Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features.

Objective: Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present.

EEG artifact elimination by extraction of ICA-component features using image processing algorithms.

Artifact rejection is a central issue when dealing with electroencephalogram recordings. Although independent component analysis (ICA) separates data in linearly independent components (IC), the classification of these components as artifact or EEG signal still requires visual inspection by experts. In this paper, we achieve automated artifact elimination using linear discriminant analysis (LDA) for classification of feature vectors extracted from ICA components via image processing algorithms.

Infrared-monitored cold response in the assessment of Raynaud's phenomenon.

Background: Evaluation of treatments for Raynaud's phenomenon (RP) requires objective response parameters in addition to clinical activity scores. Thermographic monitoring of fingertip re-warming after cold challenge has been widely used but usually requires sophisticated equipment. We have previously shown that fingertip re-warming after cold challenge follows a first-order transient response curve that can be described by a single variable, designated tau.

In vitro investigations of jet-pulses for the measurement of respiratory impedance in newborns.

The aim of this in vitro study was to investigate the measuring range and accuracy of a miniaturized equipment for respiratory impedance (Zrs) measurements in newborns using jet-pulses. Brief flow pulses (peak flow=16 L x min(-1), width=10 ms) were generated by a jet-generator consisting of a solenoid valve and an injector, situated between pneumotachograph and outflow resistance. Serially arranged resistance-inertance-compliance (R-I-C) lung models (RM=1.