Literature DB >> 26138148

The effect of multimodal and enriched feedback on SMR-BCI performance.

T Sollfrank1, A Ramsay2, S Perdikis3, J Williamson4, R Murray-Smith5, R Leeb6, J D R Millán7, A Kübler8.   

Abstract

OBJECTIVE: This study investigated the effect of multimodal (visual and auditory) continuous feedback with information about the uncertainty of the input signal on motor imagery based BCI performance. A liquid floating through a visualization of a funnel (funnel feedback) provided enriched visual or enriched multimodal feedback.
METHODS: In a between subject design 30 healthy SMR-BCI naive participants were provided with either conventional bar feedback (CB), or visual funnel feedback (UF), or multimodal (visual and auditory) funnel feedback (MF). Subjects were required to imagine left and right hand movement and were trained to control the SMR based BCI for five sessions on separate days.
RESULTS: Feedback accuracy varied largely between participants. The MF feedback lead to a significantly better performance in session 1 as compared to the CB feedback and could significantly enhance motivation and minimize frustration in BCI use across the five training sessions.
CONCLUSION: The present study demonstrates that the BCI funnel feedback allows participants to modulate sensorimotor EEG rhythms. Participants were able to control the BCI with the funnel feedback with better performance during the initial session and less frustration compared to the CB feedback. SIGNIFICANCE: The multimodal funnel feedback provides an alternative to the conventional cursorbar feedback for training subjects to modulate their sensorimotor rhythms.
Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Brain–computer interfaces; EEG; Feedback; Multimodality; Sensorimotor rhythms

Mesh:

Year:  2015        PMID: 26138148     DOI: 10.1016/j.clinph.2015.06.004

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  8 in total

1.  Heading for new shores! Overcoming pitfalls in BCI design.

Authors:  Ricardo Chavarriaga; Melanie Fried-Oken; Sonja Kleih; Fabien Lotte; Reinhold Scherer
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2016-12-30

2.  Constraints and Adaptation of Closed-Loop Neuroprosthetics for Functional Restoration.

Authors:  Robert Bauer; Alireza Gharabaghi
Journal:  Front Neurosci       Date:  2017-03-13       Impact factor: 4.677

3.  Progressive Training for Motor Imagery Brain-Computer Interfaces Using Gamification and Virtual Reality Embodiment.

Authors:  Filip Škola; Simona Tinková; Fotis Liarokapis
Journal:  Front Hum Neurosci       Date:  2019-09-26       Impact factor: 3.169

4.  "Mine Works Better": Examining the Influence of Embodiment in Virtual Reality on the Sense of Agency During a Binary Motor Imagery Task With a Brain-Computer Interface.

Authors:  Hamzah Ziadeh; David Gulyas; Louise Dørr Nielsen; Steffen Lehmann; Thomas Bendix Nielsen; Thomas Kim Kroman Kjeldsen; Bastian Ilsø Hougaard; Mads Jochumsen; Hendrik Knoche
Journal:  Front Psychol       Date:  2021-12-24

Review 5.  Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review.

Authors:  Daniela Camargo-Vargas; Mauro Callejas-Cuervo; Stefano Mazzoleni
Journal:  Sensors (Basel)       Date:  2021-06-24       Impact factor: 3.576

Review 6.  Challenges and Opportunities for the Future of Brain-Computer Interface in Neurorehabilitation.

Authors:  Colin Simon; David A E Bolton; Niamh C Kennedy; Surjo R Soekadar; Kathy L Ruddy
Journal:  Front Neurosci       Date:  2021-07-02       Impact factor: 4.677

7.  The Effects of Transcranial Direct Current Stimulation (tDCS) on Multitasking Throughput Capacity.

Authors:  Justin Nelson; Richard A McKinley; Chandler Phillips; Lindsey McIntire; Chuck Goodyear; Aerial Kreiner; Lanie Monforton
Journal:  Front Hum Neurosci       Date:  2016-11-29       Impact factor: 3.169

8.  The Impact of Different Visual Feedbacks in User Training on Motor Imagery Control in BCI.

Authors:  Dariusz Zapała; Piotr Francuz; Ewelina Zapała; Natalia Kopiś; Piotr Wierzgała; Paweł Augustynowicz; Andrzej Majkowski; Marcin Kołodziej
Journal:  Appl Psychophysiol Biofeedback       Date:  2018-03
  8 in total

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