Systems, devices, and methods for interpreting movement

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.