Abstract
In this research, a person identification system has been simulated using electrocardiogram (ECG) signals as biometrics. Ten adult people were participated as the subjects in this research taken from their signal ECG using the one-lead ECG machine. A total of 65 raw ECG waves from the 10 subjects were analyzed. This raw signal is then processed using the Hjorth Descriptor and Sample Entropy (SampEn) to get the signal features. Support Vector Machine (SVM) algorithm was used as the classifier for the subject authentication based upon the record of ECG signal. The results of the research showed that the highest accuracy value of 93.8% was found in Hjorth Descriptor. Compared to SampEn, this method is quite promising to be implemented for having a good performance and fewer features.
Highlights
Biometric can be defined as a unique feature measurement from the physical features found in each person
Another analysis method in the frequency domain on ECG biometric is Fourier transform as reported in the study [13] informing that the Fast Fourier Transform (FFT) method combined with the nearest neighbour classifier had a good performance for the ECG‟s biometric
Person authentication has been successfully simulated using the biometric characteristics of ECG signals as the new modalities in biometrics
Summary
Biometric can be defined as a unique feature measurement from the physical features found in each person. The Support Vector Machine (SVM) method was used for the feature-based authentication Another analysis method in the frequency domain on ECG biometric is Fourier transform as reported in the study [13] informing that the Fast Fourier Transform (FFT) method combined with the nearest neighbour classifier had a good performance for the ECG‟s biometric. This proposed study focuses on time series analysis methods using Hjorth Descriptor and Sample Entropy for ECG biometrics These methods have been selected for having good performance based upon some previous research to classify ECG and Epileptic EEG signals [15]-[17]. The contributions of this research in the theoretical and practical domain include: the use of appropriate methods in the person authentication through ECG signals, i.e. to determine an algorithm, in this case, purposely to reduce the computational complexity.
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