Evaluation of the Accuracy of Contactless Consumer Sleep-Tracking Devices Application in Human Experiment: A Systematic Review and Meta-Analysis

Abstract

Compared with the gold standard, polysomnography (PSG), and silver standard, actigraphy, contactless consumer sleep-tracking devices (CCSTDs) are more advantageous for implementing large-sample and long-period experiments in the field and out of the laboratory due to their low price, convenience, and unobtrusiveness. This review aimed to examine the effectiveness of CCSTDs application in human experiments. A systematic review and meta-analysis (PRISMA) of their performance in monitoring sleep parameters were conducted (PROSPERO: CRD42022342378). PubMed, EMBASE, Cochrane CENTRALE, and Web of Science were searched, and 26 articles were qualified for systematic review, of which 22 provided quantitative data for meta-analysis. The findings show that CCSTDs had a better accuracy in the experimental group of healthy participants who wore mattress-based devices with piezoelectric sensors. CCSTDs' performance in distinguishing waking from sleeping epochs is as good as that of actigraphy. Moreover, CCSTDs provide data on sleep stages that are not available when actigraphy is used. Therefore, CCSTDs could be an effective alternative tool to PSG and actigraphy in human experiments.

Keywords: actigraphy; polysomnography; sleep stages; validation.

Figure 1

PRISMA flow diagram.

Figure 2

Types of CCSTDs and contactless sleep monitoring mechanism.

Figure 3

Comparison of the epoch-by-epoch (EBE) agreement for asleep/awake subgroups using error bars. (a) Sensors, (b) device types, (c) participants, and (d) brands (the number of samples of the same brand greater than or equal to two will be included in the same group, and the other samples are divided into (1) other brands of bedside device, and (2) other brands of mattress device). N, number of studies; CV, coefficient of variation; bedside, bedside devices; mattress-based, mattress-based devices; healthy, healthy participants; healthy + patient, both healthy and patient participants; others(M), other brands of mattress device; others(B), other brands of bedside device; accuracy, proportion of correctly classified sleep and wake epochs; sensitivity, proportion of correctly classified sleep epochs; specificity, proportion of correctly classified wake epochs [54].

Figure 3

Comparison of the epoch-by-epoch (EBE) agreement for asleep/awake subgroups using error bars. (a) Sensors, (b) device types, (c) participants, and (d) brands (the number of samples of the same brand greater than or equal to two will be included in the same group, and the other samples are divided into (1) other brands of bedside device, and (2) other brands of mattress device). N, number of studies; CV, coefficient of variation; bedside, bedside devices; mattress-based, mattress-based devices; healthy, healthy participants; healthy + patient, both healthy and patient participants; others(M), other brands of mattress device; others(B), other brands of bedside device; accuracy, proportion of correctly classified sleep and wake epochs; sensitivity, proportion of correctly classified sleep epochs; specificity, proportion of correctly classified wake epochs [54].

Figure 4

Comparison of the epoch-by-epoch (EBE) agreement for sleep stages in the error bars. N, number of studies; CV, coefficient of variation. Accuracy, proportion of correctly classified epochs for each stage over the total number of epochs; sensitivity, proportion of epochs classified as each stage; specificity, proportion of epochs not classified as each stage [54].