Neuro-fuzzy Modeling of Multi-field Surface Neuroprostheses for Hand Grasping

This thesis presents a novel neuro-fuzzy modeling approach for grasp neuroprostheses. At first, it offers a detailed study of discomfort due to the application of Functional Electrical Stimulation to the upper limb. Then, it discusses briefly previous methods to model hand movements induced by FES with the purpose of introducing the new modeling approach based on intelligent systems. This approach is thoroughly described in the book, together with the proposed application to induce hand and finger movements by means of a surface FES system based on multi-field electrodes. The validation tests, carried out on both healthy and neurologically impaired subjects, demonstrate the efficacy of the proposed modeling method. All in all, the book proposes an innovative system based on fuzzy neural networks that is expected to improve the design and validation of advanced control systems for non-invasive grasp neuroprostheses.

Nominated as an outstanding PhD thesis by the Intelligent Control Engineering group of the Comité Español de Automática (CEA) Proposes the use of fuzzy neural networks to model hand movements induced by a surface multi-field neuroprosthesis Reports on a detailed analysis of discomfort caused by FES application on the upper limb Provides readers with basic knowledge of all important concepts (such as FES and intelligent computing techniques) used in the book

Inhalt
Introduction.- Phisiology.- Functional Electrical Stimulation.- Discomfort analysis.- Pain-maps.- FES modeling.- Computational Intelligence.- Neuro-fuzzy model.- Neuro-fuzzy model.- Conclusions.