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Comparison of six envelope extraction methods based on abnormal heart sounds

机译:六种基于异常心音的包络提取方法的比较

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How to extract envelopes accurately is the most important problem in analyzing heart sound signals, especially for abnormal heart sound signals. An effective envelope extraction is a key to the detection of S1 and S1 periods and noise separation, moreover, for estimating the type of heart disease. This paper compares six efficient envelope extraction methods based on abnormal heart sounds, with comparisons after the envelope endpoints auto-detection and the error analysis. The result indicates that the envelope extracted with Wavelet-Hilbert-Huang transform method is the most accurate one with 97% of endpoints detection rate and 16.15 ms error margin, which can provide accurate identification for S1 and S1 durations.
机译:如何准确地提取包络是分析心音信号,尤其是异常心音信号时最重要的问题。有效的包络提取是检测S 1 和S 1 周期以及进行噪声分离以评估心脏病类型的关键。本文比较了基于异常心音的六种有效包络提取方法,并在包络端点自动检测和错误分析之后进行了比较。结果表明,采用小波-希尔伯特-黄变换提取的包络是最准确的包络,端点检测率达97%,误差裕度为16.15 ms,可以准确识别S 1 和S 1 持续时间。

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