01627nas a2200277   4500000000100000000000100001008004100002260001200043653001900055653001000074653002800084653002400112100002300136700002000159700001600179700002800195700002000223700002500243700002600268245012400294856009800418300001000516490000600526520080300532022001401335       2015                            d  c03/201510aVirtual Worlds10aFuzzy10aRehabilitation Robotics10aCollision Detection1 aLuis Daniel Lledó1 aArturo Bertomeu1 aJorge Díez1 aFrancisco Javier Badesa1 aRicardo Morales1 aJosé María Sabater1 aNicolas Garcia-Aracil00aAuto-adaptative Robot-aided Therapy based in 3D Virtual Tasks controlled by a Supervised and Dynamic Neuro-Fuzzy System  uhttp://www.ijimai.org/journal/sites/default/files/files/2015/02/ijimai20143_2_8_pdf_17229.pdf  a63-680 v33 aThis 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.  a1989-1660