{"title":"基于小波变换分析的fNIRS信号基线漂移检测指标","authors":"Gihyoun Lee, Seung Hyun Lee, S. Jin, J. An","doi":"10.1109/IWW-BCI.2017.7858163","DOIUrl":null,"url":null,"abstract":"The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS signals, when they have drift globally. Wavelet based de-trending technique is very popular to correct the baseline drift (BD) in fNIRS. However, this method globally distorted the total multichannel signals even if just one channel's signal was locally drifted. This paper suggests BD detection index to indicate BD as an objective index. The experiments show the performance of the proposed detection index as graphic results with current de-trending algorithm.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Baseline drift detection index using wavelet transform analysis for fNIRS signal\",\"authors\":\"Gihyoun Lee, Seung Hyun Lee, S. Jin, J. An\",\"doi\":\"10.1109/IWW-BCI.2017.7858163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS signals, when they have drift globally. Wavelet based de-trending technique is very popular to correct the baseline drift (BD) in fNIRS. However, this method globally distorted the total multichannel signals even if just one channel's signal was locally drifted. This paper suggests BD detection index to indicate BD as an objective index. The experiments show the performance of the proposed detection index as graphic results with current de-trending algorithm.\",\"PeriodicalId\":443427,\"journal\":{\"name\":\"2017 5th International Winter Conference on Brain-Computer Interface (BCI)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th International Winter Conference on Brain-Computer Interface (BCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWW-BCI.2017.7858163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWW-BCI.2017.7858163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Baseline drift detection index using wavelet transform analysis for fNIRS signal
The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS signals, when they have drift globally. Wavelet based de-trending technique is very popular to correct the baseline drift (BD) in fNIRS. However, this method globally distorted the total multichannel signals even if just one channel's signal was locally drifted. This paper suggests BD detection index to indicate BD as an objective index. The experiments show the performance of the proposed detection index as graphic results with current de-trending algorithm.
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