Paper
12 March 2008 Real-time classification of activated brain areas for fMRI-based human-brain-interfaces
Tobias Moench, Maurice Hollmann, Ramona Grzeschik, Charles Mueller, Ralf Luetzkendorf, Sebastian Baecke, Michael Luchtmann, Daniela Wagegg, Johannes Bernarding
Author Affiliations +
Abstract
Functional MR imaging (fMRI) enables to detect different activated brain areas according to the performed tasks. However, data are usually evaluated after the experiment, which prohibits intra-experiment optimization or more sophisticated applications such as biofeedback experiments. Using a human-brain-interface (HBI), subjects are able to communicate with external programs, e.g. to navigate through virtual scenes, or to experience and modify their own brain activation. These applications require the real-time analysis and classification of activated brain areas. Our paper presents first results of different strategies for real-time pattern analysis and classification realized within a flexible experiment control system that enables the volunteers to move through a 3D virtual scene in real-time using finger tapping tasks, and alternatively only thought-based tasks.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tobias Moench, Maurice Hollmann, Ramona Grzeschik, Charles Mueller, Ralf Luetzkendorf, Sebastian Baecke, Michael Luchtmann, Daniela Wagegg, and Johannes Bernarding "Real-time classification of activated brain areas for fMRI-based human-brain-interfaces", Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69161R (12 March 2008); https://doi.org/10.1117/12.769848
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Statistical analysis

Functional magnetic resonance imaging

Brain

Scanners

Image classification

Magnetic resonance imaging

Data analysis

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