一种面向心电信号处理的奇异谱分析改进算法

心电图(ECG)作为人体的关键生理信号被广泛应用于医疗领域，但在采集过程中心电信号容易受到噪声干扰而影响 信号质量。为此，设计了一种奇异谱分析(SSA)的改进算法用于心电信号降噪处理。奇异谱分析改建算法是在 SSA中的主 元重组(grouping)阶段引入逻辑回归(LR) 算法，将主元重组方式改进为自动重组，实现面向心电信号的 SSA 自监督降噪处 理。使用基于 AD620 的心电信号采集装置，构建53条心电信号测试集进行验证，使用奇异谱分析的改进算法，主元自动选择 的准确性为98.68%,重构的心电信号信噪比(SNR)由10.43 dB平均提高到20.17 dB,能够有效提取出清晰的PQRST 波，使 其在医疗领域心电信号检测与降噪方面具有很好的实用化前景。

Improved algorithm for singular spectrum analysis in ECG signals processing

As a key physiological signal,electrocardiogram(ECG)is widely used in the medical field.However,the ECG signal is easily interfered by noise during the collection process,which affects the signal quality.An improved algorithm of singular spectrum analysis(SSA)is designed for ECG signal noise reduction.The logistic regression(LR)algorithm is introduced in the principle component grouping stage of SSA,and the principle component method is improved to automatic grouping to realize SSA self-supervised noise reduction processing for ECG signals.Using an ECG signal acquisition device based on AD620,of 53 ECG signals was constructed as a testing set for verification.Using the improved algorithm of singular spectrum analysis,the accuracy of automatic selection of principal elements was 98.68%. The signal-to-noise ratio(SNR)of the reconstructed ECG signal increased from 10.43 dB to 20.17 dB on average.It can extract clear PQRST waves effectively,and has good practical prospects in ECG signal detection and noise reduction in the medical field.