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

Research Project

Project/Area Number 15H06922
Research Category

Grant-in-Aid for Research Activity Start-up

Allocation TypeSingle-year Grants
Research Field Brain biometrics
Research InstitutionAdvanced Telecommunications Research Institute International

Principal Investigator

Penaloza Christian  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
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
KeywordsBCI / Brain Computer Interface / Android / Motor Imagery / BMI / Deep Learning / Brain Machine Interface / Error Potential / Robot Learning
Outline of Final 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.

Report

(3 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Annual Research Report
  • Research Products

    (3 results)

All 2017 2016

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Acknowledgement Compliant: 1 results) Presentation (1 results) Book (1 results)

  • [Journal Article] {Android Feedback based Training modulates Sensorimotor Rhythms during Motor Imagery2017

    • Author(s)
      Christian Penaloza, Maryam Alimardani and Shuichi Nishio
    • Journal Title

      IEEE Transactions on Neural Systems

      Volume: なし

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] Detecting error-related negativity while operating Android with BMI2016

    • Author(s)
      Kodai Shatani, Christian I. Penaloza, Shuichi Nishio
    • Organizer
      The 30th Annual Conference of the Japanese Society for Artificial Intellitgence (JSAI 2016)
    • Place of Presentation
      KitaKyushu, Japan
    • Year and Date
      2016-06-06
    • Related Report
      2016 Annual Research Report
  • [Book] Book Chapter: Towards Brain-controlled Androids: From Science Fiction to Reality2017

    • Author(s)
      Christian I. Penaloza, Shuichi Nishio and Hiroshi Ishiguro
    • Publisher
      IGI-Global
    • Related Report
      2016 Annual Research Report

URL: 

Published: 2015-08-26   Modified: 2018-03-22  

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