A robust parametric estimator for single-trial movement related brain potentials

Author

Lange, Daniel H. ; Inbar, Gideon F.

Author_Institution

Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel

Volume

43

Issue

4

fYear

1996

fDate

4/1/1996 12:00:00 AM

Firstpage

341

Lastpage

347

Abstract

Current estimators for single-trial evoked potentials (EP´s) require a signal-to-noise ratio (SNR) of 0 dB or better to obtain high quality estimations, yet many types of EP´s suffer from substantially lower SNR´s. This paper presents a robust-evoked-potential-estimator (REPE) facilitating high quality estimations of single movement related EP´s with a relatively low SNR. The estimator is based on a standard ARX model, enhanced to support estimation under poor SNR conditions. The REPE was tested successfully on a computer simulated data set giving reliable single-trial estimations for the low SNR range of around -20 dB. The REPE was also applied to experimental data, producing clear single-trial estimations of movement related brain signals recorded in a classic scenario of self-paced finger tapping experiment.

Keywords

bioelectric potentials; biomechanics; electroencephalography; medical signal processing; parameter estimation; -20 dB; 0 dB; computer simulated data set; experimental data; robust parametric estimator; self-paced finger tapping experiment; signal-to-noise ratio; single-trial movement related brain potentials; standard ARX model; Brain modeling; Computational modeling; Computer simulation; Electroencephalography; Fingers; Robustness; Signal generators; Signal processing; Signal to noise ratio; Testing; Algorithms; Artifacts; Brain; Electroencephalography; Evoked Potentials; Fingers; Humans; Models, Neurological; Movement; Signal Processing, Computer-Assisted;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/10.486254

Filename

486254