An experimental study on estimating sleep period time using accelerometer and electrodermal activity in ring-shaped wearable devices.

There has been growing interest in sleep tracking technologies utilizing ring-shaped wearable devices. This study aimed to develop a method for accurately estimating sleep duration, onset, and offset using such a device. Conventional wrist-worn accelerometer-based devices often show limited accuracy, particularly during periods of low movement. Likewise, algorithms relying solely on electrodermal activity (EDA) signals struggle to detect frequent wake episodes due to their low temporal resolution. To address these limitations, we developed a ring-shaped wearable device and a set of algorithms that integrate both accelerometer and EDA signals. The performance of the proposed algorithms was evaluated through a clinical study involving 25 participants, the majority of whom had sleep disorders. Results showed that combining these complementary signals enabled accurate detection of sleep onset and offset within 10 min and maintained high accuracy even in conditions such as minimal movement or frequent wake episodes. These findings suggest that multimodal sensing may offer a promising direction for enhancing the reliability of sleep monitoring in real-world settings.