Self-adaption electrocardiograph (ECG) detection method and monitoring system thereof

Abstract

The invention discloses a self-adaption electrocardiograph (ECG) detection method and a monitoring system thereof. The detection method comprises the following steps: performing band-pass filtering, absolute value operation and low-pass filtering on an output ECG signal of an acquisition module; and detecting the R wave of the signal subjected to low-pass filtering by setting a threshold value. The monitoring system comprises an ECG acquisition module, intelligent equipment and a remote terminal, wherein the ECG acquisition module comprises an ECG pre-amplification circuit, a 50-Hz wave trap, a secondary amplification circuit, an anti-aliasing filter circuit, an analog / digital (A / D) conversion circuit, a microcontroller and a Bluetooth module; the microcontroller is connected with the intelligent equipment through the Bluetooth module; and the intelligent equipment loads the self-adaption ECG detection method and is connected with the remote terminal through a network. The method is simple and quick and suitable for a low-end microprocessor. When the method is used in combination with the monitoring system, a portable ECG monitoring system can be implemented and has the characteristics of multiple functions, low power consumption, low cost, small volume and the like.

Description

technical field [0001] The invention relates to medical device monitoring equipment, and more specifically, to an adaptive electrocardiogram detection method and a monitoring system thereof. Background technique [0002] Heart disease has always been the number one killer threatening human life, and it is one of the diseases with the highest morbidity and mortality. With the improvement of living standards and health awareness, people hope to monitor the health of the heart at any time and to carry out timely diagnosis and treatment in critical situations. Therefore, the development of a portable wireless ECG monitoring system is of great significance. mHealth is a useful and potentially powerful tool in improving the quality of health care. [0003] At present, many methods popular at home and abroad all have advantages and disadvantages in different degrees to the methods of ECG signal processing. QRS detection based on wavelet transform, neural network method, adaptive...

AI Technical Summary

Problems solved by technology

However, they have not been well popularized. The reason is that there are the following problems:

[0005] 1. The provided ECG processing function and the recorded ECG information are limited, and it is difficult for doctors to obtain comprehensive ECG information, which reduces the doctor's correct rate of disease diagnosis

[0006] 2. Generally, a digital signal processor is used as the core device for ECG data analysis, while data communication, liquid crystal display, real-time clock, program memory, etc. all need to expand special functional devices, so the structure is more complex and the volume is relatively large. At the same time, the power consumption is relatively large, and the price is relatively expensive, which is unbearable for ordinary patients

[0007] 3. The supporting monitoring network and ECG data processing center are not yet perfect, and cannot catch up with the pace of the new era of the Internet of Things

[0008] 4. For this reason, doctors need to analyze and judge the ECG waveform, and it is difficult for the electrocardiograph to enter the ordinary hundred

There are flaws in the current ECG analysis method, and the phenomenon of misjudgment of heart rate exists.

Images