A portable watch using Kalman method for heart rate monitoring during movement

this paper designed a wrist watch for heart rate monitoring while the subject is in movement. Since the body motion artifact easily affects the arm portion, to eliminate the movement noise, kalman filter was used to get the optimal estimation of pulse rate. Our method uses accelerometer built in the watch to improve the accuracy of heart rate estimation. We evaluated the performance of the proposed system against a standard holter device for ECG measurement. Experimental results were running came closer to the holter ECG in high accuracy(r=0.97, SD=7.1). We, therefore, report the heart rate estimation method which has a higher degree of usability. Besides, since the energy consumed by heart rate monitoring accounts for a larger proportion for the watch, to save power, the autocorrelation algorithm was used to estimate the quality of PPG signal. So that, when the heart rate could not be monitored for the reasons that the watch is not worn or not worn properly, the watch could initiatively identify these states and close the PPG related modules to save power. The result of the experiments showed that our method has a high accuracy in wearing state recognition.