Capturing data for individual physiological monitoring

• US 10,192,033 B2
• Filed: 03/03/2016
• Issued: 01/29/2019
• Est. Priority Date: 05/22/2007
• Status: Active Grant

• Current Assignee: Monument Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Monument Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Inventors: Kurtz, Andrew F., Gobeyn, Kevin M., Olson, Donald E., Border, John N.
• Primary Examiner(s): Strege, John
• Application Number:
  US15/059,786
• Publication Number:
  US 20160188831A1
• Time in Patent Office: 1,062 Days
• 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, health data, semantic data, and identification data from a subject;

receiving, via the processor, subject image data;

measuring, via the processor, environmental factors;

perform, via the processor, data analysis on the health data, semantic data, and identification data received and the environmental factors;

determining, via the processor, nominal input capture parameters and wellness parameters;

preparing, via the processor, a reference image based on the determined nominal input capture parameters, wellness parameters, and data analysis; and

comparing a received image with the reference image, and determining possible causes and interventions of identified health issues based on comparing the received image with the reference image.

2. The method of claim 1, wherein preparing the reference image includes changing a range of variable capture conditions to prepare a collection of baseline data.

3. The method of claim 2, wherein the collection of baseline data includes a plurality of reference images.

4. The method of claim 1, further comprising generating reference image parameters to quantify physical attributes for reference features of the subject.

5. The method of claim 4, wherein reference features include distance between the eyes of the subject.

6. The method of claim 4, further comprising identifying the subject based at least in part on the reference image parameters.

7. A system comprising:

one or more processors configured to;

receive health data, semantic data, and identification data from a subject;

receive subject image data;

measure environmental factors;

perform data analysis on the health data, semantic data, and identification data received and the environmental factors;

determine nominal input capture parameters and wellness parameters; and

prepare a reference image based on the determined nominal input capture parameters, wellness parameters, and data analysis; and

compare a received image with the reference image, and determine possible causes and interventions of identified health issues based on comparing the received image with the reference image.

8. The system of claim 7, wherein preparation of the reference image includes changing a range of variable capture conditions to prepare a collection of baseline data.

9. The system of claim 8, wherein collection of baseline data includes a plurality of reference images.

10. The system of claim 7, wherein the one or more processors are further configured to generate reference image parameters to quantify physical attributes for reference features of the subject.

11. A non-transitory computer-readable medium having processor-executable instructions stored thereon, the instructions, when executed by a processor, causing the processor to perform steps comprising:

receiving health data, semantic data, and identification data from a subject;

receiving subject image data;

measuring environmental factors;

performing data analysis on the health data, semantic data, and identification data, received and the environmental factors;

determining nominal input capture parameters and wellness parameters;

preparing a reference image based on the determined nominal input capture parameters, wellness parameters, and data analysis; and

comparing a received image with the reference image, and determining possible causes and interventions of identified health issues based on comparing the received image with the reference image.

12. The non-transitory computer-readable medium of claim 11, wherein instructions to prepare the reference image instructions, which when executed by the processor, cause the processor to change a range of variable capture conditions to prepare a collection of baseline data.

13. The non-transitory computer-readable medium of claim 12, wherein the collection of baseline data includes collecting a plurality of reference images.

14. The non-transitory computer-readable medium of claim 11, further comprising instructions, which when executed by the processor, cause the processor to generate reference image parameters to quantify physical attributes for reference features of the subject.

15. The non-transitory computer-readable medium of claim 14, wherein said reference features include distance between eyes of the subject.

16. The non-transitory computer-readable medium of claim 15, further comprising instructions, which when executed by the processor, cause the processor to identify the subject based, at least in part, on the reference image parameters.