Methodological Design for Integration of Human EEG Data with Behavioral Analyses into Human-Human/Robot Interactions in a Real-World Context

Maria Rodalyn V. Sanchez (1) , Satoru Mishima (1) , Masayuki Fujiwara (2) , Guangyi Ai (3) , Melanie Jouaiti (4, 5) , Yuliia Kobryn (5, 4) , Sébastien Rimbert (4, 5) , Laurent Bougrain (4, 5) , Patrick Hénaff (5, 4) , Hiroaki Wagatsuma (1, 6, 7)

1 Graduate School of Life Science and Systems Engineering
2 JAIST - Japan Advanced Institute of Science and Technology
3 Department of Computer Science and Technology, Neusoft Institute Guangdong
4 NEUROSYS - Analysis and modeling of neural systems by a system neuroscience approach
5 LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
6 RIKEN CBS - RIKEN Center for Brain Science [Wako]
7 AIST - Artificial Intelligence Research Center [Tokyo]

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.

Mots clés: Human-Robot interaction; Synchronization; Electroencephalography; Eye-tracker; Motion capture system

Domaines: Robotique [cs.RO]; Interface homme-machine [cs.HC]; Traitement du signal et de l'image [eess.SP]

Maria Rodalyn V. Sanchez, Satoru Mishima, Masayuki Fujiwara, Guangyi Ai, Melanie Jouaiti, et al.. Methodological Design for Integration of Human EEG Data with Behavioral Analyses into Human-Human/Robot Interactions in a Real-World Context. ICICIC2019 - The 14th International Conference on Innovative Computing, Information and Control, Aug 2019, Seoul, South Korea. pp.8. ⟨hal-02437374⟩