Mitigating the effect of non-stationarity in spectral analysis-an application to neonate heart rate analysis.

In order to mitigate the effect of non-stationarity in frequency domain analysis of data, we propose a modification to the power spectral estimation, a widely used technique to characterize physiological signals. Spectral analysis requires partitioning data into smaller epochs determined by the desired frequency resolution. The modified approach proposed here involves dividing the data within each epoch by the standard deviation of the data for that epoch. We applied this modified approach to cardiac beat-to-beat interval data recorded from a newborn infant undergoing hypothermia treatment for birth asphyxia. The critically ill infant had episodes of tachyarrhythmia, distributed sporadically throughout the study, which affected the stationarity of the heart rate. Over the period of continuous heart rate recording, the infant's clinical course deteriorated progressively culminating in death. Coinciding with this clinical deterioration, the heart rate signal showed striking changes in both low-frequency and high-frequency power indicating significant impairment of the autonomic nervous system. The standard spectral approach failed to capture these phenomena because of the non-stationarity of the signal. Conversely, the modified approach proposed here captured the deteriorating physiology of the infant clearly.