{"title":"心电信号的参数功率谱分析用于阻塞性睡眠呼吸暂停分类","authors":"X. Wang, J. M. Eklund, C. McGregor","doi":"10.1109/CBMS.2014.37","DOIUrl":null,"url":null,"abstract":"This work applies time-varying parametric power spectral density analysis to ECG and derived signals in order to discover the frequency components related to obstructive sleep apnoea. Heart rate variability signals were derived from the original ECG signals using R-R wave intervals. The power spectral densities were calculated using a parametric method across the heart rate variability frequency bands. Based on the power spectrum values, a number of beat-by-beat frequency power features were extracted from a PhysioNet dataset and studied together with the PhysioNet apnoea expert annotations.","PeriodicalId":398710,"journal":{"name":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Parametric Power Spectrum Analysis of ECG Signals for Obstructive Sleep Apnoea Classification\",\"authors\":\"X. Wang, J. M. Eklund, C. McGregor\",\"doi\":\"10.1109/CBMS.2014.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work applies time-varying parametric power spectral density analysis to ECG and derived signals in order to discover the frequency components related to obstructive sleep apnoea. Heart rate variability signals were derived from the original ECG signals using R-R wave intervals. The power spectral densities were calculated using a parametric method across the heart rate variability frequency bands. Based on the power spectrum values, a number of beat-by-beat frequency power features were extracted from a PhysioNet dataset and studied together with the PhysioNet apnoea expert annotations.\",\"PeriodicalId\":398710,\"journal\":{\"name\":\"2014 IEEE 27th International Symposium on Computer-Based Medical Systems\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 27th International Symposium on Computer-Based Medical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2014.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2014.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parametric Power Spectrum Analysis of ECG Signals for Obstructive Sleep Apnoea Classification
This work applies time-varying parametric power spectral density analysis to ECG and derived signals in order to discover the frequency components related to obstructive sleep apnoea. Heart rate variability signals were derived from the original ECG signals using R-R wave intervals. The power spectral densities were calculated using a parametric method across the heart rate variability frequency bands. Based on the power spectrum values, a number of beat-by-beat frequency power features were extracted from a PhysioNet dataset and studied together with the PhysioNet apnoea expert annotations.
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