Study Objectives: Machine learning (ML) models have been employed in the setting of sleep
disorders. This review aims to summarize the existing data about the role of ML techniques …

Carbon dioxide (CO 2) monitoring in human subjects is of crucial importance in medical
practice. Transcutaneous monitors based on the Stow-Severinghaus electrode make a good …

In this work, a detection and classification method for sleep apnea and hypopnea, using
photopletysmography (PPG) and peripheral oxygen saturation (SpO 2) signals, is proposed …

Objective: This paper presents a methodology to automatically screen for sleep apnea
based on the detection of apnea and hypopnea events in the blood oxygen saturation (SpO …

Obstructive Sleep Apnea (OSA) is characterized by repetitive episodes of airflow reduction
(hypopnea) or cessation (apnea), which, as a prevalent sleep disorder, can cause people to …

Study objectives To investigate inter-scorer agreement and scoring time differences
associated with visual and computer-assisted analysis of polysomnographic (PSG) …

Automatic diagnosis of the Sleep Apnea‐Hypopnea Syndrome (SAHS) has become an
important area of research due to the growing interest in the field of sleep medicine and the …

Abstract Pediatric Sleep Apnea–Hypopnea (SAH) presents a significant health challenge,
particularly in diagnostic contexts, where conventional Polysomnography (PSG) testing …

Sleep Apnea Hypopnea Syndrome (SAHS) is a sleep disorder where patients experience
multiple airflow cessations or reductions during the night. It is recognized as a common …

Highlights•A comparative study over respiratory pattern classification in the field of
SAHS.•Several missing data imputation techniques and machine learning algorithms were …