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A Real-Time QRS Complex Detector Based on Discrete Wavelet Transform and Adaptive Threshold as Standalone Application on ARM Microcontrollers

机译:基于离散小波变换的实时QRS复杂探测器和Arm微控制器上的独立应用程序的自适应阈值

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The electrocardiogram (ECG) is one of the most used tools to detect the health state of the heart. The QRS complex is an important waveform in an ECG signal and it serves as reference point for most ECG signal processing algorithms. In this paper a real-time QRS complex detector based on discrete wavelet transform (DWT) is proposed. In contrast with other algorithms, ours is able to automatically select the detail coefficients that will be used to detect the QRS complex after applying the DWT to the signal. The algorithm was compared with other published methods and evaluated with two datasets, one of them with arrhythmia and the other in healthy conditions. The results for the signals with arrhythmia were 99.30% for sensitivity, 99.61% for positive predictivity and 1.12% for error detection rate, while in the signals in healthy conditions the values were of 99.95%, 99.98% and 0.0006% respectively. Finally, the algorithm was implemented on an ARM microcontroller showing its real-time processing capability
机译:心电图(ECG)是最常用的工具,以检测心脏的健康状况之一。 QRS复合波是在ECG信号的一个重要波形,并将其作为基准点为最ECG信号处理算法。本文提出了一种实时QRS基于离散小波变换(DWT),提出了复杂的检测器。在与其他算法相反,我们能够自动地选择将被用于检测施加DWT到信号后复合物中的QRS细节系数。该算法与其他已发表的方法相比,用两个数据集,其中一人与心律失常和其他健康状况进行评估。用于与心律失常的信号的结果为灵敏度99.30 %,对阳性预测性和用于错误检测率1.12 %99.61 %,而在健康条件的信号的值分别为99.95 %,99.98 %和0.0006 % 分别。最后,在算法上显示出它的实时处理能力的ARM微控制器实现

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