Auto-adaptative Robot-aided Therapy based in 3D Virtual Tasks controlled by a Supervised and Dynamic Neuro-Fuzzy System

被引：5

作者：

Lledo, L. D. ^{[1
]}

Bertomeu, A. ^{[1
]}

Diez, J. ^{[1
]}

Badesa, F. J. ^{[1
]}

Morales, R. ^{[1
]}

Sabater, J. M. ^{[1
]}

Garcia-Aracil, N. ^{[2
]}

机构：

[1] Miguel Hernandez Univ Elche, Elche, Spain

[2] Miguel Hernandez Univ Elche, Control & Syst Engn, Elche, Spain

来源：

INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2015年 / 3卷 / 02期

关键词：

Rehabilitation robotics; Physiological state; Neural networks; Fuzzy logic system; Virtual reality; Collision detection;

D O I：

10.9781/ijimai.2015.328

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an application formed by a classification method based on the architecture of ART neural network (Adaptive Resonance Theory) and the Fuzzy Set Theory to classify physiological reactions in order to automatically and dynamically adapt a robot-assisted rehabilitation therapy to the patient needs, using a three-dimensional task in a virtual reality system. Firstly, the mathematical and structural model of the neuro-fuzzy classification method is described together with the signal and training data acquisition. Then, the virtual designed task with physics behavior and its development procedure are explained. Finally, the general architecture of the experimentation for the auto-adaptive therapy is presented using the classification method with the virtual reality exercise.

引用

收藏

页码：63 / 68

页数：6

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