{"title":"利用Savitzky-Golay和Butterworth滤波器提取胎儿心电图","authors":"Henry Sheng Hoong Siew, Y. Alshebly, Marwan Nafea","doi":"10.1109/i2cacis54679.2022.9815469","DOIUrl":null,"url":null,"abstract":"The health and well-being of a fetus can be conducted by constantly monitoring its cardiac activity while in pregnancy. The cardiac movement of the mother and fetus can be monitored by placing several electrodes at the thoracic and abdominal parts of the mother to examine the heart of both the mother and fetus. However, the cardiac activity of the mother may affect the fetal one. Often, the abdominal data is corrupted by the mother’s heart data, which covers the fetal heartbeat signal. This paper presents a method to extract maternal electrocardiogram (MECG) and fetal ECG (FECG) signals from thoracic and abdominal signals from the Daisy database. The proposed method utilizes a combination of the Butterworth and Savitsky-Golay filters to perform the filtering and windowing processes required to extract the MECG. Savitzky-Golay filtered windows are used to perform the FECG signal extraction. The proposed approach was also used to determine the heart rates of the mother and fetus, which were around 85.5 and 132.5 bpm, respectively. The proposed method shows promising performance in terms of noise filtering and extracting the PQRST complex when compared with previously reported methods. The proposed method can be potentially used to filter and extract different biosignals when adjusted to suit the specific applications.","PeriodicalId":332297,"journal":{"name":"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Fetal ECG Extraction Using Savitzky-Golay and Butterworth Filters\",\"authors\":\"Henry Sheng Hoong Siew, Y. Alshebly, Marwan Nafea\",\"doi\":\"10.1109/i2cacis54679.2022.9815469\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The health and well-being of a fetus can be conducted by constantly monitoring its cardiac activity while in pregnancy. The cardiac movement of the mother and fetus can be monitored by placing several electrodes at the thoracic and abdominal parts of the mother to examine the heart of both the mother and fetus. However, the cardiac activity of the mother may affect the fetal one. Often, the abdominal data is corrupted by the mother’s heart data, which covers the fetal heartbeat signal. This paper presents a method to extract maternal electrocardiogram (MECG) and fetal ECG (FECG) signals from thoracic and abdominal signals from the Daisy database. The proposed method utilizes a combination of the Butterworth and Savitsky-Golay filters to perform the filtering and windowing processes required to extract the MECG. Savitzky-Golay filtered windows are used to perform the FECG signal extraction. The proposed approach was also used to determine the heart rates of the mother and fetus, which were around 85.5 and 132.5 bpm, respectively. The proposed method shows promising performance in terms of noise filtering and extracting the PQRST complex when compared with previously reported methods. The proposed method can be potentially used to filter and extract different biosignals when adjusted to suit the specific applications.\",\"PeriodicalId\":332297,\"journal\":{\"name\":\"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/i2cacis54679.2022.9815469\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i2cacis54679.2022.9815469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fetal ECG Extraction Using Savitzky-Golay and Butterworth Filters
The health and well-being of a fetus can be conducted by constantly monitoring its cardiac activity while in pregnancy. The cardiac movement of the mother and fetus can be monitored by placing several electrodes at the thoracic and abdominal parts of the mother to examine the heart of both the mother and fetus. However, the cardiac activity of the mother may affect the fetal one. Often, the abdominal data is corrupted by the mother’s heart data, which covers the fetal heartbeat signal. This paper presents a method to extract maternal electrocardiogram (MECG) and fetal ECG (FECG) signals from thoracic and abdominal signals from the Daisy database. The proposed method utilizes a combination of the Butterworth and Savitsky-Golay filters to perform the filtering and windowing processes required to extract the MECG. Savitzky-Golay filtered windows are used to perform the FECG signal extraction. The proposed approach was also used to determine the heart rates of the mother and fetus, which were around 85.5 and 132.5 bpm, respectively. The proposed method shows promising performance in terms of noise filtering and extracting the PQRST complex when compared with previously reported methods. The proposed method can be potentially used to filter and extract different biosignals when adjusted to suit the specific applications.