PSGAnalyzer: The Intelligent Sleep Analysis Platform Empowering Sleep Disorder Diagnosis and Treatment

作者：Wenhao Li, Yi Liu, Dongbin Lyu, Ruiyi Qian, Zhe Liu, Liujinxiang Zhu, Guan Ning Lin · 年份：2024 · DOI：10.1109/bibm62325.2024.10822659 · 研究领域：Sleep and related disorders、Sleep and Wakefulness Research、Context-Aware Activity Recognition Systems

The growing prevalence of sleep disorders and the need for efficient diagnostic tools have heightened interest in automated sleep analysis solutions. Traditional polysomnography (PSG) analysis requires intensive manual interpretation, limiting its scalability in the face of increasing diagnostic demand. PSGAnalyzer addresses this challenge by providing a comprehensive and automated platform that integrates multiple analysis modules. It includes (a) a Sleep Stage Classification module, which accurately segments sleep stages following American Academy of Sleep Medicine (AASM) standards, supported by advanced artifact-removal techniques for high-quality data; (b) a Blood Oxygen Saturation Analysis module that tracks SpO₂ levels and highlights potential hypoxic events to aid in respiratory disorder assessment; and (c) a Heart Rate Monitoring module, which analyzes heart rate variability across sleep stages to provide insights into cardiovascular health and autonomic nervous system activity during sleep. By offering a detailed, efficient, and fully automated PSG analysis, PSGAnalyzer is poised to support clinicians in diagnosing and monitoring sleep disorders more effectively, meeting the growing clinical demand for high-throughput, data-driven sleep health assessments.