Literature DB >> 22832032

Lingual electrotactile stimulation as an alternative sensory feedback pathway for brain-computer interface applications.

J Adam Wilson1, Léo M Walton, Mitch Tyler, Justin Williams.   

Abstract

This article describes a new method of providing feedback during a brain-computer interface movement task using a non-invasive, high-resolution electrotactile vision substitution system. We compared the accuracy and movement times during a center-out cursor movement task, and found that the task performance with tactile feedback was comparable to visual feedback for 11 participants. These subjects were able to modulate the chosen BCI EEG features during both feedback modalities, indicating that the type of feedback chosen does not matter provided that the task information is clearly conveyed through the chosen medium. In addition, we tested a blind subject with the tactile feedback system, and found that the training time, accuracy, and movement times were indistinguishable from results obtained from subjects using visual feedback. We believe that BCI systems with alternative feedback pathways should be explored, allowing individuals with severe motor disabilities and accompanying reduced visual and sensory capabilities to effectively use a BCI.

Entities:  

Mesh:

Year:  2012        PMID: 22832032     DOI: 10.1088/1741-2560/9/4/045007

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  14 in total

1.  BCI-FES: could a new rehabilitation device hold fresh promise for stroke patients?

Authors:  Brittany M Young; Justin Williams; Vivek Prabhakaran
Journal:  Expert Rev Med Devices       Date:  2014-07-25       Impact factor: 3.166

2.  The critical stability task: quantifying sensory-motor control during ongoing movement in nonhuman primates.

Authors:  Kristin M Quick; Jessica L Mischel; Patrick J Loughlin; Aaron P Batista
Journal:  J Neurophysiol       Date:  2018-06-27       Impact factor: 2.714

3.  Non-linearity of Skin Properties in Electrotactile Applications: Identification and Mitigation.

Authors:  Mehdi Rahimi; Fang Jiang; Yantao Shen
Journal:  IEEE Access       Date:  2019-11-25       Impact factor: 3.367

4.  BCI-FES With Multimodal Feedback for Motor Recovery Poststroke.

Authors:  Alexander B Remsik; Peter L E van Kan; Shawna Gloe; Klevest Gjini; Leroy Williams; Veena Nair; Kristin Caldera; Justin C Williams; Vivek Prabhakaran
Journal:  Front Hum Neurosci       Date:  2022-07-06       Impact factor: 3.473

Review 5.  A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke.

Authors:  Alexander Remsik; Brittany Young; Rebecca Vermilyea; Laura Kiekhoefer; Jessica Abrams; Samantha Evander Elmore; Paige Schultz; Veena Nair; Dorothy Edwards; Justin Williams; Vivek Prabhakaran
Journal:  Expert Rev Med Devices       Date:  2016-05       Impact factor: 3.166

6.  Designing Guiding Systems for Brain-Computer Interfaces.

Authors:  Nataliya Kosmyna; Anatole Lécuyer
Journal:  Front Hum Neurosci       Date:  2017-07-31       Impact factor: 3.169

7.  Perceived Intensity and Discrimination Ability for Lingual Electrotactile Stimulation Depends on Location and Orientation of Electrodes.

Authors:  Joel Moritz; Philip Turk; John D Williams; Leslie M Stone-Roy
Journal:  Front Hum Neurosci       Date:  2017-04-21       Impact factor: 3.169

8.  Case report: post-stroke interventional BCI rehabilitation in an individual with preexisting sensorineural disability.

Authors:  Brittany M Young; Zack Nigogosyan; Veena A Nair; Léo M Walton; Jie Song; Mitchell E Tyler; Dorothy F Edwards; Kristin Caldera; Justin A Sattin; Justin C Williams; Vivek Prabhakaran
Journal:  Front Neuroeng       Date:  2014-06-24

9.  Brain-Computer Interface Training after Stroke Affects Patterns of Brain-Behavior Relationships in Corticospinal Motor Fibers.

Authors:  Brittany M Young; Julie M Stamm; Jie Song; Alexander B Remsik; Veena A Nair; Mitchell E Tyler; Dorothy F Edwards; Kristin Caldera; Justin A Sattin; Justin C Williams; Vivek Prabhakaran
Journal:  Front Hum Neurosci       Date:  2016-09-16       Impact factor: 3.169

10.  Machine Learning Classification to Identify the Stage of Brain-Computer Interface Therapy for Stroke Rehabilitation Using Functional Connectivity.

Authors:  Rosaleena Mohanty; Anita M Sinha; Alexander B Remsik; Keith C Dodd; Brittany M Young; Tyler Jacobson; Matthew McMillan; Jaclyn Thoma; Hemali Advani; Veena A Nair; Theresa J Kang; Kristin Caldera; Dorothy F Edwards; Justin C Williams; Vivek Prabhakaran
Journal:  Front Neurosci       Date:  2018-05-29       Impact factor: 4.677

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