標題: | Neural Activities Classification of Human Inhibitory Control Using Hierarchical Model |
作者: | Chikara, Rupesh Kumar Ko, Li-Wei 交大名義發表 生物科技學系 生物資訊及系統生物研究所 National Chiao Tung University Department of Biological Science and Technology Institude of Bioinformatics and Systems Biology |
關鍵字: | electroencephalography (EEG);ERP-P300;hierarchical classification model;phase locking value;brain-computer interface;human inhibitory control |
公開日期: | 1-九月-2019 |
摘要: | Human inhibitory control refers to the suppression of behavioral response in real environments, such as when driving a car or riding a motorcycle, playing a game and operating a machine. The P300 wave is a neural marker of human inhibitory control, and it can be used to recognize the symptoms of attention deficit hyperactivity disorder (ADHD) in human. In addition, the P300 neural marker can be considered as a stop command in the brain-computer interface (BCI) technologies. Therefore, the present study of electroencephalography (EEG) recognizes the mindset of human inhibition by observing the brain dynamics, like P300 wave in the frontal lobe, supplementary motor area, and in the right temporoparietal junction of the brain, all of them have been associated with response inhibition. Our work developed a hierarchical classification model to identify the neural activities of human inhibition. To accomplish this goal phase-locking value (PLV) method was used to select coupled brain regions related to inhibition because this method has demonstrated the best performance of the classification system. The PLVs were used with pattern recognition algorithms to classify a successful-stop versus a failed-stop in left-and right-hand inhibitions. The results demonstrate that quadratic discriminant analysis (QDA) yielded an average classification accuracy of 94.44%. These findings implicate the neural activities of human inhibition can be utilized as a stop command in BCI technologies, as well as to identify the symptoms of ADHD patients in clinical research. |
URI: | http://dx.doi.org/10.3390/s19173791 http://hdl.handle.net/11536/153119 |
DOI: | 10.3390/s19173791 |
期刊: | SENSORS |
Volume: | 19 |
Issue: | 17 |
起始頁: | 0 |
結束頁: | 0 |
顯示於類別: | 期刊論文 |