Sleep Measurement Tools: A Narrative Review of Recent Advances

Dr. Darshana Nariya

Abstract: Background: Accurate sleep measurement underpins clinical diagnosis, research, and consumer health tracking. Over the past decade the field has expanded beyond laboratory polysomnography (PSG) to include actigraphy, consumer wearables, contactless sensors, smartphone applications, and AI-driven signal analysis. Objective: This narrative review synthesizes recent advances (2020-2026) in sleep measurement tools, evaluates their comparative validity, and outlines future directions. Methods: A structured, non-systematic search of PubMed and Embase used MeSH terms and free-text keywords covering polysomnography, actigraphy, wearable and contactless sensors, artificial intelligence, and sleep questionnaires, restricted to English-language articles published between January 2019 and July 2026; reference lists of key reviews were hand-searched. Results: PSG remains the diagnostic reference standard but is limited by cost, access, and the first-night effect. Actigraphy reliably estimates total sleep time and efficiency but performs poorly at multi-stage classification. Consumer wrist wearables and smart rings combining accelerometry, photoplethysmography, and skin-temperature sensing approach 90-95% agreement with PSG for sleep-wake detection, though wake specificity remains variable. Contactless radar and under-mattress sensors permit unobtrusive, longitudinal cardiorespiratory monitoring. Deep-learning and foundation models increasingly automate PSG scoring and extract prognostic information. Subjective instruments such as the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale remain valuable for perceived sleep quality but show limited criterion validity against objective sleep disorders. Conclusions: No single tool is universally superior; each occupies a niche defined by trade-offs among accuracy, scalability, cost, and patient burden. Rigorous, standardised validation across diverse populations remains the principal need as the field moves toward AI-augmented, multimodal, home-based sleep assessment.

Keywords: polysomnography; actigraphy; wearable electronic devices; sleep apnea syndromes; artificial intelligence; sleep quality

How to Cite?: Dr. Darshana Nariya, "Sleep Measurement Tools: A Narrative Review of Recent Advances", Volume 15 Issue 9, September 2026, International Journal of Science and Research (IJSR), Pages: 670-677, https://www.ijsr.net/getabstract.php?paperid=SR26910150333, DOI: https://dx.doi.org/10.21275/SR26910150333

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