Study on the features extraction of ERP evoked by the mental arithmetic tasks based on the sample entropy
10.3760/cma.j.issn.1673-4181.2015.04.003
- VernacularTitle:基于样本熵的心算任务诱发事件相关电位特征提取的研究
- Author:
Wei YUE
;
Liqing SONG
;
Suogang WANG
- Publication Type:Journal Article
- Keywords:
Mental arithmetic;
Event related potential;
P300;
Feature;
Sample entropy
- From:
International Journal of Biomedical Engineering
2015;38(4):201-205
- CountryChina
- Language:Chinese
-
Abstract:
Objective To study the feature extraction methods for the event related potential (ERP) evoked by mental arithmetical tasks through the sample entropy, in order to enhance the features of electroencephalograph (EEG) signals for brain computer interface (BCI).Methods Three types of mental arithmetic tasks including a simple counting, a random number and a stroke of Chinese character counting were proposed and 16 channel EEG signals were recorded from eight healthy subjects.The sample entropy method was then applied in characteristic signal complexity analysis.The characteristic and difference of signal complexity of ERP evoked by three types of mental arithmetical tasks were explored.Results The entropy value for EEG signal evoked by non-target stimulus was higher than that by the target stimulus with the significant difference (P＜0.01).The entropy of the mental arithmetic based on the Chinese characters counting task was significandy higher than that of the other two tasks (P＜0.05).EEG signals evoked by target/non-target were fundamentally signals under the state of attention or non-attention.Conclusions For the Chinese characters counting task, more complex information have been processed by the brain and the non-linear connection between nerve cells are much more complicated and a higher entropy value is achieved.In summary, the mental arithmetic task can effectively activate the relevant brain regions and the sample entropy can distinguish signals evoked by target or non-target stimuli.
