Hina Magsi, Ali Hassan Sodhro, F. Chachar, Saeed Ahmed Khan
{"title":"利用滤波器对信号进行降噪分析","authors":"Hina Magsi, Ali Hassan Sodhro, F. Chachar, Saeed Ahmed Khan","doi":"10.1109/ICOMET.2018.8346412","DOIUrl":null,"url":null,"abstract":"This paper designs and compares three different filtering methods to reduce the effects of noise in medical health applications such as an electrocardiogram (ECG). The low pass filter excludes the noise at a low-level, moving average filter takes average values of the signal, and Finite Impulse Response (FIR) removes the high frequency components from the ECG and gives the low frequency component which is the desired information signal. Simulation results reveal that FIR filter performs better by reducing the attenuation in the ECG signal than low pass filter and moving average filters and is appropriate for the medical health applications.","PeriodicalId":381362,"journal":{"name":"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Analysis of signal noise reduction by using filters\",\"authors\":\"Hina Magsi, Ali Hassan Sodhro, F. Chachar, Saeed Ahmed Khan\",\"doi\":\"10.1109/ICOMET.2018.8346412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper designs and compares three different filtering methods to reduce the effects of noise in medical health applications such as an electrocardiogram (ECG). The low pass filter excludes the noise at a low-level, moving average filter takes average values of the signal, and Finite Impulse Response (FIR) removes the high frequency components from the ECG and gives the low frequency component which is the desired information signal. Simulation results reveal that FIR filter performs better by reducing the attenuation in the ECG signal than low pass filter and moving average filters and is appropriate for the medical health applications.\",\"PeriodicalId\":381362,\"journal\":{\"name\":\"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOMET.2018.8346412\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOMET.2018.8346412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of signal noise reduction by using filters
This paper designs and compares three different filtering methods to reduce the effects of noise in medical health applications such as an electrocardiogram (ECG). The low pass filter excludes the noise at a low-level, moving average filter takes average values of the signal, and Finite Impulse Response (FIR) removes the high frequency components from the ECG and gives the low frequency component which is the desired information signal. Simulation results reveal that FIR filter performs better by reducing the attenuation in the ECG signal than low pass filter and moving average filters and is appropriate for the medical health applications.