脑任务识别的光谱波段功率和不对称比

Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467) Pub Date : 1900-01-01 DOI:10.1109/ISSPA.2001.950258

R. Palaniappan, R. Paramesran

{"title":"脑任务识别的光谱波段功率和不对称比","authors":"R. Palaniappan, R. Paramesran","doi":"10.1109/ISSPA.2001.950258","DOIUrl":null,"url":null,"abstract":"We use the power and asymmetry ratio of spectral bands to recognise mental tasks from electroencephalogram signals using a fuzzy ARTMAP neural network. Classical spectral analysis using the Wiener-Khintchine theorem and modem parametric spectral analysis using the autoregressive method are used to obtain these features. The highest classification results of 90% for a subject recognising two mental tasks validate the method.","PeriodicalId":236050,"journal":{"name":"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Power and asymmetry ratio of spectral bands for mental task recognition\",\"authors\":\"R. Palaniappan, R. Paramesran\",\"doi\":\"10.1109/ISSPA.2001.950258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We use the power and asymmetry ratio of spectral bands to recognise mental tasks from electroencephalogram signals using a fuzzy ARTMAP neural network. Classical spectral analysis using the Wiener-Khintchine theorem and modem parametric spectral analysis using the autoregressive method are used to obtain these features. The highest classification results of 90% for a subject recognising two mental tasks validate the method.\",\"PeriodicalId\":236050,\"journal\":{\"name\":\"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPA.2001.950258\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.2001.950258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

我们使用模糊ARTMAP神经网络，利用谱带的功率和不对称比从脑电图信号中识别心理任务。利用维纳-钦定理的经典谱分析和自回归方法的现代参数谱分析得到了这些特征。一个受试者识别两种心理任务的最高分类结果为90%，证实了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Power and asymmetry ratio of spectral bands for mental task recognition

We use the power and asymmetry ratio of spectral bands to recognise mental tasks from electroencephalogram signals using a fuzzy ARTMAP neural network. Classical spectral analysis using the Wiener-Khintchine theorem and modem parametric spectral analysis using the autoregressive method are used to obtain these features. The highest classification results of 90% for a subject recognising two mental tasks validate the method.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)

自引率

0.00%

发文量