The analysis of mental stress using time-frequency distribution of heart rate variability signal

Conventional power spectrum methods based on fast Fourier transform (FFT), autoregressive(AR) model are not appropriate for analyzing biomedical signals whose spectral characteristics change rapidly. On the other hand, time-frequency analysis has more desirable characteristics of a time-varying spec...

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Bibliographic Details
Published inThe 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 1; pp. 283 - 285
Main Authors Seong, H.M., Lee, J.S., Shin, T.M., Kim, W.S., Yoon, Y.R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2004
Subjects
Blood flow
Cardiology
Fast Fourier transforms
Hafnium
Heart beat
Heart rate variability
HRV
Human factors
mental stress
Signal analysis
Spectral analysis
Time frequency analysis
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Summary:Conventional power spectrum methods based on fast Fourier transform (FFT), autoregressive(AR) model are not appropriate for analyzing biomedical signals whose spectral characteristics change rapidly. On the other hand, time-frequency analysis has more desirable characteristics of a time-varying spectrum. In this study, we investigated the spectral components of heart rate variability (HRV) in a time-frequency domain. Then, from the instantaneous frequency, obtained from time-frequency distribution, the method extracting frequency components of HRV was proposed. The subjects were 17 healthy young men. A coin-stacking task was used to induce mental stress. In the results, the emotional stress of subjects produced an increase in sympathetic activity. Sympathetic activation was responsible for the significant increase in the LF/HF ratio. The subjects were divided into two groups with task ability. The subject who had higher mental stress had a lack of task ability.
ISBN:9780780384392
0780384393
DOI:10.1109/IEMBS.2004.1403147