{"title":"HRVTool -一个开源的Matlab工具箱,用于分析心率变异性","authors":"M. Vollmer","doi":"10.22489/cinc.2019.032","DOIUrl":null,"url":null,"abstract":"Motivation: Many software tools for ECG processing are commercial. New innovative and alternative features for heart rate variability analysis (HRV) and improved methods in ECG preprocessing cannot be incorporated. Moreover, software manuals are lacking of clarity and often conceal the exact calculation methods that makes clinical interpretation difficult, and reproducibility is reduced. Software description: HRVTool provides an opensource and intuitive user-friendly environment for the HRV analysis in Matlab. The software is available at http://marcusvollmer.github.io/HRV and supports the processing of ECG, pulsatile waveforms and RR intervals from various sources (mat and text files containing raw data, Polar, PhysioNet, Hexoskin, BIOPAC, European Data Format, ISHNE Holter Standard Format, and Machine-Independent Beat files). An integrated heart beat detector locates R peaks or pulse waves. Visual inspection, and manual adjustments of beat locations are possible and the corresponding annotation file can be saved in a standard Matlab format or as a delimited text file. HRV statistics are computed in a sliding window to evaluate the alteration over time. HRV metrics can be exported. An animation of intervals supports pattern identification. Moreover the Matlab class (HRV.m) includes functions for windowed HRV computation that can be used for batch processing.","PeriodicalId":6716,"journal":{"name":"2019 Computing in Cardiology Conference (CinC)","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"HRVTool - an Open-Source Matlab Toolbox for Analyzing Heart Rate Variability\",\"authors\":\"M. Vollmer\",\"doi\":\"10.22489/cinc.2019.032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Motivation: Many software tools for ECG processing are commercial. New innovative and alternative features for heart rate variability analysis (HRV) and improved methods in ECG preprocessing cannot be incorporated. Moreover, software manuals are lacking of clarity and often conceal the exact calculation methods that makes clinical interpretation difficult, and reproducibility is reduced. Software description: HRVTool provides an opensource and intuitive user-friendly environment for the HRV analysis in Matlab. The software is available at http://marcusvollmer.github.io/HRV and supports the processing of ECG, pulsatile waveforms and RR intervals from various sources (mat and text files containing raw data, Polar, PhysioNet, Hexoskin, BIOPAC, European Data Format, ISHNE Holter Standard Format, and Machine-Independent Beat files). An integrated heart beat detector locates R peaks or pulse waves. Visual inspection, and manual adjustments of beat locations are possible and the corresponding annotation file can be saved in a standard Matlab format or as a delimited text file. HRV statistics are computed in a sliding window to evaluate the alteration over time. HRV metrics can be exported. An animation of intervals supports pattern identification. Moreover the Matlab class (HRV.m) includes functions for windowed HRV computation that can be used for batch processing.\",\"PeriodicalId\":6716,\"journal\":{\"name\":\"2019 Computing in Cardiology Conference (CinC)\",\"volume\":\"5 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Computing in Cardiology Conference (CinC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22489/cinc.2019.032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Computing in Cardiology Conference (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22489/cinc.2019.032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
HRVTool - an Open-Source Matlab Toolbox for Analyzing Heart Rate Variability
Motivation: Many software tools for ECG processing are commercial. New innovative and alternative features for heart rate variability analysis (HRV) and improved methods in ECG preprocessing cannot be incorporated. Moreover, software manuals are lacking of clarity and often conceal the exact calculation methods that makes clinical interpretation difficult, and reproducibility is reduced. Software description: HRVTool provides an opensource and intuitive user-friendly environment for the HRV analysis in Matlab. The software is available at http://marcusvollmer.github.io/HRV and supports the processing of ECG, pulsatile waveforms and RR intervals from various sources (mat and text files containing raw data, Polar, PhysioNet, Hexoskin, BIOPAC, European Data Format, ISHNE Holter Standard Format, and Machine-Independent Beat files). An integrated heart beat detector locates R peaks or pulse waves. Visual inspection, and manual adjustments of beat locations are possible and the corresponding annotation file can be saved in a standard Matlab format or as a delimited text file. HRV statistics are computed in a sliding window to evaluate the alteration over time. HRV metrics can be exported. An animation of intervals supports pattern identification. Moreover the Matlab class (HRV.m) includes functions for windowed HRV computation that can be used for batch processing.