2539 results about "Spectral analysis" patented technology

A chromatic confocal technique and apparatus for the rapid three-dimensional measurement of an object shape, particularly of a tooth in a patient's jaw, using an array of polychromatic point light sources, a planar detector matrix, a beam splitter for lateral spectral separation, and an objective for illuminating and recording the object. Spectral defined reference light bundles are generated, injected into the detection beam path via a reference beam path and, following spectral splitting, are focused on the detector matrix as reference image points, wherein laterally shifted sub-matrices are numerically defined on the detector matrix for spectral analysis of the object light, which sub-matrices are implemented as spectral cells for three-dimensional measurement of the shape of the object.

The systems of the present invention provide improved accuracy in monitoring, analysing, detecting, predicting and / or providing alerts and alarms associated with depth of anaesthesia, depth of consciousness, hypnotic state, sedation depth, fatigue or vigilance of a subject, with as few as 3 surface electrodes. The systems incorporate real-time phase, amplitude and frequency analysis of a subject's electro-encephalogram. The systems weight outputs of various types of analyses to produce an integrated analysis or display for precise indication or alert to users of the systems including anaesthetists, nurses and other medical personnel, transport drivers and machine workers. The systems weight the outputs of one or more analysis algorithms including combinations of simultaneous, real-time R&K analysis, AEP spectral analysis-SEF-MF, Bi-coherence analysis, initial wave analysis, auditory response, arousal analysis, body movement analysis, 95% spectral edge analysis and anaesthetic phase and spectral energy variance measurement in association with a subject's state of consciousness.

A method and computer program product comprising an algorithm adapted to execute a method of identifying the spatial coordinates of a sustaining source of fibrillatory activity in a heart by computing a set of point-dependent dominant frequencies and a set of point-dependent regularity indices for a set of products of point-dependent unipolar discrete power spectra and point-dependent bipolar discrete power spectra, derived by spectral analyses of corresponding unipolar and bipolar cardiac depolarization signals simultaneously acquired from a set of points of the heart. A maximum dominant frequency is selected whose associated coordinates identify the point of the sustaining source of fibrillatory activity. The magnitude of the regularity index is interpreted to verify the identification of the spatial coordinates of the sustaining source of fibrillatory activity. When indicated, surgical intervention is directed to the spatial coordinates of the sustaining source of fibrillatory activity.

A medical instrument system comprises an elongate instrument body; an optical fiber coupled in a constrained manner to the elongate instrument body, the optical fiber including one or more Bragg gratings; a detector operably coupled to a proximal end of the optical fiber and configured to detect respective light signals reflected by the one or more Bragg gratings; and a controller operatively coupled to the detector, wherein the controller is configured to determine a geometric configuration of at least a portion of the elongate instrument body based on a spectral analysis of the detected reflected portions of the light signals.

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

A portion of a polarization maintaining (PM) optical fiber having two polarization states is analyzed. First and second spectral responses of the PM fiber portion are determined. In a preferred implementation, the spectral responses are determined using Optical Frequency Domain Reflectometry (OFDR). Each polarization state of the PM fiber portion has a corresponding spectral component in the first spectral response. First and second spectral analyses of the PM fiber portion are performed using the first and second spectral responses. Based on those spectral analyses of the PM fiber portion, a first physical characteristic affecting the PM fiber portion is determined that is distinct from a second different physical characteristic affecting the fiber portion. Example physical characteristics include temperature and strain. An output signal related to the first physical characteristics affecting the fiber portion is provided, e.g., for display, further processing, etc.