{"title":"一种测量心电和心电信号脉冲传递时间的新算法","authors":"Radjef Lilia, Omari Taha","doi":"10.5121/ijbes.2023.10101","DOIUrl":null,"url":null,"abstract":"Pulse transit Time (PTT) is a physiological parameter that is based on characteristics of the pulse waveform, a direct indicator of Cardiovascular Diseases (CVD). The (PTT) is defined as the time taken for the arterial pulse to travel from the heart to a peripheral site. It is commonly derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) signal calculations and is calculated as the interval between the peak of the electrocardiogram (ECG) R-wave and a time point on the photoplethysmogram (PPG). In this study, we propose a new and lowcomplexity algorithm for the Pulse transit time (PTT) measurement, using these two signals and detecting (PTT- foot) and (PTT- peak). We built a 37 subjects dataset containing a simultaneous recording of the (ECG) and (PPG). The calculation of (PTT) consists of detecting the peak and foot points of a (PPG) and the R-peak of the (ECG) signal. Intermediate operations such as normalization and thresholding to detect the local maxima and minima, are processed on noisy signals, this algorithm is improved by a windowing temporal analysis. The obtained results are promising for the first step. The average sensitivity (SEN) and accuracy (ACC) obtained were (97.5%, and 96.82%) respectively for R-peaks detection and respectively (97.77%, and 97.64%) for (PPG-peak) detection. The sensitivity (SEN) and accuracy (ACC) of (PPG- foot) detection were (98.33%, and 94.14%).","PeriodicalId":73426,"journal":{"name":"International journal of biomedical engineering and clinical science","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A NEW ALGORITHM FOR MEASURING PULSE TRANSIT TIME FROM ECG AND PPG SIGNALS\",\"authors\":\"Radjef Lilia, Omari Taha\",\"doi\":\"10.5121/ijbes.2023.10101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pulse transit Time (PTT) is a physiological parameter that is based on characteristics of the pulse waveform, a direct indicator of Cardiovascular Diseases (CVD). The (PTT) is defined as the time taken for the arterial pulse to travel from the heart to a peripheral site. It is commonly derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) signal calculations and is calculated as the interval between the peak of the electrocardiogram (ECG) R-wave and a time point on the photoplethysmogram (PPG). In this study, we propose a new and lowcomplexity algorithm for the Pulse transit time (PTT) measurement, using these two signals and detecting (PTT- foot) and (PTT- peak). We built a 37 subjects dataset containing a simultaneous recording of the (ECG) and (PPG). The calculation of (PTT) consists of detecting the peak and foot points of a (PPG) and the R-peak of the (ECG) signal. Intermediate operations such as normalization and thresholding to detect the local maxima and minima, are processed on noisy signals, this algorithm is improved by a windowing temporal analysis. The obtained results are promising for the first step. The average sensitivity (SEN) and accuracy (ACC) obtained were (97.5%, and 96.82%) respectively for R-peaks detection and respectively (97.77%, and 97.64%) for (PPG-peak) detection. The sensitivity (SEN) and accuracy (ACC) of (PPG- foot) detection were (98.33%, and 94.14%).\",\"PeriodicalId\":73426,\"journal\":{\"name\":\"International journal of biomedical engineering and clinical science\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of biomedical engineering and clinical science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/ijbes.2023.10101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of biomedical engineering and clinical science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/ijbes.2023.10101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A NEW ALGORITHM FOR MEASURING PULSE TRANSIT TIME FROM ECG AND PPG SIGNALS
Pulse transit Time (PTT) is a physiological parameter that is based on characteristics of the pulse waveform, a direct indicator of Cardiovascular Diseases (CVD). The (PTT) is defined as the time taken for the arterial pulse to travel from the heart to a peripheral site. It is commonly derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) signal calculations and is calculated as the interval between the peak of the electrocardiogram (ECG) R-wave and a time point on the photoplethysmogram (PPG). In this study, we propose a new and lowcomplexity algorithm for the Pulse transit time (PTT) measurement, using these two signals and detecting (PTT- foot) and (PTT- peak). We built a 37 subjects dataset containing a simultaneous recording of the (ECG) and (PPG). The calculation of (PTT) consists of detecting the peak and foot points of a (PPG) and the R-peak of the (ECG) signal. Intermediate operations such as normalization and thresholding to detect the local maxima and minima, are processed on noisy signals, this algorithm is improved by a windowing temporal analysis. The obtained results are promising for the first step. The average sensitivity (SEN) and accuracy (ACC) obtained were (97.5%, and 96.82%) respectively for R-peaks detection and respectively (97.77%, and 97.64%) for (PPG-peak) detection. The sensitivity (SEN) and accuracy (ACC) of (PPG- foot) detection were (98.33%, and 94.14%).