基于香农信息熵的心电R波检测算法

经过多年的研究与发展,各种各样的心电检测算法层出不穷且各有千秋。随着便携式检测设备的兴起,心电检测算法的实时性与准确性的结合显得尤为重要。为此我们提出一种新的基于信息熵的心电检测算法。本文中我们将阐述该算法通过信息熵有效地提取出心电信息,实现高效简单稳定的波形检测逻辑并结合动态阈值调整该逻辑判断,提高心电信号的判断准确率。利用MIT-BIH数据库对我们提出的算法进行测试验证,并与数种已有算法进行比对,体现该算法不仅满足实时的要求还具有较好的检测准确率。

With the emergence ofportable inspection equipment, the combination of real-time performance and precision is particularly important to the ECG detection algorithm.Therefore we propose a new ECG detection algorithm based on Shannon entropy.In this paper, we describe the Shannon entropy which can effectively extract the ECG information and improve the accuracy of ECG detection.Using the characteristic of Shannon entropy, we achieve an efficient and stable waveform detection algorithm and update the threshold in real-time.The performance of the algorithm is evaluated on standard ECG records from MIT-BIH database.The proposed algorithm has been contrasted with several algorithms, and the contrastive result shows that the proposed algorithm not only can meet the requirements of real-time, but also has a high detection accuracy.