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Authors: Yicong Gong ; Carly Gross ; David Fan ; Ahmed Nasrallah ; Nathaniel Maas ; Kelly Cashion and Vijayan K. Asari

Affiliation: University of Dayton, United States

Keyword(s): Brain Machine Interface, Robotic Arm, Electroencephalography, Independent Component Analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Bio-Inspired and Humanoid Robotics ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: We present a methodology to explore the capabilities of an existing interface for controlling a robotic arm with information extracted from brainwaves. Brainwaves are collected through the use of an Emotiv EPOC headset. The headset utilizes electroencephalography (EEG) technology to collect active brain signals. We employ the Emotiv software suites to classify the thoughts of a subject representing specific actions. The system then sends an appropriate signal to a robotic interface to control the robotic arm. We identified several actions for mapping, implemented these chosen actions, and evaluated the system’s performance. We also present the limitations of the proposed system and provide groundwork for future research.

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Paper citation in several formats:
Gong, Y.; Gross, C.; Fan, D.; Nasrallah, A.; Maas, N.; Cashion, K. and K. Asari, V. (2014). Study of an EEG based Brain Machine Interface System for Controlling a Robotic Arm. In Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014) - NCTA; ISBN 978-989-758-054-3, SciTePress, pages 339-344. DOI: 10.5220/0005157803390344

@conference{ncta14,
author={Yicong Gong. and Carly Gross. and David Fan. and Ahmed Nasrallah. and Nathaniel Maas. and Kelly Cashion. and Vijayan {K. Asari}.},
title={Study of an EEG based Brain Machine Interface System for Controlling a Robotic Arm},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014) - NCTA},
year={2014},
pages={339-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005157803390344},
isbn={978-989-758-054-3},
}

TY - CONF

JO - Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014) - NCTA
TI - Study of an EEG based Brain Machine Interface System for Controlling a Robotic Arm
SN - 978-989-758-054-3
AU - Gong, Y.
AU - Gross, C.
AU - Fan, D.
AU - Nasrallah, A.
AU - Maas, N.
AU - Cashion, K.
AU - K. Asari, V.
PY - 2014
SP - 339
EP - 344
DO - 10.5220/0005157803390344
PB - SciTePress

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