Percorrer por autor "Lang, E. W."
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- Nonlinear projective techniques to extract artifacts in biomedical signalsPublication . Teixeira, Ana; Tomé, A. M.; Stadlthanner, K.; Lang, E. W.Biomedical signals are generally contaminated with artifacts and noise. In case the artifacts dominate, the useful signal can easily be extracted with projective subspace techniques. Then, biomedical signals which often represent one dimensional time series, need to be transformed to multidimensional signal vectors for the latter techniques to be applicable. The transformation can be achieved by embedding an observed signal in its delayed coordinates. Using this embedding we propose to cluster the resulting feature vectors and apply a singular spectrum analysis (SSA) locally in each cluster to recover the undistorted signals. We also compare the reconstructed signals to results obtained with kernel-PCA. Both nonlinear subspace projection techniques are applied to artificial data to demonstrate the suppression of random noise signals as well as to an electroencephalogram (EEG) signal recorded in the frontal channel to extract its prominent electrooculogram (EOG) interference.
- Subspace techniques to remove artifacts from EEG: A quantitative analysisPublication . Teixeira, Ana; Tome, A. M.; Lang, E. W.; Martins da Silva, A.In this work we discuss and apply projective subspace techniques to both multichannel as well as single channel recordings. The single-channel approach is based on singular spectrum analysis(SSA) and the multichannel approach uses the extended infomax algorithm which is implemented in the opensource toolbox EEGLAB. Both approaches will be evaluated using artificial mixtures of a set of selected EEG signals. The latter were selected visually to contain as the dominant activity one of the characteristic bands of an electroencephalogram (EEG). The evaluation is performed both in the time and frequency domain by using correlation coefficients and coherence function, respectively.
