Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces

被引:72
作者
Hwang, Han-Jeong [1 ,2 ]
Lim, Jeong-Hwan [1 ]
Kim, Do-Won [1 ]
Im, Chang-Hwan [1 ]
机构
[1] Hanyang Univ, Dept Biomed Engn, Seoul 133791, South Korea
[2] Berlin Inst Technol, Machine Learning Grp, D-10587 Berlin, Germany
基金
新加坡国家研究基金会;
关键词
mental task classification; brain-computer interface; near-infrared spectroscopy; binary communication; locked-in syndrome; MOTOR IMAGERY; EYE-MOVEMENTS; SET-UP; BCI; CLASSIFICATION; CONNECTIVITY; CORTEX; RESPONSES; SIGNALS; SYSTEM;
D O I
10.1117/1.JBO.19.7.077005
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focused on enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated the performances of a variety of mental task combinations in order to determine the mental task pairs that are best suited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses while seven participants performed eight different mental tasks. Classification accuracies were then estimated for all possible pairs of the eight mental tasks (C-8(2) = 28). Based on this analysis, mental task combinations with relatively high classification accuracies frequently included the following three mental tasks: "mental multiplication," "mental rotation," and "right-hand motor imagery." Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
引用
收藏
页数:9
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