Methodological Design for Integration of Human EEG Data with Behavioral Analyses into Human-Human/Robot Interactions in a Real-World Context
| Autor: | Maria Sanchez, Satoru Mishima, Masayuki Fujiwara, Guangyi Ai, Melanie Jouaiti, Yuliia Kobryn, Sébastien Rimbert, Laurent Bougrain, Patrick HENAFF, Hiroaki Wagatsuma |
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| Přispěvatelé: | Graduate School of Life Science and Systems Engineering, Japan Advanced Institute of Science and Technology (JAIST), Department of Computer Science and Technology, Neusoft Institute Guangdong, Analysis and modeling of neural systems by a system neuroscience approach (NEUROSYS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), RIKEN Center for Brain Science [Wako] (RIKEN CBS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Artificial Intelligence Research Center [Tokyo] (AIST), National Institute of Advanced Industrial Science and Technology [Tokyo] (AIST), Creativ'Lab, National Institute of Advanced Industrial Science and Technology (AIST), RIKEN Center for Brain Science (RIKEN CBS), Artificial Intelligence Research Center (AIST), Bougrain, Laurent |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Motion capture system
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing Eye-tracker [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO] Human-Robot interaction [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] Electroencephalography [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC] [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC] Synchronization |
| Zdroj: | ICICIC2019-The 14th International Conference on Innovative Computing, Information and Control ICICIC2019-The 14th International Conference on Innovative Computing, Information and Control, Aug 2019, Seoul, South Korea. pp.8 HAL |
| Popis: | International audience; Analysis of human activities is a complex task that needs multifactorial considerations. So an electroencephalographic (EEG) data analysis can be improved by a conjunction of devices that monitor time courses of multiple types of physiological factors of the subject and counterparts when interactions are ongoing in the environment. In this article, we proposed a method to provide the complementary hardware and software treatment that associate devices to be able to synchronize simultaneous data recording to fit the high sampling rate of the EEG signal, such as more than 512 Hz. This method of synchronizing physiological data gathered from three different devices through the use of trigger signals is crucial for an accurate post-analysis and was validated in the experiment. The proposed method is widely applicable in various cases accompanied with EEG measurements and offer a wide possibility in device developments for rehabilitation and communications. |
| Databáze: | OpenAIRE |
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