Performance study for multimodel client identification system using cardiac and speech signals

Hadri Hussain, Sh-Hussain Salleh, Chee-Ming Ting, Fuad Noman, M. M. Mohammad, Ahmad Zubaidi Abdul Latif, Osamah Al-Hamdani

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

A person's physiological or behavioral characteristic can be used as a biometric and provides automatic identification. There are several advantages of this identification method over the traditional approaches. Overall, biometric techniques can potentially prevent unauthorized access. Unlike the traditional approaches which uses keys, ID, and password, these approaches can be lost, stolen, forged and even forgotten. Biometric systems or pattern recognitions system have been acknowledged by many as a solution to overcome the security problems in this current times. This work looks into the performance of these signals at a frequency samples of 16 kHz. The work was conducted for Client Identification (CID) for 20 clients. The building block for these biometric system is based on MFCC-HMM. The purpose is to evaluate the system based on the performance of training data sets of 30%, 50% and 70%. This work is evaluated using biometric signals of Electrocardiogram (ECG), heart sound (HS) and speech (SP) in order to find the best performance based on the complexity of states and Gaussian. The best CID performance was obtained by SP at 95% for 50% training data at 16 kHz. The worst CID performance was obtained by ECG achieving only 53.21 % for 30% data training.

Original languageEnglish
Title of host publicationThe 12th International Symposium on Medical Information and Communication Technology
EditorsRen Ping Liu, Matti Hamalainen, Kohei Ohno, Graeme Woodward
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages166-171
Number of pages6
ISBN (Electronic)9781538633892
ISBN (Print)9781538633908
DOIs
Publication statusPublished - 2018
Externally publishedYes
EventInternational Symposium on Medical Information and Communication Technology (ISMICT) 2018 - Sydney, Australia
Duration: 26 Mar 201828 Mar 2018
Conference number: 12th
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/mostRecentIssue.jsp?punumber=8554188

Publication series

NameInternational Symposium on Medical Information and Communication Technology, ISMICT
PublisherIEEE, Institute of Electrical and Electronics Engineers
Volume2018-March
ISSN (Print)2326-828X
ISSN (Electronic)2326-8301

Conference

ConferenceInternational Symposium on Medical Information and Communication Technology (ISMICT) 2018
Abbreviated titleISMICT 2018
Country/TerritoryAustralia
CitySydney
Period26/03/1828/03/18
Internet address

Keywords

  • Client Identification
  • Electrocardiogram
  • Hidden Markov Model
  • Mel-Frequency Cepstral Coeffiecients

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