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Characterization of a Tooth Microphone Coupled to an Oral Appliance Device: a New System for Monitoring OSA Patients

机译:耦合到口服设备装置的牙齿麦克风的表征:一种监测OSA患者的新系统

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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.
机译:阻塞性睡眠呼吸暂停(OSA)是一种高度普遍的慢性疾病,尤其是老年人和肥胖的人口。尽管构成了严重的健康,社会和经济问题,但由于目前设备的局限性,大多数患者仍然未经记录和未经治疗。在这项工作中,我们提出了一种以非侵入性和廉价的方式诊断OSA和监测家庭治疗依从性和有效性的新方法:用口腔家电治疗(OA)相结合的声学分析和打鼾声音的声音分析。 AudioDontics推出了一个新的传感器,齿麦筒麦克风,耦合到OA器件,这是该系统的主支柱。这项工作的目的是表征该传感器的响应,将其与商业气管麦克风(BIoPac换能器)进行比较。含有OSA相关声音的信号与两个麦克风同时获取,用于此目的。在自定义MATLAB接口中,在时间,频率和时频域中进行处理和分析它们。我们开展了一个重点放在呼吸,鼾声和呼吸暂停发作的单一事件方法。我们发现,通过两个麦克风获得的信号的质量非常相似,尽管牙齿麦克风谱集中在高频带处的能量更多。这开启了关于Snores的高频分量和呼吸声的新研究领域。这些特性与其内部位置,无线选择和与可定制的OA的组合一起,使牙齿麦克风具有巨大的潜力,以减少睡眠障碍的影响,通过使患者在家中迅速检测和连续监测。

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