The spread of wearable watch devices with photoplethysmography (PPG) sensors has made it possible to use continuous pulse wave data during daily life. We examined if PPG pulse wave data can be used to detect sleep apnea, a common but underdiagnosed health problem associated with impaired quality of life and increased cardiovascular risk. In 41 patients undergoing diagnostic polysomnography (PSG) for sleep apnea, PPG was recorded simultaneously with a wearable watch device. The pulse interval data were analyzed by an automated algorithm called auto-correlated wave detection with adaptive threshold (ACAT) which was developed for electrocardiogram (ECG) to detect the cyclic variation of heart rate (CVHR), a characteristic heart rate pattern accompanying sleep apnea episodes. The median (IQR) apnea-hypopnea index (AHI) was 17.2 (4.4–28.4) and 22 (54%) subjects had AHI ≥15. The hourly frequency of CVHR (Fcv) detected by the ACAT algorithm closely correlated with AHI (r = 0.81), while none of the time-domain, frequency-domain, or non-linear indices of pulse interval variability showed significant correlation. The Fcv was greater in subjects with AHI ≥15 (19.6 ± 12.3 /h) than in those with AHI <15 (6.4 ± 4.6 /h), and was able to discriminate them with 82% sensitivity, 89% specificity, and 85% accuracy. The classification performance was comparable to that obtained when the ACAT algorithm was applied to ECG R-R intervals during the PSG. The analysis of wearable watch PPG by the ACAT algorithm could be used for the quantitative screening of sleep apnea.
The relationships between average shear-wave velocity of the ground and the site amplification factor for peak ground acceleration, peak ground velocity, seismic intensity and response spectral amplitudes are examined by using the strong motion records from the Yokohama Dense Strong-Motion Network. Regarding the amplification factors for peak ground acceleration, peak ground velocity and seismic intensity, the results by the records from smaller magnitude earthquakes and from larger magnitude earthquakes are different. This is due to the different spectral contents of the records from smaller and larger earthquakes. The amplification factors for peak ground acceleration, peak ground velocity and seismic intensity show higher correlations with the average shear-wave velocities of the ground down to 10m, 30m and 20 to 30 m, respectively. The amplification factors for response spectral amplitudes for shorter, mid and longer periods show higher correlations with the average shear-wave velocities of the ground down to 10m, 20m and 30 m, respectively. The correlations of the spectral amplitude at longer period range are higher than those at shorter period range.
In this study we examined the relaxing effects of listening to music on a total of 12 women aged from their 20s to their 40s by measuring their blood flow, heart rate variability, and their body surface temperature. As a result, We found that there was a tendency for the volume of blood flow to the fingertips to significantly increase when listening to classical music, but there was a variety of changes in blood flow between each age group for healing music and J-Pop music. When measuring heart rate it was found that the LF/HF value, which is an index for the autonomic nervous system which shows tension and stress, fell significantly when listening to each type of music. Lastly, there was a trend for body surface temperature to rise when listening to classical or healing music, a rise which was particularly significant when listening to healing music. This study shows that a relaxing effect can be expected for all indices when listening to classical music. However, for healing music and J-Pop, personal musical preferences seemed to have an effect and the results were varied.
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