Nowadays, more and more people use smart watches, and sleep monitoring is one of the important features of many smart watches. Many people appreciate this function to track their sleep status. Not only healthy individuals, but also some people with diabetes may use smart watches to monitor their sleep. In modern society, people pay great attention to sleep, yet they often do not know their actual sleep quality, so they naturally turn to the sleep monitoring function of smart watches.
As a portable device, a smart watch monitors sleep mainly by detecting body movement through an accelerometer, combined with photoplethysmography (PPG) sensors to track physiological parameters such as heart rate and blood oxygen. It then uses algorithms to estimate sleep stages, typically divided into deep sleep, light sleep, and rapid eye movement (REM) sleep.
Some high-end smart watches also adopt Cardiopulmonary Coupling (CPC) analysis to improve the accuracy of sleep structure identification. CPC technology measures sleep quality by analyzing the relationship between heart rate variability and respiratory variability. By evaluating the coherence and cross-spectral power of these two signals, it generates a cardiopulmonary coupling dynamic spectrum during sleep and provides sleep staging results. CPC can offer clinical sleep staging, including deep sleep, light sleep, dreaming, wakefulness, and sleep apnea syndrome. It is clear that smart watches with CPC technology provide more detailed and refined staging, making them technically superior to conventional models.
However, according to public data, the accuracy of sleep monitoring by smart watches remains relatively low. For example, the consistency between their judgments of “deep sleep” and “REM sleep” and clinical monitoring is about 60%–70%, and some tests show a sleep staging accuracy of around 75%–85%. In other words, for the time being, people with diabetes should regard smart watch sleep monitoring only as a reference.
Sleep data can be affected by how tightly the watch is worn, body movements during sleep, and vibrations from transportation such as high-speed trains and airplanes. Although most smart watches use similar monitoring principles, differences in technology naturally lead to variations in results. Some devices also have flaws such as failing to record nighttime awakenings or delayed sleep onset detection.
Notably, not everyone needs sleep monitoring via a smart watch. It is more suitable for people with poor sleep quality, sleep disorders, or suspected sleep apnea. For the general public, especially people with diabetes, it may be unnecessary. People can usually judge their own sleep quality subjectively — for instance, whether they feel energetic after sleep, whether their sleep duration is sufficient, and whether they wake up frequently at night.
Over-focusing on smart watch sleep data may even cause anxiety among people with diabetes. As long as patients get enough sleep and feel refreshed afterward, there is no need to insist on using sleep monitoring.
When using smart watch sleep monitoring, people with diabetes should understand who truly needs this function, rather than using it just because it is available. For most people with diabetes, this feature is neither needed nor necessary.
In clinical practice, sleep quality is diagnosed and evaluated using polysomnography (PSG). PSG assesses sleep comprehensively by measuring more than a dozen overnight indicators, including electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), electrocardiogram (ECG), and respiratory movements. Therefore, polysomnography is recognized as the gold standard.
If sleep abnormalities or problems occur, people with diabetes are advised to undergo clinical polysomnography. It provides far more comprehensive evaluation indicators, which cannot be matched by the sleep monitoring function of smart watches.