Tomoya Tanaka, T. Fujita, K. Sonoda, M. Nii, K. Kanda, K. Maenaka, A. C. Kit, S. Okochi, K. Higuchi
{"title":"Wearable health monitoring system by using fuzzy logic heart-rate extraction","authors":"Tomoya Tanaka, T. Fujita, K. Sonoda, M. Nii, K. Kanda, K. Maenaka, A. C. Kit, S. Okochi, K. Higuchi","doi":"10.1080/1931308X.2013.847621","DOIUrl":null,"url":null,"abstract":"Continuous human monitoring is substantially useful to realize a high QoL (quality of life) society. In the previous work, we fabricated a prototype system for monitoring an electrocardiograph (ECG), heart rate (HR), 3 axes human body acceleration, temperature for human body and human circumstances, simultaneously. These data are transmitted to the host PC and used for analyzing the human activities and conditions such as a heart rate variability (HRV). The HRV that calculated from HR is valuable for recognizing a mental or physical stress of human subjects. In this study, we demonstrate a fuzzy logic HR extraction algorithm on the prototype system to realize an autonomous HRV monitoring system. On-board fuzzy algorithm will reduce the communication traffic and improve an accuracy of the HR extraction. From the implementation result, the error ratio of the HR extraction is improved from 0.9 % to 0.4 %.","PeriodicalId":23749,"journal":{"name":"World Automation Congress 2012","volume":"43 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Automation Congress 2012","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1931308X.2013.847621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Continuous human monitoring is substantially useful to realize a high QoL (quality of life) society. In the previous work, we fabricated a prototype system for monitoring an electrocardiograph (ECG), heart rate (HR), 3 axes human body acceleration, temperature for human body and human circumstances, simultaneously. These data are transmitted to the host PC and used for analyzing the human activities and conditions such as a heart rate variability (HRV). The HRV that calculated from HR is valuable for recognizing a mental or physical stress of human subjects. In this study, we demonstrate a fuzzy logic HR extraction algorithm on the prototype system to realize an autonomous HRV monitoring system. On-board fuzzy algorithm will reduce the communication traffic and improve an accuracy of the HR extraction. From the implementation result, the error ratio of the HR extraction is improved from 0.9 % to 0.4 %.