Literature DB >> 21097231

Online performance evaluation of motor imagery BCI with augmented-reality virtual hand feedback.

Zheng Yang Chin1, Kai Keng Ang, Chuanchu Wang, Cuntai Guan.   

Abstract

The online performance of a motor imagery-based Brain-Computer Interface (MI-BCI) influences its effectiveness and usability in real-world clinical applications such as the restoration of motor control. The online performance depends on factors such as the different feedback techniques and motivation of the subject. This paper investigates the online performance of the MI-BCI with an augmented-reality (AR) 3D virtual hand feedback. The subject experiences the interaction with 3D virtual hands, which have been superimposed onto his real hands and displayed on the computer monitor from a first person point-of-view. While performing motor imagery, he receives continuous visual feedback from the MI-BCI in the form of different degrees of reaching and grasping actions of the 3D virtual hands with other virtual objects. The AR feedback is compared with the conventional horizontal bar feedback on 8 subjects, of whom 7 are BCI-naïve. The subjects found the AR feedback to be more engaging and motivating. Despite the higher mental workload involved in the AR feedback, their online MI-BCI performance compared to the conventional horizontal bar feedback was not affected. The results provide motivation to further develop and refine the AR feedback protocol for MI-BCI.

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Year:  2010        PMID: 21097231     DOI: 10.1109/IEMBS.2010.5627911

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  2 in total

1.  A Study of Various Feature Extraction Methods on a Motor Imagery Based Brain Computer Interface System.

Authors:  Seyed Navid Resalat; Valiallah Saba
Journal:  Basic Clin Neurosci       Date:  2016-01

2.  An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study.

Authors:  Amaia Benitez-Andonegui; Rodion Burden; Richard Benning; Rico Möckel; Michael Lührs; Bettina Sorger
Journal:  Front Neurosci       Date:  2020-04-28       Impact factor: 4.677

  2 in total

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