A Novel Evaluation Index and Optimization Method for Ankle Rehabilitation Robots Based on Ankle-Foot Motion.

Journal: Journal of biomechanical engineering
Published Date:

Abstract

The ability of ankle rehabilitation robots to accurately mimicking the actual human ankle motion is an important judgment basis for robot-assisted rehabilitation training. This paper proposes an evaluation index and mechanism parameter optimization method based on ankle-foot motion trajectory by exploring the human ankle-foot motion principle. First, the ankle UR equivalent model and a 3-degree-of-freedom (DOF) parallel ankle rehabilitation robot are described. Second, the ankle-foot motion data are measured by the body surface marker method, which proved the coupling of ankle-foot motion. Then, a new evaluation index, the ankle-foot motion comfort zone, is proposed, which is essentially the superimposed ankle-foot motion trajectory measured about 3-5 mm wide. Third, a mechanism parameter optimization method, is proposed in terms of the ankle-foot motion comfort zone as the evaluation index, which is applied to the 3-DOF parallel ankle rehabilitation robot, and the optimization results proved the feasibility of the method. Finally, the optimized rehabilitation robot is fitted with different ankle motions, and a prototype model is designed for kinematics simulation, which verifies the adaptability of the optimization method. This study provides a theoretical basis for the configuration design of ankle rehabilitation robots and provides a new direction for the optimization of the mechanism parameters.

Authors

  • Jianjun Zhang
    Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, Texas, USA.
  • Zhihao Ma
    School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China; Intelligent Rehabilitation Device and Detection Technology Engineering Research Center of the Ministry of Education, Tianjin 300130, China; Hebei Province Key Laboratory of Robot Perception and Human-Machine Fusion, Tianjin 300130, China.
  • Jun Wei
    Guangzhou Perception Vision Medical Technology Inc. Guangzhou 510000 China.
  • Shuai Yang
    School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei, Anhui, China.
  • Chenglei Liu
    School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.
  • Shijie Guo