NDLI: An Automatic Patient-Adapted ECG Heartbeat Classifier Allowing Expert Assistance

Content Provider	IEEE Xplore Digital Library
Author	Llamedo, M. Martinez, J.P.
Copyright Year	1964
Abstract	In this paper, we present a patient-adaptable algorithm for ECG heartbeat classification, based on a previously developed automatic classifier and a clustering algorithm. Both classifier and clustering algorithms include features from the RR interval series and morphology descriptors calculated from the wavelet transform. Integrating the decisions of both classifiers, the presented algorithm can work either automatically or with several degrees of assistance. The algorithm was comprehensively evaluated in several ECG databases for comparison purposes. Even in the fully automatic mode, the algorithm slightly improved the performance figures of the original automatic classifier; just with less than two manually annotated heartbeats (MAHB) per recording, the algorithm obtained a mean improvement for all databases of 6.9% in accuracy A, of 6.5% in global sensitivity S and of 8.9% in global positive predictive value P⁺. An assistance of just 12 MAHB per recording resulted in a mean improvement of 13.1% in A, of 13.9% in S, and of 36.1% in P⁺. For the assisted mode, the algorithm outperformed other state-of-the-art classifiers with less expert annotation effort. The results presented in this paper represent an improvement in the field of automatic and patient-adaptable heartbeats classification, concluding that the performance of an automatic classifier can be improved with an efficient handling of the expert assistance.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	9
File Size	1247845
Starting Page	2312
Ending Page	2320
File Format	PDF
ISSN	00189294
Volume Number	59
Issue Number	8
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart beat Clustering algorithms Databases Electrocardiography Electromagnetic compatibility Vectors Morphology patient adaptable Clustering heartbeat classification linear classifier
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Analysis of a semiautomatic algorithm for ECG heartbeat classification

A Patient-Adapting Heartbeat Classifier Using ECG Morphology and Heartbeat Interval Features

Mathematical Morphology Based ECG Feature Extraction for the Purpose of Heartbeat Classification

Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters

Hybrid wavelet-mathematical morphology feature extraction for heartbeat classification

An efficient ECG modeling for heartbeat classification

A patient-adaptable ECG beat classifier using a mixture of experts approach

Heartbeat Classification Using Feature Selection Driven by Database Generalization Criteria

Automatic classification of heartbeats using ecg morphology and heartbeat interval features (2004)

An Automatic Patient-Adapted ECG Heartbeat Classifier Allowing Expert Assistance

Similar Documents

Analysis of a semiautomatic algorithm for ECG heartbeat classification

A Patient-Adapting Heartbeat Classifier Using ECG Morphology and Heartbeat Interval Features

Mathematical Morphology Based ECG Feature Extraction for the Purpose of Heartbeat Classification

Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters

Hybrid wavelet-mathematical morphology feature extraction for heartbeat classification

An efficient ECG modeling for heartbeat classification

A patient-adaptable ECG beat classifier using a mixture of experts approach

Heartbeat Classification Using Feature Selection Driven by Database Generalization Criteria

Automatic classification of heartbeats using ecg morphology and heartbeat interval features (2004)

An Automatic Patient-Adapted ECG Heartbeat Classifier Allowing Expert Assistance