Direct mathematical method for real-time ischemic episodes detection from electrocardiograms using the discrete Hermite transform.

A real-time automated identification technique is developed for the detection of ischemic episodes in long-term electrocardiographic (ECG) signals using mathematical expansions involving the Discrete Dilated Hermite Transform. The Discrete Hermite functions could be viewed as a set of orthogonal vectors that resemble a finite Fourier series. They are generated easily as eigenvectors of a symmetric tridiagonal matrix that commutes with the centered Fourier matrix.

A gene selection method for classifying cancer samples using 1D discrete wavelet transform.

Selecting a set of discriminant genes for biological samples is an important task for designing highly efficient classifiers using DNA microarray data. The wavelet transform is a very common tool in signal-processing applications, but its potential in the analysis of microarray gene expression data is yet to be explored fully. In this paper, we present a wavelet-based feature selection method that assigns scores to genes for differentiating samples between two classes.

Adaptive filtering of ballistocardiogram artifact from EEG signals using the dilated discrete Hermite transform.

Electroencephalogram (EEG) signals, when recorded within the strong magnetic field of an MRI scanner are subject to various artifacts, of which the ballistocardiogram (BCG) is one of the prominent ones affecting the quality of the EEG. The BCG artifact varies slightly in shape and amplitude for every cardiac cycle making it difficult to identify and remove. This paper proposes a novel method for the identification and elimination of this artifact using the shape basis functions of the new dilated discrete Hermite transform.

Real time monitoring of ischemic changes in electrocardiograms using discrete Hermite functions.

A novel scheme for real time detection of ischemic features from long term electrocardiograms (ECG), based on the dilated discrete Hermite expansion is proposed. The discrete Hermite functions used for the expansion are eigenvectors of a symmetric tridiagonal matrix that commutes with the centered Fourier matrix. The ECG signals were expanded in terms of Hermite functions using a simple dot product.

A robust DSP integrator for accelerometer signals.

The need for an accepted method for determining position data from digital accelerometer readings with known frequency range is very important. The method of this paper uses spectral information and provides more stability and accuracy than classic methods for the DSP case. It even reduces to a classic method for the nonoscillatory case.