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BackgroundA newly developed fetal movement acceleration measurement recorder has made it possible to count gross movements for hours. The purpose of this study was to determine the normal reference values for such movements.MethodsOne hundred and six pregnant women recorded fetal movements by themselves when they slept at home weekly from 28 weeks to term. The normal reference values were determined based on the data that could be recorded for more than 4 h per night.ResultsA total of 2,458 h of data from 385 recordings from 64 women was available. The median ratio of 10-s periods in which fetal movements occurred to the total time interval was 17% at 28 gestational weeks, decreasing to ∼6% at term. The number of fetal movements was 74 times/h, decreasing to 29 times at term. The number, the mean, and the longest durations of periods with no fetal movement, meaning no fetal movements were found for more than 5 min, were 1.56 times/h, 7.95 and 14.25 min, respectively, at 28 weeks, and increasing to 2.54 times, and 9.63 and 19.67 min, respectively, at term.ConclusionsThis study provides normal reference values for gross fetal movement count using the fetal movement acceleration measurement recorder.

Background and objectives The pathophysiologic aspects of parasympathetic nerve (PN) function during sleep in patients with obstructive sleep apnea (OSA) studied by classical power spectrum analysis on heart rate variability (HRV) are highly controversial. The controversy is attributed to methodologic concerns, such as poor time resolution involved in power spectrum analysis. We aimed to establish the appropriate method for the investigation of PN function in OSA patients with apneas and hypopneas using instantaneous time–frequency analysis with complex demodulation (CD) and sufficient time resolution. Methods A total of 30 patients with PSG-confirmed mild to severe OSA were recruited for the analysis of frequency spectra contained in R-R intervals (RRI) of overnight electrocardiograph (ECG) tracings. High-frequency (HF) domains ranging between 0.15 and 0.40 Hz were selected for analysis. Among these domains, the HF domain with the maximum instantaneous amplitude was defined as the main HF peak and was used as the surrogate marker of PN discharge. Based on density spectrum array (DSA) map for main HF peak constructed with a time scale of 1 s and a frequency resolution of 0.002 Hz (HF-DSA map), the shift in central frequency (CF) of main HF peak over time was continuously monitored. When the main HF peak with the same CF lasted for more than 20 s or 5 min on HF-DSA map, the PN function was considered to be stable or very stable. The measurements were then repeated after continuous positive airway pressure (CPAP) treatment. Results The extent of PN-evoked modulation of RRI was enhanced in nonrapid eye movement (NREM) sleep, though the stability was reduced in both NREM and rapid eye movement (REM) sleep. These peculiar behaviors of PN function were reversed by CPAP treatment. Conclusion We found that instantaneous time–frequency analysis allowed estimation of transitional changes in PN function during sleep in OSA patients.

STUDY OBJECTIVES Cyclic alternating pattern (CAP) is frequently followed by changes in heart rate (HR) and blood pressure (BP), but the sequential associations between CAP and autonomic nerve activity have not been studied. The study aimed to reveal the precise changes in heart rate variability (HRV) during phase A of the CAP cycle. DESIGN Polysomnography was recorded according to the CAP Atlas (Terzano, 2002), and BP and electrocardiogram were simultaneously recorded. The complex demodulation method was used for analysis of HRV and evaluation of autonomic nerve activity. SETTING Academic sleep laboratory. PARTICIPANTS Ten healthy males. MEASUREMENTS AND RESULTS The increase in HR (median [first quartile - third quartile]) for each subtype was as follows: A1, 0.64 (-0.30 to 1.69), A2, 1.44 (0.02 to 3.79), and A3, 6.24 (2.53 to 10.76) bpm (A1 vs. A2 P < 0.001, A1 vs. A3 P < 0.001, A2 vs. A3 P < 0.001). The increase in BP for each subtype was as follows: A1, 1.23 (-2.04 to 5.75), A2, 1.76 (-1.46 to 9.32), and A3, 12.51 (4.75 to 19.94) mm Hg (A1 vs. A2 P = 0.249, A1 vs. A3 P < 0.001, A2 vs. A3 P < 0.001). In all of phase A, the peak values for HR and BP appeared at 4.2 (3.5 to 5.4) and 8.4 (7.0 to 10.3) seconds, respectively, after the onset of phase A. The area under the curve for low-frequency and high-frequency amplitude significantly increased after the onset of CAP phase A (P < 0.001) and was higher in the order of subtype A3, A2, and A1 (P < 0.001). CONCLUSIONS All phase A subtypes were accompanied with increased heart rate variability, and the largest heart rate variability was seen in subtype A3, while a tendency for less heart rate variability was seen in subtype A1.

A real-time rapid eye movement (REM) sleep detection system has been developed, which is composed of a portable digital recorder and a personal computer (PC) connected with a USB interface. The recorder amplifies, filters and samples the polygraphic signals such as electromyogram (EMG), electrooculogram (EOG), and electroencephalogram (EEG), and then sends them to the PC. The PC enables the real-time detection of REM sleep by heuristically evaluating the EMG activities, number of rapid eye movements, and the power spectral density of the EEG for every 10 s epoch. The performance of the developed system has been assessed by comparing the scores with those of off-line processing.