Authors:
Eman Ahmed
1
;
Reda A. El-Khoribi
2
;
Alexandre Muzy
3
;
Gilles Bernot
3
and
Gamal Darwish
2
Affiliations:
1
Faculty of Computers and Information, Cairo University, Giza, Egypt, Laboratoire d’ Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S) UNS CNRS, Université Côte d’Azur and France
;
2
Faculty of Computers and Information, Cairo University, Giza and Egypt
;
3
Laboratoire d’ Informatique, Signaux et Systèmes de Sophia-Antipolis (I3S) UNS CNRS, Université Côte d’Azur and France
Keyword(s):
Fetus Human, Movement, Goal, Sensory-motor Loop.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Bioinformatics and Systems Biology
;
Pattern Recognition
;
Software Engineering
Abstract:
Humans have the ability to make many complex movements at the same time with full coordination through the whole body. This requires control of all body muscles. The body muscles are controlled by the Central Nervous System (CNS) which consists of the brain and the spinal cord through a group of neurons called the motor neurons. Each muscle is controlled by lower-level motor neurons called the motor neurons. A motor neuron controls a group of muscle fibers of the muscle such that when it is activated, this group contracts. Hence, a muscle movement occurs. Currently, many questions remain unanswered: How this system evolves to generate the complex movements? How to control the muscles to achieve a certain goal such as reaching a target position? and
how a human becomes able to define goals in the first place? It is believed that the development of motion begins prenatally with spontaneous fetal movements. In this paper, we are trying to answer these questions by proposing a theoretic
al model of human learning of motion starting from being a fetus. Simulation is provided using computational intelligence and statistical methods.
(More)