{"title":"从腹部心电图无阈值检测母体心率","authors":"M. Algunaidi, M. A. Mohd. Ali","doi":"10.1109/ICSIPA.2009.5478697","DOIUrl":null,"url":null,"abstract":"This work is involved the threshold-free detection of QRS complexes in an abdominal electrocardiogram (AECG) waveform. The precision in the identification of QRS complexes is of great importance for on-line maternal heart rate calculation and, will lead to on line fetal heart detection,. During the last century much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks, and others, each of which has different effectiveness and weaknesses. Although their performance is generally good, but, the main weakness is that, they are threshold dependent. In the proposed algorithm a RR moving interval is calculated, based on normal maximum and minimum heart rate (HR). This has the advantage of ensuring that every R-peak is contained between the edges of the moving interval. Thus the effectiveness of this algorithm is that, it is threshold independent, and after every peak detection the RR moving interval is updated to calculate the next peak contained between its edges. The complete algorithm is implemented using MATLAB 7.4. The method is validated using 20 recorded data. The average sensitivity and average positive predictivity of the detection method are 99.05% and 99.8% respectively.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Threshold-free detection of maternal heart rate from abdominal electrocardiogram\",\"authors\":\"M. Algunaidi, M. A. Mohd. Ali\",\"doi\":\"10.1109/ICSIPA.2009.5478697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work is involved the threshold-free detection of QRS complexes in an abdominal electrocardiogram (AECG) waveform. The precision in the identification of QRS complexes is of great importance for on-line maternal heart rate calculation and, will lead to on line fetal heart detection,. During the last century much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks, and others, each of which has different effectiveness and weaknesses. Although their performance is generally good, but, the main weakness is that, they are threshold dependent. In the proposed algorithm a RR moving interval is calculated, based on normal maximum and minimum heart rate (HR). This has the advantage of ensuring that every R-peak is contained between the edges of the moving interval. Thus the effectiveness of this algorithm is that, it is threshold independent, and after every peak detection the RR moving interval is updated to calculate the next peak contained between its edges. The complete algorithm is implemented using MATLAB 7.4. The method is validated using 20 recorded data. The average sensitivity and average positive predictivity of the detection method are 99.05% and 99.8% respectively.\",\"PeriodicalId\":400165,\"journal\":{\"name\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIPA.2009.5478697\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Signal and Image Processing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2009.5478697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Threshold-free detection of maternal heart rate from abdominal electrocardiogram
This work is involved the threshold-free detection of QRS complexes in an abdominal electrocardiogram (AECG) waveform. The precision in the identification of QRS complexes is of great importance for on-line maternal heart rate calculation and, will lead to on line fetal heart detection,. During the last century much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks, and others, each of which has different effectiveness and weaknesses. Although their performance is generally good, but, the main weakness is that, they are threshold dependent. In the proposed algorithm a RR moving interval is calculated, based on normal maximum and minimum heart rate (HR). This has the advantage of ensuring that every R-peak is contained between the edges of the moving interval. Thus the effectiveness of this algorithm is that, it is threshold independent, and after every peak detection the RR moving interval is updated to calculate the next peak contained between its edges. The complete algorithm is implemented using MATLAB 7.4. The method is validated using 20 recorded data. The average sensitivity and average positive predictivity of the detection method are 99.05% and 99.8% respectively.