Literature DB >> 19535289

Single-trial discrimination of type and speed of wrist movements from EEG recordings.

Ying Gu1, Kim Dremstrup, Dario Farina.   

Abstract

OBJECTIVE: The study explored the possibility of identifying movement type and speed from EEG recordings.
METHODS: EEG signals were acquired from 9 healthy volunteers during imagination of four tasks of the right wrist that involved two speeds (fast and slow) and two types of movement (wrist extension and rotation), each repeated 60 times in random order. Average movement-related cortical potentials (MRCPs) were compared among the four tasks. Moreover, single-trial classification was performed using the rebound rate of MRCP and the power in the mu and beta bands as features.
RESULTS: The rebound rate of the average MRCPs was greater for faster than for slower movements but did not depend on the type of movement. Accordingly, pairs of tasks executed at different speeds led to lower misclassification rate than pairs of tasks executed at the same speed. The average misclassification rate between task pairs was 21+/-2% for the best channel and task pair.
CONCLUSION: The task parameter speed can be discriminated in single-trial EEG traces with greater accuracy than the type of movement when tasks are executed at the same joint. SIGNIFICANCE: The speed of movement execution may be included among the variables that characterize imagined tasks for brain-computer interface applications.

Mesh:

Year:  2009        PMID: 19535289     DOI: 10.1016/j.clinph.2009.05.006

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


  24 in total

1.  Detecting and classifying three different hand movement types through electroencephalography recordings for neurorehabilitation.

Authors:  Mads Jochumsen; Imran Khan Niazi; Kim Dremstrup; Ernest Nlandu Kamavuako
Journal:  Med Biol Eng Comput       Date:  2015-12-06       Impact factor: 2.602

2.  EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks.

Authors:  Bradley J Edelman; Bryan Baxter; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2015-08-12       Impact factor: 4.538

3.  Comparison of feature selection and classification methods for a brain-computer interface driven by non-motor imagery.

Authors:  Alvaro Fuentes Cabrera; Dario Farina; Kim Dremstrup
Journal:  Med Biol Eng Comput       Date:  2009-12-30       Impact factor: 2.602

4.  Detecting movement intent from scalp EEG in a novel upper limb robotic rehabilitation system for stroke.

Authors:  Nikunj A Bhagat; James French; Anusha Venkatakrishnan; Nuray Yozbatiran; Gerard E Francisco; Marcia K O'Malley; Jose L Contreras-Vidal
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2014

5.  Offline Identification of Imagined Speed of Wrist Movements in Paralyzed ALS Patients from Single-Trial EEG.

Authors:  Ying Gu; Dario Farina; Ander Ramos Murguialday; Kim Dremstrup; Pedro Montoya; Niels Birbaumer
Journal:  Front Neurosci       Date:  2009-08-10       Impact factor: 4.677

6.  Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges.

Authors:  J D R Millán; R Rupp; G R Müller-Putz; R Murray-Smith; C Giugliemma; M Tangermann; C Vidaurre; F Cincotti; A Kübler; R Leeb; C Neuper; K-R Müller; D Mattia
Journal:  Front Neurosci       Date:  2010-09-07       Impact factor: 4.677

Review 7.  Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.

Authors:  Lichao Xu; Minpeng Xu; Tzyy-Ping Jung; Dong Ming
Journal:  Cogn Neurodyn       Date:  2021-04-10       Impact factor: 3.473

8.  Evaluation of EEG features in decoding individual finger movements from one hand.

Authors:  Ran Xiao; Lei Ding
Journal:  Comput Math Methods Med       Date:  2013-04-24       Impact factor: 2.238

9.  Comparison of movement related cortical potential in healthy people and amyotrophic lateral sclerosis patients.

Authors:  Ying Gu; Dario Farina; Ander R Murguialday; Kim Dremstrup; Niels Birbaumer
Journal:  Front Neurosci       Date:  2013-05-14       Impact factor: 4.677

10.  Decoding Sensorimotor Rhythms during Robotic-Assisted Treadmill Walking for Brain Computer Interface (BCI) Applications.

Authors:  Eliana García-Cossio; Marianne Severens; Bart Nienhuis; Jacques Duysens; Peter Desain; Nöel Keijsers; Jason Farquhar
Journal:  PLoS One       Date:  2015-12-16       Impact factor: 3.240

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