A novel dry active electrode for EEG recording.

The design and testing of a "dry" active electrode for electroencephalographic recording is described. A comparative study between the EEG signals recorded in human volunteers simultaneously with the classical Ag-AgCl and "dry" active electrodes was carried out and the reported preliminary results are consistent with a better performance of these devices over the conventional Ag-AgCl electrodes.

Frontal-plane QRS axis revisited: accuracy of current approximations and reappraisal of their merit in the diagnosis of right ventricular hypertrophy.

The frontal-plane mean QRS vector orientation (AQRSxy)--the so-called electrical axis--is an ECG feature commonly used for the diagnosis of right ventricular hypertrophy and is correctly measured by calculating the areas subtended by QRS deflections in two different leads. To overcome the drawbacks of doing this by hand, two alleged approximations of AQRSxy have become popular and are in current use: one is based on the measurement of QRS component wave peak amplitudes and the other on the estimation of the half-area vector of the frontal plane loop. The values obtained with the correct and the two more practical methods are compared and their diagnostic efficiency is assessed by means of a procedure for ECG criteria optimization based on the receiver operating characteristics (ROC) curve analyzed in terms of information theory. The authors conclude that the two more popular methods for AQRSxy determination provide similar values that, although correlated with the true measure of the parameter are statistically different from it. On the other hand, the diagnostic efficiency of AQRSxy alone, regardless of the method by which it is computed, is only as good as, if not bettered by, other much more easily measurable frontal-plane parameters (ie, left to rightward forces amplitude ratio in adults and rightward forces amplitude in pediatric patients).

A new ECG classifier based on linear prediction techniques.

A longstanding tradition in automatic ECG classification has been the use of conventional features (amplitudes, duration, etc.) as waveform descriptors for pattern discrimination purposes. This paper presents an alternative approach in statistical ECG classification. It is based on the use of linear prediction coefficients, a sort of "abstract" features which, as waveform descriptors, enjoy the desirable property of whole-signal dependency, being rather insensitive to high-frequency noise. Experimental results obtained on 400 ECGs distributed by four clinical groups according to clinicopathological data (normal, myocardial infarction, right and left hypertrophies) show interesting potentialities of this new method, namely a classification error for equal class prevalences (30%) significantly lower than by using conventional features. Classification and cluster separability results are presented and discussed as well as the viability of the new method in a clinical environment.