Interpolating average based detrending fluctuation method for measuring heart rate variability in the menstrual cycle

Every woman spends her life with a cyclic occurrence of the menstrual cycle of approximately 28 days. During a menstrual cycle, there are many physical, psychological and behavioural changes in women that affect the autonomic activities of the heart. However, health management is an important factor to be considered as it influences the entire quality of women life. Thus, Heart Rate Variability (HRV) analysis is an appropriate tool to examine the physiological effects of the menstrual cycle in young healthy women. So, in this paper, Detrended Fluctuation Analysis method (DFA) is used for analyzing the HRV in the phases of the menstrual cycle. In DFA, there is a limitation of abrupt jumps in detrended profile that leads to the inaccurate detection of properties of HRV. In order to overcome the limitations of abrupt jumps in the DFA method, a novel method is proposed in this paper. The trend in proposed method is created by averaging the integrated HRV time series of each window in its respective time scale. Then, cubic interpolation is done for estimating new data points within each averaged segment. Finally, proposed trend is used to estimate scaling exponent function. The proposed method detects the properties of HRV variations accurately among phases of the menstrual cycle when applied on self-recorded dataset.

Automated summary

Every woman experiences a menstrual cycle of approximately 28 days, with physical, psychological and behavioral changes affecting heart autonomic activities. Heart Rate Variability (HRV) analysis is a useful tool to study these effects. A novel method proposed in this paper accurately detects HRV variations during different phases of the menstrual cycle.