Literature DB >> 15188863

Toward a direct brain interface based on human subdural recordings and wavelet-packet analysis.

Bernhard Graimann1, Jane E Huggins, Simon P Levine, Gert Pfurtscheller.   

Abstract

Highly accurate asynchronous detection of movement related patterns in individual electrocorticogram channels has been shown using detection based on either event-related potentials (ERPs) or event-related desynchronization and synchronization (ERD/ERS). A method using wavelet-packet features selected with a genetic algorithm was proposed to simultaneously detect ERP and ERD/ERS and was tested on data from seven subjects and four motor tasks. The proposed wavelet method performed better than previous methods with perfect detection for four subject/task combinations and hit percentages greater than 90% with false positive percentages less than 15% for at least one task for all seven subjects.

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Year:  2004        PMID: 15188863     DOI: 10.1109/TBME.2004.826671

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  21 in total

1.  A comparison approach toward finding the best feature and classifier in cue-based BCI.

Authors:  R Boostani; B Graimann; M H Moradi; G Pfurtscheller
Journal:  Med Biol Eng Comput       Date:  2007-02-23       Impact factor: 2.602

2.  Delta band contribution in cue based single trial classification of real and imaginary wrist movements.

Authors:  Aleksandra Vuckovic; Francisco Sepulveda
Journal:  Med Biol Eng Comput       Date:  2008-04-17       Impact factor: 2.602

3.  Improving mental task classification by adding high frequency band information.

Authors:  Li Zhang; Wei He; Chuanhong He; Ping Wang
Journal:  J Med Syst       Date:  2010-02       Impact factor: 4.460

4.  A comparison of univariate, vector, bilinear autoregressive, and band power features for brain-computer interfaces.

Authors:  Clemens Brunner; Martin Billinger; Carmen Vidaurre; Christa Neuper
Journal:  Med Biol Eng Comput       Date:  2011-09-25       Impact factor: 2.602

5.  Electrocorticographic amplitude predicts finger positions during slow grasping motions of the hand.

Authors:  Soumyadipta Acharya; Matthew S Fifer; Heather L Benz; Nathan E Crone; Nitish V Thakor
Journal:  J Neural Eng       Date:  2010-05-20       Impact factor: 5.379

6.  A self-paced brain interface system that uses movement related potentials and changes in the power of brain rhythms.

Authors:  Mehrdad Fatourechi; Gary E Birch; Rabab K Ward
Journal:  J Comput Neurosci       Date:  2007-01-10       Impact factor: 1.621

7.  Optimal spacing of surface electrode arrays for brain-machine interface applications.

Authors:  Marc W Slutzky; Luke R Jordan; Todd Krieg; Ming Chen; David J Mogul; Lee E Miller
Journal:  J Neural Eng       Date:  2010-03-02       Impact factor: 5.379

8.  Real-time two-dimensional asynchronous control of a computer cursor with a single subdural electrode.

Authors:  César Márquez-Chin; Milos R Popovic; Egor Sanin; Robert Chen; Andres M Lozano
Journal:  J Spinal Cord Med       Date:  2012-09       Impact factor: 1.985

9.  Hidden Markov model and support vector machine based decoding of finger movements using electrocorticography.

Authors:  Tobias Wissel; Tim Pfeiffer; Robert Frysch; Robert T Knight; Edward F Chang; Hermann Hinrichs; Jochem W Rieger; Georg Rose
Journal:  J Neural Eng       Date:  2013-09-18       Impact factor: 5.379

10.  A hybrid PDMS-Parylene subdural multi-electrode array.

Authors:  Manuel Ochoa; Pinghung Wei; Andrew J Wolley; Kevin J Otto; Babak Ziaie
Journal:  Biomed Microdevices       Date:  2013-06       Impact factor: 2.838

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