Talk · ACM/IEEE International Conference on Human-Robot Interaction · March 1, 2018
Brain-Computer Interface Humanoid Pre-trained for Interaction with People
Batyrkhan Saduanov, Dana Tokmurzina, Tohid Alizadeh, Berdakh Abibullaev
Abstract
This study presents a Brain-Computer Interface (BCI) based remotepresence system for humanoid NAO robot. The system would beuseful for partially or fully paralyzed patients to interact with peo-ple and live active social life. A P300 based BCI is used to controlhigh-level desires of the humanoid and visual stimulus presenta-tion is implemented to control a humanoid robot. "Programmingby Demonstration (PbD)" methods are used to train the robot toperform human interactive actions and NAO robot native speller isused to talk with people. In general, the proposed solution combinestwo major techniques: Programming by demonstration and BCI. Anexperiment is designed and conducted on 5 different healthy sub-jects to perform a handshake, waving, walking and etc., verifyingthe applicability of the proposed approach.
More by Berdakh Abibullaev
- Onset Review: traceable analysis of high-frequency oscillations and seizure onset in intracranial EEGZenodo · 2026
- Multi-scale EEG feature decoding with Swin Transformers for subject independent motor imagery BCIsScientific Reports · 2026 · Citations: 12
- Generative data augmentation for machine learning-based quantitative cancer cell detection using optical fiber biosensorsEPJ Web of Conferences · 2026
- Deep learning in intracranial EEG for seizure detection: advances, challenges, and clinical applicationsFrontiers in Neuroscience · 2025 · Citations: 13