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Teodiano Freire Bastos Filho

Researcher at Universidade Federal do Espírito Santo

Publications -  53
Citations -  271

Teodiano Freire Bastos Filho is an academic researcher from Universidade Federal do Espírito Santo. The author has contributed to research in topics: Mobile robot & Wheelchair. The author has an hindex of 8, co-authored 48 publications receiving 225 citations. Previous affiliations of Teodiano Freire Bastos Filho include Federal University of Amazonas.

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Analysis of the use of a robot to improve social skills in children with autism spectrum disorder

TL;DR: The studies indicate that the robot stimulated social skills in 4/5 of the ASD children, which shows that its concepts are useful to improve socialization and quality of life.
Proceedings ArticleDOI

Human-Machine Interface Based on Electro-Biological Signals for Mobile Vehicles

TL;DR: A system to allow the communication between a human being and a robot, through a human-machine interface (HMI), makes possible to use electro-biological signals, such as electromyogram, electrooculogram and electroencephalogram to control devices like an autonomous wheelchair.
Journal ArticleDOI

Fall Detection System by Machine Learning Framework for Public Health

TL;DR: This paper proposes a low cost and more accessible system for fall detection using inertial sensors, which will advise any person around the elder about the fall and has potential to be used to detect falls.
Journal ArticleDOI

An approach to avoid obstacles in mobile robot navigation: the tangential escape

TL;DR: The tangential escape approach is able to guide the robot along trajectories that result in a reduction of the traveling time, thus saving batteries and reducing the motor wearing, allowing concluding that the robot reaches any reachable goal, with or without a prescribed final orientation.
Proceedings ArticleDOI

Electric Powered Wheelchair Command by Information Fusion from Eye Tracking and BCI

TL;DR: This proposal allows the user to command an Electric Power Wheelchair by information fusion from commercial Brain-Computer Interface and Eye Tracker devices, surpassing challenges of non-intentional commands and high workload of the user.