Multiscale principal component analysis to separate respiratory influences from the tachogram: Application to stress monitoring

The effects of mental stress on heart rate variability (HRV) have been studied widely. However, the influence of respiration on short-term HRV is often ignored. Therefore, this study uses multiscale principal component analysis to separate the tachogram in 2 components: a component which is directly related to respiration, and a residual component which contains only changes in the heart rate that are unrelated to respiration. This approach is applied on data of 40 subjects during a baseline condition, a mental stress task and an attention task. The application of power spectral HRV analysis on the 2 components of the tachogram, reveals that stress influences the tachogram both via the respiration as well as directly via the functioning of the ANS. These results show that separation of the respiratory component of the tachogram can be a valuable tool to interpret HRV measures. Moreover, this approach might unveil changes in the functioning of the ANS that are otherwise masked by differing respiratory patterns.