Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Wireless Sensor Network

ISSN Print: 1945-3078
ISSN Online: 1945-3086
www.scirp.org/journal/wsn
E-mail: wsn@scirp.org

Google-based Impact Factor: 1
Citations h5-index & Ranking*

Journals Menu

"Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care"
written by Haiying ZHOU, Kun-Mean HOU, Decheng ZUO,
published by Wireless Sensor Network, Vol.1 No.4, 2009

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	A global training model for beat classification using basic electrocardiogram morphological features
	CMC-COMPUTERS …, 2022

[2]	Electrocardiogram generation software for testing of parameter extraction algorithms
	2020

[3]	Inference with Convolutional Neural Networks on Analog Neuromorphic Hardware
	2020

[4]	Application of learning algorithms in smart home IoT system security
	2018

[5]	Intelligent ECG processing and abnormality detection using adaptive ensemble models
	2017

[6]	Classification of normal and arrhythmic ECG using wavelet transform based template-matching technique
	2017

[7]	A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm
	Computer Methods and Programs in Biomedicine, 2017

[8]	Rate-distortion classification for self-tuning IoT networks
	2017

[9]	Automatic rate-distortion classification for the IoT: Towards signal-adaptive network protocols
	2017

[10]	Classification of normal and arrhythmic ECG using wavelet transform based templatematching technique
	2017

[11]	АЛГОРИТЪМ ЗА ОПРЕДЕЛЯНЕ НА ПЕРСОНАЛНИТЕ АНАТОМИЧНИ КОЕФИЦИЕНТИ В СИСТЕМА ЗА НЕПРЕКЪСНАТО СЛЕДЕНЕ НА СЪСТОЛНОТО И ДИАСТОЛНО НАЛЯГАНЕ ПО МЕТОДА НА PULSE TRANSIT TIME
	Twelfth Scientific Conference with International Participation SPACE, ECOLOGY, SAFETY, 2016

[12]	A remote electrocardiogram monitoring system with good swiftness and high reliablility
	Computers & Electrical Engineering, 2016

[13]	Improved abnormality detection from raw ECG signals using feature enhancement
	2016

[14]	Cardiac Arrhythmias Classification and Compression using a Hybrid Technique
	2015

[15]	Data mining for Internet of Things: A survey.
	2014

[16]	An efficient abnormal beat detection scheme from ECG signals using neural network and ensemble classifiers
	Software, Knowledge, Information Management and Applications (SKIMA), 2014 8th International Conference, 2014

[17]	Data mining for internet of things: A survey
	Communications Surveys & Tutorials, IEEE , 2014

[18]	A Novel Time-domain Diagnostic Method for ECG Signal System Based on a Smart-phone
	NULL 2012

[19]	Real-Time Cardiac Arrhythmias Monitoring for Pervasive Health Care
	2012

[20]	PROIECT DE DISERTA?IE
	NULL 2011

[21]	Time-domain ECG signal analysis based on smart-phone
	Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE, 2011

[22]	PROIECT DE DISERTAŢIE
	2011

[23]	Pervasive cardiac monitoring system for remote continuous heart care
	Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference, 2010

[1]	A Global Training Model for Beat Classification Using Basic Electrocardiogram Morphological Features Computers, Materials & Continua, 2022 DOI:10.32604/cmc.2022.015474

[2]	ELECTROCARDIOGRAM GENERATION SOFTWARE FOR TESTING OF PARAMETER EXTRACTION ALGORITHMS Applied Computer Science, 2020 DOI:10.35784/acs-2020-27

[3]	A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm Computer Methods and Programs in Biomedicine, 2017 DOI:10.1016/j.cmpb.2017.02.028

[4]	Rate-distortion classification for self-tuning IoT networks 2017 IEEE International Conference on Communications Workshops (ICC Workshops), 2017 DOI:10.1109/ICCW.2017.7962766

[5]	Automatic Rate-Distortion Classification for the IoT: Towards Signal-Adaptive Network Protocols GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 DOI:10.1109/GLOCOM.2017.8255033

[6]	A remote electrocardiogram monitoring system with good swiftness and high reliablility Computers & Electrical Engineering, 2016 DOI:10.1016/j.compeleceng.2016.02.004

[7]	Improved abnormality detection from raw ECG signals using feature enhancement 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 2016 DOI:10.1109/FSKD.2016.7603383

[8]	Data Mining for Internet of Things: A Survey IEEE Communications Surveys & Tutorials, 2014 DOI:10.1109/SURV.2013.103013.00206

[9]	An efficient abnormal beat detection scheme from ECG signals using neural network and ensemble classifiers The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014), 2014 DOI:10.1109/SKIMA.2014.7083561

[10]	Data Mining for Internet of Things: A Survey IEEE Communications Surveys & Tutorials, 2014 DOI:10.1109/SURV.2013.103013.00206

[11]	Time-domain ECG signal analysis based on smart-phone 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011 DOI:10.1109/IEMBS.2011.6090713

[12]	Wireless Body Area Networks 2011 DOI:10.1201/b11522-4

[13]	Pervasive Cardiac Monitoring System for Remote Continuous Heart Care 2010 4th International Conference on Bioinformatics and Biomedical Engineering, 2010 DOI:10.1109/ICBBE.2010.5514669

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Wireless Sensor Network

Wireless Sensor Network

Journals Menu

Home

About SCIRP

Service

Policies