{"title":"改进的叠加模板减法提高无创胎儿心电图QRS检测的时间准确性。","authors":"Phuc K T Le, Van-Toi Vo, Le-Giang Tran","doi":"10.1088/1361-6579/adea2b","DOIUrl":null,"url":null,"abstract":"<p><p><i>Objective</i>. To develop and evaluate method pipelines combining superimposition template subtraction (STS) and independent component analysis (ICA) for the most temporally accurate fetal electrocardiogram (fECG) signals extraction from abdominal recordings.<i>Approach</i>. Four method pipelines were developed by combining versions of STS and ICA algorithms to leverage their complementary strengths while mitigating their individual weaknesses. These pipelines were designed to adapt to various signal characteristics and were tested using recordings from the 2013 PhysioNet challenge and abdominal and direct fetal ECG database.<i>Main results</i>. Over the whole dataset, the best performing method pipeline achieved an average F1 score of 95.2% for fetal heart rate detection using a small error window of only 10 ms, demonstrating effective maternal signal suppression and accurate fetal signal extraction.<i>Significance</i>. Noninvasive monitoring of fetal health through electrocardiography could enable early detection of distress, but is challenged by the presence of overlapping maternal and fetal signals. This work demonstrates that strategically combining STS and ICA techniques can overcome these challenges and provide highly accurate fECG extraction.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Increasing temporal accuracy of noninvasive fetal electrocardiogram QRS detection with modified superimposition template subtraction.\",\"authors\":\"Phuc K T Le, Van-Toi Vo, Le-Giang Tran\",\"doi\":\"10.1088/1361-6579/adea2b\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>Objective</i>. To develop and evaluate method pipelines combining superimposition template subtraction (STS) and independent component analysis (ICA) for the most temporally accurate fetal electrocardiogram (fECG) signals extraction from abdominal recordings.<i>Approach</i>. Four method pipelines were developed by combining versions of STS and ICA algorithms to leverage their complementary strengths while mitigating their individual weaknesses. These pipelines were designed to adapt to various signal characteristics and were tested using recordings from the 2013 PhysioNet challenge and abdominal and direct fetal ECG database.<i>Main results</i>. Over the whole dataset, the best performing method pipeline achieved an average F1 score of 95.2% for fetal heart rate detection using a small error window of only 10 ms, demonstrating effective maternal signal suppression and accurate fetal signal extraction.<i>Significance</i>. Noninvasive monitoring of fetal health through electrocardiography could enable early detection of distress, but is challenged by the presence of overlapping maternal and fetal signals. This work demonstrates that strategically combining STS and ICA techniques can overcome these challenges and provide highly accurate fECG extraction.</p>\",\"PeriodicalId\":20047,\"journal\":{\"name\":\"Physiological measurement\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physiological measurement\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-6579/adea2b\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physiological measurement","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1088/1361-6579/adea2b","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOPHYSICS","Score":null,"Total":0}
Increasing temporal accuracy of noninvasive fetal electrocardiogram QRS detection with modified superimposition template subtraction.
Objective. To develop and evaluate method pipelines combining superimposition template subtraction (STS) and independent component analysis (ICA) for the most temporally accurate fetal electrocardiogram (fECG) signals extraction from abdominal recordings.Approach. Four method pipelines were developed by combining versions of STS and ICA algorithms to leverage their complementary strengths while mitigating their individual weaknesses. These pipelines were designed to adapt to various signal characteristics and were tested using recordings from the 2013 PhysioNet challenge and abdominal and direct fetal ECG database.Main results. Over the whole dataset, the best performing method pipeline achieved an average F1 score of 95.2% for fetal heart rate detection using a small error window of only 10 ms, demonstrating effective maternal signal suppression and accurate fetal signal extraction.Significance. Noninvasive monitoring of fetal health through electrocardiography could enable early detection of distress, but is challenged by the presence of overlapping maternal and fetal signals. This work demonstrates that strategically combining STS and ICA techniques can overcome these challenges and provide highly accurate fECG extraction.
期刊介绍:
Physiological Measurement publishes papers about the quantitative assessment and visualization of physiological function in clinical research and practice, with an emphasis on the development of new methods of measurement and their validation.
Papers are published on topics including:
applied physiology in illness and health
electrical bioimpedance, optical and acoustic measurement techniques
advanced methods of time series and other data analysis
biomedical and clinical engineering
in-patient and ambulatory monitoring
point-of-care technologies
novel clinical measurements of cardiovascular, neurological, and musculoskeletal systems.
measurements in molecular, cellular and organ physiology and electrophysiology
physiological modeling and simulation
novel biomedical sensors, instruments, devices and systems
measurement standards and guidelines.