{"title":"Fuzzy classification of heart rate trends and artifacts","authors":"Dean F. Sittig, K. Cheung, L. Berman","doi":"10.1109/CBMS.1992.245009","DOIUrl":null,"url":null,"abstract":"Fuzzy set theory makes it possible to map inexact data, concepts, and events to fuzzy sets via user-defined membership functions. The authors describe a method for (1) robustly estimating the mean and slope of an arbitrary number of data points, (2) developing a set of fuzzy membership functions to classify various properties of heart rate trends, and (3) finding the longest consecutive sequence of heart rate data that fit a particular fuzzy membership function. Preliminary results indicate that fuzzy set theory has significant potential in the development of a clinically robust method for classifying heart rate data, trends, and artifacts.<<ETX>>","PeriodicalId":197891,"journal":{"name":"[1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems","volume":"222 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.1992.245009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Fuzzy set theory makes it possible to map inexact data, concepts, and events to fuzzy sets via user-defined membership functions. The authors describe a method for (1) robustly estimating the mean and slope of an arbitrary number of data points, (2) developing a set of fuzzy membership functions to classify various properties of heart rate trends, and (3) finding the longest consecutive sequence of heart rate data that fit a particular fuzzy membership function. Preliminary results indicate that fuzzy set theory has significant potential in the development of a clinically robust method for classifying heart rate data, trends, and artifacts.<>