SYSTEMS, APPARATUS, AND METHODS RELATED TO MODELING, MONITORING, AND/OR MANAGING METABOLISM

• US 20170055875A1
• Filed: 07/27/2016
• Published: 03/02/2017
• Est. Priority Date: 07/27/2015
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Ferraiolo, Christopher, Zogbi, George, CANDELL, Lawrence M., Shaw, Gary A., Siegel, Andrew M.
• Granted Patent: US 10,925,513 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0247 for compensation or correction of the measured physiological value
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/082 Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath A61B5/083, A61B5/091 take precedence
• CPC Class Codes: A61B 5/083 Measuring rate of metabolism by using breath test, e.g. measuring rate of oxygen consumption
• CPC Class Codes: A61B 5/0833 Measuring rate of oxygen consumption
• CPC Class Codes: A61B 5/0836 Measuring rate of CO2 production
• CPC Class Codes: A61B 5/0871 Peak expiratory flowmeters
• CPC Class Codes: A61B 5/097 Devices for facilitating collection of breath or for directing breath into or through measuring devices
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 19/0092 Nutrition

Abstract

Systems, apparatus, and methods related to modeling, monitoring, and/or managing metabolism of a subject include measuring a respiratory quotient (RQ) level in a subject and/or optimizing and executing a nonlinear feedback model to model energy substrate utilization in the subject based on at least one of a macronutrient composition and caloric value of food consumed by the subject, an intensity and duration of activity by the subject, a rate and maximum capacity of glycogen storage in the subject, a rate and maximum capacity of de novo lipogenesis in the subject, a quality and duration of sleep by the subject, and/or an RQ level in the subject.

Claims

1. An apparatus for measuring a respiratory quotient (RQ) level in a subject, the apparatus comprising:

a first input port for receiving respired air from the subject;

a measurement chamber for receiving the respired air from the first input port, the measurement chamber being in fluid communication with the first input port;

a first sensor located in the measurement chamber, the first sensor for measuring a series of oxygen levels in the measurement chamber;

a second sensor located in the measurement chamber, the second sensor for measuring a series of carbon dioxide levels in the measurement chamber at a temporal rate sufficient to ascertain a respiration rate of the subject;

at least one output interface;

at least one memory for storing processor-executable instructions, the series of oxygen level measurements, and the series of carbon dioxide level measurements; and

at least one processor coupled to the first sensor, the second sensor, the at least one output interface, and the at least one memory, wherein upon execution of the processor-executable instructions, the at least one processor;

obtains a first portion of the series of carbon dioxide level measurements;

determines a first respiration rate based on the first portion of the series of carbon dioxide level measurements;

iterates steps of obtaining a subsequent portion of the series of carbon dioxide level measurements, determining a subsequent respiration rate based on the subsequent portion of the series of carbon dioxide level measurements, and comparing the subsequent respiration rate to at least one prior respiration rate until a stable breathing pattern is identified;

obtains a stable breathing pattern portion of the series of oxygen level measurements and a stable breathing pattern portion of the series of carbon dioxide level measurements;

determines an average minimum oxygen level for a respiration cycle from the stable breathing pattern portion of the series of oxygen level measurements;

determines an average maximum carbon dioxide level for a respiration cycle from the stable breathing pattern portion of the series of carbon dioxide level measurements;

calculates the RQ level from the average minimum oxygen level and the average maximum carbon dioxide level; and

at least one of displays and transmits, via the at least one output interface, the calculated RQ level.

2. The apparatus of claim 1, wherein the at least one processor controls an ambient air calibration process, the ambient air calibration process comprising:

comparing at least one measurement to at least one expected value for ambient air;

if the at least one measurement is from the first sensor and sufficiently different from the at least one expected value for ambient air, performing a span calibration process on the first sensor to determine and apply a gain correction to subsequent measurements from the first sensor;

if the at least one measurement is from the second sensor and sufficiently different from the at least one expected value for ambient air, performing a zero-point calibration process on the second sensor to determine and apply an offset correction to subsequent measurements from the second sensor.

