Title :
AFCMAC: An Auto-Adaptive Fuzzy CCMAC for oculomotor system
Author :
Ghassemi, Elham ; Kapoula, Zoï
Author_Institution :
IRIS Group, Univ. Paris Descartes, Paris, France
Abstract :
This paper presents an Auto-Adaptive Fuzzy CMAC (AFCMAC) for horizontal voluntary eye movements while reading. Dynamic Fuzzy Logic is used to speed up the auto-adaptive learning ability and to increase the robust capability of the traditional CMAC. We have evaluated the AFCMAC by testing it on the eye movements - measure by the Chronos Vision Eye-Tracking device - of 5 dyslexic and 5 non-dyslexic children, in a seated position with the head-fixed while reading a French text in near viewing distance. We have used the parameter of standard deviation of binocular fixation disparity. The evaluation results have shown a satisfying performance of the AFCMAC to learn dynamically these different vergence adjustments during binocular fixation word after word in both groups of children.
Keywords :
cerebellar model arithmetic computers; eye; fuzzy logic; learning (artificial intelligence); medical computing; medical disorders; self-adjusting systems; text analysis; AFCMAC; Chronos vision eye-tracking device; French text; autoadaptive fuzzy CMAC; autoadaptive learning ability; binocular fixation disparity; cerebellum model articulation controller; dynamic fuzzy logic; dyslexic children; horizontal voluntary eye movements; near viewing distance; nondyslexic children; oculomotor system; standard deviation parameter; Arrays; Fuzzy logic; Motor drives; Muscles; Neurons; Standards; Training; Adaptive Motor Control; Auto-adaptive Fuzzy CMAC; CMAC; Cerebellum; Dynamic Fuzzy Logic; Eye Training; Ocular Motor Control; Vergence Eye Movement;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251154