{"title":"用于安全通道研究的信号处理和特征提取框架的开发","authors":"E. Kieser, H. Odendaal, D. van den Heever","doi":"10.1109/SAIBMEC.2018.8363193","DOIUrl":null,"url":null,"abstract":"This work describes a framework that was developed to export and analyze maternal heartrate and uterine activity from a Monica AN24 ECG recording device. 9478 Traces from 5356 patients were processed, the mean recording length was 47 minutes. The framework implemented additional signal cleaning algorithms and extracted accelerations, decelerations, baseline traces, commonly used heartrate variability parameters, phase rectified signal average wavelets and identified beats that were missed by the Monica detection algorithm.","PeriodicalId":165912,"journal":{"name":"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Development of a signal processing and feature extraction framework for the safe passage study\",\"authors\":\"E. Kieser, H. Odendaal, D. van den Heever\",\"doi\":\"10.1109/SAIBMEC.2018.8363193\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work describes a framework that was developed to export and analyze maternal heartrate and uterine activity from a Monica AN24 ECG recording device. 9478 Traces from 5356 patients were processed, the mean recording length was 47 minutes. The framework implemented additional signal cleaning algorithms and extracted accelerations, decelerations, baseline traces, commonly used heartrate variability parameters, phase rectified signal average wavelets and identified beats that were missed by the Monica detection algorithm.\",\"PeriodicalId\":165912,\"journal\":{\"name\":\"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAIBMEC.2018.8363193\",\"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 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAIBMEC.2018.8363193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of a signal processing and feature extraction framework for the safe passage study
This work describes a framework that was developed to export and analyze maternal heartrate and uterine activity from a Monica AN24 ECG recording device. 9478 Traces from 5356 patients were processed, the mean recording length was 47 minutes. The framework implemented additional signal cleaning algorithms and extracted accelerations, decelerations, baseline traces, commonly used heartrate variability parameters, phase rectified signal average wavelets and identified beats that were missed by the Monica detection algorithm.