{"title":"A 0.5 nW Analog ECG Processor for Real Time R-wave Detection Based on Pan-Tompkins Algorithm","authors":"Cihan Berk Gungor, H. Toreyin","doi":"10.1109/BHI.2019.8834508","DOIUrl":null,"url":null,"abstract":"Noninvasive ubiquitous health-monitoring applications necessitate real-time, accurate, and energy-efficient computation of health-related parameters. R-waves are critical features for cardiac health assessment using ECG. In this paper, an energy-efficient application specific integrated circuit (ASIC) processor for real-time R-wave detection based on the Pan-Tompkins algorithm is presented. R-wave detection through processing in the analog domain is demonstrated using simulation results. The processor is designed in a 65 nm CMOS technology and consumes 0.5 nW from a 1 V supply. Based on simulation results using the MIT-BIH arrhythmia database, the processor achieves average R-wave detection sensitivity and positive predictive values of 98.98% and 98.9%, respectively.","PeriodicalId":72024,"journal":{"name":"... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BHI.2019.8834508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Noninvasive ubiquitous health-monitoring applications necessitate real-time, accurate, and energy-efficient computation of health-related parameters. R-waves are critical features for cardiac health assessment using ECG. In this paper, an energy-efficient application specific integrated circuit (ASIC) processor for real-time R-wave detection based on the Pan-Tompkins algorithm is presented. R-wave detection through processing in the analog domain is demonstrated using simulation results. The processor is designed in a 65 nm CMOS technology and consumes 0.5 nW from a 1 V supply. Based on simulation results using the MIT-BIH arrhythmia database, the processor achieves average R-wave detection sensitivity and positive predictive values of 98.98% and 98.9%, respectively.