Literature DB >> 26891487

Movement Anticipation and EEG: Implications for BCI-Contingent Robot Therapy.

Sumner Norman, Mark Dennison, Eric Wolbrecht, Steven Cramer, Ramesh Srinivasan, David Reinkensmeyer.   

Abstract

Brain-computer interfacing is a technology that has the potential to improve patient engagement in robot-assisted rehabilitation therapy. For example, movement intention reduces mu (8-13 Hz) oscillation amplitude over the sensorimotor cortex, a phenomenon referred to as event-related desynchronization (ERD). In an ERD-contingent assistance paradigm, initial BCI-enhanced robotic therapy studies have used ERD to provide robotic assistance for movement. Here we investigated how ERD changed as a function of audio-visual stimuli, overt movement from the participant, and robotic assistance. Twelve unimpaired subjects played a computer game designed for rehabilitation therapy with their fingers using the FINGER robotic exoskeleton. In the game, the participant and robot matched movement timing to audio-visual stimuli in the form of notes approaching a target on the screen set to the consistent beat of popular music. The audio-visual stimulation of the game alone did not cause ERD, before or after training. In contrast, overt movement by the subject caused ERD, whether or not the robot assisted the finger movement. Notably, ERD was also present when the subjects remained passive and the robot moved their fingers to play the game. This ERD occurred in anticipation of the passive finger movement with similar onset timing as for the overt movement conditions. These results demonstrate that ERD can be contingent on expectation of robotic assistance; that is, the brain generates an anticipatory ERD in expectation of a robot-imposed but predictable movement. This is a caveat that should be considered in designing BCIs for enhancing patient effort in robotically-assisted therapy.

Entities:  

Year:  2016        PMID: 26891487      PMCID: PMC5548638          DOI: 10.1109/TNSRE.2016.2528167

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  42 in total

Review 1.  Internal models for motor control and trajectory planning.

Authors:  M Kawato
Journal:  Curr Opin Neurobiol       Date:  1999-12       Impact factor: 6.627

2.  Motor learning elicited by voluntary drive.

Authors:  Martin Lotze; Christoph Braun; Niels Birbaumer; Silke Anders; Leonardo G Cohen
Journal:  Brain       Date:  2003-04       Impact factor: 13.501

3.  Event-related beta EEG-changes during passive and attempted foot movements in paraplegic patients.

Authors:  Gernot R Müller-Putz; Doris Zimmermann; Bernhard Graimann; Kurt Nestinger; Gerd Korisek; Gert Pfurtscheller
Journal:  Brain Res       Date:  2006-12-22       Impact factor: 3.252

4.  Does post-movement beta synchronization reflect an idling motor cortex?

Authors:  F Cassim; C Monaca; W Szurhaj; J L Bourriez; L Defebvre; P Derambure; J D Guieu
Journal:  Neuroreport       Date:  2001-12-04       Impact factor: 1.837

Review 5.  Robotics and other devices in the treatment of patients recovering from stroke.

Authors:  Bruce T Volpe; Mark Ferraro; Daniel Lynch; Paul Christos; Jennifer Krol; Christine Trudell; Hermano I Krebs; Neville Hogan
Journal:  Curr Neurol Neurosci Rep       Date:  2005-11       Impact factor: 5.081

6.  Brain-machine interface in chronic stroke rehabilitation: a controlled study.

Authors:  Ander Ramos-Murguialday; Doris Broetz; Massimiliano Rea; Leonhard Läer; Ozge Yilmaz; Fabricio L Brasil; Giulia Liberati; Marco R Curado; Eliana Garcia-Cossio; Alexandros Vyziotis; Woosang Cho; Manuel Agostini; Ernesto Soares; Surjo Soekadar; Andrea Caria; Leonardo G Cohen; Niels Birbaumer
Journal:  Ann Neurol       Date:  2013-08-07       Impact factor: 10.422

7.  Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke.

Authors:  Ethan Buch; Cornelia Weber; Leonardo G Cohen; Christoph Braun; Michael A Dimyan; Tyler Ard; Jurgen Mellinger; Andrea Caria; Surjo Soekadar; Alissa Fourkas; Niels Birbaumer
Journal:  Stroke       Date:  2008-02-07       Impact factor: 7.914

8.  Decoding individual finger movements from one hand using human EEG signals.

Authors:  Ke Liao; Ran Xiao; Jania Gonzalez; Lei Ding
Journal:  PLoS One       Date:  2014-01-08       Impact factor: 3.240

9.  Proprioceptive feedback and brain computer interface (BCI) based neuroprostheses.

Authors:  Ander Ramos-Murguialday; Markus Schürholz; Vittorio Caggiano; Moritz Wildgruber; Andrea Caria; Eva Maria Hammer; Sebastian Halder; Niels Birbaumer
Journal:  PLoS One       Date:  2012-10-05       Impact factor: 3.240

10.  Modulation of event-related desynchronization in robot-assisted hand performance: brain oscillatory changes in active, passive and imagined movements.

Authors:  Emanuela Formaggio; Silvia Francesca Storti; Ilaria Boscolo Galazzo; Marialuisa Gandolfi; Christian Geroin; Nicola Smania; Laura Spezia; Andreas Waldner; Antonio Fiaschi; Paolo Manganotti
Journal:  J Neuroeng Rehabil       Date:  2013-02-26       Impact factor: 4.262

View more
  3 in total

1.  Controlling pre-movement sensorimotor rhythm can improve finger extension after stroke.

Authors:  S L Norman; D J McFarland; A Miner; S C Cramer; E T Wolbrecht; J R Wolpaw; D J Reinkensmeyer
Journal:  J Neural Eng       Date:  2018-07-31       Impact factor: 5.379

2.  Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals.

Authors:  Vijaykumar Rajasekaran; Eduardo López-Larraz; Fernando Trincado-Alonso; Joan Aranda; Luis Montesano; Antonio J Del-Ama; Jose L Pons
Journal:  J Neuroeng Rehabil       Date:  2018-01-03       Impact factor: 4.262

3.  Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network.

Authors:  Minmin Miao; Wenjun Hu; Hongwei Yin; Ke Zhang
Journal:  Comput Math Methods Med       Date:  2020-07-20       Impact factor: 2.238

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.