Literature DB >> 23366796

Detection of event-related desynchronization during attempted and imagined movements in tetraplegics for brain switch control.

Yvonne Blokland1, Rutger Vlek, Betül Karaman, Fatma Özin, Dick Thijssen, Thijs Eijsvogels, Willy Colier, Marianne Floor-Westerdijk, Jörgen Bruhn, Jason Farquhar.   

Abstract

Motor-impaired individuals such as tetraplegics could benefit from Brain-Computer Interfaces with an intuitive control mechanism, for instance for the control of a neuroprosthesis. Whereas BCI studies in healthy users commonly focus on motor imagery, for the eventual target users, namely patients, attempted movements could potentially be a more promising alternative. In the current study, EEG frequency information was used for classification of both imagined and attempted movements in tetraplegics. Although overall classification rates were considerably lower for tetraplegics than for the control group, both imagined and attempted movement were detectable. Classification rates were significantly higher for the attempted movement condition, with a mean rate of 77%. These results suggest that attempted movement is an appropriate task for BCI control in long-term paralysis patients.

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Year:  2012        PMID: 23366796     DOI: 10.1109/EMBC.2012.6346835

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  9 in total

1.  Give me a sign: decoding four complex hand gestures based on high-density ECoG.

Authors:  M G Bleichner; Z V Freudenburg; J M Jansma; E J Aarnoutse; M J Vansteensel; N F Ramsey
Journal:  Brain Struct Funct       Date:  2014-10-02       Impact factor: 3.270

2.  Upper limb movements can be decoded from the time-domain of low-frequency EEG.

Authors:  Patrick Ofner; Andreas Schwarz; Joana Pereira; Gernot R Müller-Putz
Journal:  PLoS One       Date:  2017-08-10       Impact factor: 3.240

3.  Classification of Articulator Movements and Movement Direction from Sensorimotor Cortex Activity.

Authors:  E Salari; Z V Freudenburg; M P Branco; E J Aarnoutse; M J Vansteensel; N F Ramsey
Journal:  Sci Rep       Date:  2019-10-02       Impact factor: 4.379

Review 4.  Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control.

Authors:  Gernot R Müller-Putz; Reinmar J Kobler; Joana Pereira; Catarina Lopes-Dias; Lea Hehenberger; Valeria Mondini; Víctor Martínez-Cagigal; Nitikorn Srisrisawang; Hannah Pulferer; Luka Batistić; Andreea I Sburlea
Journal:  Front Hum Neurosci       Date:  2022-03-11       Impact factor: 3.169

Review 5.  Determining optimal mobile neurofeedback methods for motor neurorehabilitation in children and adults with non-progressive neurological disorders: a scoping review.

Authors:  Ahad Behboodi; Walker A Lee; Victoria S Hinchberger; Diane L Damiano
Journal:  J Neuroeng Rehabil       Date:  2022-09-28       Impact factor: 5.208

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

Review 7.  Motor imagery reinforces brain compensation of reach-to-grasp movement after cervical spinal cord injury.

Authors:  Sébastien Mateo; Franck Di Rienzo; Vance Bergeron; Aymeric Guillot; Christian Collet; Gilles Rode
Journal:  Front Behav Neurosci       Date:  2015-09-11       Impact factor: 3.558

8.  Comparison of EEG-features and classification methods for motor imagery in patients with disorders of consciousness.

Authors:  Yvonne Höller; Jürgen Bergmann; Aljoscha Thomschewski; Martin Kronbichler; Peter Höller; Julia S Crone; Elisabeth V Schmid; Kevin Butz; Raffaele Nardone; Eugen Trinka
Journal:  PLoS One       Date:  2013-11-25       Impact factor: 3.240

9.  Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis.

Authors:  Zhongfei Bai; Kenneth N K Fong; Jack Jiaqi Zhang; Josephine Chan; K H Ting
Journal:  J Neuroeng Rehabil       Date:  2020-04-25       Impact factor: 4.262

  9 in total

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