基于香农能量与自适应阈值的心电QRS复合波检测算法

针对现有心电QRS复合波检测算法对于一些信号异常的情况检测效果仍然不理想的问题，提出了一种基于香农能量与自适应阈值相结合的心电QRS复合波检测算法，以解决QRS复合波检测的低准确率问题。首先，从预处理后的信号提取香农能量包络；然后，结合改进的自适应阈值方法对QRS复合波进行检测；最后，根据QRS复合波增强后的信号定位所检测的QRS复合波的位置。使用MIT-BIH心律失常数据库的数据对所提算法进行性能评估，结果表明，所提算法即使在信号中存在高大的P波、T波、不规则心律以及严重的噪声干扰时依然能准确检测QRS复合波的位置，总体数据检测的敏感性、阳性检测度和准确率分别达到了99.88%、99.85%和99.73%，且该算法能够在保证准确率的情况下快速地完成QRS复合波的检测任务。

QRS complex detection algorithm of electrocardiograph based on Shannon energy and adaptive threshold

In view of the problem that the existing QRS complex detection algorithms of electrocardiograph are still not ideal for the detection of some signal abnormalities, a QRS complex detection method combining Shannon energy with adaptive threshold was proposed to solve the problem of low accuracy of QRS complex detection. Firstly, the Shannon energy envelope was extracted from the pre-processed signal. Then, the QRS complex was detected by the improved adaptive threshold method. Finally, the location of the detected QRS complex was located according to the enhanced signal of the detected QRS complex. The MIT-BIH arrhythmia database was employed to evaluate the performance of the proposed algorithm. Results show that the algorithm can accurately detect the location of the QRS complex even when high P wave, T wave, irregular rhythm and serious noise interference exist in the signal, and has the sensitivity, positive and accuracy of the overall data detection reached 99.88%, 99.85% and 99.73% respectively, meanwhile the proposed algorithm can quickly complete the QRS complex detection task with the accuracy guaranteed.