scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Analysis of Phonocardiogram signal for biometric identification system

01 Jan 2015-pp 1-4
TL;DR: Analysis of Phonocardiogram (PCG) signal for biometric identification system is proposed and the recorded PCG signal of the same person is converted into a template and then used as an alternative approach forBiometric identification.
Abstract: In the paper, analysis of Phonocardiogram (PCG) signal for biometric identification system is proposed. The PCG signal can be used for identification of a person. The PCG signal is preprocessed to remove the noise and then the S 1 and S 2 sounds, which are important features of PCG signal, extracted from it. Shannon entropy method is used for envelope extraction. These features are stored in a database as a template. Features from the different PCG signals are used to make different templates. The recorded PCG signal of the same person is converted into a template and then used as an alternative approach for biometric identification.
Citations
More filters
Journal ArticleDOI
TL;DR: One of the crucial areas of pregnancy research is to analyze the pregnancy development, where scientists analyze the different conditions of fetuses to understand their development.
Abstract: One of the crucial areas of pregnancy research is to analyze the pregnancy development. For this purpose, scientists analyze the different conditions of fetuses to understand their development. In ...

19 citations

Book ChapterDOI
19 Sep 2017
TL;DR: The state of the art of the data fusion oriented to biometric authentication and identification, exploring its techniques, benefits, advantages, disadvantages, and challenges is summarized.
Abstract: There is a growing interest in data fusion oriented to identification and authentication from biometric traits and physiological signals, because of its capacity for combining multiple sources and multimodal analysis allows improving the performance of these systems. Thus, we considered necessary make an analytical review on this domain. This paper summarizes the state of the art of the data fusion oriented to biometric authentication and identification, exploring its techniques, benefits, advantages, disadvantages, and challenges.

17 citations

01 Jan 2003
TL;DR: In this article, the authors presented the hardware design of 2-channel data acquisition system for heart sound and Electrocardiogram (ECG) simultaneously from patients; and software algorithm to detect the first heart sound (S1) and second heart sound(S2).
Abstract: This paper presents the hardware design of 2- channel data acquisition system for heart sound and Electrocardiogram (ECG) to capture the heart sound and ECG simultaneously from patients; and software algorithm to detect the first heart sound (S1) and second heart sound(S2). The algorithm utilizes Instantaneous Energy of ECG to estimate the presence of S1 and S2. Thus, heart sound segmentation can be done as it is essential in the automatic diagnosis of heart sounds. The Instantaneous Energy of ECG is performed to verify the occurrence of S1 and S2 as it is widely accepted pathologically that Phonocardiogram (PCG) and Electrocardiogram (ECG) are two noninvasive source of information depicting the cardiac activity [6]. The hardware consists of instrumentation amplifier, filter, isolation amplifier for each channel, multiplexer, Analogue to Digital Converter (ADC) and microcontroller 68HC11 to control and handle communication protocols with PC. The algorithm was tested for 210 cardiac cycles of heart sound and ECG recorded from patients from normal and abnormal simultaneously.

3 citations

Journal ArticleDOI
TL;DR: In this article, a survey of the technologies and methodologies used in the phonocardiogram (PCG) biometric systems is presented, which includes data acquisition, de-noising, extracting PCG peaks, feature extraction, feature reduction, classification, and evaluation.

2 citations

References
More filters
Proceedings ArticleDOI
07 Sep 1997
TL;DR: A segmentation algorithm which separates the heart sound signal into four parts: the first heart sound, the systole, the second heart sound and the diastole is described, based on the normalized average Shannon energy of a PCG signal.
Abstract: Desribes the development of a segmentation algorithm which separates the heart sound signal into four parts: the first heart sound, the systole, the second heart sound and the diastole. The segmentation of phonocardiogram (PCG) signals is the first step of analysis and the most important procedure in the automatic diagnosis of heart sounds. This algorithm is based on the normalized average Shannon energy of a PCG signal. The performance of the algorithm has been evaluated using 515 periods of PCG signals recording from 37 objects including normal and abnormal. The algorithm has achieved a 93 percent correct ratio.

387 citations

Proceedings ArticleDOI
30 Oct 1997
TL;DR: A heart sound segmentation algorithm, which separates the heart sound signal into four parts (the first heart sound, the systolic period, the second heart sound and the diastolic period), has been developed and shown to perform correctly in over 93% of cases.
Abstract: A heart sound segmentation algorithm, which separates the heart sound signal into four parts (the first heart sound, the systolic period, the second heart sound and the diastolic period), has been developed. The algorithm uses discrete wavelet decomposition and reconstruction to produce intensity envelopes of approximations and details of the original phonocardiographic signal. The performance of the algorithm has been evaluated using 1165 cardiac periods from 77 digital phonocardiographic recordings including normal and abnormal heart sounds. The algorithm has been shown to perform correctly in over 93% of cases.

169 citations


"Analysis of Phonocardiogram signal ..." refers methods in this paper

  • ...Determining instantaneous phase: For finding the boundaries of the local waves, the instantaneous phase waveform is calculated from the smooth Shannon entropy envelope of the signal....

    [...]

Journal ArticleDOI
TL;DR: The proposed HSAD method accurately determines boundaries of major acoustic events of the PCG signal with signal-to-noise ratio of 5 dB and is suitable for real-time wireless cardiac health monitoring and electronic stethoscope devices.

118 citations

Journal ArticleDOI
TL;DR: A novel cardiac sound spectral analysis method using the normalized autoregressive power spectral density (NAR-PSD) curve with the support vector machine (SVM) technique is proposed for classifying the cardiac sound murmurs and the method is validated for the classification of heart valvular disorders.

115 citations


Additional excerpts

  • ...Phase of smoothened PCG signal V. CONCLUSION In this paper, the analysis of PCG signal for biometric identification system is discussed....

    [...]

Journal ArticleDOI
TL;DR: A cardiac sound registration system has been designed incorporating functions such as heart signals segmentation, classification and characterization for automated identification and ease of interpretation by the users and has a high potential as a diagnostic aid for primary health-care sectors.

107 citations


Additional excerpts

  • ...Phase of smoothened PCG signal V. CONCLUSION In this paper, the analysis of PCG signal for biometric identification system is discussed....

    [...]