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Dual Predictive Quaternion Kalman Filter and its Application in Seamless Wireless Mobile Human Lower Limb Posture Tracking

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Abstract

Accurate tracking of human posture is one of the key factors of rehabilitation training for patients with motor function injury. In this work, one human lower limb posture tracking method employing five inertial measurement units (IMUs) will be proposed. Moreover, in order to improve the estimation accuracy of the quaternion of IMU, especially the outage of the IMU due to the mobile communication, the dual predictive quaternion Kalman filter (KF) will be proposed for the IMU. To the dual predictive KF, two predictive quaternion KFs are employed for one IMU in this paper, one is used to estimate the angular velocity, the other one is used to estimate the quaternion, then, the estimated angular velocity and quaternion have been used for the proportional integral (PI)-based angular velocity compensation. The real test shows that the proposed method is effective to improve the accuracy of the human lower limb posture tracking, especially when the IMU data is outage due to the wireless communication.

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Data Availability

The raw data were provided by University of Jinan, Jinan, China. The raw data used in this study are available from the corresponding author upon request.

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Acknowledgements

This work was supported in part by 1) Shandong Natural Science Foundation ZR2023MF121 and ZR2020MF0672, 2) the National Key R &D Program of China 2018AAA0101703, 3) the Shandong Key Research and Development Program under Grant 2019GGX104026, 4) 2022 Shandong Province Science and Technology Small and Medium Enterprises Innovation Ability Enhancement Project 2022TSGC2037

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Correspondence to Yuan Xu.

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Liu, W., Li, M., Liu, F. et al. Dual Predictive Quaternion Kalman Filter and its Application in Seamless Wireless Mobile Human Lower Limb Posture Tracking. Mobile Netw Appl 28, 1865–1876 (2023). https://doi.org/10.1007/s11036-023-02139-1

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