A Magnetoencephalographic/Encephalographic (MEG/EEG) Brain-Computer Interface Driver for Interactive iOS Mobile Videogame Applications Utilizing the Hadoop Ecosystem, MongoDB, and Cassandra NoSQL Databases

In Phase I, we collected data on five subjects yielding over 90% positive performance in Magnetoencephalographic (MEG) mid-and post-movement activity. In addition, a driver was developed that substituted the actions of the Brain Computer Interface (BCI) as mouse button presses for real-time use in v...

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Bibliographische Detailangaben
Veröffentlicht in:	Diseases Jg. 6; H. 4; S. 89
1. Verfasser:	McClay, Wilbert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 28.09.2018 MDPI
Schlagworte:	Bayesian analysis Brain brain-computer interface Cassandra Computational neuroscience Computer & video games Computer applications Data acquisition EEG Electroencephalography Emotiv EPOC headset encephalographic (EEG) Factor analysis Flight Hadoop Ecosystem Implants Interfaces iOS Mobile Applications Learning algorithms Machine learning machine learning algorithms magnetoencephalographic (MEG) Magnetoencephalography MongoDB OpenVibe Sensors Signal processing United States > US California Hadoop Ecosystem magnetoencephalographic (MEG) brain-computer interface Cassandra OpenVibe Emotiv EPOC headset MongoDB iOS Mobile Applications encephalographic (EEG) machine learning algorithms
ISSN:	2079-9721, 2079-9721
Online-Zugang:	Volltext
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