IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · May 2008
Single-trial EEG source reconstruction for brain-computer interface.
A new way to improve the classification rate of an EEG-based brain-computer interface (BCI) could be to reconstruct the brain sources of EEG and to apply BCI methods to these derived sources instead of raw measured electrode potentials. EEG source reconstruction methods are based on electrophysiological information that could improve the discrimination between BCI tasks. In this paper, we present an EEG source reconstruction method for BCI. ⋯ The features are ranked with mutual information before being fed to a proximal support vector machine. The dataset IV of the BCI competition II and data from four subjects serve as test data. Results show that the EEG inverse solution improves the classification rate and can lead to results comparable to the best currently known methods.
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IEEE Trans Biomed Eng · May 2008
Estimation of the aortic pressure waveform and beat-to-beat relative cardiac output changes from multiple peripheral artery pressure waveforms.
We introduce a patient- and time-specific technique to estimate the clinically more relevant aortic pressure (AP) waveform and beat-to-beat relative changes in cardiac output (CO) from multiple peripheral artery pressure (PAP) waveforms distorted by wave reflections. The basic idea of the technique is to first estimate the AP waveform by applying a new multichannel blind system identification method that we have developed (rather than the conventional generalized transfer function) to the PAP waveforms and then estimate the beat-to-beat proportional CO by fitting a Windkessel model to the estimated waveform in which wave distortion should be attenuated. ⋯ These estimation errors represent substantial improvements compared to those obtained with several alternative PAP waveform analysis techniques. With further successful testing, the new technique may ultimately be employed for automated and less invasive monitoring of central hemodynamics in various cardiovascular patients.
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IEEE Trans Biomed Eng · May 2008
Analysis of FMRI data with drift: modified general linear model and Bayesian estimator.
The slowly varying drift poses a major problem in the analysis of functional magnetic resonance imaging (fMRI) data. In this paper, based on the observation that noise in fMRI is long memory fractional noise and the slowly varying drift resides in a subspace spanned only by large scale wavelets, we examine a modified general linear model (GLM) in wavelet domain under Bayesian framework. ⋯ Results obtained from simulated as well as real fMRI data show that the proposed Bayesian estimator can accurately capture the noise structure, and hence, result in robust estimation of the parameters in GLM. Besides, the proposed model selection criterion works well and could efficiently remove the drift.
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IEEE Trans Biomed Eng · Apr 2008
Robust unsupervised detection of action potentials with probabilistic models.
We develop a robust and fully unsupervised algorithm for the detection of action potentials from extracellularly recorded data. Using the continuous wavelet transform allied to probabilistic mixture models and Bayesian probability theory, the detection of action potentials is posed as a model selection problem. Our technique provides a robust performance over a wide range of simulated conditions, and compares favorably to selected supervised and unsupervised detection techniques.
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This paper presents a new algorithm for electrocardiogram (ECG) signal compression based on local extreme extraction, adaptive hysteretic filtering and Lempel-Ziv-Welch (LZW) coding. The algorithm has been verified using eight of the most frequent normal and pathological types of cardiac beats and an multi-layer perceptron (MLP) neural network trained with original cardiac patterns and tested with reconstructed ones. Aspects regarding the possibility of using the principal component analysis (PCA) to cardiac pattern classification have been investigated as well. A new compression measure called "quality score," which takes into account both the reconstruction errors and the compression ratio, is proposed.