Analyzing physiological signals recorded with a wearable sensor across the menstrual cycle using circular statistics

Figures

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  FIGURE 1. An idealized 28-day cycle illustration of (A) a basal body temperature (BBT) chart of an ovulating subject depicting a biphasic pattern, and (B) fluctuations of the ovarian hormones estrogen, progesterone, follicle stimulating hormone (FSH), and the luteinizing hormone (LH).

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  FIGURE 2. Steps of the heuristic algorithm for processing and plotting each physiological signal.

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  FIGURE 3. Polar Histogram plots (0°–359°) of the average values across the menstrual cycles for (top) ovulating, and (bottom) non-ovulating subjects; 31 ovulating cycles, 8 non-ovulating cycles. 0° indicates the start of menses and 180° indicates ovulation. Notice that the window of ovulation (days 13 through 15) is highlighted in red on polar histograms for ovulating cycles. The listed p-values were calculated using the Rayleigh test.

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  FIGURE 4. Mean value of phases across 31 cycles for (A) heart rate, (B) inter-beat-interval (IBI), (C) distal skin temperature, (D) tonic component of the EDA, and (E) and the EDA signal magnitude area of the phasic component in the frequency domain measured with the Empatica E4 wristband for ovulating subjects’ during sleep showing significant differences between five phases of the menstrual cycle using a paired t-test with a Bonferroni correction (α ≤ 0.005) (Phases: Menses, Mid-follicular, Ovulation, Mid-luteal, and Late-luteal) n = 31. Note: **α ≤ 0.005, *0.005 < α ≤ 0.05.