Assessing Time-Resolved fNIRS for Brain-Computer Interface Applications of Mental Communication
Assessing Time-Resolved fNIRS for Brain-Computer Interface Applications of Mental Communication
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DOI：
10.3389/fnins.2020.00105
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发表时间：
2020-02-18
影响因子：
4.3
通讯作者：
St Lawrence, Keith
中科院分区：
文献类型：
--
作者：
Abdalmalak, Androu;Milej, Daniel;St Lawrence, Keith
脑机接口（bci）作为一种提高残疾患者生活质量的工具越来越受欢迎。最近，基于时间分辨功能近红外光谱（TR-fNIRS）的脑机接口因其增强的深度灵敏度导致较低的脑外层信号污染而受到关注。本研究首次介绍了基于TR-fNIRS的脑机接口在健康参与者“心理交流”中的应用。研究人员招募了21名参与者，反复向他们提出一系列问题，并要求他们想象打网球是“是”，而保持放松是“否”。光子平均飞行时间的变化被用来计算氧和脱氧血红蛋白浓度的变化，因为它在深度灵敏度和信噪比之间提供了一个很好的折衷。从平均氧血红蛋白信号中提取特征，将其分类为“是”或“否”反应。使用线性判别分析（LDA）和支持向量机（SVM）分类器对响应进行分类，采用留一交叉验证法。使用LDA和SVM，所有参与者的总体准确率分别为75%和76%。结果还显示，问题之间的准确性没有显著差异。此外，记录了21名参与者中7名在运动想象（MI）和休息时的生理参数[心率（HR）和平均动脉压（MAP）]，以研究这些参数在不同条件下的变化。这些参数在不同条件下无显著差异。这些结果表明，TR-fNIRS可以作为脑损伤患者的脑机接口。
Brain-computer interfaces (BCIs) are becoming increasingly popular as a tool to improve the quality of life of patients with disabilities. Recently, time-resolved functional near-infrared spectroscopy (TR-fNIRS) based BCIs are gaining traction because of their enhanced depth sensitivity leading to lower signal contamination from the extracerebral layers. This study presents the first account of TR-fNIRS based BCI for "mental communication" on healthy participants. Twenty-one (21) participants were recruited and were repeatedly asked a series of questions where they were instructed to imagine playing tennis for "yes" and to stay relaxed for "no." The change in the mean time-of-flight of photons was used to calculate the change in concentrations of oxy- and deoxyhemoglobin since it provides a good compromise between depth sensitivity and signal-to-noise ratio. Features were extracted from the average oxyhemoglobin signals to classify them as "yes" or "no" responses. Linear-discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the responses using the leave-one-out cross-validation method. The overall accuracies achieved for all participants were 75% and 76%, using LDA and SVM, respectively. The results also reveal that there is no significant difference in accuracy between questions. In addition, physiological parameters [heart rate (HR) and mean arterial pressure (MAP)] were recorded on seven of the 21 participants during motor imagery (MI) and rest to investigate changes in these parameters between conditions. No significant difference in these parameters was found between conditions. These findings suggest that TR-fNIRS could be suitable as a BCI for patients with brain injuries.