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The [Formula: see text]-test implementation in both databases shows that there are significant variations in HRV features, where meanRR and HR have suggestive significant ([Formula: see text]) changes, while maxRR, minRR, maxminRR, and SDNN have strongly significant ([Formula: see text]) changes. To validate the statistical analysis of HRV, feature classification has been done using SVM and kNN classifiers. A significant improvement of 2% and 14.02% has been observed in the overall accuracy of SVM and kNN classifiers after feature selection, respectively. These HRV features can be used for the early prediction of various Cardio-Vascular Diseases (CVD).<\/jats:p>","DOI":"10.1142\/s0219467820500369","type":"journal-article","created":{"date-parts":[[2020,10,5]],"date-time":"2020-10-05T02:41:52Z","timestamp":1601865712000},"page":"2050036","source":"Crossref","is-referenced-by-count":0,"title":["Statistical Analysis of HRV Parameters for the Detection of Arrhythmia"],"prefix":"10.1142","volume":"20","author":[{"given":"Kirthi","family":"Tripathi","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan 173234, Himachal Pradesh, India"}]},{"given":"Harsh","family":"Sohal","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan 173234, Himachal Pradesh, India"}]},{"given":"Shruti","family":"Jain","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan 173234, Himachal Pradesh, India"}]}],"member":"219","published-online":{"date-parts":[[2020,10,2]]},"reference":[{"key":"S0219467820500369BIB001","first-page":"300","volume-title":"Signal Processing, Computing and Control (ISPCC), 2017 4th Int. 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