Modified Dominant Mode Rejection Beamformer for Localizing Brain Activities When Data Covariance Matrix Is Rank Deficient
| Autor: | Babak Mohammadzadeh Asl, Alireza Talesh Jafadideh |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Signal processing
Rank (linear algebra) Covariance matrix 0206 medical engineering Biomedical Engineering Brain Magnetoencephalography Electroencephalography Signal Processing Computer-Assisted 02 engineering and technology Signal-To-Noise Ratio 020601 biomedical engineering Signal-to-noise ratio Minimum-variance unbiased estimator Image Processing Computer-Assisted Humans Projection (set theory) Adaptive beamformer Algorithm Evoked Potentials Eigenvalues and eigenvectors Algorithms Mathematics |
| Zdroj: | IEEE transactions on bio-medical engineering. 66(8) |
| ISSN: | 1558-2531 |
| Popis: | Objective : Minimum variance beamformer (MVB) and its extensions fail in localizing short time brain activities particularly evoked potentials because of rank deficiency or inaccurate estimation of a data covariance matrix. In this paper, the conventional dominant mode rejection (DMR) adaptive beamformer is modified to localize brain short time activities. Methods : In the modified DMR, it is attempted to obtain a well-conditioned covariance matrix by dividing the eigenvalues of the data covariance matrix into dominant, medium, and small eigenvalues and then modifying medium and small parts. The performance of the proposed approach is compared with diagonal loading MVB (DL_MVB) and fast fully adaptive (FFA) beamformer by using simulated event-related potentials and real event-related field data. Eigenspace versions of DL_MVB and modified DMR are also implemented. Results : In all simulations, the modified DMR obtains the least localization error (0–5 mm) and spread radius (0–8 mm) when the signal-to-noise ratio (SNR) varies from 0 to 10 dB with step 1 dB. In real data, the new approach in comparison to two other ones attains the most concentrated power spectrum. Eigenspace projection of DL_MVB presents better results than DL_MVB but worse results than the modified DMR. Applying eigenspace projection on the proposed method improves its performance at high SNR levels. Conclusion : Empirical results illustrate the superiority of the proposed DMR method to the DL_MVB and FFA in localizing brain short time activities. Significance : The proposed method can be utilized in source localization of epilepsy for presurgical clinical evaluation purpose and also in applications dealing with the localization of evoked potentials and fields. |
| Databáze: | OpenAIRE |
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