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基于气管呼吸音的声门呼吸时相检测

Acoustic breath-phase detection using tracheal breath sounds.

机构信息

Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

出版信息

Med Biol Eng Comput. 2012 Mar;50(3):297-308. doi: 10.1007/s11517-012-0869-9. Epub 2012 Feb 24.

Abstract

Current breathing flow estimation methods use tracheal breath sounds, but one step of the process, 'breath phase (inspiration/expiration) detection', is done by either assuming alternating breath phases or using a second acoustic channel of lung sounds. The alternating assumption is unreliable for long recordings, non-breathing events, such as apnea, swallow or cough change the alternating nature of the phases. Using lung sounds intensity requires the addition of a secondary channel and the associated labor. Hence, an automatic and accurate method for breath-phase detection using only tracheal sounds would be of great benefit. We present a method using several breath sound parameters to differentiate between the two respiratory phases. The proposed method is novel and independent of flow level; it requires only one prior- and one post-breath sound segment to identify the phase. The proposed method was tested on data from 93 healthy individuals, without any history of pulmonary diseases breathing at 4 different flow levels. The most prominent features were from the duration, volume and shape of the sound envelope. This method has shown an accuracy of 95.6% with 95.5% sensitivity and 95.6% specificity for breath-phase identification without assuming breath-phase-alteration and/or using any other information.

摘要

目前的呼吸流量估计方法使用气管呼吸音,但该过程的一个步骤,“呼吸相(吸气/呼气)检测”,要么通过假设呼吸相交替,要么使用肺音的第二个声学通道来完成。对于长时间的记录、非呼吸事件(如呼吸暂停、吞咽或咳嗽),交替假设是不可靠的,这些事件会改变呼吸相的交替性质。使用肺音强度需要增加一个辅助通道和相关的劳动力。因此,仅使用气管声音自动准确地检测呼吸相的方法将非常有益。我们提出了一种使用多个呼吸声音参数来区分两种呼吸相的方法。所提出的方法是新颖的,并且不依赖于流量水平;它只需要一个前置和一个后置呼吸声音片段来识别相。该方法在来自 93 名无肺部疾病的健康个体的呼吸在 4 种不同流量水平下的数据上进行了测试。最显著的特征来自声音包络的持续时间、体积和形状。该方法在不假设呼吸相改变和/或使用任何其他信息的情况下,对呼吸相识别的准确率为 95.6%,灵敏度为 95.5%,特异性为 95.6%。

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