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

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

Editor's Note

The term 'Digital Economy' was coined for the first time by Don Tapscott in 1995 in his best-seller The Digital Economy: Promise and Peril in the Age of Networked Intelligence. When he wrote the book 20 years ago, he announced how he thought the Internet would fully transform the nature of business and government. We have now extended the concept, illustrating how digital technologies are rapidly transforming business practices, the economy and societies. Technology, and its impact on business strategy and society, continues to rise in importance. The Digital Economy, sometimes also called “Digital Business” has become a philosophy for many top executive teams as they seek competitive advantages in a world of fast moving technological change. When we talk about digital technologies, we are not only talking about the internet, nor only ICT (Information and Communications Technology), but other concepts such as mobile, telecommunications or content. The digital economy is by no means an exclusively economic concept. Therefore, it might be more appropriate to speak of digital society or digital technology. What matters is that digital is a transverse concept that affects individuals, businesses and public administrations

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

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