BACKGROUND: We developed a method, called the metabolic heat conformation (MHC) method, for the noninvasive measurement of blood glucose. The MHC method involves the measurement of physiologic indices related to metabolic heat generation and local oxygen supply, which correspond to the glucose concentration in the local blood supply. METHODS: We used noninvasive thermal and optical sensors on the fingertip of an individual to measure thermal generation, blood flow rate, hemoglobin (Hb) concentration, and oxyhemoglobin concentration. The calibration model incorporates mathematical procedures to convert signals from the sensor pickup to final glucose concentrations. The mathematical procedures are multivariate statistical analyses, involving values from sensor signals, polynomials from various values, regression analyses of individual patients, and cluster analyses of patient groups. The glucose value is calculated for each patient measurement, applying one of the clusters by discriminant analysis. RESULTS: Regression analysis was performed to compare the noninvasive method with the hexokinase method, using 127 data points (109 data points from diabetic patients, 18 data points from nondiabetic patients) with glucose concentrations ranging from 3.0 to 22.5 mmol/L (54-405 mg/dL). The correlation coefficient (r) was 0.91. Reproducibility was measured for healthy fasting persons; the CV was 6% at 5.56 mmol/L (100 mg/dL). CONCLUSIONS: These data provide preliminary evidence that the MHC method can be used to estimate blood glucose concentrations noninvasively.
BACKGROUND: We developed a method, called the metabolic heat conformation (MHC) method, for the noninvasive measurement of blood glucose. The MHC method involves the measurement of physiologic indices related to metabolic heat generation and local oxygen supply, which correspond to the glucose concentration in the local blood supply. METHODS: We used noninvasive thermal and optical sensors on the fingertip of an individual to measure thermal generation, blood flow rate, hemoglobin (Hb) concentration, and oxyhemoglobin concentration. The calibration model incorporates mathematical procedures to convert signals from the sensor pickup to final glucose concentrations. The mathematical procedures are multivariate statistical analyses, involving values from sensor signals, polynomials from various values, regression analyses of individual patients, and cluster analyses of patient groups. The glucose value is calculated for each patient measurement, applying one of the clusters by discriminant analysis. RESULTS: Regression analysis was performed to compare the noninvasive method with the hexokinase method, using 127 data points (109 data points from diabeticpatients, 18 data points from nondiabetic patients) with glucose concentrations ranging from 3.0 to 22.5 mmol/L (54-405 mg/dL). The correlation coefficient (r) was 0.91. Reproducibility was measured for healthy fasting persons; the CV was 6% at 5.56 mmol/L (100 mg/dL). CONCLUSIONS: These data provide preliminary evidence that the MHC method can be used to estimate blood glucose concentrations noninvasively.