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Proposal of a Brain Computer Interface to command an autonomous car

Proposal of a Brain Computer Interface to command an autonom...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Javier Castillo Sandra Müller Eduardo Caicedo Alberto Ferreira De Souza Teodiano Bastos Post-Graduate Program of Electrical Engineering Federal University of Espirito Santo Vitoria Brazil Post-Graduate Program of Electrical Engineering University of Valle Cali Valle Colombia Post-Graduate Program of Informatics Federal University of Espirito Santo Vitoria Brazil

This paper presents a proposal of Brain Computer Interface (BCI) to command an autonomous car. This BCI is based on the paradigm of visual evoked potentials (VEP) and event-related desynchronization (ERD). A menu interface is presented to the user with disabilities in order he/she can choose a destination for the autonomous car. The selection of the final destination is performed using visual stimuli flickering at different frequencies, analyzed through the analysis of brain signals present at the occipital region of the user's scalp. The power spectrum of these signals is then obtained, in order to get the frequency of the visual stimulation. Preliminary tests were performed with healthy users and people with disabilities, which reached an average success rate above 90%. The proposed system is also capable of turning on/off the stimuli, thus reducing the fatigue associated with particular visual stimuli.

关键词： Brain-computer interfaces Mobile robots Visualization Equations Proposals Educational institutions Navigation

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Feature extraction techniques based on power spectrum for a SSVEP-BCI

Feature extraction techniques based on power spectrum for a ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Javier Castillo Sandra Müller Eduardo Caicedo Teodiano Bastos Post-Graduate Program of Electrical Engineering Federal University of Espirito Santo Vitoria Brazil Post-Graduate Program of Electrical Engineering University of Valle Cali Valle Colombia

ISBN: (纸本)9781479924004

This paper presents a comparison among three methods for Steady-State Visually Evoked Potentials (SSVEP) detection. These techniques are based on Power Spectral Density Analysis (PSDA) and Canonical Correlation Analysis (CCA). The first method estimates the signal-to-noise ratio of the power spectrum in each stimulus frequency using PSDA, which is called Traditional-PSDA. The second analysis estimates the relation between the difference of the stimulus frequency and its neighbor frequencies, using the power spectrum in these neighbor frequencies, and seeks the neighbor frequency which present the lowest relation value. This technique is referred to Ratio-PSDA. The third and final technique called Hybrid-PSDA-CCA. The performances of the methods were evaluated using a database of electroencephalogram (EEG) signals. The EEG signals were recorded from 19 volunteers, from which six people present disabilities. They were stimulated with visual stimuli flickering at 5.6, 6.4, 6.9 and 8.0 Hz. The system performance was evaluated considering the accuracy and the Information Transfer Rate (ITR) for each stimulus frequency. The results showed that the Hybrid-PSDA-CCA method achieved the best result with an average accuracy of 91.44%.

关键词： Electroencephalography Correlation Electric potential Brain-computer interfaces Equations Frequency estimation Accuracy

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Proposal of evaluation methods of interaction between a mobile robot and children with Autism Spectrum Disorder

Proposal of evaluation methods of interaction between a mobi...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Christiane M. Goulart Javier Castillo Carlos T. Valado Eliete Caldeira Malte Trauernicht Teodiano F. Bastos-Filho Post-Graduate Program in Biotechnology Federal University of Espirito Santo Vitoria Brazil Post-Graduate Program in Electrical Engineering Federal University of Espirito Santo Vitoria Brazil Graduate Program in Electrical Engineering Institute of Engineering Groningen The Netherlands

Manifestations of cognitive and neurobehavioral disorders such as repetitive movements, impaired communication and social interaction level characterize Autism Spectrum Disorder - ASD, a condition of unknown etiology and still without cure. Currently, many researches integrate robotics to the treatment of ASD with varied functions that allow interaction with children with this disorder. Therefore, evaluation criteria become important to analyze the efficiency the use of robotics in this interaction. The methods here proposed are Goal Attainment Scaling (GAS), System Usability Scale (SUS) and Fitts' Law. The use of such methods of evaluation allows transpose qualitative assessments into quantitative, making the work more robust and reliable.

