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

机译:耦合到口腔器械设备的牙麦克风的特征:监测OSA患者的新系统

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摘要

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)是一种高度流行的慢性疾病,尤其是在老年人和肥胖人群中。尽管构成严重的健康,社会和经济问题,但由于当前设备的限制,大多数患者仍未得到诊断和治疗。在这项工作中,我们提出了一种新颖的方法来诊断OSA并以一种非侵入性的廉价方式在家中监测治疗的依从性和有效性:将呼吸声和打nor声的声学分析与口腔矫治器疗法(OA)结合起来。 Audiodontics已经推出了一种新的传感器,即与OA设备耦合的牙齿麦克风,这是该系统的主要支柱。这项工作的目的是表征该传感器的响应,并将其与商用气管麦克风(Biopac换能器)进行比较。为此,与两个麦克风同时获取了包含OSA相关声音的信号。在自定义的MATLAB界面中,在时域,频域和时频域中对它们进行了处理和分析。我们执行了针对呼吸,打sn和呼吸暂停发作的单事件方法。我们发现,尽管齿式麦克风的频谱将更多的能量集中在高频频段,但两个麦克风所获得的信号质量非常相似。这为打sn和呼吸音的高频成分开辟了新的研究领域。这些特征以及其口腔内位置,无线选项以及可定制的OA组合在一起,使麦克风能够通过在家中对患者进行快速检测和连续监测,具有极大的潜力来减少睡眠障碍的影响。

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