P. Oktivasari, S. Imam, Riandini, A. H. Salman, F. Haryanto, Suprijadi
{"title":"心律失常与正常心电图信号的识别","authors":"P. Oktivasari, S. Imam, Riandini, A. H. Salman, F. Haryanto, Suprijadi","doi":"10.1109/iCAST51016.2020.9557678","DOIUrl":null,"url":null,"abstract":"The heart is a vital organ for the human organism. The emergence of heart disease can be fatal for sufferers. For some conclusions, arrhythmias (heart rhythm disorders) are the primary cardiovascular disease. The cardiac activity can be read through the heart's record tool. The working relationship of this tool is by installing electrodes on the body, and then the heart will give a signal due to heart electricity. After that, the device emits a heart signal. The resulting signal is conditioned and processed into an ECG signal consisting of PQRST parameters and transferred to a computer stored in a database. Data processing considers the R-R wave intervals and Heart Rate (HR), then classified using Artificial Neural Networks to produce conclusions about the results of the diagnosis in the form of examination reports. The technology platforms used are ADS 8232 and NI My-DAQ. The goal of this study is a heart record system that is designed to be able to read PQRST waves that can define the heart condition of a patient and can distinguish arrhythmia or usual irregularities. Regarding the outcomes of the training, the network recognizes 100% of the data being trained.","PeriodicalId":334854,"journal":{"name":"2020 International Conference on Applied Science and Technology (iCAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Arrhythmia and Normal Identification of Electrocardiogram (ECG) Signals\",\"authors\":\"P. Oktivasari, S. Imam, Riandini, A. H. Salman, F. Haryanto, Suprijadi\",\"doi\":\"10.1109/iCAST51016.2020.9557678\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The heart is a vital organ for the human organism. The emergence of heart disease can be fatal for sufferers. For some conclusions, arrhythmias (heart rhythm disorders) are the primary cardiovascular disease. The cardiac activity can be read through the heart's record tool. The working relationship of this tool is by installing electrodes on the body, and then the heart will give a signal due to heart electricity. After that, the device emits a heart signal. The resulting signal is conditioned and processed into an ECG signal consisting of PQRST parameters and transferred to a computer stored in a database. Data processing considers the R-R wave intervals and Heart Rate (HR), then classified using Artificial Neural Networks to produce conclusions about the results of the diagnosis in the form of examination reports. The technology platforms used are ADS 8232 and NI My-DAQ. The goal of this study is a heart record system that is designed to be able to read PQRST waves that can define the heart condition of a patient and can distinguish arrhythmia or usual irregularities. Regarding the outcomes of the training, the network recognizes 100% of the data being trained.\",\"PeriodicalId\":334854,\"journal\":{\"name\":\"2020 International Conference on Applied Science and Technology (iCAST)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Applied Science and Technology (iCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iCAST51016.2020.9557678\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Applied Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iCAST51016.2020.9557678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Arrhythmia and Normal Identification of Electrocardiogram (ECG) Signals
The heart is a vital organ for the human organism. The emergence of heart disease can be fatal for sufferers. For some conclusions, arrhythmias (heart rhythm disorders) are the primary cardiovascular disease. The cardiac activity can be read through the heart's record tool. The working relationship of this tool is by installing electrodes on the body, and then the heart will give a signal due to heart electricity. After that, the device emits a heart signal. The resulting signal is conditioned and processed into an ECG signal consisting of PQRST parameters and transferred to a computer stored in a database. Data processing considers the R-R wave intervals and Heart Rate (HR), then classified using Artificial Neural Networks to produce conclusions about the results of the diagnosis in the form of examination reports. The technology platforms used are ADS 8232 and NI My-DAQ. The goal of this study is a heart record system that is designed to be able to read PQRST waves that can define the heart condition of a patient and can distinguish arrhythmia or usual irregularities. Regarding the outcomes of the training, the network recognizes 100% of the data being trained.