Calorie Monitoring Sensor And Method For Cell Phones, Smart Watches, Occupancy Sensors, And Wearables

• US 20150148632A1
• Filed: 11/24/2014
• Published: 05/28/2015
• Est. Priority Date: 11/26/2013
• Status: Abandoned Application

• Current Assignee: JB IP Acquisitions LLC
• Original Assignee: JB IP Acquisitions LLC
• Inventors: Benaron, David Alan
• Application Number:
  US14/552,468
• Publication Number:
  US 20150148632A1
• Time in Patent Office: Days
• US Class Current: 600/322
• CPC Class Codes: A61B 2560/0247 for compensation or correction of the measured physiological value
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02427 Details of sensor
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/0806 by whole-body plethysmography measuring blood flow using plethysmography A61B5/0295; impedance plethysmography A61B5/053; measuring volume of the body or parts thereof A61B5/1073
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• 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 5/085 Measuring impedance of respiratory organs or lung elasticity
• CPC Class Codes: A61B 5/091 Measuring volume of inspired or expired gases, e.g. to determine lung capacity
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/4875 Hydration status, fluid retention of the body
• CPC Class Codes: A61B 5/6802 Sensor mounted on worn items
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/7207 : of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7225 : Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7253 : characterised by using transforms

Abstract

An improved sensor (102) for calorie monitoring in mobile devices, wearables, security, illumination, photography, and other devices and systems uses an optional phosphor-coated broadband white LED (103) to produce broadband light (114), which is then transmitted along with any ambient light to target (125) such as the ear, face, or wrist of a living subject. Some of the scattered light returning from the target to detector (141) is passed through narrowband spectral filter set (155) to produce multiple detector regions, each sensitive to a different narrowband wavelength range, and the detected light is spectrally analyzed to determine a measure of calories, such as calories expended, calories ingested, calorie balance, or rate of calories expended, in part based on a noninvasive measure of respiration, such as respiratory rate, respiratory effort, respiratory depth, or respiratory variability. In one example, variations in concentration in components of the bloodstream over time, such as hemoglobin and water in the arteries, are determined based on the detected light, and the measure of respiration is then determined based on the variations in concentration over time. In the absence of the LED light, ambient light may be sufficient illumination for analysis. The same sensor can provide identifying features of type or status of a tissue target, such as heart rate or heart rate variability, hydration status, sleep state, or even occupancy counting. Calorie monitoring systems incorporating the sensor as well as methods are also disclosed.

Claims

1. A method for estimating calories in a living subject, comprising the steps of:

(a) noninvasively detecting light, said detected light being at least in part backscattered from or transmitted through the subject;

(b) determining a measure of respiration, said measure determined at least in part based on a function of a concentration of components of the bloodstream over time determined by analysis of the detected light; and

,

(c) generating an output that is a function of the estimated calories expended or consumed by the subject, said output based at least in part on the measure of respiration.

4. The method of claim 1, 2, or 3, wherein the detected light is broadband ambient light.

5. The method of claim 1, 2, or 3, wherein the detected light is broadband LED light.

6. The method of claim 1, 2, or 3, wherein the output is a measure selected from the list of measures including calories expended, calories consumed, calorie balance, and a rate of calorie expenditure over a period of time.

7. The method of claim 1, 2, or 3, wherein the output is determined using a function of one or more of an estimated water, fat, or protein content of the blood.

8. The method of claim 1, 2, or 3, wherein the output is measure of a condition of calories consumed being more than calories expended.

9. The method of claim 1, 2, or 3, wherein the output is measure of a condition of calories consumed being less than calories expended.

2. A method for estimating calories in a living subject, comprising the steps of:

(a) noninvasively detecting broadband light after an interaction with the subject, and further after separating or filtering said broadband light into different wavebands of light prior to detection;

(b) determining a measure of respiration, said measure based at least in part on a spectral analysis of the detected light over an interval of time; and

,

(c) generating an output that is a function of the estimated calories expended or consumed by the subject, said output based at least in part on the measure of respiration.

