Study Objectives: To update sleep medicine providers regarding (1) published research on the uses and performance of novel sleep tracking and testing technologies (2) the use of artificial intelligence to acquire and process sleep data and (3) research trends and gaps regarding the development and/or evaluation of these technologies.

Methods: Medline and Embase electronic databases were searched for studies utilizing screening and diagnostic sleep technologies, published between 2020 and 2022 in journals focusing on human sleep. Studies' quality was determined based on the Study Design criteria of The Oxford Centre for Evidence-Based Medicine Levels of Evidence.

Results: 96 of 3849 articles were included. Most studies were adult performance evaluation (validation) studies, often comparing a novel technology to polysomnography. Sleep tracker publications tended to be USA-based, non-industry funded, performance studies on healthy adults using non-FDA (Food and Drug Administration) cleared technologies. Sleep apnea testing technologies were more frequently industry-funded and FDA-cleared. All studied technologies utilized software with an algorithm and/or artificial intelligence. Few studies used randomized control designs, or accounted for recruitment/attrition biases associated with participants' age, race/ethnicity, or comorbid health conditions.

Conclusions: Evidence-based publications have not kept pace with the proliferation and landscape of' consumer and clinical sleep technologies. Due to the variance in technologies used within sleep research, careful review of the software used within studies is recommended. Future publications may fill identified gaps by including underrepresented populations, maintaining independence from industry, and through rigorous study design.

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http://dx.doi.org/10.5664/jcsm.11562DOI Listing

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