Nicola Bevilacqua, G. Andria, F. Attivissimo, A. Nisio, M. Spadavecchia
{"title":"Development of an adaptive bandwidth filter for the estimation of respiratory parameters using a piezoelectric belt","authors":"Nicola Bevilacqua, G. Andria, F. Attivissimo, A. Nisio, M. Spadavecchia","doi":"10.1109/MeMeA54994.2022.9856425","DOIUrl":null,"url":null,"abstract":"Respiration rate is one of the most important physiological parameters to estimate clinical conditions or to monitor respiration during sport activities. Therefore, it is necessary to develop integrated devices with different acquisition processes with the main purpose of balancing non-invasive methods and reliable results. In this paper, the respiratory signal is acquired by a piezoelectric belt and analyzed by an innovative algorithm that takes advantages of an adaptive bandwidth filter to identify respiration condition and quantify respiratory rate. A DAQ board is used for the acquisition of samples which is connected to a PC's USB port. Medical decision support is provided by clinical classification based on the estimation of the breath rate; moreover, through detection of outliers, the proposed algorithm could point out moments of dyspnea.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MeMeA54994.2022.9856425","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Respiration rate is one of the most important physiological parameters to estimate clinical conditions or to monitor respiration during sport activities. Therefore, it is necessary to develop integrated devices with different acquisition processes with the main purpose of balancing non-invasive methods and reliable results. In this paper, the respiratory signal is acquired by a piezoelectric belt and analyzed by an innovative algorithm that takes advantages of an adaptive bandwidth filter to identify respiration condition and quantify respiratory rate. A DAQ board is used for the acquisition of samples which is connected to a PC's USB port. Medical decision support is provided by clinical classification based on the estimation of the breath rate; moreover, through detection of outliers, the proposed algorithm could point out moments of dyspnea.