University of Missouri

St. Louis Medical Devices, Inc.

W. R. Grace Co.-conn.

Zhi Xu

David W Larsen

Wayne Garver

James M Anderson

Rakesh Bose

Robert D Rosenthal

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes a light source to strike a target area of a sample, a light detector positioned to receive light from the light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, a processor to receive the output signal from the light detector based on the received output signal, calculate the attenuance attributable to blood in a sample present in the target area with a ratio factor, eliminate effect of uncertainty caused by temperature dependent detector response of the light detector, and then determine a blood glucose level associated with a sample present in the target area based on the calculated attenuance with the processor.

Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes utilizing at least one light source configured to strike a target area of a sample, utilizing at least one light filter positioned to receive light transmitted through the target area from the at least one light source, utilizing at least one light detector positioned to receive light from the at least one light source and filtered by the at least one light filter, and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, receiving the output signal from the at least one light detector with a processor and based on the received output signal, calculating the attenuance attributable to blood in a sample with a signal-to-noise ratio of at least 20-to-1; and determining a blood glucose level.

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes utilizing at least one light source configured to strike a target area of a sample, utilizing at least one light filter positioned to receive light transmitted through the target area of the sample from the at least one light source, utilizing at least one light detector positioned to receive light from the at least one light source and filtered by the at least one light filter, and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, receiving the output signal from the at least one light detector with a processor, calculating the attenuance attributable to blood with a ratio factor based on the received output signal, and determining a blood glucose level based on the calculated attenuance.

A method and system for detecting glucose in a biological sample is disclosed. This includes illuminating a biological sample with a light source, collecting transmitted, transflected or reflected light from the sample with a detector, generating spectral data of one or more components in the sample other than glucose in a spectral data analysis device, and analyzing the spectral data of the one or more components, sufficient to provide a glucose measurement from the spectral data of the one or more components other than glucose with the spectral data analysis device.

Method and system for non-invasive blood glucose measurement using signal change of the non-glucose components induced by the presence of glucose

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes at least one light source configured to strike a target area of a sample, at least one light detector positioned to receive light from the at least one light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, a processor configured to receive the output signal from the at least one light detector based on the received output signal, calculate the attenuance attributable to blood in a sample present in the target area with a ratio factor, eliminate effect of uncertainty caused by temperature dependent detector response of the at least one light detector, and then determine a blood glucose level associated with a sample present in the target area based on the calculated attenuance with the processor.

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes at least one light source configured to strike a target area of a sample, at least one light detector, which includes a preamplifier having a feedback resistor, positioned to receive light from the at least one light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, and a processor configured to receive the output signal from the at least one light detector and based on the received output signal, calculate the attenuance attributable to blood in a sample present in the target area and eliminate effect of uncertainty caused by temperature dependent detector response of the at least one light detector, and based on the calculated attenuance, determine a blood glucose level associated with a sample.

Method and system for non-invasive blood glucose detection utilizing spectral data of one or more components other than glucose

Increased sensitivity of spectrometers through reducing noise in independent voltage signals via a differential voltage analyzer utilizing a reference wavelength from a wavelength region in which the optical absorption of the sample is negligible. In an embodiment, a grating permits selection of a reference wavelength. In another embodiment, filters permit selection of a reference wavelength. In yet another embodiment, both a grating and a filter permit selection of a reference wavelength. In an aspect, the differential voltage analyzer reduces noise by minimizing a differential voltage between the independent voltage signals and the reference voltage signal by adjusting the value of a cancellation coefficient.

Multichannel ultra-sensitive optical spectroscopic detection

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes at least one light source configured to strike a target area of a sample, at least one light detector positioned to receive light from the at least one light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, and a processor configured to receive the output signal from the at least one light detector and based on the received output signal, calculate the attenuance attributable to blood in a sample present in the target area and eliminate effect of uncertainty caused by temperature dependent detector response of the at least one light detector, and based on the calculated attenuance, determine a blood glucose level associated with a sample present in the target area.

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. This includes at least one light source configured to strike a target area of a sample, at least one light detector positioned to receive light from the at least one light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected, a processor configured to receive the output signal from the at least one light detector based on the received output signal, calculate the attenuance attributable to blood in a sample present in the target area with a ratio factor, eliminate effect of uncertainty caused by temperature dependent detector response of the at least one light detector, and then determine a blood glucose level with a sample present in target area based on the calculated attenuance with the processor.

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St. Louis, MO, United States of America

Zhi Xu