Speech Signal Analysis for the Estimation of Heart Rates Under Different Emotional States

Aibek Ryskaliyev, Sanzhar Askaruly, Alex Pappachen James

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

5 Citations (Scopus)
32 Downloads (Pure)

Abstract

A non-invasive method for the monitoring of heart activity can help to reduce the deaths caused by heart disorders such as stroke, arrhythmia and heart attack. The human voice can be considered as a biometric data that can be used for estimation of heart rate. In this paper, we propose a method for estimating the heart rate from human speech dynamically using voice signal analysis and by the development of an empirical linear predictor model. The correlation between the voice signal and heart rate are established by classifiers and prediction of the heart rates with or without emotions are done using linear models. The prediction accuracy was tested using the data collected from 15 subjects, it is about 4050 samples of speech signals and corresponding electrocardiogram samples. The proposed approach can use for early non-invasive detection of heart rate changes that can be correlated to an emotional state of the individual and also can be used as a tool for diagnosis of heart conditions in real-time situations.
Original languageEnglish
Title of host publicationInternational Conference on Advances in Computing, Communications and Informatics
Publication statusPublished - Aug 12 2016

Fingerprint

Signal analysis
Biometrics
Electrocardiography
Classifiers
Monitoring

Keywords

  • cs.SD
  • cs.CV

Cite this

Ryskaliyev, A., Askaruly, S., & James, A. P. (2016). Speech Signal Analysis for the Estimation of Heart Rates Under Different Emotional States. In International Conference on Advances in Computing, Communications and Informatics

Speech Signal Analysis for the Estimation of Heart Rates Under Different Emotional States. / Ryskaliyev, Aibek; Askaruly, Sanzhar; James, Alex Pappachen.

International Conference on Advances in Computing, Communications and Informatics. 2016.

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

Ryskaliyev, A, Askaruly, S & James, AP 2016, Speech Signal Analysis for the Estimation of Heart Rates Under Different Emotional States. in International Conference on Advances in Computing, Communications and Informatics.
Ryskaliyev A, Askaruly S, James AP. Speech Signal Analysis for the Estimation of Heart Rates Under Different Emotional States. In International Conference on Advances in Computing, Communications and Informatics. 2016
Ryskaliyev, Aibek ; Askaruly, Sanzhar ; James, Alex Pappachen. / Speech Signal Analysis for the Estimation of Heart Rates Under Different Emotional States. International Conference on Advances in Computing, Communications and Informatics. 2016.
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abstract = "A non-invasive method for the monitoring of heart activity can help to reduce the deaths caused by heart disorders such as stroke, arrhythmia and heart attack. The human voice can be considered as a biometric data that can be used for estimation of heart rate. In this paper, we propose a method for estimating the heart rate from human speech dynamically using voice signal analysis and by the development of an empirical linear predictor model. The correlation between the voice signal and heart rate are established by classifiers and prediction of the heart rates with or without emotions are done using linear models. The prediction accuracy was tested using the data collected from 15 subjects, it is about 4050 samples of speech signals and corresponding electrocardiogram samples. The proposed approach can use for early non-invasive detection of heart rate changes that can be correlated to an emotional state of the individual and also can be used as a tool for diagnosis of heart conditions in real-time situations.",
keywords = "cs.SD, cs.CV",
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PY - 2016/8/12

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N2 - A non-invasive method for the monitoring of heart activity can help to reduce the deaths caused by heart disorders such as stroke, arrhythmia and heart attack. The human voice can be considered as a biometric data that can be used for estimation of heart rate. In this paper, we propose a method for estimating the heart rate from human speech dynamically using voice signal analysis and by the development of an empirical linear predictor model. The correlation between the voice signal and heart rate are established by classifiers and prediction of the heart rates with or without emotions are done using linear models. The prediction accuracy was tested using the data collected from 15 subjects, it is about 4050 samples of speech signals and corresponding electrocardiogram samples. The proposed approach can use for early non-invasive detection of heart rate changes that can be correlated to an emotional state of the individual and also can be used as a tool for diagnosis of heart conditions in real-time situations.

AB - A non-invasive method for the monitoring of heart activity can help to reduce the deaths caused by heart disorders such as stroke, arrhythmia and heart attack. The human voice can be considered as a biometric data that can be used for estimation of heart rate. In this paper, we propose a method for estimating the heart rate from human speech dynamically using voice signal analysis and by the development of an empirical linear predictor model. The correlation between the voice signal and heart rate are established by classifiers and prediction of the heart rates with or without emotions are done using linear models. The prediction accuracy was tested using the data collected from 15 subjects, it is about 4050 samples of speech signals and corresponding electrocardiogram samples. The proposed approach can use for early non-invasive detection of heart rate changes that can be correlated to an emotional state of the individual and also can be used as a tool for diagnosis of heart conditions in real-time situations.

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KW - cs.CV

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