Research On Anti-motion Artifact Heart Rate Estimation Algorithm Based On Photoplethysmography Signal

Heart rate is one of the most common physiological parameters that reflect physical health.Many professional sports medicine and fitness medical institutions in the world recommend that you use a heart rate monitoring instrument during exercise to quickly and clearly reflect the body's information,and to provide real-time feedback on the changes in heart,so as to avoid entering the dangerous anaerobic exercise area and cause physical injury or even sudden exercise-related death.Therefore,many heart rate monitoring devices have emerged,of which smart bracelets based on Photoplethysmography(PPG)are the most common,unlike Electrocardiogram(ECG),PPG signal measurement devices do not need to be close to the skin,which reduces the discomfort of the wearer,but it makes the PPG signal susceptible to motion artifacts(MA)caused by human movement,resulting in poor PPG signal quality and difficulty in extracting physiological information,which is currently the biggest challenge in using PPG signals for physiological parameter monitoring.In response to the above problems,this paper proposes an anti-motion artifact interference algorithm based on corrected acceleration(abbreviated as CA-Log NLMS),which effectively solves the contradiction between the accuracy of heart rate estimation and the time complexity of the algorithm.The main work of this paper is as follows:(1)The components of motion artifacts are analyzed and the main sources of motion artifacts are identified.Based on the characteristics of motion artifacts,a PPG signal acquisition device is designed,and developed on the STM32F103 development board using the Keil5.0 development tool to implement the simultaneous acquisition of PPG signals,tri-axial acceleration signals,tri-axial angular velocity signals,and ECG signals,and to transmit the acquired signals to the host computer via Bluetooth.(2)In order to improve the performance of wearable devices,meet application requirements,ensure the real-time performance of the heart rate monitoring system,reduce the time complexity of the motion artifact removal algorithm,and increase the algorithm calculation speed,based on the good filtering performance and simplicity of adaptive filtering,a logarithmic-based Function normalized least mean square error algorithm(Log-normalized Least Mean Square,Log-NLMS).The experimental results show that the algorithm in this paper reduces the average computing time to 0.07 s compared with other motion artifact removal algorithms.(3)Aiming at the problem of low heart rate estimation accuracy of Log-NLMS algorithm,by analyzing the characteristics of three-axis acceleration,a Log-NLMS algorithm based on corrected acceleration is proposed.The attitude angle is obtained by integrating the angular velocity of the three axes,the integration error is eliminated by Kalman filtering,and the acceleration of the three axes in the inertial reference system is finally corrected to the external acceleration in the sensor reference system,and the corrected acceleration is used as the reference signal for Log-NLMS.The experiments show that in walking state,the heart rate estimation error of this algorithm and other heart rate estimation algorithms remains below 1BPM;in running and low speed riding state,compared with other heart rate estimation algorithms,the heart rate estimation error of this algorithm is reduced by 1?2BPM;In the state of high-speed riding,the heart rate estimation error of other heart rate estimation algorithms exceeds 4BPM,while the heart rate estimation error of this algorithm remains below 4BPM.This shows that the heart rate estimation accuracy of this algorithm is better than other motion artifact removal algorithms.(4)Aiming at actual application requirements,this article designs a heart rate monitoring system based on the Android Studio development tool.Key features include user registration and login;data collection and storage,use local data management module to implement CA-Log NLMS algorithm;real-time display of filtered PPG signal,historical data display,and heart rate monitoring.The Log-NLMS algorithm based on corrected acceleration was tested and proven to be feasible for wearable devices.The accuracy of the estimation can be maintained below 4BPM and the calculation time is fast,which meets the requirements of the application.