ANALYZING AND CORRELATING SPECTRA, IDENTIFYING SAMPLES AND THEIR INGREDIENTS, AND DISPLAYING RELATED PERSONALIZED INFORMATION

• US 20160091419A1
• Filed: 12/08/2015
• Published: 03/31/2016
• Est. Priority Date: 08/05/2013
• Status: Abandoned Application

• Current Assignee: Tellspec Inc.
• Original Assignee: Tellspec Inc.
• Inventors: Watson, William Stephen, Correa, Isabel De Oliveira
• Application Number:
  US14/963,080
• Publication Number:
  US 20160091419A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 10/0045 Devices for taking samples of body liquids devices for taking blood samples A61B5/15
• CPC Class Codes: A61B 2010/0083 for taking gas samples
• CPC Class Codes: G01N 2021/6493 by alternating fluorescence/transmission or fluorescence/reflection
• CPC Class Codes: G01N 21/31 Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry G01N21/72 takes precedence
• CPC Class Codes: G01N 21/64 Fluorescence; Phosphorescence
• CPC Class Codes: G01N 21/65 Raman scattering
• CPC Class Codes: G01N 2201/0221 Portable; cableless; compact; hand-held
• CPC Class Codes: G01N 2201/12 Circuits of general importance; Signal processing
• CPC Class Codes: G01N 2201/129 Using chemometrical methods
• CPC Class Codes: G01N 2201/1293 resolving multicomponent spectra
• CPC Class Codes: G01N 33/02 Food

Abstract

Obtaining two spectra from the same sample under two different conditions at about the same time for comparison, where at least one of the spectra measures magnitudes of electromagnetic radiation on at least four different ranges or weightings of wavelengths or frequencies. Classifying a sample using these spectra obtained by a user, and using spectra obtained from different samples by different users to identify the sample. Computing correlations between data related to food and ingredient consumption by one or more users over time, and data related to passive personal log data, user entered feedback, user interaction data or personal information related to those users, and detecting: foods or ingredients to which a user may be allergic or intolerant; a possible medical condition of a user; a possible link between food and ingredient consumption and a medical or health condition; or a similarity between at least two such users.

Claims

1. A method, including a step of:

obtaining at least two spectra in response to substantially the same sample under at least two different conditions at approximately the same time;

in which at least one of said two spectra is responsive to magnitudes of electromagnetic radiation on at least four different ranges or weightings of wavelengths or frequencies.

2. The method of claim 1 in which at least two of the at least two different conditions are lighting conditions.

3. The method of claim 1 in which at least one of the at least two spectra is substantially a color photograph and at least one of the at least two spectra is a Raman, emission, reflection, diffusion, or transmission spectrum.

4. The method of claim 1 in which the at least two spectra are obtained by a handheld or wearable computing device.

5. The method of claim 4 in which the said device has the functionality of a smart phone.

6. The method of claim 4 including also steps of:

triggering an audible or visible or tactile signal in response to the said obtained spectra; and

receiving some input from the user in response to said trigger.

7. The method of claim 1 in which the said sample is at least one of the following:

(a) a sample of a food;

(b) a sample of a substance or material;

(c) a sample of a part of a human body;

(d) a sample of bodily fluids, gases, or solids;

or

(e) a sample of a liquid or gas.

8. A method including steps of:

classifying a first sample into a class using a first set of one or more scans related to that first sample obtained by a first user;

referencing a second set of one or more scans obtained by a second user related to a second sample in the said class;

or

computing information related to said first sample in response to both sets of scans.

9. The method of claim 8, in which at least some of the said scans are spectra and including at least one of the following steps:

(a) subtracting the sum of one or more of said spectra from the sum of one or more of said spectra;

(b) computing the projection of at least one of said spectra onto at least two other spectra;

(c) calculating a spline related to at least one of said spectra;

or

(d) computing differences between at least two of said spectra, and in response to such computing, determining possible inhomogeneity of said first sample.

10. The method of claim 8, including also steps of:

identifying said first sample in response to said sets of scans;

wherein such identifying includes identifying the first sample as a sample of a first food, and at least one of the following;

(a) the SKU of the first sample;

(b) the origins or supply chain of the first sample;

(c) the sensory characteristics or other properties of the first sample;

(d) the recommended preparation, cooking, and storage of the first sample;

or

(e) the species or variety of the first sample.

11. The method of claim 8 in which said computing of information includes at least one of the following steps:

a. evaluating at least one scan under at least two possible identification schemes;

b. comparing identification schemes in response to how well they identify other samples already identified;

or

c. evaluating a functional computer program with reference to a database of correlations between spectra.

12. The method of claim 8 including also a step of:

identifying one or more ingredients of said first sample in response to said sets of scans.

13. The method of claim 12 including also a step of:

ranking the one or more ingredients, where said ranking is responsive to at least one of;

(a) an estimated concentration or quantity of said ingredient in said first sample;

(b) the user feedback and/or user interaction of the first user;

(c) the personal or medical information of the first user;

(d) the similarity of said one or more ingredients to each other;

or

(e) the possible medical or health effects of the said one or more ingredients on the first user.

14. The method of claim 10 including also a step of:

ranking said first food relative to at least one or more other foods, where said ranking is responsive to at least one of;

(a) the ingredients of the said foods;

(b) the user feedback by the first user related to said foods;

(c) the volume of servings of said foods;

(d) the preferences of the first user;

or

(e) the food consumption history of the first user.

15. The method of claim 14 including also a step of selecting of a second food, where said selecting is responsive to at least one of:

a. the similarity of the said second food to the said first food;

b. the said ranking of the said second food relative to the said first food;

c. the complementarity of the said second food relative to the said first food;

d. business rules applying to the SKU of the said second food;

or

e. availability to the said first user of the said second food.

16. The method of claim 14 including also steps of ranking of at least one of the following:

a. food stores;

b. restaurants;

c. diets;

or

d. the consumption of food by the first user;

in response to the said ranking of foods.

17. The method of claim 14 including also a step of selecting possible actions by the said first user, where said selecting is responsive to said ranking of foods, and where said possible actions are related to the possible improvement of health or longevity of the said first user.

18. The method of claim 17 including also a step of selecting portfolios of said possible actions, where completion of said portfolios by a user triggers the sending of a notification to the said first user.

19. The method of claim 17 including also a step of selecting a group of users and creating a scoreboard shown to said first, wherein said scores are responsive to completion by users of said possible actions, and said group of users is chosen so that at least one of the following:

(a) the users in the group of users are similar;

or

(b) the said first user has a score less than the median score of the group of users.

20. A method including steps of:

referencing a first set of data related to food and ingredient consumption by one or more users over time;

referencing a second set of data, related to passive personal log data, user entered feedback, user interaction data or personal information, related to said one or more users over time;

computing a correlation between the first and second sets of data

and detecting at least one of

(a) a possible food or ingredient to which at least one said user is likely allergic or intolerant.

(b) a similarity between at least two such said users;

(c) a possible medical condition of at least one said user;

or

(d) a possible relationship between food and ingredient consumption and a medical or health condition.