This opens a new field of study about high-frequency components of snores and breathing sounds. We found that the quality of the signals obtained by both microphones was quite similar, although the tooth microphone spectrum concentrated more energy at the high-frequency band. We carried out a single-event approach focused on breaths, snores and apnea episodes. They were processed and analyzed in time, frequency and time-frequency domains, in a custom MATLAB interface. Signals containing OSA-related sounds were acquired simultaneously with the two microphones for that purpose. The objective of this work is to characterize the response of this sensor, comparing it with a commercial tracheal microphone (Biopac transducer). Audiodontics has introduced a new sensor, a tooth microphone coupled to an OA device, which is the main pillar of this system. In this work, we propose a novel method to diagnose OSA and monitor therapy adherence and effectiveness at home in a non-invasive and inexpensive way: combining acoustic analysis of breathing and snoring sounds with oral appliance therapy (OA). Despite constituting a serious health, social and economic problem, most patients remain undiagnosed and untreated due to limitations in current equipment. Obstructive sleep apnea (OSA) is a highly prevalent chronic disease, especially in elderly and obese populations.
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