3. The apparatus of claim 2, wherein the at least one expected value for ambient air at 760 mm Hg is at least one of:

about 19.5% (v/v) to about 23.5% (v/v) oxygen; and

about 250 ppm to about 5,000 ppm carbon dioxide.

4. The apparatus of claim 3, wherein the at least one expected value for ambient air at 760 mm Hg is at least one of:

about 20.9% (v/v) oxygen; and

about 400 ppm carbon dioxide.

5. The apparatus of claim 2, wherein the ambient air calibration process is performed each time the first sensor and the second sensor are initiated.

6. The apparatus of claim 2, wherein the ambient air calibration process further comprises storing in the at least one memory at least one of:

the gain correction applied to subsequent measurements from the first sensor; and

the offset correction applied to subsequent measurements from the second sensor,

such that a history of ambient air measurement drift is maintained for reference.

7. The apparatus of claim 1, further comprising a second input port for receiving a carbon dioxide cartridge for calibrating at least one of the first sensor and the second sensor, the second input port being in fluid communication with the measurement chamber such that the measurement chamber receives carbon dioxide released from the carbon dioxide cartridge.

8. The apparatus of claim 7, wherein the at least one processor controls a full calibration process, the full calibration process comprising:

allowing the measurement chamber to fill with ambient air;

setting a span value for the first sensor to an expected value for the ambient air;

setting a zero-point value for the second sensor to an expected value for the ambient air;

coupling the second input port with the carbon dioxide cartridge for releasing carbon dioxide from the carbon dioxide cartridge;

releasing the carbon dioxide into the measurement chamber;

setting a zero-point value for the first sensor to zero once the carbon dioxide displaces the ambient air in the measurement chamber; and

iteratively measuring oxygen levels with the first sensor in the measurement chamber as the ambient air displaces the carbon dioxide in the measurement chamber until a predetermined oxygen level is measured, the predetermined oxygen level indicating the span value for the second sensor.

9. The apparatus of claim 1, wherein:

the predetermined oxygen level is about 16.7%; and

the span value for the second sensor is about 20%.

10. The apparatus of claim 1, further comprising a component configured to:

prevent fluid communication between the first input port and the measurement chamber during an initial portion of each respiration cycle; and

allow fluid communication between the first input port and the measurement chamber during an end-tidal portion of each respiration cycle.

11. The apparatus of claim 10, wherein the component is at least one of a mechanical shutter, a vacuum pump, and a purge fan.

12. The apparatus of claim 1, wherein the first input port is compatible with at least one of a mouthpiece and a sample tube for coupling the input port to at least one of the mouth and a nostril of the subject.

13. The apparatus of claim 12, wherein the at least one of the mouthpiece and the sample tube is at least one of disposable and for hands-free use.

14. The apparatus of claim 12, wherein the mouthpiece is a repurposed sport bottle cap.

15. The apparatus of claim 1, further comprising a heating element for at least one of preventing and reducing condensation on the first sensor and the second sensor.

16. A kit for measuring a respiratory quotient (RQ) level in a subject, the kit comprising:

a carbon dioxide cartridge;

at least one of a mouthpiece and a sample tube for coupling to at least one of the mouth and a nostril of the subject; and

a device for measuring the RQ level in a subject, the device including;

a first input port for receiving, via the at least one of the mouthpiece and the sample tube, respired air from the subject;

a measurement chamber for receiving the respired air from the first input port, the measurement chamber being in fluid communication with the first input port;

a first sensor located in the measurement chamber, the first sensor for measuring a series of oxygen levels in the measurement chamber;

a second sensor located in the measurement chamber, the second sensor for measuring a series of carbon dioxide levels in the measurement chamber at a temporal rate sufficient to ascertain a respiration rate of the subject;

a second input port for receiving the carbon dioxide cartridge for calibrating at least one of the first sensor and the second sensor, the second input port being in fluid communication with the measurement chamber such that the measurement chamber receives carbon dioxide released from the carbon dioxide cartridge;

