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

Abstract : 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.
Complete list of metadatas

Cited literature [19 references]  Display  Hide  Download

https://hal.inria.fr/hal-02437374
Contributor : Laurent Bougrain <>
Submitted on : Friday, January 17, 2020 - 4:46:51 PM
Last modification on : Saturday, January 18, 2020 - 1:44:51 AM

File

[ICICIC2019-SS19-03] Methodolo...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02437374, version 1

Collections

Citation

Maria 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. International Conference on Innovative Computing, Information and Control, Aug 2019, Seoul, South Korea. pp.8. ⟨hal-02437374⟩

Share

Metrics

Record views

59

Files downloads

118