Systems, devices, and methods for interpreting movement

• US 8,007,450 B2
• Filed: 05/24/2006
• Issued: 08/30/2011
• Est. Priority Date: 05/02/2005
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Williams, Mark E.
• Primary Examiner(s): Hindenburg; Max
• Assistant Examiner(s): DANEGA, RENEE A
• Application Number:
  US11/420,039
• Publication Number:
  US 20080045804A1
• Time in Patent Office: 1,924 Days
• Field of Search: 600/595, 600/449, 738/654, 735/10
• US Class Current: 600/595
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/1124 Determining motor skills
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61B 5/4519 Muscles A61B5/389, A61B5/224 take precedence
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G06V 40/25 Recognition of walking or running movements, e.g. gait recognition

Abstract

According to some exemplary embodiments, a method or system can involve associating a plurality of biokinetographic comparison results with a first specific dysfunction from a group of specific dysfunctions, each of the biokinetographic comparison results obtained from a comparison of a biokinetographic value to a standard for a corresponding biokinetographic variable.

Claims

1. A method, comprising:

automatically associating a plurality of biokinetographic comparison results for a unique patient with a first specific dysfunction comprising orthopedic injury;

obtaining each of the biokinetographic comparison results from an automatic comparison of a biokinetographic value to a standard for a corresponding biokinetographic variable that is linked to one or more specific components of a gait cycle, said one or more specific components selected from a group consisting of a left heel strike, a right heel strike, a toe strike, a right toe lift-off, and a left toe lift-off;

determining each biokinetographic value automatically from a biokinetographic data set comprising a plurality of scalar sums of acceleration values in each of three orthogonal directions, each scalar sum corresponding to a particular point in time, and

identifying a cause of the unique patient'"'"'s condition as an orthopedic injury when the biokinetographic value for the unique patient is asymmetrical cadence with a difference between a first and second double stance time of the unique patient of greater than 25 milliseconds.

2. The method of claim 1, further comprising obtaining the biokinetographic data set.

3. The method of claim 1, further comprising for each biokinetographic variable, determining a biokinetographic value from said biokinetographic data set.

4. The method of claim 1, further comprising comparing each biokinetographic value to the standard for the corresponding biokinetographic variable.

5. The method of claim 1, further comprising rendering the biokinetographic data set.

6. The method of claim 1, further comprising rendering the plurality of biokinetographic comparison results.

7. The method of claim 1, further comprising diagnosing the first specific dysfunction.

8. The method of claim 1, further comprising assessing the first specific dysfunction.

9. The method of claim 1, further comprising determining a treatment for the first specific dysfunction.

10. The method of claim 1, further comprising providing a prognosis regarding the first specific dysfunction.

11. The method of claim 1, further comprising predicting a likelihood of falling.

12. The method of claim 1, further comprising identifying a second specific biokinetographic pattern.

13. The method of claim 1, further comprising associating a second specific biokinetographic pattern with a second specific dysfunction.

14. The method of claim 1, further comprising assessing a second specific dysfunction.

15. The method of claim 1, further comprising assessing an overall health status based on the plurality of biokinetographic comparison results.

16. The method of claim 1, wherein the first double stance time is the interval during the gait cycle from a heel strike of a first leg of the unique patient to a toe lift-off of the opposite leg of the unique patient and the second double stance time is the interval from a heel strike of the opposite leg of the unique patient to a toe lift-off of the first leg of the unique patient.

17. The method of claim 1, wherein data for the biokinetographic data set is generated by

a plurality of sensors adapted to sense different moving parts of a subject;

a recording device adapted to acquire motion data generated from the plurality of sensors when the subject moves;

a memory which stores the motion data acquired by the recording device; and

a processor configured to convert the motion data into biokinetographic data.

18. The method of claim 17, wherein a conversion of the motion data into biokinetographic data comprises graphing the scalar sums of acceleration from each sensor over time.

19. A method, comprising:

automatically;

obtaining biokinetographic data for a unique patient;

analyzing said biokinetographic data; and

identifying in said biokinetographic data a first specific biokinetographic pattern for a biokinetographic variable that is linked to specific components of a gait cycle, said specific components including a heel strike, a toe strike, and a toe lift-off;

automatically associating the first specific biokinetographic pattern with a first specific dysfunction comprising orthopedic injury when the first biokinetographic pattern for the unique patient is asymmetrical cadence with a difference between a first and second double stance time of greater than 25 milliseconds; and

identifying a cause of the unique patient'"'"'s condition as an orthopedic injury based on the association of the first biokinetographic pattern with a first specific dysfunction comprising orthopedic injury.

20. The method of claim 19, wherein said specific component of said gait cycle is a heel strike interval measured from a first heel strike to a second heel strike.

21. The method of claim 19, wherein said specific component of said gait cycle is a single stance interval measured from a heel strike to a toe lift off.

22. The method of claim 19, wherein said specific component of said gait cycle is a swing through interval measured from a toe lift off to a heel strike.

23. The method of claim 19, wherein said specific component of said gait cycle is a double stance interval measured from a heel strike to an opposite leg toe lift off.