Research And Development Of A Portable Monitor For ECG Detection

Since the emergence of the Electrocardiogram(ECG) technology in 19 th century, it becomes an integral part of a reliable basis in the diagnosis and treatment of heart disease. ECG is a pseudo-periodic signal and it has a mutation characteristics. In general, we can only found 80 percent of unusual problems in an acquisition time of 5 minutes, but the dynamic electrocardiograph which is in a 24 hour monitoring status can found 95% of the unusual problems, therefore, it becomes the irreplaceable equipment in the diagnosis of heart system. In the process of ecg signal acquisition, there exist a lot of interference, and motion artifact is the one which is the most difficult to filter but is very common, it always brings some obstacle to doctor in the observation and diagnosis.For this situation, this study designs an ecg monitoring system in the principle of low power consumption, small size and portable, and through a lot of research, we propose a method to filter the motion artifact, which is based on the independent component analysis.In order to filter the motion artifact, this paper is based on the independent component analysis algorithm and the adaptive filtering algorithm. Because the ecg signal is a pseudo periodicity signal, every two complete ecg signal has a great similarity, we can easily get his frequency through the autocorrelation function, then a priori information about the source signal is get. Send this information to the objective function of the constrained independent component analysis algorithm, a reference signal will occur. In the process of calculation, the reference signal corresponding to the target will have a biggest non-Gaussian for source signals, making the target source signal be separated firstly. We can input the output of the ICA algorithm to the adaptive filtering algorithm as the desired signal, after a period of convergence, we can get a relatively pure ecg signal. Finally, through the comparison of some commonly used algorithms, the proposed algorithms of this paper can improve the SNR to some extent, and a satisfactory results can be achieved.In the paper, we list the hardware design requirement for ecg collection after the analysis of the characteristics of ecg. After the selection of chip, we use the ADS1298 R as the analog front-end for ecg acquisition, MSP430 microcomputer as the central control unit of the whole system, and designed a model of 12 lead ecg monitoring equipment. ADS1298 R has a very high level of integration, covers the differential input channels, programmable gain amplifier, 24 bit S-D ADC, and is equipped with a digital SPI interface, meet our demand for ecg signal acquisition. MSP430F6659 microcontroller is an ultra-low power MCU, which has a very high clock frequency, the USB module integrated and a lot of IO port, is suitable for this system. In order to complete the equipment for ecg acquisition, we have to add some peripheral circuit, and download the control code to the MCU, then the ecg signal can be collected.