关键词： Variable speed drives Autism Mobile robots Usability Robot sensing systems Educational institutions

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MODAL ANALYSIS OF A METALLIC VIA HOLE BY THE WCIP

MODAL ANALYSIS OF A METALLIC VIA HOLE BY THE WCIP

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SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference

作者： Georgina K. de F. Serres Alexandre J. R. Serres Raimundo C. S. Freire Henri Baudrand Post-Graduate Program in Electrical Engineering - COPELE Federal University of Campina Grande UFCG L.A.P.L.A.C.E-G.R.E ENSEEIHT

ISBN: (纸本)9781467394932

This paper presents a new electromagnetic modeling of a via-hole using a Wave Concept Iterative Procedure. There are specific TM modes associated with the insertion of the via-hole influencing the incident and reflected waves, called the "via's modes". The formulation and results are presented considering the influence of one and two via's mode. The advantage of the model presented is the possibility to simulate planar circuits with a layer and a via-hole considering the effects of the field that propagates around the via.

关键词： WCIP Via Hole TM Mode Propagation Constant

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Adaptive BCI Based on Software Agents

Adaptive BCI Based on Software Agents

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Javier Castillo-Garcia Anibal Cotrina Alessandro Benevides Denis Delisle-Rodriguez Berthil Longo Eduardo Caicedo Andre Ferreira Teodiano Bastos School of Electrical and Electronic Engineering of Univesity of the Valle Post-Graduate Program of Electrical Engineering Federal University of Espirito Santo Post-Graduate Program of Biotechnology Federal University of Espirito Santo

ISBN: (纸本)9781424479276

The selection of features is generally the most difficult field to model in BCIs. Therefore, time and effort are invested in individual feature selection prior to data set training. Another great difficulty regarding the model of the BCI topology is the brain signal variability between users. How should this topology be in order to implement a system that can be used by large number of users with an optimal set of features? The proposal presented in this paper allows for obtaining feature reduction and classifier selection based on software agents. The software agents contain Genetic Algorithms (GA) and a cost function. GA used entropy and mutual information to choose the number of features. For the classifier selection a cost function was defined. Success rate and Cohen's Kappa coefficient are used as parameters to evaluate the classifiers performance. The obtained results allow finding a topology represented as a neural model for an adaptive BCI, where the number of the channels, features and the classifier are interrelated. The minimal subset of features and the optimal classifier were obtained with the adaptive BCI. Only three EEG channels were needed to obtain a success rate of 93% for the BCI competition III data set IVa.

关键词： Software agents Brain modeling Electroencephalography Topology Cost function Feature extraction Support vector machines

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Assessment of applicability of robotic walker for post-stroke hemiparetic individuals through muscle pattern analysis

Assessment of applicability of robotic walker for post-strok...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Flávia Aparecida Loterio John Jairo Villarejo Mayor Anselmo Frizera Neto Teodiano Freire Bastos Filho Post-Graduate Program in Biotechnology Federal University of Espirito Santo Vitoria Brazil Post-Graduate Program in Electrical Engineering Federal University of Espirito Santo Vitoria Brazil

Stroke is a leading cause of morbidity and mortality worldwide. In most patients, the stroke causes disabilities that hamper the performance of daily tasks autonomously. The most common clinical features in these individuals are hemiparesis, abnormal gait pattern, muscle spasticity and balance loss. There are several studies about the use of robotic devices in hemiparetic individuals, for example for rehabilitation. The robotic walker developed at UFES/Brazil will be assessed for its applicability, using Surface Electromyography (sEMG) to verify the muscle activation during the gait in individuals with post-stroke hemi-paresis. Preliminary tests are being made with the proposed methodology to analyse the robotic walker, but first using a conventional walker two frontal wheels as assistant gait. Two healthy volunteers performed initially a path without the aid of the walker and then with its aid along a flat straight route. sEMG signals are analyzed in order to assess the muscle activity during the gait. After analyzing the data, the results were compared between the free and assisted gait. With the use of the walker the gait speed in healthy volunteers was reduced and, consequently, changes occurred during activation of the muscles. Changes caused by shifting down are important due to improper adjustment of the height of the walker leads to gait changes. As future work, we intend assess the use of robotic walker in clinical trials.

关键词： Muscles Legged locomotion Electromyography Knee Electrodes Robot sensing systems

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Mobile robotics: A tool for interaction with children with autism

Mobile robotics: A tool for interaction with children with a...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Christiane M. Goulart Javier Castillo Carlos T. Valadão Eliete Caldeira Teodiano F. Bastos-Filho Post-Graduate Program of Biotechnology Federal University of Espirito Santo Vitoria Brazil Post-Graduate Program of Electrical Engineering Federal University of Espirito Santo Vitoria Brazil

ISBN: (纸本)9781479924004

This paper presents an implementation with mobile robot to generate actions to interact with children with autism. The robot is able to detect the child localization and approach him/her, keeping a safe proximity minimum (interaction distance). The mobile robot is equipped with laser sensor to obtain distances and an embedded control system for the interaction. The implementation allows two modes of interaction, depending on the degree of interaction with the child. The system here developed can help children with autism in the process of social evolution and be a tool for professionals and researchers of the area.

