สำนักงานเทศบาลตำบลนครชุม l ยึดมั่นธรรมาภิบาล บริการเพื่อประชาชน

How Sleep Rings Detect Light, Deep, And REM Sleep

โดย : Janice เมื่อวันที่ : พฤหัสบดี ที่ 4 เดือน ธันวาคม พ.ศ.2568

Modern sleep tracking rings utilize a combination of biometric sensors and predictive models to distinguish between the three primary sleep stages—deep, REM, and light—by recording consistent biomarker fluctuations that shift systematically throughout your sleep cycles. In contrast to hospital-based EEG methods, which require multiple wired sensors and professional supervision, these rings rely on comfortable, unobtrusive hardware to collect real-time biomarkers while you sleep—enabling accurate, at-home sleep analysis without disrupting your natural rhythm. The primary detection method in these devices is photoplethysmography (PPG), which applies infrared and green light diodes to measure changes in blood volume beneath the skin. As your body transitions between sleep stages, your circulatory patterns shift in recognizable ways: during deep sleep, your pulse slows and stabilizes, while REM <a href="https://jklyc.com/">sleep ring</a> resembles wakefulness in heart rate variability. The ring detects subtle temporal patterns to predict your sleep stage with confidence. Alongside PPG, a high-sensitivity gyroscope tracks body movement and position shifts throughout the night. In deep sleep, physical stillness is nearly absolute, whereas light sleep involves frequent repositioning. During REM, subtle jerks and spasms occur, even though your major muscle groups are temporarily paralyzed. By fusing movement data with heart rate variability, and sometimes adding thermal sensing, the ring’s adaptive AI model makes statistically grounded predictions of your sleep phase. The underlying methodology is grounded in decades of peer-reviewed sleep science that have defined objective indicators for light, deep, and REM phases. Researchers have calibrated wearable outputs to gold-standard sleep metrics, enabling manufacturers to train deep learning models that learn individual sleep profiles across populations. These models are refined through massive global datasets, leading to gradual improvements in accuracy. While sleep rings cannot match the clinical fidelity of polysomnography, they provide reliable trend data over weeks and months. Users can understand the impact of daily choices on their cycles—such as how alcohol reduces deep sleep—and make informed behavioral changes. The real value proposition lies not in the exact percentages reported each night, but in the long-term patterns they reveal, helping users cultivate sustainable rest habits. 

เข้าชม : 1