Method and apparatus for remote medical monitoring incorporating video processing and system of motor tasks

• US 6,816,603 B2
• Filed: 11/18/2002
• Issued: 11/09/2004
• Est. Priority Date: 05/18/2000
• Status: Expired due to Term

• Current Assignee: Commwell Incorporated
• Original Assignee: Commwell Incorporated
• Inventors: David, Zipora, Garber, Semion, Mikhlin, Mark, Margolis, Avmir, David, Daniel
• Primary Examiner(s): Mehta, Bhavesh M.
• Assistant Examiner(s): Choobin, Barry
• Application Number:
  US10/276,465
• Publication Number:
  US 20030228033A1
• Time in Patent Office: 722 Days
• Field of Search: 382/104, 382/103, 382/107, 382/218, 382/251, 382/38, 382/174, 382/190, 340/904, 340/907, 340/933, 348/113, 348/154, 356/313, 356/27, 353/80, 734/88, 600/301
• US Class Current: 382/107
• CPC Class Codes: A61B 5/0013 Medical image data A61B1/00011, A61B6/56, A61B8/56 take precedence
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 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 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1128 using image analysis A61B5/1127 takes precedence
• CPC Class Codes: A61B 5/4023 Evaluating sense of balance
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 40/25 Recognition of walking or running movements, e.g. gait recognition
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

Video image data is received in the form of a sequence of images representative of a subject performing one or more predetermined tasks within a new environment (FIG. 3 element 31). A plurality of silhouettes is generated from the video image data and combined to provide a motion portrait (FIG. 6). Motion characteristics are then calculated based on the motion portrait and may be compared with normal or previous motion characteristics as part of diagnostic analysis (38).

Claims

1. A method of processing video image data, the method comprising the steps of:

generating, based on the video image data, a plurality of silhouettes of a figure represented in the video image data;

forming a plurality of matrices, each matrix representing a silhouette in a frame of the video image data;

establishing a motion portrait from the plurality of matrices and based on the plurality of silhouettes; and

calculating motion characteristics from the plurality of matrices and based on the plurality of silhouettes,

wherein the motion characteristics are used to medically diagnose the figure represented in the video image data.

24. The method of claim 1, 3 or 14 using a single video image source.

26. The method of claim 1, further comprising the steps of:

saving the plurality of matrices as a data structure; and

retrieving the data structure to obtain the plurality of matrices.

27. The method of claim 1, further comprising:

summing the plurality of matrices to form a graphical fingerprint, the graphical fingerprint providing a unique characteristic template of a patient, the patient corresponding to the figure.

2. A method of measuring physiological characteristics of an individual with respect to movement of said individual comprising, in combination, the steps of:

video recording the individual performing a predefined routine of physical tasks;

processing, without human intervention, the video image recorded to define a silhouette pattern of the individual movement;

comparing the silhouette pattern with a standard;

determining the deviation of the silhouette pattern from the standard and determining whether at least one physiological characteristic is outside an expected normal range.

3. The method of claim 2 wherein the standard is a normalized representative sample for the predefined routine.

4. The method of claim 2 wherein the standard is an historic recording of the individual.

5. The method of claims 3 or 4 further including a sensor to detect a deviation from the standard.

6. The method of claim 5 wherein the deviation exceeds a limit and a sensor is provided to detect the exceeded limit.

7. The method of claim 6 wherein the deviation is announced.

8. The method of claim 2 wherein the predefined routine comprises walking from a side profile.

9. The method of claim 2 wherein the predefined routine comprises conduct of an arm motion protocol.

10. The method of claim 2 wherein the predefined routine comprises conduct of a head motion protocol.

11. The method of claim 2 wherein the predefined routine comprises a leg motion protocol.

12. The method of claim 2 wherein the predefined routine is recorded from the backside of the individual.

13. The method of claim 2 wherein the video image is recorded and stored.

20. The method of claim 2 wherein the tasks are grouped as a collection of at least two sets of tests and wherein at least one task from at least two sets is conducted with an individual during a single recording session.

22. The method of claim 2 including the step of recording at least one qualitative measurement for each task.

25. The method of claim 3, further comprising the step of:

ordering the plurality of separate tasks by associated levels of difficulty, wherein the step of instructing the entity is based upon the step of ordering.

14. A method for performing medical diagnosis based on physical motion of an individual conducted pursuant to a pre-defined protocol, comprising, in combination, the steps of:

positioning the individual in a field;

causing the individual to move in accord with an instruction;

video recording the individual movement from a fixed position;

processing, without human intervention, the video image of the individual to highlight the silhouette of the individual; and

in response to the step of analyzing, determining whether the individual movement is associated with an expected normal range.

analyzing the modification of the video image by comparing the modification to a standard and in response to the step of analyzing, determining whether the individual movement is associated with an expected normal range.

15. The method of claim 2 or 14 including the step of performing a plurality of recordings of the individual, each recording constituting distinct pattern or routine.

16. The method of claim 15 wherein the patterns or routines are of varied difficulty.

17. The method of claim 15 wherein the patterns or routines are of increasing difficulty.

18. The method of claim 15 wherein the routine or pattern is varied quantitatively.

19. The method of claim 15 wherein the routine or pattern is varied qualitatively.

21. The method of claim 2 or 14 wherein at least one qualitative measurement is conducted during a single video recording session.

23. The method of claim 2 or 14 including the step of recording at least one qualitative measurement.