Characterization of ultradian and circadian rhythms of core body temperature based on wavelet analysis.

This study was motivated by the needs of precise characterization for the ultradian and circadian rhythmicity of human core body temperature (CBT). The CBT data, two-whole-days' data of two female bed-ridden old aged suffering from cerebral infarction sequelae, was detrended to eliminate the long-term components with periods longer than two days and normalized at first. It was then analyzed by the stationary wavelets transform (SWT) to get the time-frequency information. In the step of SWT, symlet 6 was used, and the approximation waveforms in the 5th, 6th and 7th levels were used to reveal the targeted rhythmicity. The results of the SWT show that SWT can faithfully reveal the time-frequency information of feature elements (peaks and troughs) of waveforms and rhythmicity can be characterized by analyzing temporal information of feature elements.