Assessment of different methods to estimate electrocardiogram signal quality
Assessment of different methods to estimate electrocardiogram signal quality
复制标题
评估心电图信号质量的不同方法
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
I. Romero
中科院分区：
文献类型：
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作者：
B. A. S. D. Rio;T. Lopetegi;I. Romero
在测量过程中，心电信号会受到各种噪声、伪影和干扰的影响，从而降低了心电信号的质量。自动信号质量估计可以允许识别噪声水平何时高，以避免错误的ECG解释。为此，文献中提出了几种方法。这项工作评估了11种不同的方法估计心电图信号质量的文献。此外，提出了三种新的方法。这些方法在模拟数据库中进行了评估，该数据库包含具有不同类型和噪声水平的ECG，SNR值范围为-20至20 dB。从所有的质量估计研究，一个新的参数：峰度，给出了最好的性能整体测试。它给出了与信号SNR（0.95±0.00）的高相关性和与搏动检测器的输出的高相关性（正预测性=0.97±0.00）以及时间上的高分辨率（10秒的信号长度）。然而，峰度不具有高动态范围。有些方法需要了解ECG信号的一些信息（如R峰的位置），因此不适合高噪声的应用。
During the process of measurement, the ECG signal suffers from several noises, artifacts and interferences, which reduce its quality. Automatic signal quality estimation could permit indentify when the level of noise is high to avoid wrong ECG interpretation. With this aim, several methods have been proposed in the literature. This work assesses eleven different methods for estimation of ECG signal quality available in literature. In addition, three new methods are proposed. These methods were evaluated in a simulated database containing ECGs with different types and levels of noise with SNR values ranging from −20 to 20 dB. From all the quality estimators studied, one novel parameter: Kurtosis, gave the best performance overall the tests. It gave high correlation with the signal SNR (0.95±0.00) and high correlation with the output of a beat detector (Positive Predictivity=0.97±0.00) and high resolution in time (10 seconds of signal length). However kurtosis did not have a high dynamic range. Some methods require some knowledge about the ECG signal (like the position of the R peak) and therefore are not suitable for applications with high levels of noise.