Study of an EEG based Brain Machine Interface System for Controlling a Robotic Arm

Yicong Gong, Carly Gross, David Fan, Ahmed Nasrallah, Nathaniel Maas, Kelly Cashion, Vijayan K. Asari

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.

References

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Paper Citation


in Harvard Style

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 - Volume 1: NCTA, (IJCCI 2014) ISBN 978-989-758-054-3, pages 339-344. DOI: 10.5220/0005157803390344


in Bibtex Style

@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 - Volume 1: NCTA, (IJCCI 2014)},
year={2014},
pages={339-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005157803390344},
isbn={978-989-758-054-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)
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