Scherer, Reinhold and Moitzi, Gunter and Daly, Ian and Muller-Putz, Gernot R (2013) On the Use of Games for Noninvasive EEG-Based Functional Brain Mapping. IEEE Transactions on Computational Intelligence and AI in Games, 5 (2). pp. 155-163. DOI https://doi.org/10.1109/tciaig.2013.2250287
Scherer, Reinhold and Moitzi, Gunter and Daly, Ian and Muller-Putz, Gernot R (2013) On the Use of Games for Noninvasive EEG-Based Functional Brain Mapping. IEEE Transactions on Computational Intelligence and AI in Games, 5 (2). pp. 155-163. DOI https://doi.org/10.1109/tciaig.2013.2250287
Scherer, Reinhold and Moitzi, Gunter and Daly, Ian and Muller-Putz, Gernot R (2013) On the Use of Games for Noninvasive EEG-Based Functional Brain Mapping. IEEE Transactions on Computational Intelligence and AI in Games, 5 (2). pp. 155-163. DOI https://doi.org/10.1109/tciaig.2013.2250287
Abstract
The use of statistical models and statistical inference for characterizing the interplay between brain structures and human behavior (functional brain mapping) is common in neuroscience. Statistical methods, however, require the availability of sufficiently large data sets. As a result, experimental paradigms used to collect behavioral trials from individuals are data centered and not user centered. This means that experimental paradigms are tuned to collect as many trials as possible, are generally rather demanding, and are not always motivating or engaging for individuals. Subject cooperation and their compliance with the task may decrease over time. Whenever possible, paradigms are designed to control for factors such as fatigue, attention, and motivation. In this paper, we propose the use of the Kinect motion tracking sensor (Microsoft, Inc., Redmond, WA, USA) in a game-based paradigm for noninvasive electroencephalogram (EEG)-based functional motor mapping. Results from an experimental study with able-bodied subjects playing a virtual ball game suggest that the Kinect sensor is useful for isolating specific movements during the interaction with the game, and that the computed EEG patterns for hand and feet movements are in agreement with results described in the literature.
Item Type: | Article |
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Uncontrolled Keywords: | Brain-computer interface (BCI); electroencephalogram (EEG); functional brain mapping; motion tracking; serious games |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 27 May 2021 13:53 |
Last Modified: | 30 Oct 2024 17:34 |
URI: | http://repository.essex.ac.uk/id/eprint/25473 |