Model of rehabilitation training program for stroke by fuzzy reasoning

At present, using the rehabilitant robot can achieve the stroke rehabilitation training for patients, which is high intensity, targeted and repetitive rehabilitation training. It needs sound rehabilitation training program to guide the training. Due to different patients have different condition, and the same patient's condition changes as time change, however, there are some uncertainties of patients in the process of drawing up a rehabilitation training program, At the same time, the process of drawing up the program needs long time, and requires lots of manpower and material resources. In view of these issues, the model of rehabilitation training program for stroke was proposed, combing with the fuzzy reasoning (FR). Experimental results show that the model can make a rehabilitation training program and improve rehabilitation efficiency effectively.

[1]  Korris Fu-Lai Chung,et al.  Positive and negative fuzzy rule system, extreme learning machine and image classification , 2011, Int. J. Mach. Learn. Cybern..

[2]  Jonathan M. Garibaldi,et al.  Uncertain Fuzzy Reasoning: A Case Study in Modelling Expert Decision Making , 2007, IEEE Transactions on Fuzzy Systems.

[3]  W. Garraway,et al.  Motor function after stroke. , 1985, Age and ageing.

[4]  Yu-Lin He,et al.  Particle swarm optimization for determining fuzzy measures from data , 2011, Inf. Sci..

[5]  Po-Chien Chang,et al.  Fuzzy Delphi method for evaluating hydrogen production technologies , 2011 .

[6]  Jeng-Shyang Pan,et al.  Weighted Fuzzy Interpolative Reasoning Based on Weighted Increment Transformation and Weighted Ratio Transformation Techniques , 2009, IEEE Transactions on Fuzzy Systems.

[7]  Tang Yu-yong.  The invertible solution of kinematics about 5-DOF upper limb rehabilitant robot , 2007 .

[8]  Herón Molina-Lozano,et al.  A new fast fuzzy Cocke–Younger–Kasami algorithm for DNA strings analysis , 2011, Int. J. Mach. Learn. Cybern..

[9]  M. Kezunovic,et al.  Implementing Fuzzy Reasoning Petri-Nets for Fault Section Estimation , 2008, IEEE Transactions on Power Delivery.

[10]  Wen-Hui Chen,et al.  Fault Section Estimation Using Fuzzy Matrix-Based Reasoning Methods , 2011, IEEE Transactions on Power Delivery.

[11]  S. Micera,et al.  Robotic techniques for upper limb evaluation and rehabilitation of stroke patients , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.