2016 Fiscal Year Annual Research Report

Incorporating Deep Learning and Error Potential Feedback to a BMI System to Enhance User Experience

Research Project

Project/Area Number	15H06922
Research Institution	Advanced Telecommunications Research Institute International
Principal Investigator	Penaloza C. 株式会社国際電気通信基礎技術研究所, 石黒浩特別研究所, 研究員 (80753532)
Project Period (FY)	2015-08-28 – 2017-03-31
Keywords	BCI / Brain Computer Interface / Android / Motor Imagery
Outline of Annual Research Achievements	A Brain Machine Interface (BMI) system that integrates an Android robot was sucessfully developed. The android robot provided realistic visual feedback to the user so that he/she could concentrate better and modulate his/her brain activity. A new training protocol that addresses the deficiencies of the classical approach and takes advantage of body-abled user capabilities was proposed. Experimental results suggest that android feedback based BCI training improves the modulation of sensorimotor rhythms during motor imagery task. Moreover, we discovered that the influence of body ownership transfer illusion towards the android induced thrhough a haptic interface might have an effect in the modulation of event related desynchronization/synchronization (ERD/ERS) activity.
Research Progress Status	28年度が最終年度であるため、記入しない。
Strategy for Future Research Activity	28年度が最終年度であるため、記入しない。