J. Lázaro, R. Bailón, E. Gil, Yeonsik Noh, P. Laguna, K. Chon
{"title":"Pilot Study on Electrocardiogram Derived Respiratory Rate Using a Wearable Armband","authors":"J. Lázaro, R. Bailón, E. Gil, Yeonsik Noh, P. Laguna, K. Chon","doi":"10.22489/CinC.2018.054","DOIUrl":null,"url":null,"abstract":"A pilot study on deriving respiratory rate from electrocardiogram (ECG) signals recorded by a self-developed wearable armband is presented. The armband includes a pair of dry electrodes which record ECG and it is designed for long-term monitoring. Armband-ECG and plethysmography-respiration signals were simultaneously recorded from 5 subjects (3 male) while paced breathing at constant rates from 0.1 to 0.4 Hz (with an increment of 0.1 Hz). Respiratory rate was estimated from the armband-ECG by using a method based on the variations in QRS slopes and R-wave angle. The estimations were compared to those obtained from the respiration signal. Obtained median and interquartile ranges of the relative error were lower than 4% for every requested respiratory rate. This suggests that normal ranges of spontaneous respiratory rate could be estimated from the wearable armband, allowing us to consider it for long-term wearable cardio and/or respiratory monitoring.","PeriodicalId":215521,"journal":{"name":"2018 Computing in Cardiology Conference (CinC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Computing in Cardiology Conference (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22489/CinC.2018.054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
A pilot study on deriving respiratory rate from electrocardiogram (ECG) signals recorded by a self-developed wearable armband is presented. The armband includes a pair of dry electrodes which record ECG and it is designed for long-term monitoring. Armband-ECG and plethysmography-respiration signals were simultaneously recorded from 5 subjects (3 male) while paced breathing at constant rates from 0.1 to 0.4 Hz (with an increment of 0.1 Hz). Respiratory rate was estimated from the armband-ECG by using a method based on the variations in QRS slopes and R-wave angle. The estimations were compared to those obtained from the respiration signal. Obtained median and interquartile ranges of the relative error were lower than 4% for every requested respiratory rate. This suggests that normal ranges of spontaneous respiratory rate could be estimated from the wearable armband, allowing us to consider it for long-term wearable cardio and/or respiratory monitoring.