Multivariate analysis of green to ultraviolet spectra of cell and tissue samples

• US 20050222501A1
• Filed: 06/02/2005
• Published: 10/06/2005
• Est. Priority Date: 02/18/2000
• Status: Active Grant

• Current Assignee: Cercacor Laboratories
• Original Assignee: Masimo Laboratories, Inc. (Masimo Corporation)
• Inventors: Mansfield, James, Freeman, Jenny
• Granted Patent: US 7,289,835 B2
• Time in Patent Office: Days
• US Class Current: 600/316
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/0071 by measuring fluorescence emission
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/441 Skin evaluation, e.g. for skin disorder diagnosis
• CPC Class Codes: A61B 5/445 Evaluating skin irritation or skin trauma, e.g. rash, eczema, wound, bed sore
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G01J 3/28 Investigating the spectrum using colour filters G01J3/51
• CPC Class Codes: G01N 21/6486 Measuring fluorescence of biological material, e.g. DNA, RNA, cells G01N21/6428 takes precedence
• CPC Class Codes: G01N 2201/129 Using chemometrical methods
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

This invention relates to methods for processing in vivo skin auto-fluorescence spectra for determining blood glucose levels. The invention also relates to methods of classifying cells or tissue samples or quantifying a component of a cell or tissue using a multivariate classification or quantification model.

Claims

1. A method for processing in vivo skin auto fluorescence spectra emitted by a skin surface of a patient to determine a blood glucose level of the patient comprising the steps of:

collecting auto fluorescence spectra emitted from the skin surface of the patient; and

correcting the collected spectra using multivariate analysis to account for skin surface variables.

2. The method of claim 1 wherein the multivariate analysis comprises one or more quantification, classification, or data processing techniques selected from the group consisting of:

partial least squares, principal component regression, linear regression, multiple linear regression, stepwise linear regression, ridge regression, radial basis functions, linear discriminant analysis, cluster analysis, neural network analysis, smoothing filters, laplacian operators, maximum likelihood estimators, maximum entropy, first and second derivatives, peak enhancement, Fourier self-deconvolution, principal components, and varimax rotations.

3. An instrument for determining a correct glucose level of a patient by measuring in vivo autofluorescence of the patient'"'"'s skin comprising:

means for irradiating the skin with a plurality of excitation wavelengths;

means for collecting a plurality of emitted wavelengths; and

means for analyzing the collected wavelengths to determine a preliminary blood glucose level, said means for analyzing comprising means for correcting the preliminary blood glucose level to account for variations in skin, said means for correcting comprising using one or more multivariate analytical methodologies to determine the correct glucose level of the patient.