Abstract
Real-time gait analysis is an important reference for an exoskeleton control system. Gait state can be utilized for the control system’s parameter adjustment and optimization. We introduced a method by using Inertial Measurement Units (IMUs) to measure the gait motion of human when wearing a knee exoskeleton. In the measurement method, based on the body size and the real-time data of the IMU, the measurement system can generate the state data such as walking speed, step height, step stride and slope. We verified the performance of this system through the use of the exoskeleton system by 15 people during the tests the exoskeleton is unpowered. The experiment results show the accuracy achieve 93\(\%\) which presents the proposed method that can monitor the real-time gait in a relatively accurate range, which may provide a reliable reference for the exoskeleton control system.
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References
Bae, J., et al.: A lightweight and efficient portable soft exosuit for paretic ankle assistance in walking after stroke. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 2820–2827. IEEE (2018)
Byun, S., Lee, H.J., Han, J.W., Kim, J.S., Choi, E., Kim, K.W.: Walking-speed estimation using a single inertial measurement unit for the older adults. PLoS One 14(12), e0227075 (2019)
Ding, Y., Kim, M., Kuindersma, S., Walsh, C.J.: Human-in-the-loop optimization of hip assistance with a soft exosuit during walking. Sci. Robot. 3(15) (2018). https://doi.org/10.1126/scirobotics.aar5438
Haumont, T., et al.: Wilmington robotic exoskeleton: a novel device to maintain arm improvement in muscular disease. J. Pediatric Orthopaedics. 31(5), e44–e49 (2011)
Hori, K., et al.: Inertial measurement unit-based estimation of foot trajectory for clinical gait analysis. Front. Physiol. 10, 1530 (2020)
Jang, J., Kim, K., Lee, J., Lim, B., Cho, J.-K., Shim, Y.: Preliminary study of online gait recognizer for lower limb exoskeletons. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5818–5824. IEEE (2017)
Jatsun, S., Savin, S., Yatsun, A.: Parameter optimization for exoskeleton control system using Sobol sequences. In: Symposium on Robot Design, Dynamics and Control, pp. 361–368. Springer (2016). https://doi.org/10.1007/978-3-319-33714-2_40
Kim, D.-S., et al.: A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study. BMC Geriatrics 18(1), 1–8 (2018)
Lee, S., et al.: Autonomous multi-joint soft exosuit with augmentation-power-based control parameter tuning reduces energy cost of loaded walking. J. Neuroeng. Rehabil. 15(1), 1–9 (2018)
Schiffman, J.M., Gregorczyk, K.N., Bensel, C.K., Hasselquist, L., Obusek, J.P.: The effects of a lower body exoskeleton load carriage assistive device on limits of stability and postural sway. Ergonomics 51(10), 1515–1529 (2008)
Walsh, C.J., Endo, K., Herr, H.: A quasi-passive leg exoskeleton for load-carrying augmentation. Int. J. Humanoid Robot. 4(03), 487–506 (2007)
Wang, X., Kyrarini, M., Ristić-Durrant, D., Spranger, M., Gräser, A.: Monitoring of gait performance using dynamic time warping on IMU-sensor data. In: 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp. 1–6. IEEE (2016)
Chunjing, T., Chongmin, J., Liping, S., Dongming, W., Rui, C., Huan, W.: Research on the changes of urban residents’ body shape in China: based on the perspective of group analysis. In: Capital Institute of Physical Education (2018)
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Quan, J., Liu, H., Yan, G., Li, H., Zhao, Z. (2022). An IMU Based Real-Time Monitoring System for Powered Robotic Knee Exoskeleton. In: Jia, Y., Zhang, W., Fu, Y., Yu, Z., Zheng, S. (eds) Proceedings of 2021 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 804. Springer, Singapore. https://doi.org/10.1007/978-981-16-6324-6_28
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DOI: https://doi.org/10.1007/978-981-16-6324-6_28
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