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

Bernhard Graimann; Jane E. Huggins; Simon P. Levine; Gert Pfurtscheller

doi:10.1109/TBME.2004.826671

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

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

Institute of Computer Graphics and Vision (7100)

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	954-962
Journal	IEEE Transactions on Biomedical Engineering
Volume	51
Issue number	6
DOIs	https://doi.org/10.1109/TBME.2004.826671
Publication status	Published - 2004

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10.1109/TBME.2004.826671

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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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AB - 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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DO - 10.1109/TBME.2004.826671

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JO - IEEE Transactions on Biomedical Engineering

JF - IEEE Transactions on Biomedical Engineering

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ER -

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

Abstract

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