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首页> 外文会议>2014 Zone 1 Conference of the American Society for Engineering Education >Automatic detection and classification of acoustic breathing cycles
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Automatic detection and classification of acoustic breathing cycles

机译：声音呼吸周期的自动检测和分类

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This paper focuses on respiratory phase detection and classification without the help of the airflow measurements. Instead of using the airflow measurements to identify breathing phases, the proposed work depends on advanced digital signal processing techniques to process the acoustic signal of respiration that was collected using a microphone placed in front of the subject's nose. The recorded signal is processed using the voiced-unvoiced algorithm to differentiate between the voiced period and the unvoiced (silence) period. The desired features are extracted from each voiced phase. Finally, support vector machine is used to distinguish between the inspiration and the expiration phases according to the extracted features. The signals were recorded from a number of subjects who do not have a history of pulmonary diseases. The proposed method has achieved an accuracy of 95% when tested on the subjects.
机译：本文重点介绍呼吸相位检测和分类，无需借助气流测量。拟议的工作不是使用气流测量值来识别呼吸阶段，而是依靠先进的数字信号处理技术来处理呼吸声，该呼吸声是使用放置在受试者鼻子前的麦克风采集的。使用浊音算法处理记录的信号，以区分浊音周期和浊音（静音）周期。从每个浊音阶段中提取所需的特征。最后，使用支持向量机根据提取的特征来区分吸气阶段和呼气阶段。信号是从许多没有肺部疾病史的受试者中记录下来的。当对受试者进行测试时，所提出的方法已达到95％的准确性。

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