NON-INVASIVE CHARACTERIZATION OF A PHYSIOLOGICAL PARAMETER
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Abstract
The present invention provides a method and device for characterizing a physiological parameter. The method, in one application, uses one or more non-invasive sensors to collect patient data, and may also collect data on environmental conditions. At least some of the patient data has a direct relationship with the physiological parameter, that is, a change in the physiological parameter is reflected in the data set, although the magnitude of the physiological parameter may masked by noise, interference, or other environmental or patient influences. The direct patient data preferably has a generally linear relationship with the physiological parameter, and if not, the patient data is linearized according to an algorithm, table, or other adjustment process. These linearizing processes may be predefined, and may adaptively learn or adjust. A blind signal source process is applied to the linearized data to generate separated signals, and the signal associated with the physiological parameter is identified. The identified signal is scaled or further processed, and the characterization result is presented. Although the method and device are described for use with a human, they may be advantageously used on animals.
104 Citations
92 Claims
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1-76. -76. (canceled)
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77. A method selected from the group consisting of:
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a. estimating a concentration level of a blood analyte, optionally glucose, comprising; (i) non-invasively measuring a plurality of variables in a patient to obtain a set of input data, optionally by emitting at least one pair of wavelengths (optionally within the range of about 600 to about 1 millimeter) in the from an energy source towards a first selected area of the patient and detecting energy emerging from a second selected area of the patient wherein at least one first variable of the plurality of variables depends on the patient'"'"'s blood analyte concentration level and optionally comprises a variable selected from electrical impedance variable (optionally an impedance spectroscopy variable), a capacitance variable (optionally a skin capacitance variable), and a current variable, wherein at least one second variable of the plurality of variables does not depends on the patient'"'"'s blood analyte concentration level, and wherein optionally the at least one first variable depends on the at least one second variable; (ii) nonlinearly filtering at least part of the set of input data to obtain a set of filtered data, wherein optionally the nonlinearly filtering comprises an at least partially adaptive component; and (iii) applying a source separation method to the set of filtered data to obtain a set of output data, wherein optionally the source separation method is at least partially adaptive; b. estimating a blood-analyte concentration level in a patient, wherein the blood-analyte optionally is glucose comprising; (i) receiving a first set of input variables, wherein the first set of input variables do not comprise any invasively-measured variables, wherein at least one first variable of the first set of input variables is influenced by the patient'"'"'s blood analyte concentration level, and wherein at least one second variable of the first set of input variables is not influenced by the patient'"'"'s blood analyte concentration level; (ii) pre-processing at least one of the first set of input variables to produce a second set of variables, wherein the pre-processing optionally is at least partially adaptive and optionally comprises nonlinearly transforming at least one of the first set of input variables; and (iii) applying a linear separation method to the second set of variables produce a third set of variables, wherein the linear separation method optionally is at least partially adaptive and optionally comprises a blind source separation method (optionally at least one of an Independent Component Analysis (ICA) and an Independent Vector Analysis (IVA) method); and c. characterizing a target physiological parameter, comprising; (i) collecting a first data set of data from a patient, the first data set having a direct relationship with the target physiological parameter, wherein collecting the first data set optionally further comprises using an optical, electrical, RF, infrared sensor, or impedance sensor; (ii) collecting a second data set, wherein the second data set optionally is a set of data having a direct or indirect relationship with the target physiological parameter, wherein the second data set optionally is or is not indicative of a physiological parameter and/or an environmental condition, and wherein the second data set optionally is from a patient; (iii) processing the first data to generate a processed first data set that has a generally linear relationship with the target physiological parameter, wherein the processing step optionally comprises at least one of determining that the first data set has a generally linear or nonlinear relationship with the processed first data set and/or applying an algorithm or table to the first data set to generate the processed first data set; (iv) separating the processed first data set into independent signals, wherein the separation process optionally is a blind signal separation process or an independent component analysis process, and wherein the separation step optionally is adapted according to the second data set; (v) identifying a parameter signal having the target physiological parameter as its source, wherein the identification step optionally is adapted according to the second data set; (vi) scaling the parameter signal according to the second data set, wherein the scaling step optionally is adapted according to the second data set; and (vii) presenting the scaled parameter, wherein the presenting step optionally comprises visually displaying, audibly projecting, setting an alarm, sounding an alarm, communicating a message, or activating another device. - View Dependent Claims (78, 79, 80, 81, 82, 83, 84)
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85. A non-invasive blood-analyte-monitoring apparatus, comprising:
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a. an analyte-sensitive measuring component configured to measure an analyte-sensitive variable related to a concentration level of a blood analyte, optionally glucose, in a patient, wherein the analyte-sensitive variable optionally comprises a variable selected from the group consisting of an impedance variable (optionally an electrical impedance variable), a capacitance variable, and a current variable; b. an analyte-insensitive measuring component configured to measure an analyte-insensitive variable not related to the concentration level of the blood analyte in the patient, wherein the analyte-insensitive variable optionally comprises a variable selected from skin temperature, body temperature, air temperature, skin moisture, a hydration variable, a skin-device pressure variable, atmospheric pressure, device movement, and humidity; c. an analyte calculation component comprising a nonlinear calculation component that is configured to nonlinearly filter at least one variable, wherein the analyte calculation component is configured to receive the analyte-sensitive and analyte-insensitive variables as inputs and calculate the patient'"'"'s estimated blood analyte concentration level, wherein the analyte calculation component optionally is at least partially adaptive and/or comprises a blind source separation module configured to separate at least two signals (wherein the blind source separation module optionally comprises at least one of an Independent Component Analysis (ICA) module and an Independent Vector Analysis (IVA) module), wherein the nonlinearly filtering optionally comprises taking the logarithm of the at least one variable. - View Dependent Claims (86, 87, 88)
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89. A glucose monitor, comprising:
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a. a housing; b. a first sensor that is a non-invasive sensor configured to collect RF impedance data, wherein the first sensor optionally is disposed in the housing; c. a second sensor configured to collect other patient data, wherein the second sensor optionally is disposed in the housing; d. a display in the housing for presenting a measured glucose level; and e. a processor in the housing for operating the steps of; (i) receiving the set of RF impedance data; (ii) linearizing the RF impedance data to glucose; (iii) separating the linearized data using a blind signal source algorithm; (iv) identifying a glucose signal; (v) scaling the glucose signal according to the other patient data; and (v) presenting the scaled glucose signal as the measured glucose level. - View Dependent Claims (90, 91, 92)
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Specification