Literature DB >> 23744700

Towards a new modality-independent interface for a robotic wheelchair.

Teodiano Freire Bastos-Filho, Fernando Auat Cheein, Sandra Mara Torres Müller, Wanderley Cardoso Celeste, Celso de la Cruz, Daniel Cruz Cavalieri, Mário Sarcinelli-Filho, Paulo Faria Santos Amaral, Elisa Perez, Carlos Miguel Soria, Ricardo Carelli.   

Abstract

This work presents the development of a robotic wheelchair that can be commanded by users in a supervised way or by a fully automatic unsupervised navigation system. It provides flexibility to choose different modalities to command the wheelchair, in addition to be suitable for people with different levels of disabilities. Users can command the wheelchair based on their eye blinks, eye movements, head movements, by sip-and-puff and through brain signals. The wheelchair can also operate like an auto-guided vehicle, following metallic tapes, or in an autonomous way. The system is provided with an easy to use and flexible graphical user interface onboard a personal digital assistant, which is used to allow users to choose commands to be sent to the robotic wheelchair. Several experiments were carried out with people with disabilities, and the results validate the developed system as an assistive tool for people with distinct levels of disability.

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Year:  2013        PMID: 23744700     DOI: 10.1109/TNSRE.2013.2265237

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  4 in total

1.  Prediction of Optimal Facial Electromyographic Sensor Configurations for Human-Machine Interface Control.

Authors:  Jennifer M Vojtech; Gabriel J Cler; Cara E Stepp
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-06-20       Impact factor: 3.802

2.  Effectiveness of social behaviors for autonomous wheelchair robot to support elderly people in Japan.

Authors:  Masahiro Shiomi; Takamasa Iio; Koji Kamei; Chandraprakash Sharma; Norihiro Hagita
Journal:  PLoS One       Date:  2015-05-20       Impact factor: 3.240

3.  Face-Computer Interface (FCI): Intent Recognition Based on Facial Electromyography (fEMG) and Online Human-Computer Interface With Audiovisual Feedback.

Authors:  Bo Zhu; Daohui Zhang; Yaqi Chu; Xingang Zhao; Lixin Zhang; Lina Zhao
Journal:  Front Neurorobot       Date:  2021-07-16       Impact factor: 2.650

4.  A New Controller for a Smart Walker Based on Human-Robot Formation.

Authors:  Carlos Valadão; Eliete Caldeira; Teodiano Bastos-Filho; Anselmo Frizera-Neto; Ricardo Carelli
Journal:  Sensors (Basel)       Date:  2016-07-19       Impact factor: 3.576

  4 in total

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