At present, wearable devices' motion state baseline drift brings some interference to electrocardiogram (ECG) signal analysis. In this paper, a kind of morphological contour algorithm, which is cascaded by the opened-close operation and the closed-open operation, is used to filter the original ECG signal in two stages. Among them, the first-stage filter uses a structural element with a time width of 0.11s to remove the QRS complex and the P wave from the ECG signal, and the second-stage filter adopts a structural element with a time width of 0.25s to remove the T wave of the ECG signal, and obtains the baseline of the raw ECG signal, and then the drifting noise is eliminated after subtracting the baseline from the original ECG signal. The algorithm was verified on the MIT/BIH database and the collected ECG signals in the moving state, and the results show that the algorithm can improve the accuracy of R wave detection of MIT/BIH ECG signals by 10.21% and improve the accuracy of R wave detection of actual collected moving ECG signals by 41.67%. The morphometric contour-based algorithm proposed in this paper can effectively remove the baseline drift of moving ECG signals on wearable devices and improve the accuracy of R-wave detection.
KEYWORDS: Electrocardiography, Heart, Clocks, Data processing, Signal processing, Signal generators, Measurement devices, LabVIEW, Analog electronics, Linear filtering
At present, there are many kinds of wearable ECG devices in the market, but there are many problems such as large volume, low precision, high power consumption, and discomfort in wearing. The wearable ECG monitoring system is designed, which be small, deformable, comfortable to wear, and can continuously measure ECG signals in real-time. In this paper, STM32F411 is used as the microcontroller. Furthermore, TI's 24-bit ADS1292R is used as the acquisition module of the ECG signals. The measured ECG signals are passed through a 0.5-70Hz band-pass and 50Hz notch digital filter to remove motion noise signals. The processed ECG data are stored in a Micro-SD card. At the same time, the data are sent to the upper computer (Labview) through Bluetooth to display the ECG waveform and heart rate in real-time. The device was used to measure the ECG signals of people of different ages and genders under other exercise states. The results show that the device has the advantages of comfortable wearing and low power consumption. It can display the electrocardiogram and heart rate in real-time. The ECG data transmission delay does not exceed 0.5s, and the accuracy of heart rate measurement is 92.45%.
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