Activity: Talk or presentation › Conference presentation
Sleep-disordered breathing (SDB) is a health problem that includes different respiratory issues, ranging from simple snoring, through prolonged partial obstruction (PPO), to obstructive sleep apnea (OSA). New materials and technologies have led to the evolution of unobtrusive sensors such as electromechanical film transducer (Emfit) mattress, to complement the polysomnography in clinical and ambulatory environments. However, the Emfit signal has inherent problems, mainly related to the sensitivity to noise and high variability. We have researched state of the art signal processing methods to infer relevant clinical information from the Emfit sensor. Signal characteristics of the Emfit signal in SDB and its most bothersome symptom, snoring, haven been studied. We have used this knowledge to design methods and machine learning techniques to detect SDB events and epochs, improving overall sensitivity in SDB diagnostics.