关键词： Robot kinematics Robot sensing systems Autism Mobile robots Variable speed drives Control systems

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An Ethernet sniffer for On-line acquisition of EEG with the BrainNet36® device applied to a BCI

An Ethernet sniffer for On-line acquisition of EEG with the ...

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5th ISSNIP - IEEE Biosignals and Biorobotics Conference, BRC 2014

作者： Benevides, Alessandro Botti Atencio, Anibal Cotrina Castillo, Javier Filho, Teodiano Freire Bastos Benevides, Alessander Botti Electrical Engineering Post-Graduate Program Federal University of Espirito Santo Vitória Espírito Santo 29075-910 Brazil ICT Doctoral School University of Trento Trento Trentino 38123 Italy

ISBN: (纸本)9781479956890

This paper presents an Ethernet sniffer programmed in ANSI C to export in an on-line way the electroencephalographic (EEG) data acquired with the device BrainNet36®, which is a Brazilian EEG device for clinical and polysomnography purposes. The sniffer proved to be useful for off-line analysis of the EEG and also for on-line applications, as Brain Computer-Interfaces (BCIs). Despite its limitations and packet losses at around 1.7% due to noise, the off-line analysis of the EEG successfully replicated results of the literature regarding the Event-Related (De)Synchronization (ERD/ERS) and Evoked Potentials (EPs) calculated for mental tasks. For on-line applications the sniffer was used to program a single-switch BCI for on-line classification of motor and no motor mental tasks with high success rate. Nowadays, the BrainNet36® device is being used for EEG research at many Brazilian universities, therefore, we hope that this article may encourage on-line applications. Finally, as the sniffer operation is explained here with examples, this text may serve as a reference guide for potential user's. © 2014 IEEE.

关键词： Brain computer interface

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Using Brain-Computer Interface to control an avatar in a Virtual Reality Environment

Using Brain-Computer Interface to control an avatar in a Vir...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Berthil Borges Longo Alessandro Botti Benevides Javier Castillo Teodiano Bastos-Filho Post-Graduate Program in Biotechnology Universidade Federal do Esprito Santo Vitoria Brazil Post-Graduate Program in Electrical Engineering Universidade Federal do Esprito Santo Vitoria Brazil

The proposal of this research is to present the development of a tool that might be useful in rehabilitation, for subjects with disability, that suffer from some kind of limbs movement limitation. This tool carries a 3D Virtual Reality Environment (VRE), which emulates the movement of a healthy person, using the immersion of the subject through an avatar. To do so, and test its feasibility, pre acquired motor imagery signals were used to test the VRE as an off-line Brain Computer Interface (BCI) feedback. The subject's brain waves were captured by an Electroencephalography (EEG) equipment. For training the classifier, 45 trials, 25 seconds long, were used, and 15 trials for its validation. Five mental tasks were tested with the BCI, and the one with the best results (imagination of the manipulation of a cube) was used to move the avatar through a virtual room.

关键词： Electroencephalography Brain-computer interfaces Avatars Three-dimensional displays Legged locomotion Training

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A SPECTRUM SENSING ALGORITHM BASED ON STATISTIC TESTS FOR COGNITIVE NETWORKS SUBJECT TO FADING

A SPECTRUM SENSING ALGORITHM BASED ON STATISTIC TESTS FOR CO...

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European Signal Processing Conference

作者： Fabricio B. S. de Carvalho Jeronimo S. Rocha Waslon T. A. Lopes Marcelo S. Alencar Post-Graduate Program in Electrical Engineering - PPgEE - COPELE DEE - UFCG Iecom - UFCG

ISBN: (纸本)9781479946037

Cognitive radio is a viable technology for the next generation of wireless communications. The ability to sense the electromagnetic spectrum and to enable vacant bands to other users has been investigated in the past years. One important issue is the use of an efficient spectrum sensing algorithm to monitor the frequency band occupancy. Usually, the effects of fading are overseen in the analysis of those algorithms. This paper aims to evaluate the performance of a spectrum sensing algorithm based on Jarque-Bera test. Rayleigh fading is considered in this paper. Preliminary simulation results are provided, to demonstrate the potential of the proposed strategy.

关键词： Cognitive Radio Signal Processing Spectrum Sensing Statistic Tests Jarque-Bera Test Rayleigh Fading Channel

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