System and method for non-invasive glucose monitoring using near infrared spectroscopy
Inventors
Assignees
New Jersey Institute of Technology
Publication Number
US-10653343-B2
Publication Date
2020-05-19
Expiration Date
2033-09-30
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Abstract
A method for noninvasively measuring blood concentration of a substance, such as, for example, blood glucose levels, is described herein. The method may comprise measuring an initial absorption data using near infrared spectroscopy (NIR), and obtaining a second set of absorption data. The initial absorption data, along with the second set of absorption data, may then be adjusted by applying a convolution function and a Monte Carlo simulation to the raw data. In a step, an initial estimate of the level of the substance in the blood, such as, for example, initial blood glucose level, may be calculated based on the adjusted data and pulse oximetry information using a mixing model equation.
Core Innovation
The invention describes a method and apparatus for non-invasively measuring blood concentration of substances, primarily glucose, by utilizing near infrared spectroscopy (NIR). The process involves illuminating a particular area of a patient's skin, capturing initial absorption and a secondary set of absorption data at different sampling rates and wavelengths within the 600 nm to 1000 nm range. This data collection includes time tags related to physiological events such as systolic and diastolic phases of the heart cycle, and incorporates pulse oximetry measurements.
The raw absorption data is adjusted using a convolution function representative of signal degradation, and enhanced by applying a Monte Carlo simulation that models the tissue’s optical properties. A mixing model equation, incorporating coefficients for melanin, blood, and baseline tissue, is then used together with the oximetry information to estimate substance concentration such as blood glucose. The accuracy of the estimate is further improved by using a genetic algorithm optimization, resulting in a final measurement from the detected absorption data.
The addressed problem is the invasiveness and discomfort associated with traditional blood glucose monitoring techniques which require regular blood samples through finger pricks. The invention aims to provide a non-invasive, pain-free method that enables continuous or repeated monitoring of blood glucose and other blood-borne substances without the physical drawbacks of existing enzyme-based analyses.
Claims Coverage
There are two independent claims, each defining a method for non-invasive monitoring of blood concentration of a substance or glucose using specific spectroscopic and computational techniques.
Non-invasive blood substance monitoring using near infrared spectroscopy and mixing model
This feature consists of illuminatiing a specified skin location with NIR light sources (600 nm to 1,000 nm), sampling initial and secondary absorption data at different rates over heart cycle events, and detecting absorption coefficients using linear source-detector array sensors. The method includes adjusting the absorption data based on a convolution function and estimating the blood substance level through a mixing model equation that sums weighted absorption coefficients for melanin, blood, and baseline tissue. The baseline concentration is determined as a difference between one and the sum of melanin and blood concentrations, and its coefficient is based on a natural exponential function of the wavelength. A genetic algorithm chromosome, associated with the concentration of the substance in tissue, is used to optimize and finalize the reading.
Non-invasive glucose monitoring method using NIR with temporal sampling, convolution adjustment, and genetic algorithm
This method involves sampling initial and secondary absorption data from skin at different rates in response to NIR illumination (600 nm to 1,000 nm), with detection by aligned NIR linear source-detector array sensors. The absorption data is adjusted using a convolution function and includes coefficients for melanin, blood, and baseline skin. Blood glucose levels are estimated using pulse oximetry information and a mixing model equation that incorporates these coefficients. Additionally, a genetic algorithm chromosome associated with glucose concentration is utilized to obtain a final glucose reading.
The independent claims comprehensively cover a non-invasive method for acquiring blood substance or glucose levels by analyzing NIR absorption data, correcting it computationally, and optimizing the result using genetic algorithm-based estimation techniques.
Stated Advantages
Enables non-invasive, pain-free blood glucose and substance monitoring, overcoming discomfort and sensitivity issues caused by traditional enzyme-based, invasive blood sampling methods.
Allows for repeated or continuous measurements, thereby improving compliance for chronic patients requiring frequent monitoring.
Provides a method and apparatus that can monitor additional blood substances with measurable distinction from water, such as glycolated hemoglobin and cholesterol, through multispectral NIR spectroscopy.
Documented Applications
Blood glucose monitoring for diabetes management without requiring invasive blood draws.
Monitoring of other circulating blood substances distinguishable from water in the NIR spectrum, including glycolated hemoglobin and cholesterol.
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