Analysis of ECG biosignal recognition for client identifiction

Hadri Hussain, Chee-Ming Ting, Fuad Numan, M. Nasir Ibrahim, Nur Fariza Izan, M. M. Mohammad, Hadrina Sh-Hussain

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

5 Citations (Scopus)


The most common application for a recognition system of speech signal, finger print, iris, etc. Are used for biometrie applications. While other biometric signals like electrocardiogram (ECG) and the Heart Sound (HS) are generally used to identify cluster-related diseases. Nonetheless, performance of a traditional biometric system can be easily compromised as it is prone to spoof attack. This paper proposes a unimodal biometric security system that is based on ECG. Physiological biometrics characteristic are based on a human body's, such as the hand geometry, face, palm, ECG and even brain signal. The biosignal data collected by a biometric system would initially be segmented. The Mel-Frequency Cepstral Coefficients (MFCC) method is used for extracting each segmented feature. The Hidden Markov Model (HMM) is used to model the client, and categorize unknown input based on the model. The recognition system involved training and testing of the collected features, known as Client Identification (CID). In this paper, 20 clients were tested with this developed system. The best overall performance for 20 clients at 16 kHz was 71.4% for ECG trained at 50% of the training data, while the worst overall performance was 66.6% for 30% training data.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2017)
EditorsSyed Khaleel Ahmed
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781509055593
Publication statusPublished - 2017
Externally publishedYes
EventIEEE International Conference on Signal and Image Processing Applications (ICSIPA) 2017 - Kuching, Sarawak, Malaysia
Duration: 12 Sep 201714 Sep 2017
Conference number: 5th (Proceedings)


ConferenceIEEE International Conference on Signal and Image Processing Applications (ICSIPA) 2017
Abbreviated titleICSIPA 2017
CityKuching, Sarawak
Internet address


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

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