Capturing data for individual physiological monitoring

• US 9,298,883 B2
• Filed: 08/08/2014
• Issued: 03/29/2016
• Est. Priority Date: 05/22/2007
• Status: Expired due to Fees

• Current Assignee: Intellectual Ventures Fund 83 LLC (Intellectual Ventures LLC)
• Original Assignee: Intellectual Ventures Fund 83 LLC (Intellectual Ventures LLC)
• Inventors: Kurtz, Andrew F., Gobeyn, Kevin M., Olson, Donald E., Border, John N.
• Primary Examiner(s): STREGE, JOHN B
• Application Number:
  US14/454,913
• Publication Number:
  US 20140348403A1
• Time in Patent Office: 599 Days
• Field of Search: 382/128
• US Class Current: 1/1
• CPC Class Codes: A61B 3/10 Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• 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 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/1176 Recognition of faces
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/442 Evaluating skin mechanical properties, e.g. elasticity, hardness, texture, wrinkle assessment
• CPC Class Codes: A61B 5/444 Evaluating skin marks, e.g. mole, nevi, tumour, scar
• CPC Class Codes: A61B 5/445 Evaluating skin irritation or skin trauma, e.g. rash, eczema, wound, bed sore
• CPC Class Codes: A61B 5/4547 Evaluating teeth
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method for capturing images of an individual to determine wellness for such individual, including establishing baseline physiological data for the individual, and baseline capture condition data for the individual; detecting and identifying the presence of the individual in the image capture environment; providing semantic data associated with the individual; capturing one or more images of the individual during a capture event and determining the capture conditions present during the capture event; using the event capture conditions, the baseline physiological data for the individual and the baseline capture condition data to determine the acceptability of event captured images; and using the acceptable images and the semantic data in determining the wellness of the individual.

Claims

1. A method comprising:

receiving, via a processor, an image of a subject;

performing, via the processor, an image normalization to image data in the received image;

determining, via the processor, trends and triggers in normalized image data;

querying a wellness database based on the determined trends and triggers; and

determining, based on the query results and the determined trends and triggers, possible causes and interventions of identified health issues.

2. The method of claim 1, wherein the image normalization comprises measuring normalization factors.

3. The method of claim 2, wherein the image normalization comprises validating specific normalization data.

4. The method of claim 3, wherein the image normalization comprises calculating normalized image data from normalization transforms.

5. The method of claim 1, further comprising calculating, via the processor, wellness factors.

6. The method of claim 1, further comprising performing a false positive reduction process.

7. The method of claim 6, wherein the false positive reduction process comprises utilizing semantic data to identify false positives.

8. The method of claim 1, further comprising accumulating, via the processor, a record from two or more images of the subject and condition data associated with two or more acceptable captured images, wherein the record provides a visual history of the subject over a time period with the images in the visual history to enable detection of changes in physiological conditions of the subject over the time period.

9. A system comprising:

one or more processors configured to;

receive a subject image;

perform an image normalization to image data in the received subject image;

determine trends and triggers in normalized image data;

query a wellness database based on the determined trends and triggers; and

determine, based on the query results and the determined trends and triggers, possible causes and interventions of identified health issues.

10. The system of claim 9, wherein the image normalization comprises measuring normalization factors.

11. The system of claim 10, wherein the image normalization comprises validating specific normalization data.

12. The system of claim 11, wherein the image normalization comprises calculating normalized image data from normalization transforms.

13. The system of claim 9, wherein the one or more processors are further configured to calculate wellness factors.

14. The system of claim 9, wherein the one or more processors are further configured to perform a false positive reduction process.

15. A non-transitory computer-readable medium having instructions stored thereon, the instructions comprising:

instructions to receive a subject image;

instructions to perform an image normalization to image data in the received subject image;

instructions to determine trends and triggers in normalized image data;

instructions to query a wellness database based on the determined trends and triggers; and

instructions to determine, based on the query results and the determined trends and triggers, possible causes and interventions of identified health issues.

16. The non-transitory computer-readable medium of claim 15, wherein the image normalization comprises measuring normalization factors.

17. The non-transitory computer-readable medium of claim 16, wherein the image normalization comprises validating specific normalization data.

18. The non-transitory computer-readable medium of claim 17, wherein the image normalization comprises calculating normalized image data from normalization transforms.

19. The non-transitory computer-readable medium of claim 15, wherein the instructions further comprise instructions to calculate wellness factors.

20. The non-transitory computer-readable medium of claim 15, wherein the instructions further comprise instructions to perform a false positive reduction process.