Application of Improved Differential Algorithm in Wearable Device ECG Monitoring

ECG can accurately reflect the activity process of the human heart. Through ECG monitoring, users can detect various types of cardiac diseases as early as possible and take effective countermeasures in time. However, problems such as noise interference and algorithm defects seriously affect the accuracy of ECG detection. In this paper, aiming at eliminating the interference signal superimposed in the ECG signal, an improved filter is designed by combining the second-order shaped IIR low-pass filter and the second-order high-pass Butterworth filter, and a better filtering effect of the interference signal is achieved. Then, in view of the problem that the traditional differential threshold algorithm cannot cope with the fluctuation of ECG data and causes false detection of QRS complexes, this paper proposes an improved differential threshold algorithm that combines differential threshold adaptation and RR interval threshold self-correction. The accuracy and anti-interference ability of QRS complex detection are effectively improved. Finally, a wearable ECG monitoring device with STM32 as the core processor is designed, and the improved filter and improved differential algorithm are applied to the ECG monitoring device. After testing, the equipment runs stably in practical applications, meanwhile the improved filter and improved differential algorithm have good application effects, and all performance of the equipment meet the requirements of the index.