연락처 : WC 이메일 : nikimarcotte@free.fr

Contemporary wearable sleep monitors utilize a combination of biometric sensors and predictive models to identify and classify the three primary sleep stages—REM, deep, and light—by capturing dynamic biological signals that follow established patterns throughout your sleep cycles. In contrast to hospital-based EEG methods, which require brainwave electrodes and overnight stays, these rings rely on discreet, contact-based sensors to gather continuous data while you sleep—enabling reliable longitudinal sleep tracking without disrupting your natural rhythm.

The core sensing technology in these devices is optical blood flow detection, which employs tiny light emitters and photodetectors to measure changes in blood volume beneath the skin. As your body transitions between sleep ring stages, your cardiovascular dynamics shift in recognizable ways: during deep sleep, your pulse slows and stabilizes, while during REM sleep, heart rate becomes irregular and elevated. The ring detects subtle temporal patterns to estimate your current sleep phase.

In parallel, an embedded accelerometer tracks body movement and position shifts throughout the night. Deep sleep is characterized by minimal motor activity, whereas light sleep features periodic shifts and turning. REM sleep often manifests as brief muscle twitches, even though your major muscle groups are temporarily paralyzed. By fusing movement data with heart rate variability, and sometimes incorporating respiratory rate estimates, the ring’s multi-parameter classifier makes statistically grounded predictions of your sleep phase.

This detection framework is grounded in extensive clinical sleep studies that have mapped physiological signatures to each sleep stage. Researchers have aligned ring-derived signals with polysomnography data, enabling manufacturers to optimize classification algorithms that learn individual sleep profiles across populations. These models are enhanced by feedback from thousands of nightly recordings, leading to incremental gains in precision.

While sleep rings cannot match the clinical fidelity of polysomnography, they provide a practical window into your sleep habits. Users can identify how habits influence their rest—such as how screen exposure fragments sleep architecture—and make informed behavioral changes. The true power of these devices lies not in a single night’s stage breakdown, but in the long-term patterns they reveal, helping users build healthier sleep routines.