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by Keyword: Signal to noise ratio


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Castillo, Y., Blanco, D., Whitney, J., Mersky, B., Jané, R., (2017). Characterization of a tooth microphone coupled to an oral appliance device: A new system for monitoring OSA patients Engineering in Medicine and Biology Society (EMBC) 39th Annual International Conference of the IEEE , IEEE (Seogwipo, South Korea) , 1543-1546

Obstructive sleep apnea (OSA) is a highly prevalent chronic disease, especially in elderly and obese populations. Despite constituting a serious health, social and economic problem, most patients remain undiagnosed and untreated due to limitations in current equipment. 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). Audiodontics has introduced a new sensor, a tooth microphone coupled to an OA device, which is the main pillar of this system. The objective of this work is to characterize the response of this sensor, comparing it with a commercial tracheal microphone (Biopac transducer). Signals containing OSA-related sounds were acquired simultaneously with the two microphones for that purpose. They were processed and analyzed in time, frequency and time-frequency domains, in a custom MATLAB interface. We carried out a single-event approach focused on breaths, snores and apnea episodes. 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. This opens a new field of study about high-frequency components of snores and breathing sounds. These characteristics, together with its intraoral position, wireless option and combination with customizable OAs, give the tooth microphone a great potential to reduce the impact of sleep disorders, by enabling prompt detection and continuous monitoring of patients at home.

Keywords: Microphones, Teeth, Sleep apnea, Time-frequency analysis, Signal to noise ratio, Monitoring, Acoustics