Mental stress detection using cardiorespiratory wavelet cross-bispectrum

In this work quadratic phase coupling between respiration and heart rate variability (HRV) has been studied during emotional and mental stress using wavelet cross-bispectrum (WCB). A total of 80 healthy volunteers subjected to a standard stress protocol have been analyzed. Some features derived from the WCB, such as the frequencies at which the maximum peak is located, the distribution of the dominant peaks and the phase entropy have shown statistical significant differences between stress and relax stages. A support vector machine classifier based on these features discriminates stress stages from relax ones with an accuracy ranging from 68 to 89%, suggesting that the interactions between respiration and HRV are altered during stress and may be used to assess it.