M. Risk, D. Ślȩzak, P. Turjanski, A. Panelli, R. Taborda, G. Marshall
{"title":"Time series calculation of heart rate using multi rate FIR filters","authors":"M. Risk, D. Ślȩzak, P. Turjanski, A. Panelli, R. Taborda, G. Marshall","doi":"10.1109/CIC.2007.4745542","DOIUrl":null,"url":null,"abstract":"The spectral analysis of heart rate variability, based on the Fourier transform, needs even sampled data. The objectives of this study were to develop an interpolation method based on multi rate FIR filters, and then to implement this method for parallel processing machines. A total of three data sets were used: a) simulated heart rate with an IPFM model, b) autonomic blockage database (both pharmacological and postural), and c) long term Holter studies (recordings of 24 hours). Spectral analysis, for the three data sets, was processed for both interpolation using FIR filters and cubic splines, the results for Bland and Altman analysis for low frequency band, showed a difference of -47plusmn131 ms2; then for the high frequency band, the difference was 3plusmn48 ms2. The presented method of time series calculation, using FIR filters, probed to be equivalent for both simulated and real data, and is suitable for parallel programming implementation.","PeriodicalId":406683,"journal":{"name":"2007 Computers in Cardiology","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Computers in Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2007.4745542","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The spectral analysis of heart rate variability, based on the Fourier transform, needs even sampled data. The objectives of this study were to develop an interpolation method based on multi rate FIR filters, and then to implement this method for parallel processing machines. A total of three data sets were used: a) simulated heart rate with an IPFM model, b) autonomic blockage database (both pharmacological and postural), and c) long term Holter studies (recordings of 24 hours). Spectral analysis, for the three data sets, was processed for both interpolation using FIR filters and cubic splines, the results for Bland and Altman analysis for low frequency band, showed a difference of -47plusmn131 ms2; then for the high frequency band, the difference was 3plusmn48 ms2. The presented method of time series calculation, using FIR filters, probed to be equivalent for both simulated and real data, and is suitable for parallel programming implementation.