Performance evaluation of finger-worn devices for sleep stage classification and sleep apnea detection: a systematic...

Recently, sleep wearables have experienced a boom, particularly devices worn on the finger, such as smart rings, which have garnered growing attention. However, there currently exists no review that comprehensively and systematically evaluates the accuracy of these devices.

This scoping review evaluates 11 finger-worn devices against polysomnography (PSG) across 28 articles from inception to April, 2025, assessing sleep staging (primarily healthy participants) and obstructive sleep apnea (OSA) detection (clinical cohorts) via heterogeneous sensors and algorithms. Current evidence in our study demonstrates efficacy in sleep/wake classification (pooled accuracy = 87%, 95%CI = 86%~89%) and severe OSA screening, but reveals persistent challenges in multi-stage sleep analysis (pooled accuracy for light/deep/rapid eye movement (REM) sleep = 0.65, 0.81, 0.74, respectively) and mild OSA detection. All devices, except one, demonstrated higher accuracy at an apnea-hypopnea index (AHI) threshold of 30 than at thresholds of 5 or 15.

Finger-worn devices may be used for longitudinal sleep/wake tracking in healthy adults or as a triage tool for severe OSA, but should not replace PSG for diagnosis of mild OSA or detailed sleep architecture assessment. Achieving PSG-comparable accuracy in multi-stage sleep analysis and mild OSA detection requires addressing algorithmic transparency, population diversity, and standardized methodologies.