IEEE Transactions on Neural Systems and Rehabilitation Engineering (Jan 2024)

An Upper Limb Exoskeleton Motion Generation Algorithm Based on Separating Shoulder and Arm Motion

  • Jiajia Wang,
  • Shuo Pei,
  • Junlong Guo,
  • Anyang Dong,
  • Bojian Liu,
  • Yufeng Yao

DOI
https://doi.org/10.1109/TNSRE.2024.3356724
Journal volume & issue
Vol. 32
pp. 1142 – 1153

Abstract

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Many rehabilitation exoskeletons have been used in the field of stroke rehabilitation. Generating human-like motion is necessary for exoskeletons to help patients perform activities of daily living (ADL) while maintaining interaction quality and ergonomics. However, most of the current motion generation algorithms utilize inverse kinematics (IK) to solve the final configuration before generation, and do not consider the movement of shoulder girdle. Separately considering the shoulder girdle motion and arm motion, this paper proposes an algorithm integrated IK to generate human-like motion. The arm moves towards the target with a bell-shaped velocity in the absence of the final configuration, and the shoulder girdle maintain natural passive motion. Moreover, the generated motion can be mapped to the configuration space of exoskeletons. Compared with the experimental data collected using a motion capture system, the values of RMSE and HPDI of the generated wrist trajectory in the task space are within 0.2 and 0.17, respectively, while those of RMSE in the joint space are within 15 deg, which demonstrates the human-like nature of the generated motion.

Keywords