Sleep evaluation by a newly developed PVDF sensor non-contact sheet: a comparison with standard polysomnography and wrist actigraphy

Abstract

Polysomnographic (PSG) recording of multiple physiological measures remains the gold standard for sleep assessment in both basic and clinical human sleep research. However, PSG requires many unnatural conditions that can influence sleep phenomena. Recently, non-contact sheet sensors (SS) have been developed for sleep evaluation. Sheet sensor technology provides advantages over existing minimally intrusive devices used to analyze sleep-related behavior, such as wrist actigraphy (WA), beginning with freedom from attachment to any probes or devices. Current SS measures additionally include two physiological measures -heart rate (HR) and respiration rate (RR). To test the validity of SS analyses, we performed simultaneous recordings of SS and standard PSG in thirteen healthy adult sleepers, with WA additionally available for nine of the subjects. Sleep period features were compared among the three methods, and HR and RR data from SS and PSG were compared. Comparisons between the automatic scoring of SS and WA and visual PSG scoring showed good sleep-wake discrimination (88.3% and 89.4% respectively). Sleep onset estimation relative to PSG was also good for both SS and WA (0.38 and -2.44 epoch differences, respectively). In addition, HR and RR measured by SS were also compared with PSG. Both HR and RR closely approximated PSG physiological measures (error rates: HR 2.4%, RR 4.3%). In summary, SS is expected to be less disruptive and easier to use for long-term home sleep monitoring.

Subjective Happiness Is Associated with Objectively Evaluated Sleep Efficiency and Heart Rate during Sleep: An Exploratory Study Using Non-Contact Sheet Sensors

“…The correlation analysis between sleep variables measured via SS and subjective sleep quality revealed that objective sleep time and sleep efficiency were correlated with subjective sleep quality ("initiation and maintenance of sleep", "refreshing," and "sleep length") upon waking. The reliability and validity of SSs have already been confirmed through simultaneous measurement with PSG and actigraphy [12]. Our data also supported the efficacy of SSs as an accurate method of measuring subjective sleep quality upon waking.…”

“…Although polysomnography (PSG) is the gold standard for objective sleep evaluation, the method involves attaching electrodes to the head, which can inhibit natural sleep and can be difficult to conduct at home. Non-contact sheet sensors (SSs) are a recently-developed type of sensor confirmed to have the reliability and validity of PSG and actigraphy [12]. Thus, SSs constitute a convenient method for collecting sleep data, and can facilitate diagnoses, evaluations of treatment, and clinical research on sleep disorders.…”

Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography

“…The AG underestimated SOL by 19.7 min, compared to PSG, which is similar to previous studies on healthy adults, regardless of the device or algorithm used [12,21,28,29,[36][37][38][41][42][43][44][45][46][47][48]. Studies using the ActiGraph GT3X+ and Cole-Kripke algorithm have reported underestimations of SOL ranging from 6.4 to 15.1 min [19,28,36,46].…”

A Soft Bioelectronic Patch for Simultaneous Respiratory and Cardiovascular Monitoring

“…Emerging wearable bioelectronics are garnering substantial interest in recent decades due to their portability, wearability, and capability of providing continous monitoring, [23][24][25][26][27][28][29] which make them potential solutions in making up for the deficiency of PSG in sleep monitoring. [30][31][32][33][34] To date, wearable and flexible sensors with different working mechanisms, such as piezoelectric, [35] ferroelectric, [36] resistive, [37][38][39][40] capacitance [41,42] and triboelectric, [43][44][45][46][47][48][49] magnetoelastic [50][51][52][53][54] have been developed for wearable biomechanical sensing, which also shows remarkable ability to monitor respiratory signals during sleep. Table S1, Supporting Information shows representative technical indicators of these work on respiration monitoring.…”