Detection of Sleep Stages and Arousals Using Neural Network Classifiers

Embedded software featuring neural-network classifiers designed to detect and classify sleep stages (N1/N2, N3, REM, Wake), autonomic arousals, and an Arousal Index based on data (specifically instantaneous pulse rate and full-resolution flow waveforms) collected during PAP therapy.

Polysomnography (PSG) is an overnight, in-laboratory diagnostic procedure that records multiple physiological parameters during sleep. It typically includes monitoring of brain activity (EEG), eye movements (EOG), muscle activity (EMG), heart rhythm (ECG), respiratory effort, airflow, oxygen saturation, and body position. PSG is used to evaluate sleep architecture, identify sleep stages, detect arousals, and diagnose sleep disorders such as sleep apnea. The collected data are analyzed manually by trained sleep technologists following standardized scoring criteria.

EnsoSleep is software-only medical device intended for use by physicians to assess sleep quality and aid in the diagnosis of sleep disorders. The software analyzes physiological signals and automatically scores sleep study results, including respiratory, sleep staging, arousal and movement events. Automatically scored events and physiological signals are analyzed, displayed, and summarized for review by clinicians.