Literature DB >> 24144637

Mobile EEG and its potential to promote the theory and application of imagery-based motor rehabilitation.

Cornelia Kranczioch1, Catharina Zich2, Irina Schierholz2, Annette Sterr3.   

Abstract

Studying the brain in its natural state remains a major challenge for neuroscience. Solving this challenge would not only enable the refinement of cognitive theory, but also provide a better understanding of cognitive function in the type of complex and unpredictable situations that constitute daily life, and which are often disturbed in clinical populations. With mobile EEG, researchers now have access to a tool that can help address these issues. In this paper we present an overview of technical advancements in mobile EEG systems and associated analysis tools, and explore the benefits of this new technology. Using the example of motor imagery (MI) we will examine the translational potential of MI-based neurofeedback training for neurological rehabilitation and applied research.
© 2013.

Keywords:  BCI; Brain computer interface; MI; Mobile EEG; Motor imagery; Neurofeedback; Neurological rehabilitation; Wireless EEG

Mesh:

Year:  2013        PMID: 24144637     DOI: 10.1016/j.ijpsycho.2013.10.004

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  18 in total

1.  Investigation of the effect of EEG-BCI on the simultaneous execution of flight simulation and attentional tasks.

Authors:  Giovanni Vecchiato; Gianluca Borghini; Pietro Aricò; Ilenia Graziani; Anton Giulio Maglione; Patrizia Cherubino; Fabio Babiloni
Journal:  Med Biol Eng Comput       Date:  2015-12-08       Impact factor: 2.602

2.  A Usability Study of Low-cost Wireless Brain-Computer Interface for Cursor Control Using Online Linear Model.

Authors:  Reza Abiri; Soheil Borhani; Justin Kilmarx; Connor Esterwood; Yang Jiang; Xiaopeng Zhao
Journal:  IEEE Trans Hum Mach Syst       Date:  2020-05-14       Impact factor: 2.968

3.  Exploring miniaturized EEG electrodes for brain-computer interfaces. An EEG you do not see?

Authors:  Martin G Bleichner; Micha Lundbeck; Matthias Selisky; Falk Minow; Manuela Jäger; Reiner Emkes; Stefan Debener; Maarten De Vos
Journal:  Physiol Rep       Date:  2015-04

4.  Proposing Metrics for Benchmarking Novel EEG Technologies Towards Real-World Measurements.

Authors:  Anderson S Oliveira; Bryan R Schlink; W David Hairston; Peter König; Daniel P Ferris
Journal:  Front Hum Neurosci       Date:  2016-05-10       Impact factor: 3.169

5.  Combined Action Observation and Motor Imagery Neurofeedback for Modulation of Brain Activity.

Authors:  Christopher L Friesen; Timothy Bardouille; Heather F Neyedli; Shaun G Boe
Journal:  Front Hum Neurosci       Date:  2017-01-10       Impact factor: 3.169

Review 6.  Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach.

Authors:  Simon Ladouce; David I Donaldson; Paul A Dudchenko; Magdalena Ietswaart
Journal:  Front Hum Neurosci       Date:  2017-01-12       Impact factor: 3.169

Review 7.  Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation.

Authors:  Leonardo Furlan; Adriana Bastos Conforto; Leonardo G Cohen; Annette Sterr
Journal:  Neural Plast       Date:  2015-12-30       Impact factor: 3.599

Review 8.  Categorisation of Mobile EEG: A Researcher's Perspective.

Authors:  Anthony D Bateson; Heidi A Baseler; Kevin S Paulson; Fayyaz Ahmed; Aziz U R Asghar
Journal:  Biomed Res Int       Date:  2017-12-04       Impact factor: 3.411

9.  A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.

Authors:  Hendrik Wöhrle; Marc Tabie; Su Kyoung Kim; Frank Kirchner; Elsa Andrea Kirchner
Journal:  Sensors (Basel)       Date:  2017-07-03       Impact factor: 3.576

10.  Improved Volitional Recall of Motor-Imagery-Related Brain Activation Patterns Using Real-Time Functional MRI-Based Neurofeedback.

Authors:  Epifanio Bagarinao; Akihiro Yoshida; Mika Ueno; Kazunori Terabe; Shohei Kato; Haruo Isoda; Toshiharu Nakai
Journal:  Front Hum Neurosci       Date:  2018-04-24       Impact factor: 3.169

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