Rehabilitation evaluation is an important part of rehabilitation training. It is closely related to the robot-assisted training effect. Different rehabilitation robots need different methods to evaluate patients. Rehabilitation training is a long process, and the patient’s performance scores will continue to change. A lower-limb rehabilitation robot needs a dynamic performance score to evaluate rehabilitation’s effects. This study used an analytic hierarchy process and fuzzy comprehensive evaluation methods to establish a rehabilitation evaluation system for lower-limb rehabilitation robots. A multi-scale personalized rehabilitation plan is conceived, based on the evaluation system and the combination of objective factors. This method dynamically adjusts the plan according to the rehabilitation situation of patients, which is beneficial to the improvement of the efficiency and initiative of training.

1. [1] X. Li and J. Zhong, “Upper Limb Rehabilitation Robot System Based on Internet of Things Remote Control,” IEEE Access, Vol.8, pp. 154461-154470, 2020. https://doi.org/10.1109/ACCESS.2020.3014378
2. [2] T. Zhi, C. Meng, and L. Fu, “Design of Intelligent Rehabilitation Evaluation Scale for Stroke Patients Based on Genetic Algorithm and Extreme Learning Machine,” J. of Sensors, Vol.2022, Article No.9323152, 2022. https://doi.org/10.1155/2022/9323152
3. [3] Y. Iwamoto et al., “Clinical Prediction Rule for Identifying the Stroke Patients Who Will Obtain Clinically Important Improvement of Upper Limb Motor Function by Robot-Assisted Upper Limb,” J. of Stroke and Cerebrovascular Diseases, Vol.31, No.7, Article No.106517, 2022. https://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106517
4. [4] L. Chen et al., “A Study on an Evaluation Method of a Rehabilitation Robot Based on Fuzzy Comprehensive Evaluation,” Advanced Materials Research, Vols.926-930, pp. 1144-1147, 2014. https://doi.org/10.4028/www.scientific.net/AMR.926-930.1144
5. [5] L. Chen and Z. Hua, “Athlete Rehabilitation Evaluation System Based on Internet of Health Things and Human Gait Analysis Algorithm,” Complexity, Vol.2021, Article No.6663224, 2021. https://doi.org/10.1155/2021/6663224
6. [6] X. L. Huang and T. B. Yan, “Rehabilitation Cortical,” 5th Edition, p. 151, People’s Medical Publishing House, 2013 (in Chinese).
7. [7] S. Arun et al., “Rehabilitation Evaluation of the Newly Developed Polymeric Based Passive Polycentric Knee Joint,” Disability and Rehabilitation: Assistive Technology, Vol.15, No.8, pp. 871-877, 2020. https://doi.org/10.1080/17483107.2019.1621955
8. [8] A. F. A. Aziz et al., “What Is Next After Transfer of Care from Hospital to Home for Stroke Patients? Evaluation of a Community Stroke Care Service Based in a Primary Care Clinic,” J. of Neurosciences in Rural Practice, Vol.4, No.4, pp. 413-420, 2013. https://doi.org/10.4103/0976-3147.120243
9. [9] J. L. Moore et al., “Implementation of High-Intensity Stepping Training During Inpatient Stroke Rehabilitation Improves Functional Outcomes,” Stroke, Vol.51, No.2, pp. 563-570, 2020. https://doi.org/10.1161/STROKEAHA.119.027450
10. [10] B. Koopman, E. H. F. van Asseldonk, and H. van der Kooij, “Selective Control of Gait Subtasks in Robotic Gait Training: Foot Clearance Support in Stroke Survivors with a Powered Exoskeleton,” J. of NeuroEngineering and Rehabilitation, Vol.10, Article No.3, 2013. https://doi.org/10.1186/1743-0003-10-3
11. [11] H. Wang et al., “Design and Analysis of a Spatial Four-DOF Lower-Limb Rehabilitation Robot,” J. of Fundamental and Applied Sciences, Vol.10, No.4S, pp. 175-180, 2018.
12. [12] P.-J. Pan, “The Research of Human-Computer Interaction System and Rehabilitation Evaluation Methods of Upper Extremity Exoskeleton Rehabilitation Robot,” Master’s Thesis, Hebei University of Technology, 2015 (in Chinese).
13. [13] M. Torrisi et al., “Beyond Motor Recovery After Stroke: The Role of Hand Robotic Rehabilitation Plus Virtual Reality in Improving Cognitive Function,” J. of Clinical Neuroscience, Vol.92, pp. 11-16, 2021. https://doi.org/10.1016/j.jocn.2021.07.053
14. [14] J. Wang et al., “Rehabilitation Evaluation Methodology of Upper Limb Rehabilitation Robot Based on AHP-Fuzzy Comprehensive Evaluation,” J. of Shenyang University (Natural Science), Vol.24, No.3, pp. 47-51, 2012 (in Chinese).
15. [15] R. Wang et al., “Denoising Surface Electromyography Signals Based on Complementary Ensemble Empirical-Mode Decomposition and Multi-Scale Entropy,” 2021 40th Chinese Control Conf. (CCC), pp. 3138-3142, 2021. https://doi.org/10.23919/CCC52363.2021.9549382