Authors:
Marcos Yuzuru O. Camada
1
;
Diego Stéfano
2
;
Jés J. F. Cerqueira
2
;
Antonio Marcus N. Lima
3
;
André Gustavo S. Conceição
2
and
Augusto C. P. L. da Costa
2
Affiliations:
1
IFBaiano, Brazil
;
2
Federal University of Bahia, Brazil
;
3
Federal University of Campina Grande, Brazil
Keyword(s):
HRI, HMM, Fuzzy Inference System, Autism, Stereotyped Gesture, Assistive Robotic.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Cognitive Robotics
;
Enterprise Information Systems
;
Human-Robots Interfaces
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge-Based Systems Applications
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Modeling
Abstract:
Autists may exhibit difficulty in interaction (social and communication) with others and also stereotyped
gestures. Thus, autists have difficulty to recognize and to express emotions. Human-Robot Interaction (HRI)
researches have contributed with robotic devices able to be mediator among autist, therapists and parents. The
stereotyped behaviors of these individuals are due to their defense mechanism from of their hypersensitivity.
The affective state of a person can be quantify from poses and gestures. This paper proposes a system is able
to infer the defense level of autists from their stereotyped gestures. This system is part of the socially assistive
robot project called HiBot. The proposed system consist of two cognitive subsystems: Hidden Markov Models
(HMM), in order to determine the stereotyped gesture, and Fuzzy Inference System (FIS), to infer activation
level of these gestures. The results of these simulations show this approach is able to infer the defense level
for an tas
k or the presence of the robot.
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