Research On Anti-motion Disturbance Technology For Wearable Heart Rate Monitor

With the rapid development of social material civilization and increased population aging,wearable physiological monitoring equipment has become a research hotspot for electronic intelligence.But the removal of motion noise interference is one of the key contents and difficulties in the research and development if wearable physiological devices.Heart rate is very important for people.A set of equipment which can measure heart rate in real time,portable,and accurately has important value for the health monitoring of the elderly and patients.However,at present,there are limitations in the devices on the market,such as 5poor wearing comfort,inconvenience in use,and low measurement accuracy in motion.In order to solve the above problems,this paper designed and developed a system for wearable heart rate monitoring equipment.The system combines the hardware?heart rate extraction algorithm and motion noise removal algorithm to improve the resistance of the device to motion noise,so as to achieve accurate heart rate monitoring anywhere and anytime.The in-depth study of the sampling rate reduction caused by the simultaneous acquisition of motion signals and pulse wave signals was conducted.In terms of hardware,the hardware design of the wearable heart rate monitoring system adopts the M2 medical chip as the main controller and integrates the BMA250 triaxial acceleration sensor and the CC2504 bluetooth circuit,and the pulse wave signal and the motion reference signal can be collected synchronously and sent to the mobile terminal to process in real time.Aiming at the inaccuracy of the measurement of the special heart rate or the presence of noise in the traditional heart rate algorithm,an in-depth study has been conducted.In terms of hearts rate extraction algorithm,the pulse wave is processed using time domain extraction of heart rate and frequency domain verification.A fast Fourier transform is taken in the frequency domain to extract the verification heart rate.In the motion noise removal algorithm,the motion state decision tree method is introduced to reduce the sampling rate of the device after adding the motion reference signal.By determining the current motion as a slight motion and a strong motion,motionless reference signals are used respectively.Wavelet threshold denoising method and improved variable step size LMS adaptive filtering algorithm.Through the matlab algorithm simulation and the actual verification of the prototype,the anti-motion interference algorithm developed in this paper effectively reduces the impact of noise,so that the signal to noise ratio of the signal is generally improved by about 3dB.Compared with the general LMS algorithm,the calculation speed is faster and after processing.The signal delay is reduced by about 0.2s.The heart rate extraction algorithm used by the system,compared with the traditional time domain algorithm,in the case of poor signal quality,the accuracy deviation does not exceed 3 times/minute,compared to the frequency domain extraction algorithm,the measurement accuracy is 1 time/minute,the switchboard is Compared with similar products in the market,it has the advantages of small size,good portability,high accuracy,and the ability to measure in a variety of situations in everyday life.