and Motor imagery tasks and the performances of four classification methods. Our results showed no significant correlation between BCI performance and the MIQ-RS scores. However, we reveal that BCI performance is correlated to habits and frequency of practicing manual activities.

摘要

预测受试者使用脑机接口(BCI)的能力是BCI领域的主要问题之一。预测BCI性能的相关应用包括使BCI适应用户需求和期望的能力、评估BCI在中风康复中的使用效率,以及最终使研究人群同质化。最近有少数研究提出使用主观问卷,如修订第二版运动想象问卷(MIQ-RS)。然而,需要进一步研究来证实这类主观问卷作为BCI性能评估工具的有效性。在本研究中,我们旨在回答以下问题:MIQ-RS能否用于估计基于运动想象的BCI的性能?如果不能,我们能否识别出可作为性能估计指标的不同标志物?为了回答这些问题,我们在BCI使用过程中记录了35名健康志愿者的脑电图信号。这些受试者之前已经完成了MIQ-RS问卷。我们进行了离线分析,以评估与动觉和运动想象任务相关的问卷分数与四种分类方法的性能之间的相关性。我们的结果表明,BCI性能与MIQ-RS分数之间没有显著相关性。然而,我们发现BCI性能与手工活动的习惯和练习频率相关。

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User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.用户对运动想象脑机接口中表现的自我预测
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