Proceedings ArticleDOI
Low complexity approach for controlling a robotic arm using the Emotiv EPOC headset
Santiago Aguiar,Wilson Yanez,Diego S. Benitez +2 more
- pp 1-6
TLDR
The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%) and allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm.Abstract:
A relative simple approach based on the computation of the area of a parametric curve produced by the 2D space representation of a set of parametric experimental functions defined by the signals of only two active EEG electrodes of a low cost neuroheadset (Emotiv EPOC) is proposed on this paper for the fast recognition of eye winks activity as control commands. This approach together with the use of the signals from the gyroscope available in the EPOC device, allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm. The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%).read more
Citations
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Posted ContentDOI
10 years of EPOC: A scoping review of Emotiv’s portable EEG device
TL;DR: The use of low-cost electroencephalography (EEG) devices has become increasingly available over the last decade as discussed by the authors and one of these devices, Emotiv EPOC, is currently used in a wide variety of settings, including brain-computer interface (BCI) and cognitive neuroscience research.
Book ChapterDOI
EEG-Controlled Prosthetic Arm for Micromechanical Tasks
TL;DR: A novel approach is introduced in this paper to extract eyeblink signals from EEG to control a prosthetic arm using Linear Discriminant Analysis (LDA) and K-Nearest Neighbor (KNN).
Proceedings ArticleDOI
Classification of EEG Signals from Motor Imagery of Hand Grasp Movement Based on Neural Network Approach
TL;DR: The purpose of this study is to discover an appropriate combination for the best classification accuracy of right-hand grasp movement based on EEG headset.
References
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