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The online estimation of the joint angle based on the gravity acceleration using the accelerometer and gyroscope in the wireless networks

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Abstract

This study aims at the online estimation of the hip and knee angle in the sagittal plane for the motion surveillance only using the tri-axis accelerometers and gyroscopes of IMU, without considering the magnetic disturbance. The proposed method utilizes the projection of gravity acceleration on each sensor coordinate system to estimate the joint angle which rotating around the horizontal axis and approximately horizontal axis. With the third row of the rotation matrix independent of the yaw angle, the proposed method first calculates the projection of the gravity acceleration on each IMU sensor coordinate system only using accelerometer and gyroscope. And then, the rotation matrix between two adjacent coordinate systems is directly calculated. After evaluating the body to sensor rotation matrix, the rotation matrix between two adjacent body segments can be calculated, ultimately. Two types of experiments are adopted in the paper. The results show that the proposed method obtains the outstanding performance with the RMSE lower than 0.8 deg in the horizontal rotation experiment. In the limb joint experiment, the RMSE of the hip joint is lower than 3.12 deg, while the RMSE of the knee joint is lower than 3.83 deg for all predefined locomotion modes. The characteristic of our approach is that it can be run online without any parameter adjustment and additional time latency while ensuring estimation accuracy.

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Acknowledgements

This research was supported by national key research and development plan 2018YFC0832105 and 2018YFC0806800.

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Correspondence to Feng Jiang.

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Ding, Z., Yang, C., Ma, J. et al. The online estimation of the joint angle based on the gravity acceleration using the accelerometer and gyroscope in the wireless networks. Multimed Tools Appl 79, 16265–16279 (2020). https://doi.org/10.1007/s11042-019-07911-8

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  • DOI: https://doi.org/10.1007/s11042-019-07911-8

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