视觉诱发电位的频谱分析

2015 Signal Processing Symposium (SPSympo) Pub Date : 2015-06-10 DOI:10.1109/SPS.2015.7168275

A. Dobrowolski, Marta Okon

{"title":"视觉诱发电位的频谱分析","authors":"A. Dobrowolski, Marta Okon","doi":"10.1109/SPS.2015.7168275","DOIUrl":null,"url":null,"abstract":"The paper presents a conception of classification method of Visual Evoked Potentials (VEP) to physiological or pathological case based on power spectral parameters. The authors have verified their concept through a series of numerical experiments performed using a dedicated application. As a result of experiments, the final method provided only 4 cases of wrong classification among training data (6%) and 13 among the testing data (43%).","PeriodicalId":193902,"journal":{"name":"2015 Signal Processing Symposium (SPSympo)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Spectral analysis of visual evoked potentials\",\"authors\":\"A. Dobrowolski, Marta Okon\",\"doi\":\"10.1109/SPS.2015.7168275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a conception of classification method of Visual Evoked Potentials (VEP) to physiological or pathological case based on power spectral parameters. The authors have verified their concept through a series of numerical experiments performed using a dedicated application. As a result of experiments, the final method provided only 4 cases of wrong classification among training data (6%) and 13 among the testing data (43%).\",\"PeriodicalId\":193902,\"journal\":{\"name\":\"2015 Signal Processing Symposium (SPSympo)\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Signal Processing Symposium (SPSympo)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPS.2015.7168275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing Symposium (SPSympo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPS.2015.7168275","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

提出了一种基于功率谱参数的视诱发电位(VEP)生理或病理分类方法。作者通过使用专用应用程序进行的一系列数值实验验证了他们的概念。实验结果表明，最终方法在训练数据中只有4例(6%)分类错误，在测试数据中只有13例(43%)分类错误。

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

Spectral analysis of visual evoked potentials

The paper presents a conception of classification method of Visual Evoked Potentials (VEP) to physiological or pathological case based on power spectral parameters. The authors have verified their concept through a series of numerical experiments performed using a dedicated application. As a result of experiments, the final method provided only 4 cases of wrong classification among training data (6%) and 13 among the testing data (43%).

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

2015 Signal Processing Symposium (SPSympo)

自引率

0.00%

发文量