Core Algorithmic Technology

Our proprietary sleep core algorithm, developed in-house, employs cutting-edge machine learning and sound recognition technologies to conduct a thorough analysis of users' sleep patterns and quality. Using high-precision audio monitoring, the system records audio data in real-time during the user's sleep. Subsequently, through sophisticated audio processing techniques involving segmentation and analysis of recordings, it identifies key sleep events such as snoring, awakenings, sleep talking, environmental noises, and instances of sleep apnea.

By integrating time-series analysis and biostatistical data, our algorithm accurately delineates the duration and frequency of sleep cycles, deep sleep stages, and REM phases. This enables us to offer scientifically precise assessments of sleep quality and personalized improvement plans. This highly integrated technological approach provides users with unprecedented insights into their sleep, driving advancements in sleep health management.