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Reliability Estimation of Heart Rate Measurement Using Wrist-Worn Devices | IEEE Conference Publication | IEEE Xplore

Reliability Estimation of Heart Rate Measurement Using Wrist-Worn Devices


Abstract:

Heart Rate (HR) measurement using wrist-worn devices suffers from noises owing to body movement. Even though many researchers have proposed sophisticated methods for the ...Show More

Abstract:

Heart Rate (HR) measurement using wrist-worn devices suffers from noises owing to body movement. Even though many researchers have proposed sophisticated methods for the compensation of noisy measurement, such factors cause corruption of sensor data itself, leading to difficulty in compensation. In this paper, we design a method for the reliability estimation of HR measurement. The key idea is that the change of HR correlates with the magnitude of body movement and current HR. For modeling the correlation, we construct a modified Kalman filter that estimates the displacement of HR from the statistical data of HR measured by a chest-worn device and the variance of acceleration measured by a wrist-worn device. Then, we define the reliability of HR measurement as the absolute error between the output of the modified Kalman filter and the HR measured by a wrist-worn device. For evaluation, we compare our method with a conventional outlier removal and smoothing after compensation using one of the state-of-the-art methods based on deep learning. As a result, our method successfully removes 18.9% of the measurement with low reliability while achieving the mean absolute error of 6.25bpm, superior to the conventional methods.
Date of Conference: 17-19 November 2021
Date Added to IEEE Xplore: 14 December 2021
ISBN Information:
Conference Location: Tokyo, Japan

References

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