This is because factors such as gender, age, profession, and social class can largely affect sleep quality. Therefore, a broader scope of participants should be taken into consideration during future proposals and assessments of sleep cycle tracking systems. Following our survey, although existing devices showed promising results, most of the studies are restricted to a small sample of healthy individuals. We have performed a literature search between 20 and the following databases were used for retrieving related articles to unobtrusive sleep cycle monitoring: IEEE, Google Scholar, Journal of Clinical Sleep Medicine (JCSM), and PubMed Central (PMC). To this end, this paper aims to review the several attempts made by researchers toward unobtrusive sleep monitoring, specifically sleep cycle. These alternatives can be in the form of wearables (e.g., actigraphs) or nonwearable (e.g., under-mattress sleep trackers). Collecting longitudinal data on sleep can accelerate epidemiological studies exploring the effect of sleep on health and disease. In an attempt to solve this issue, sleep experts are continually looking for unobtrusive and affordable alternatives that can provide longitudinal sleep tracking. As a result, the vast majority of patients do not receive a proper diagnosis. Polysomnography is the gold-standard method for measuring sleep but is inconvenient and limited to a laboratory or a hospital setting. Future work is needed to test the validity of this device in clinical populations. This non-wearable device significantly outperformed clinical grade actigraphy (ICCs between 0.44 and 0.96) and self-reported sleep measures (ICCs below 0.75).Ī non-wearable device demonstrated better agreement with polysomnography than actigraphy. Agreement was also excellent for the notoriously difficult metrics of SOL (ICC=0.92) and WASO (ICC=0.92). However, the newer non-wearable device (Beddit 3.5) yielded excellent reliability with polysomnography for TST (ICC=0.998) and SE% (ICC=0.98) across normal and restricted sleep conditions. The early version of the non-wearable device (Beddit 3.0) displayed poor reliability (ICCs<0.30). We tested accuracy against polysomnography for total sleep time (TST), sleep efficiency (SE%), sleep onset latency (SOL), and wake after sleep onset (WASO). Sleep was measured using polysomnography, wristband actigraphy (Actiwatch Spectrum Plus), self-report, and an early or newer version of a non-wearable device that uses a sensor strip to measure movement, heart rate, and breathing (Beddit, Apple Inc.). In a controlled sleep laboratory environment, we randomly assigned participants to go to bed at 10:30pm (normal sleep) or 1:30am (restricted sleep), setting lights-on at 7:00am. Participants were 35 healthy adults (Mage=18.97, SD=0.95 years 77.14% female 42.86% Caucasian). To determine the accuracy of early and newer versions of a non-wearable sleep tracking device relative to polysomnography and actigraphy, under conditions of normal and restricted sleep duration. Consumers should be careful in interpreting the conclusions on sleep quality and efficiency provided by the device. Also, it failed to discriminate between non-rapid eye movement sleep stages and did not detect the rapid eye movement sleep stage.Ĭonclusions: These findings indicate that BST is not a valid device to monitor sleep. However, it underestimated WASO and thus overestimated TST and SE. Results: BST was able to distinguish SOL with some accuracy. Methods: We performed sleep studies simultaneously with PSG and BST in ten healthy young adults (5 female/5 male) during two non-consecutive nights in a sleep laboratory. Additionally, we examined whether BST can differentiate sleep stages. We measured total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE). In this study, the sleep parameter assessment accuracy of Beddit Sleep Tracker (BST), an unobtrusive and non-wearable sleep monitoring device based on ballistocardiography, was evaluated by comparing it with polysomnography (PSG) measures. Yet, majority of currently available home sleep monitoring devices lack validation. Additionally, sleep disorder diagnostics, and sleep and dream research would benefit from reliable and valid home sleep monitoring devices. Study Objectives: Growing interest in monitoring sleep and well-being has created a market for consumer home sleep monitoring devices.
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