Abstract
At present, due to the limited information, the single man-machine interface control has some defects in human motion prediction, such as low accuracy and poor robustness. In this work, a multi-modal real-time acquisition system that combines surface electromyography (sEMG), inertial measurement (IMU) and A-mode ultrasound (AUS) information is used to upper limb motion prediction. The device we developed can simultaneously collect three kinds of signals, eliminating the operation of manual alignment. sEMG can reflect the electrical activity of muscle contraction, AUS can detect the deformation of deep muscles, and IMU can obtain information such as the speed and acceleration of the limbs. One healthy subjects participated in the experiment. The results show that the motion prediction accuracy of three modal information fusion is higher than that of any one or two information fusion, which is expected to provide a better control method in exoskeleton or prosthesis.
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Liu, Y., Yin, Z., Yang, H., Yang, X., Liu, H. (2022). A Synchronous Acquisition System of Ultrasound, sEMG and IMU for Human Motion Prediction. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13457. Springer, Cham. https://doi.org/10.1007/978-3-031-13835-5_8
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DOI: https://doi.org/10.1007/978-3-031-13835-5_8
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