{"title":"基于人工神经网络的HRV分类器对心脏健康预后的影响","authors":"Ramesh Kumar Sunkaria, Vinod Kumar, Suresh Chandra Saxena, Achala M Singhal","doi":"10.1504/IJEH.2014.064332","DOIUrl":null,"url":null,"abstract":"<p><p>A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists. </p>","PeriodicalId":39775,"journal":{"name":"International Journal of Electronic Healthcare","volume":"7 4","pages":"315-30"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJEH.2014.064332","citationCount":"5","resultStr":"{\"title\":\"An ANN-based HRV classifier for cardiac health prognosis.\",\"authors\":\"Ramesh Kumar Sunkaria, Vinod Kumar, Suresh Chandra Saxena, Achala M Singhal\",\"doi\":\"10.1504/IJEH.2014.064332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists. </p>\",\"PeriodicalId\":39775,\"journal\":{\"name\":\"International Journal of Electronic Healthcare\",\"volume\":\"7 4\",\"pages\":\"315-30\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/IJEH.2014.064332\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Electronic Healthcare\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJEH.2014.064332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electronic Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJEH.2014.064332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
An ANN-based HRV classifier for cardiac health prognosis.
A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists.
期刊介绍:
The IJEH is an authoritative, fully-refereed international journal which presents current practice and research in the area of e-healthcare. It is dedicated to design, development, management, implementation, technology, and application issues in e-healthcare.