Dynamic heart rate detection method

Abstract

The invention particularly relates to a dynamic heart rate detection method. The method comprises the following steps that 1, an initial electrocardio signal is acquired through an electrocardio detection device; an acceleration simulation signal which is generated due to exercise is acquired through a triaxial accelerometer, and the acceleration simulation signal is subjected to signal conversionto obtain a dynamic noise signal array; 2, the dynamic noise signal array in the initial electrocardio signal is removed, a valid electrocardio signal is acquired and processed through an R-wave detection algorithm, and the dynamic heart rate is obtained. According to the dynamic heart rate detection method, myoelectricity noise generated due to exercise and signals of contact noise generated when an electrode moves relative to the skin due to inertia during high-intensity exercise can be removed, the heart rate of the human body can still be effectively and accurately detected when the humanbody does high-intensity exercise or even strenuous exercise, and accordingly the application range of wearable dynamic electrocardio detection is remarkably enlarged.

Description

Technical field [0001] The invention specifically relates to a dynamic heart rate detection method. Background technique [0002] Wearable ECG technology is to embed the ECG collection system in the clothes people wear daily. It senses the systolic and diastolic movements of the human heart through electrodes, heart sounds, transmitting or transmissive sensors, and converts it into heart rate, so that it can be in a natural state at any time Obtaining ECG data anywhere is an effective method for real-time monitoring of human ECG. For electrode type ECG sensing, the human heart will produce the following figure 1 QRS wave shown. [0003] The R detection algorithm is the most convenient way to obtain the heart rate, but the heart rate detection is often affected by interference and errors occur. The commonly used algorithms for R wave detection include amplitude method and slope method, etc. These algorithms are based on the characteristics of the R wave in the ECG signal that the ...

AI Technical Summary

Problems solved by technology

However, since the human body is in a state of motion, especially during high-intensity exercise, the electrocardiographic signals such as human body electromyography or sensors moving relative to the skin due to inertia will be greatly disturbed, and the amplitude method and slope method are difficult to correctly process and evaluate

At present, there are many heart rate detection devices at home and abroad that are mainly aimed at static or aerobic exercise physiological signals, and are not suitable for dynamic ECG detection, especially heart rate detection for strenuous exercise.

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