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.
References
Cui J, Xing W, Qin H, Hua Y, Zhang X, Liu X (2022) Research on permanent magnet synchronous motor control system based on adaptive kalman filter. Appl Sci 12(10):4944–4944
Gao L, Zhang G, Yu B, Qiao Z, Wang J (2020) Wearable human motion posture capture and medical health monitoring based on wireless sensor networks. Measurement 166:108252
Gao N, Li J, Feng K, Xu T, Gao S, Li B (2019) Design of attitude measurement algorithm based on two-stage Complementary filter. Journal of Sensing Technology 32(12):1824–1829
Gao Y, Wang W (2022) Guo X (2022) Yu C (2022) Research on integrated navigation technology of rotorcraft UAV based on AKF. Information Technology and Informatization 5:159–163
Lebel K, Boissy P, Nguyen H, Duval C (2016) Autonomous quality control of joint orientation measured with inertial sensors. Sensors 16(7):1037
Li M, Xu Y, Gao Y, Feng J, Jin G (2022a) Lower limb posture capture using quaternion Kalman filter. 4th EAI International Conference on Multimedia Technology and Enhanced Learning (EAI ICMTEL 2022)
Li W, Ni T, Zhao D, Zhang P, Shi X (2022b) Active suspension control method of high mobility rescue vehicle based on ensemble Kalman filter. J Jilin Univ (Engineering edition) pp 1–11
Ling J (2021) Target tracking using Kalman filter based algorithms. J Phys Conf Ser 2078(1)
Liu HY, Li Q (2018) Application of kalman filter algorithm in ahrs attitude angle calculation. Industrial Control Computer 31(06):69–71
Liu KZ, Tang SH, Zhang Y, Li HY, Lv FQ (2022) Attitude solution of inclined RTK based on complementary filtering algorithm. Science Technology and Engineering 22(24):10402–10408
Liu M, Cai Y, Zhang L, Wang Y (2021) Attitude estimation algorithm of portable mobile robot based on Complementary filterr. Micromachines 12(11):1373
Nikishina V, Petrash E, Nikishin I (2019) Application of a hardware and software system of computer vision for rehabilitation training of post-stroke patients. Biomed Eng 53(1):44–50
Shawky E, El-Shimy M, Mokhtar A, El-Badawy ESA, Shalaby HMH (2020) Improving the visible light communication localization system using Kalman filtering with averaging. J Opt Soc Am B 37(11):A130–A138
Simpson LA, Eng JJ, Liu X, Hsieh JTC, Wolfe DL (2012) The health and life priorities of individuals with spinal cord injury: A systematic review. J Neurotrauma 29(8):1548C1555
Wang SH (2021) Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network. Information Fusion 67:208–229
Wang SH, Celebi ME, Zhang YD, Yu X, Tyukin I (2021) Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects. Information Fusion 76(2):376–421
Wang T, Zhang B, Liu C, Liu T, Han Y, Wang S, Ferreira JP, Dong W, Zhang X (2022) A review on the rehabilitation exoskeletons for the lower limbs of the elderly and the disabled. Electronics 11(3):388
Wei W, Song X, Wang G (2020) Realization of MEMS-IMU attitude solution based on improved adaptive Complementary filter. Electronic Measurement Technology 43(24):81–86
Wu Y, Niu Y, Li W (2022) Application research of kinect somatosensory technology in human lower limb rehabilitation training system. Modern electronic technology 45(12):165–172
Xie Y, Lin G, Huang Q, Li C, Hallett M, Voon V, Ren R, Chen S, Wang G (2021) Opinions and clinical practice of functional movement disorders: a nationwide survey of clinicians in china. BMC Neurol 21(435)
Xue L, Yang B, Yang X, Yuan D, Wang X, Chang H (2021) A redundant fused MIMU attitude system algorithm based on two-stage data fusion of MEMS gyro clusters array. Measurement 184:109993
Yue J (2018) Research on motion capture algorithm of human lower limbs based on inertial measurement unit
Zhang J (2018) Zhu B (2018) Medical rehabilitation detection system based on motion capture. The electronic world 2018(8):161–163
Zhang J, Li WG, Zhang JH, Nie P, Zhang CZ (2020) Mimu gesture decoding algorithm based on kalman filter research. Computer measurement and control 28(12):233–237
Zhang L, Wang S, Selezneva MS, Neusypin KA (2022) A new adaptive Kalman filter for navigation systems of carrier-based aircraft. Chin J Aeronaut 35(1):416–425
Zhang P (2021) Research on human posture calculation algorithm based on multi-sensor information fusion 03:46
Zhang Y, Zhao G (2022) Conservative treatment and rehabilitation training for rectus femoris tear in basketball training based on computer vision. Applied bionics and biomechanics 2022(6230025)
Zhang YD, Dong Z, Wang SH, Yu X, Gorriz JM (2020) Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation. Information Fusion 64:149–187
Zhao S, Huang B (2020) Trial-and-error or avoiding a guess? initialization of the Kalman filter. Automatica 121
Zheng C (2019) Overview of radar track tracking algorithms based on Kalman filter. Horizon of science and technology 2019(11):33–34
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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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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DOI: https://doi.org/10.1007/s11036-023-02139-1