Abstract
Ecumenically, the fastest growing segment of Big Data is human biology-related data and the annual data creation is on the order of zetabytes. The implications are global across industries, of which the treatment of brain related illnesses and trauma could see the most significant and immediate effects. The next generation of health care IT and sensory devices are acquiring and storing massive amounts of patient related data. An innovative Brain-Computer Interface (BCI) for interactive 3D visualization is presented utilizing the Hadoop Ecosystem for data analysis and storage. The BCI is an implementation of Bayesian factor analysis algorithms that can distinguish distinct thought actions using magneto encephalographic (MEG) brain signals. We have collected data on five subjects yielding 90% positive performance in MEG mid- and post-movement activity. We describe a driver that substitutes the actions of the BCI as mouse button presses for real-time use in visual simulations. This process has been added into a flight visualization demonstration. By thinking left or right, the user experiences the aircraft turning in the chosen direction. The driver components of the BCI can be compiled into any software and substitute a user’s intent for specific keyboard strikes or mouse button presses. The BCI’s data analytics of a subject’s MEG brainwaves and flight visualization performance are stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse.
Highlights
The use of brain-computer interfaces (BCIs), sometimes called mind-machine interfacing (MMI) or brain-machine interfacing (BMI), has been evolving for many years. These interfaces are used for both noninvasive procedures (such as magneto encephalography (MEG) and electroencephalography (EEG))
What follows is a brief discussion of the history and importance of BCIs in the noninvasive procedures of magneto encephalographic (MEG) and EEG as they relate to recent applications ranging from interactive video game technology to robotics and mobile applications
The Mind Balance interface uses direct electroencephalography (EEG), cerebral data nodes, and Bluetooth wireless technology, all fitted into a sophisticated “Cerebus”
Summary
The use of brain-computer interfaces (BCIs), sometimes called mind-machine interfacing (MMI) or brain-machine interfacing (BMI), has been evolving for many years. These interfaces are used for both noninvasive procedures (such as magneto encephalography (MEG) and electroencephalography (EEG)). Headset to capture brain activity and feed it into a C# signal processing engine, which subsequently analyzes those signals and determines whether a subject is looking to the left or right. In this game, a frog-like character, “MAWG,” must be walked across a tightrope, using one’s mental focus. Yu and Wang elaborate further and advocate the use of the Hadoop ecosystem as a means to distribute, store, manage and share the massive data and why it is an important issue [20]
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