Abstract
A central issue in Computational Neuroethology is the fusion of information coming from a wide variety of devices, by computational tools and techniques aiming to correlate the neural substrate and the observable behavior. In this paper we are concerned with the fusion of information from two specific commercial devices, the Emotiv EPOC+ EEG recorder, and the Rokoko motion capture suite based on inertial motion units (IMU). We have built an ad hoc system for synchronized data capture. We test the system on the recognition of simple activities. We are able to confirm that the fusion of the neural activity information and the motion information improves the activity recognition.
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Raw signals need a specific license which we can not pay at this time.
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Acknowledgments
This work has been partially supported by FEDER funds through MINECO project TIN2017-85827-P, and project KK-2018/00071 of the Elkartek 2018 funding program of the Basque Government
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Araquistain, I.B., Garmendia, X., Graña, M., de Lope Asiain, J. (2019). Fusion of Inertial Motion Sensors and Electroencephalogram for Activity Detection. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Understanding the Brain Function and Emotions. IWINAC 2019. Lecture Notes in Computer Science(), vol 11486. Springer, Cham. https://doi.org/10.1007/978-3-030-19591-5_33
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DOI: https://doi.org/10.1007/978-3-030-19591-5_33
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