Abstract
Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention. Recent advances have been developed for the BCI-based drone control system as the demand for drone control increases. Especially, drone swarm control based on brain signals could provide various industries such as military service or industry disaster. This paper presents a prototype of a brain-swarm interface system for a variety of scenarios using a visual imagery paradigm. We designed the experimental environment that could acquire brain signals under a drone swarm control simulator environment. Through the system, we collected the electroencephalogram (EEG) signals with respect to four different scenarios. Seven subjects participated in our experiment and evaluated classification performances using the basic machine learning algorithm. The grand average classification accuracy is higher than the chance level accuracy. Hence, we could confirm the feasibility of the drone swarm control system based on EEG signals for performing high-level tasks.
Original language | English |
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Title of host publication | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781728147079 |
DOIs | |
Publication status | Published - 2020 Feb |
Event | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 - Gangwon, Korea, Republic of Duration: 2020 Feb 26 → 2020 Feb 28 |
Publication series
Name | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 |
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Conference
Conference | 8th International Winter Conference on Brain-Computer Interface, BCI 2020 |
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Country/Territory | Korea, Republic of |
City | Gangwon |
Period | 20/2/26 → 20/2/28 |
Bibliographical note
Funding Information:Research was funded by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning).
Publisher Copyright:
© 2020 IEEE.
Keywords
- brain-computer interface
- drone swarm control
- electroencephalogram
- visual imagery
ASJC Scopus subject areas
- Behavioral Neuroscience
- Cognitive Neuroscience
- Artificial Intelligence
- Human-Computer Interaction