Detection of circaseptan rhythm and the "Monday effect" from long-term pulse rate dynamics.

This study proposes a methodology to detect circaseptan (CS) rhythm in pulse rate (PR) data and to investigate the "Monday effect" in CS rhythm. Daily PR was collected from a middle-aged healthy working woman over one year. PR, SDNN index and sample entropy (SampEn) were chosen as the indexes of PR dynamics. In order to avoid interference from other biorhythms, ensemble empirical mode decomposition (EEMD) method was used to decompose the original PR series into multiple components. And the single cosinor method was applied to fit the detrended component signal. An optimal 7-day period was found in all indexes (P = 0.0103, P = 0.0133, P = 0.0122 for PR, SDNN index and SampEn, separately) that demonstrated an underlying CS rhythm. In the following study, a statistical Monday decrease in PR dynamics was observed especially significant in the detrended signal. The results suggested a direct relationship between the "Monday effect" and the CS variation, and also indicated a cardiac susceptibility to the social activities. The findings in CS periodicity and the "Monday effect" may help understand the human's biorhythm, provide evidence for preventive and optimized timing treatment, and also serve to daily health management.