3. A method for estimating calories in a living subject, comprising the steps of:

(a) noninvasively detecting broadband light arriving after interaction with the subject, and further after separating or filtering said broadband light into different wavebands prior to detection, and generating spectral data;

(b) analyzing the spectral data to computationally partition the data into more than one physiological compartment of different temporal or physiological characteristics and to computationally separate the detected light into more than one blood or tissue components;

(c) determining a measure of respiration, said measure based at least in part on the computational partitioning and the computational separation; and

,

(d) generating an output that is a function of the estimated calories expended or consumed by the subject, said output based at least in part on the measure of respiration.

10. A device for estimating calories in a living subject, comprising:

(a) at least one sensor configured to noninvasively detect light being backscattered from or transmitted through the subject; and

,

(b) a processor, and memory storing one or more programs for execution by the processor, the one or more programs including instructions for determining at least a measure of respiration, said measure of respiration determined at least in part based on a measure of components of the bloodstream over time determined using the detected light, and for generating an output that is a function of the calories expended or consumed by the subject, said output based at least in part on the measure of respiration.

14. The device of claim 10, 11, 12, or 13 wherein the device is configured as part of a system selected from the list of systems including a mobile personal health monitor, a mobile phone, a wearable device, wearable clothing, wearable glasses, a wearable bracelet, wearable earphones, wearable contact lenses, a security system, and a occupancy sensor.

15. The device of claim 10, 11, 12, or 13, further comprising at least one spectral filter deposited directly on the sensor, wherein the sensitivity of the detector to different wavelength bands is achieved using said at least one filter.

16. The device of claim 15, wherein the at least one of the at least one spectral filters is configured to be a narrowband spectral filter.

17. The device of claim 10, 11, 12, or 13, wherein the sensor is configured to operate in a non-contact manner with the subject.

11. A device for estimating calories in a living subject, comprising:

(a) one or more sensors configured to noninvasively detect broadband light after interaction with the subject, each of said sensors further comprising at least one narrowband spectral filter configured to produce one or more sensor regions, each sensor region configured to be sensitive to a predetermined waveband of light; and

,

(b) a processor, and memory storing one or more programs for execution by the processor, the one or more programs including instructions for determining at least a measure of respiration, said measure determined at least in part on a spectral analysis of detected light over an interval of time, and for generating an output that is a function of the calories expended or consumed by the subject, said output based at least in part on the measure of respiration.

12. A device for estimating calories in a living subject, comprising:

(a) one or more sensors configured to noninvasively detect broadband light after interaction with the subject, each sensor further comprising a narrowband spectral filter configured to be sensitive to a predetermined waveband of light; and

,

(b) a processor, and memory storing one or more programs for execution by the processor, the one or more programs including instructions for generating spectral data using the detected light, analyzing the spectral data to computationally partition the data into more than one physiological compartment of different temporal or physiological characteristics and to computationally separate the detected light into more than one blood or tissue components, determining at least a measure of respiration at least in part based on the computational partitioning and computational separation, and generating an output that is a function of the calories expended or consumed by the subject, said output based at least in part on the measure of respiration.

13. A device for estimating calories in a living subject, comprising:

(a) a solid-state broadband white LED illuminator configured to illuminate a target site on the subject with broadband light;

(b) three or more sensors configured to noninvasively detect light returning after interaction with the subject, each sensor further comprising a narrowband spectral filter configured to be sensitive to a predetermined waveband of light; and

,

(c) a processor, and memory storing one or more programs for execution by the processor, the one or more programs including instructions for generating spectral data using the detected light, determining at least a measure of respiration at least in part based on a spectral analysis of the spectral data, and generating an output that is a function of the calories expended or consumed by the subject, said output based at least in part on the measure of respiration.