New analysis of HRV through wavelet transform

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Abstract
This article introduces a new analysis of heart rate variability (HRV) using the wavelet transform (WT) in place of conventional methods. This transform maps the signal into a two‐dimensional function on a time‐scale plane. It allows us to precisely determine the location and the power of the HRV spectrum. We apply this method to empirical data containing several stress factors and detect a decrease in power at high frequencies when subjects hyperventilate. We can use this method to detect peaks of power at lower frequencies. We analyze the WT results statistically to determine the relationship between frequency bands at each condition. The correlation coefficients for the WT results between scales change when the stress factors are given. This method reveals the characteristics of the power spectrum at lower frequencies. These are known to play an important role in the modulation of the sympathetic nervous system. This method can be useful in studying computer users’ stress responses under different working conditions.