NDLI: Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals

Content Provider	IEEE Xplore Digital Library
Author	Sidek, K. Khali, I.
Copyright Year	2012
Description	Author affiliation: Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Melbourne, VIC, Australia (Sidek, K.; Khali, I.)
Abstract	In this paper, a person identification mechanism implemented with Cardioid based graph using electrocardiogram (ECG) is presented. Cardioid based graph has given a reasonably good classification accuracy in terms of differentiating between individuals. However, the current feature extraction method using Euclidean distance could be further improved by using Mahalanobis distance measurement producing extracted coefficients which takes into account the correlations of the data set. Identification is then done by applying these extracted features to Radial Basis Function Network. A total of 30 ECG data from MITBIH Normal Sinus Rhythm database (NSRDB) and MITBIH Arrhythmia database (MITDB) were used for development and evaluation purposes. Our experimentation results suggest that the proposed feature extraction method has significantly increased the classification performance of subjects in both databases with accuracy from 97.50% to 99.80% in NSRDB and 96.50% to 99.40% in MITDB. High sensitivity, specificity and positive predictive value of 99.17%, 99.91% and 99.23% for NSRDB and 99.30%, 99.90% and 99.40% for MITDB also validates the proposed method. This result also indicates that the right feature extraction technique plays a vital role in determining the persistency of the classification accuracy for Cardioid based person identification mechanism.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	3396
Ending Page	3399
File Size	307933
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346694
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrocardiography Feature extraction Databases Accuracy Euclidean distance Medical services Neurons
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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

A novel biometric authentication approach using electrocardiogram signals

Adaptive technique for P and T wave delineation in electrocardiogram signals

Sleep apnoea episodes recognition by a committee of ELM classifiers from ECG signal

Person identification in irregular cardiac conditions using electrocardiogram signals

The PLR-DTW method for ECG based biometric identification

Arrhythmia detection and classification using morphological and dynamic features of ECG signals

Accurate Arrhythmia classification using auto-associative neural network

Cardioid graph based ECG biometric using compressed QRS complex

Metric learning for automatic sleep stage classification

Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals

Similar Documents

A novel biometric authentication approach using electrocardiogram signals

Adaptive technique for P and T wave delineation in electrocardiogram signals

Sleep apnoea episodes recognition by a committee of ELM classifiers from ECG signal

Person identification in irregular cardiac conditions using electrocardiogram signals

The PLR-DTW method for ECG based biometric identification

Arrhythmia detection and classification using morphological and dynamic features of ECG signals

Accurate Arrhythmia classification using auto-associative neural network

Cardioid graph based ECG biometric using compressed QRS complex

Metric learning for automatic sleep stage classification

Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals