Sleep Staging Using Noncontact-Measured Vital Signs.

As a physiological phenomenon, sleep takes up approximately 30% of human life and significantly affects people's quality of life. To assess the quality of night sleep, polysomnography (PSG) has been recognized as the gold standard for sleep staging. The drawbacks of such a clinical device, however, are obvious, since PSG limits the patient's mobility during the night, which is inconvenient for in-home monitoring. In this paper, a noncontact vital signs monitoring system using the piezoelectric sensors is deployed. Using the so-designed noncontact sensing system, heartbeat interval (HI), respiratory interval (RI), and body movements (BM) are separated and recorded, from which a new dimension of vital signs, referred to as the coordination of heartbeat interval and respiratory interval (CHR), is obtained. By extracting both the independent features of HI, RI, and BM and the coordinated features of CHR in different timescales, Wake-REM-NREM sleep staging is performed, and a postprocessing of staging fusion algorithm is proposed to refine the accuracy of classification. A total of 17 all-night recordings of noncontact measurement simultaneous with PSG from 10 healthy subjects were examined, and the leave-one-out cross-validation was adopted to assess the performance of Wake-REM-NREM sleep staging. Taking the gold standard of PSG as reference, numerical results show that the proposed sleep staging achieves an averaged accuracy and Cohen's Kappa index of 82.42% and 0.63, respectively, and performs robust to subjects suffering from sleep-disordered breathing.

[Novel type of unperturbed sleep monitoring scheme under pillow based on hidden Markov model].

Sleep status is an important indicator to evaluate the health status of human beings. In this paper, we proposed a novel type of unperturbed sleep monitoring system under pillow to identify the pattern change of heart rate variability (HRV) through obtained RR interval signal, and to calculate the corresponding sleep stages combined with hidden Markov model (HMM) under the no-perception condition. In order to solve the existing problems of sleep staging based on HMM, ensemble empirical mode decomposition (EEMD) was proposed to eliminate the error caused by the individual differences in HRV and then to calculate the corresponding sleep stages. Ten normal subjects of different age and gender without sleep disorders were selected from Guangzhou Institute of Respirator Diseases for heart rate monitoring. Comparing sleep stage results based on HMM to that of polysomnography (PSG), the experimental results validate that the proposed noninvasive monitoring system can capture the sleep stages S1-S4 with an accuracy more than 60%, and performs superior to that of the existing sleep staging scheme based on HMM.

Carbon quantum dots decorated MoSe2 photocatalyst for Cr(VI) reduction in the UV-vis-NIR photon energy range.

Developing whole spectrum responsive photocatalysts is one of greatly significant subjects from the viewpoint of using solar energy. Here we have firstly developed a carbon quantum dots-decorated MoSe2 photocatalyst that is active in the whole spectrum of solar light for Cr(VI) reduction. The Cr(VI) reduction rate of higher than 99% has been achieved with 1wt.% nanocarbon emersions under UV, visible and near-infrared irradiation at 180min. Improvement is attributed to its excellent light absorption, efficient charge separation, and the light down converting effect of carbon quantum dots.