压力传感器与音频测量融合用于呼吸评估的可行性分析

Madison Cohen-McFarlane, Bruce Wallace, P. Xi, R. Goubran, F. Knoefel
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引用次数: 3

摘要

由于传感器和传感器测量系统的快速发展,远程健康监测是一个新兴的领域。呼吸系统可能受到各种潜在疾病的影响,呼吸事件监测可以为医疗专业人员提供否则无法获得的信息。一个值得关注的关键领域是夜间的呼吸,其变化可能表明呼吸和睡眠相关疾病。以前的工作已经提出使用压力敏感垫(PSM)或音频测量来独立检测这些变化。然而,无论是PSM测量还是音频测量都不能捕获所有呼吸事件,并且存在与连续监视相关的隐私问题(特别是在录制音频时)。本文提出了一种同时利用PSM和音频测量的系统的可行性。在这里,一个单独的参与者被要求躺在PSM上,并在麦克风录音的同时执行一系列呼吸事件(正常呼吸,快速呼吸,缓慢呼吸,喘气,模仿中枢睡眠呼吸暂停,喘息,打鼾和咳嗽)。信号处理应用于两种测量,以调查呼吸频率和不常见的呼吸事件。然后比较得到的信号。讨论了两种测量方法的优点和缺点,并提出了音频和PSM测量融合的示例场景,以捕获阻塞性睡眠呼吸暂停事件。
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Feasibility analysis of the fusion of pressure sensors and audio measurements for respiratory evaluations
The field of remote health monitoring is a growing field, which is being driven by the rapid advances in sensors and sensor measurement systems. The respiratory system can be affected by a variety of underlying conditions and respiratory event monitoring can provide medical professionals with information that would otherwise be unavailable. A key area of concern is respiration over the course of a night, changes in which can be indicative of breathing and sleep related disorders. Previous work has proposed the use of pressure sensitive mats (PSM) or audio measurement to independently detect these changes. However, neither the PSM measurement nor the audio measurement is able to capture all respiratory events and there are privacy concerns associated with continuous monitoring (especially when recording audio). This paper presents the feasibility of a system that would utilize both PSM and audio measurements. Here, a single participant was asked to lay down on a PSM and to perform a series of respiratory events (normal breathing, fast breathing, slow breathing, gasping, mimicking central sleep apnea, wheezing, snoring, and coughing) while a microphone was recording. Signal processing was applied to both measurements in order to investigate both breathing rate and uncommon respiratory events. The resulting signals were then compared. The advantages and disadvantages of both measurements are discussed and a sample scenario of the fusion of audio and PSM measurements is presented in order to capture obstructive sleep apnea events.
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