Effect of particulate matter on continuous positive airway pressure adherence in obstructive sleep apnea patients.

Background: Sleep quality could be affected by air pollution, especially for particulate matter with a diameter of less than 10 microns (PM) and particulate matter with a diameter of less than 2.5 microns (PM). However, no direct study demonstrates the relationship and impact of air pollution especially PM and PM on continuous positive airway pressure (CPAP) adherence.

Factors influencing continuous positive airway pressure adherence in elderly with obstructive sleep apnea.

Background: Continuous positive airway pressure (CPAP) is the most effective treatment for symptomatic obstructive sleep apnea (OSA). The identification of actual predictors of CPAP adherence in real-world practice is essential since it enhances more individualized management for the patient. CPAP acceptance and adherence in elderly patients with OSA have the same challenges but the conclusion remains unclear.

Automatic Driver Drowsiness Detection Using Artificial Neural Network Based on Visual Facial Descriptors: Pilot Study.

Purpose: Driving while drowsy is a major cause of traffic accidents globally. Recent technologies for detection and alarm within automobiles for this condition are limited by their reliability, practicality, cost, and lack of clinical validation. In this study, we developed an early drowsiness detection algorithm and device based on the "gold standard brain biophysiological signal" and facial expression digital data.