Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 강경태 | - |
dc.date.accessioned | 2018-02-26T01:48:41Z | - |
dc.date.available | 2018-02-26T01:48:41Z | - |
dc.date.issued | 2015-10 | - |
dc.identifier.citation | TELEMEDICINE AND E-HEALTH, v. 21, No. 10, Page. 814-821 | en_US |
dc.identifier.issn | 1530-5627 | - |
dc.identifier.issn | 1556-3669 | - |
dc.identifier.uri | http://online.liebertpub.com/doi/abs/10.1089/tmj.2014.0187 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/40561 | - |
dc.description.abstract | Background:Electrocardiogram (ECG) telemonitoring is one of the most promising applications of medical telemetry. However, previous approaches to ECG telemonitoring have largely relied on public databases of ECG results.Materials and Methods:In this article we propose a smart ECG system called Pit-a-Pat, which extracts features from ECG signals and detects arrhythmia. It is designed to run on an Android (Google, Mountain View, CA) device, without requiring modifications to other software.Results:We implemented the Pit-a-Pat system using a commercial ECG device, and the experimental results demonstrate the effectiveness and accuracy of Pit-a-Pat for monitoring the ECG signal and analyzing the cardiac activity of a mobile patient.Conclusions:The proposed system allows monitoring of cardiac activity with automatic analysis, thereby providing a convenient, inexpensive, and ubiquitous adjunct to personal healthcare. | en_US |
dc.description.sponsorship | This work was partly supported by a grant from the Institute for Information & Communications Technology Promotion (IITP), funded by the Korean government (MSIP) (No. B0101-15-0557, Resillient Cyber-Physical Systems Research), and partly supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the MSIP (NRF-2013R1A1A1059188). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | MARY ANN LIEBERT | en_US |
dc.subject | electrocardiogram monitoring | en_US |
dc.subject | telemedicine | en_US |
dc.subject | heartbeat classification | en_US |
dc.subject | personal healthcare | en_US |
dc.subject | decision tree | en_US |
dc.subject | random forests | en_US |
dc.subject | HEARTBEAT CLASSIFICATION | en_US |
dc.subject | ECG | en_US |
dc.subject | ALGORITHM | en_US |
dc.subject | NETWORKS | en_US |
dc.subject | FEATURES | en_US |
dc.subject | SUPPORT | en_US |
dc.subject | HEALTH | en_US |
dc.title | Pit-a-Pat: A Smart Electrocardiogram System for Detecting Arrhythmia | en_US |
dc.type | Article | en_US |
dc.relation.no | 10 | - |
dc.relation.volume | 21 | - |
dc.identifier.doi | 10.1089/tmj.2014.0187 | - |
dc.relation.page | 814-821 | - |
dc.relation.journal | TELEMEDICINE AND E-HEALTH | - |
dc.contributor.googleauthor | Park, Juyoung | - |
dc.contributor.googleauthor | Lee, Kuyeon | - |
dc.contributor.googleauthor | Kang, Kyungtae | - |
dc.relation.code | 2015003288 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF COMPUTING[E] | - |
dc.sector.department | DIVISION OF COMPUTER SCIENCE | - |
dc.identifier.pid | ktkang | - |
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