Abstract: A method, system, apparatus and device for processing an ECG signal to remove or reduce noise from the ECG signal attributable to EMG and/or motion artifacts. The novel algorithm common to all aspects of the device can include wavelet decomposing an ECG signal to produce a set of approximation coefficients and a plurality of sets of detail coefficients, locally fitting subsets of the set of approximation coefficients to second order polynomials, adjusting the set of approximation coefficients by the locally fitted second order polynomials, setting some of the detail coefficients to zero, and reconstructing an ECG signal with reduced noise based on the modified set of approximation coefficients and the modified plurality of sets of detail coefficients.

Abstract: An optical coherence tomography (OCT) image of the anterior chamber of an eye is processed to determine automatically a location in the image corresponding to Schwalbe's line. First, the method finds the location of the corneal endothelium. Then the method fits a model to the detected corneal endothelium. Then the method determines the location of Schwalbe's line based on the relationship between the detected corneal endothelium and the fitted model, such as where the detected corneal endothelium diverges most from the fitted model. The Schwalbe's line is used to obtain a numerical measure of the anterior chamber angle of the eye. The method can be used in a process for screening patients for glaucoma. In the case of patients found to be suffering from glaucoma, treatment can be performed.

Abstract: A method, system, apparatus and device for processing an ECG signal to remove or reduce noise from the ECG signal attributable to EMG and/or motion artifacts. The novel algorithm common to all aspects of the device can include wavelet decomposing an ECG signal to produce a set of approximation coefficients and a plurality of sets of detail coefficients, locally fitting subsets of the set of approximation coefficients to second order polynomials, adjusting the set of approximation coefficients by the locally fitted second order polynomials, setting some of the detail coefficients to zero, and reconstructing an ECG signal with reduced noise based on the modified set of approximation coefficients and the modified plurality of sets of detail coefficients.

Abstract: An optical coherence tomography (OCT) image of the anterior chamber of an eye is processed to determine automatically a location in the image corresponding to Schwalbe's line. First, the method finds the location of the corneal endothelium. Then the method fits a model to the detected corneal endothelium. Then the method determines the location of Schwalbe's line based on the relationship between the detected corneal endothelium and the fitted model, such as where the detected corneal endothelium diverges most from the fitted model. The Schwalbe's line is used to obtain a numerical measure of the anterior chamber angle of the eye. The method can be used in a process for screening patients for glaucoma. In the case of patients found to be suffering from glaucoma, treatment can be performed.

Abstract: Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (?(t)) weighted by the weights (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (?) of the first signal (x(t)).

Abstract: Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (?(t)) weighted by the weights (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (?) of the first signal (x(t)).

Abstract: A reconstruction method for reconstructing a first signal from a set of sampled values generated by sampling a second signal at a sub-Nyquist rate and at uniform intervals, the method includes retrieving from the set of sampled values a set of shifts and weights with which the first signal can be reconstructed.

Abstract: Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (?(t)) weighted by the weigths (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (?) of the first signal (x(t)).

Abstract: Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (?(t)) weighted by the weights (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (?) of the first signal (x(t)).

Abstract: Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (?(t)) weighted by the weigths (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (?) of the first signal (x(t)).