at least one output interface;

at least one memory for storing processor-executable instructions, the series of oxygen level measurements, and the series of carbon dioxide level measurements; and

at least one processor coupled to the first sensor, the second sensor, the at least one output interface, and the at least one memory, wherein upon execution of the processor-executable instructions, the at least one processor;

obtains a first portion of the series of carbon dioxide level measurements;

determines a first respiration rate based on the first portion of the series of carbon dioxide level measurements;

iterates steps of obtaining a subsequent portion of the series of carbon dioxide level measurements, determining a subsequent respiration rate based on the subsequent portion of the series of carbon dioxide level measurements, and comparing the subsequent respiration rate to at least one prior respiration rate until a stable breathing pattern is identified;

obtains a stable breathing pattern portion of the series of oxygen level measurements and a stable breathing pattern portion of the series of carbon dioxide level measurements;

determines an average minimum oxygen level for a respiration cycle from the stable breathing pattern portion of the series of oxygen level measurements;

determines an average maximum carbon dioxide level for a respiration cycle from the stable breathing pattern portion of the series of carbon dioxide level measurements;

calculates the RQ level from the average minimum oxygen level and the average maximum carbon dioxide level; and

at least one of displays and transmits, via the at least one output interface, the calculated RQ level.

17-20. -20. (canceled)

21. A computer-facilitated method for managing body weight of a subject, the method comprising:

determining from data related to the subject obtained via at least one input device;

a macronutrient composition and caloric value of food consumed by the subject;

an intensity and duration of activity by the subject;

a rate and maximum capacity of glycogen storage in the subject; and

a rate and maximum capacity of de novo lipogenesis in the subject;

optimizing, via at least one processor, a nonlinear feedback model to model energy substrate utilization in the subject based on the macronutrient composition and caloric value of food consumed by the subject, the intensity and duration of activity by the subject, the rate and maximum capacity of glycogen storage in the subject, and the rate and maximum capacity of de novo lipogenesis in the subject;

obtaining at least one initial physiological parameter associated with the subject, the at least one initial physiological parameter including an initial body weight of the subject; and

controlling, via the at least one processor, operation of the optimized nonlinear feedback model based on the at least one initial physiological parameter to determine a target value of one or more energy substrate utilization variables that at least one of maintains and alters the body weight of the subject, wherein the one or more energy substrate utilization variables comprise at least one of;

the macronutrient composition and caloric value of food consumed by the subject; and

the intensity and duration of activity by the subject.

26. The method of claim 21, wherein the at least one initial physiological parameter further comprises at least one of height, age, gender, body mass index (BMI), body fat percentage, waist circumference, hip circumference, and chest circumference.

27. The method of claim 21, wherein the nonlinear feedback model is optimized further based on a quality and duration of sleep by the subject.

22-24. -24. (canceled)

25. A system for managing body weight of a subject, the system comprising:

at least one input device for obtaining data related to the subject;

at least one memory device for storing the data related to the subject and processor-executable instructions; and

at least one processor in communication with the at least one input device and the at least one memory device, wherein upon execution of the processor-executable instructions, the at least one processor;

determines from the data related to the subject at least one initial physiological parameter associated with the subject, the at least one initial physiological parameter including an initial body weight of the subject; and

controls operation of a nonlinear feedback model to determine, based on the at least one initial physiological parameter, a target value of one or more energy substrate utilization variables that at least one of maintains and alters the body weight of the subject, wherein;

the nonlinear feedback model is optimized to model energy substrate utilization in the subject based on at least one of;

a macronutrient composition and caloric value of food consumed by the subject;

an intensity and duration of activity by the subject;

a rate and maximum capacity of glycogen storage in the subject;

a rate and maximum capacity of de novo lipogenesis in the subject; and

a quality and duration of sleep by the subject; and

the one or more energy substrate utilization variables comprise at least one of;

the macronutrient composition and caloric value of food consumed by the subject; and

the intensity and duration of activity by the subject.

28. (canceled)