Automated near-fall detector

• US 10,548,512 B2
• Filed: 06/24/2010
• Issued: 02/04/2020
• Est. Priority Date: 06/24/2009
• Status: Active Grant

• Current Assignee: The Medical Research, Infrastructure And Health Services Fund Of The Tel Aviv Medical Center
• Original Assignee: The Medical Research, Infrastructure And Health Services Fund Of The Tel Aviv Medical Center
• Inventors: Hausdorff, Jeffrey M., Giladi, Nir
• Primary Examiner(s): Abouelela, May A
• Application Number:
  US13/380,863
• Publication Number:
  US 20120101411A1
• Time in Patent Office: 3,512 Days
• Field of Search: 600300, 600587, 600595
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses

Abstract

A method of gait data collection, the method comprising collecting movement data, determining from the data a movement parameter that includes a third order derivative of position, comparing the movement parameter with a threshold value, and counting at least a near fall if the movement parameter exceeds the threshold value.

Claims

1. A method of determining gait irregularity, including near fall events, in an event of which a user recovers from a momentary loss of balance during the gait, the method comprising:

electronically collecting movement data using a single detector configured to measure acceleration of the user'"'"'s body, said detector configured to be located at a single location on the user'"'"'s body, wherein said collected movement data is collected by said single detector, wherein said single location is a torso of the body;

using a processor in communication with said detector, electronically determining a movement parameter value from said data collected at the single location on the user'"'"'s body, wherein said movement parameter value comprises a measure of maximum acceleration, and wherein said movement parameter value relates to a movement parameter in a substantially vertical direction;

electronically comparing, using said processor, said movement parameter value determined from said data collected using said detector with a threshold value, wherein said electronically comparing comprises comparing said measure of maximum acceleration with said threshold value to identify near fall events during the gait;

identifying near fall events during the gait using a result of said comparing; and

electronically storing a count of a plurality of near fall events in a memory.

2. A method according to claim 1, wherein the method comprises determining a fall.

3. A method according to claim 1, wherein determining comprises matching a pattern with respect to time of the movement data with a reference pattern.

4. A method according to claim 3, wherein the reference pattern represents proper gait pattern.

5. A method according to claim 3, wherein the reference pattern represents improper gait pattern.

6. A method according to claim 3, wherein the reference pattern represents a gait pattern exhibiting at least one near fall event.

7. A method according to claim 3, wherein the matching classifies the data as exhibiting a fall, a near fall event, or lack thereof.

8. A method according to claim 3, wherein the matching comprises at least one of correlation, cross-correlation, wavelets matching or neural networks or a combination thereof.

9. A method of gait data collection according to claim 1, wherein said electronically comparing comprises comparing said measure of movement in the vertical direction with said threshold value to identify near fall events during the gait.

10. A method of gait data collection according to claim 1, wherein

determining from said data further includes determining a second movement parameter value,

comparing said movement parameter value further includes comparing said second movement parameter value with a second threshold value, and

counting a plurality of near fall events comprises counting at least a near fall event if said movement parameter value exceeds said threshold value and said second movement parameter value exceeds said second threshold value.

11. A method of gait data collection according to claim 10, wherein said second movement parameter value includes one of the group consisting of;

a rate of change of acceleration, an angular velocity, an anterior-posterior acceleration, a medio-lateral acceleration.

12. A method of gait data collection according to claim 10, wherein said second movement parameter value relates to a movement parameter in a substantially vertical direction.

13. A method of gait data collection according to claim 1, wherein said threshold value is a predetermined value.

14. A method of gait data collection according to claim 1, wherein said threshold value is a continuously updated function of said movement parameter value.

15. A method of gait data collection according to claim 14, wherein said function is a mean of multiple movement parameter values plus a multiple of a standard deviation of said multiple movement parameter values.

16. A method of gait data collection according to claim 1, wherein said counting of near fall events provides a quantitative measure of effectiveness of therapeutic interventions.

17. A method of determining gait irregularity according to claim 1,

wherein said movement data includes cyclic acceleration data;

and

electronically determining comprises;

determining from said acceleration data periods of cycles; and

identifying a gait irregularity when a period of a cycle exceeds a threshold.

18. A method of determining gait irregularity according to claim 17,

wherein said cyclic acceleration data includes peaks;

and

electronically determining comprises;

determining from said acceleration data periods between said peaks; and

identifying a gait irregularity when a period between said peaks exceeds a threshold.

19. A method of gait data collection, according to claim 1,

wherein said movement data includes cyclic acceleration data, each cycle including a cycle shape;

and

electronically determining comprises;

determining from said acceleration data periods between said peaks; and

identifying a gait irregularity when a cycle shape varies above a threshold.

20. A method of gait data collection, according to claim 1, wherein said movement data includes cyclic acceleration data, each cycle including a cycle shape;

and

electronically determining comprises;

determining from said acceleration cross-correlation between cycles; and

identifying a gait irregularity when a cross-correlation between cycles exceeds a threshold.

21. A method of gait data collection according to claim 1, wherein

electronically determining comprises:

determining from said data an acceleration frequency spread; and

identifying an irregularity of the gait from said acceleration frequency spread.

22. A method of gait data collection, according to claim 21, wherein determining said acceleration frequency spread is by using a Fourier transform.

23. A method of gait data collection, according to claim 1, comprising:

electronically determining from said movement data a step width.

24. A method of gait data collection, according to claim 1, the method comprising:

electronically determining from said movement data a step length.

25. A method of gait data collection according to claim 1, wherein said movement parameter value relates to movement in substantially an anterior-posterior direction.

26. A method according to claim 1, wherein said electronically collecting is using a sensor.

27. A method according to claim 1, wherein said counting of near fall events provides quantifiable parameters for assessing a person.

28. A method according to claim 1, wherein said identifying near fall events during the gait includes using the result of said comparing, if said determined movement parameter value exceeds said threshold value.

29. A method according to claim 1, wherein said using the processor includes electronically determining the movement parameter value from collected acceleration data alone.

30. A method of determining gait irregularity, including near fall events, in an event of which a user recovers from a momentary loss of balance during the gait, the method comprising:

electronically collecting movement data using a single detector configured to measure acceleration of the user'"'"'s body, said detector configured to be located at a single location on the user'"'"'s body, wherein said collected movement data is collected by said single detector, wherein said single location is a torso of the body,

using a processor in communication with said detector, electronically determining a plurality of movement parameter values from said data collected at the single location on the user'"'"'s body, wherein said plurality of movement parameter values comprise a measure of maximum acceleration, and where said plurality of movement parameter values includes at least one movement parameter value related to a movement parameter in a substantially vertical direction,

electronically determining, using said processor, from said data at least one irregularity of the gait, including identifying near fall events during the gait, said electronically determining including electronically comparing each of said plurality of movement parameter values with an associated threshold value, wherein said electronically comparing comprises comparing said measure of maximum acceleration with said threshold value to identify near fall events during the gait, including comparing said at least one movement parameter value related to the movement parameter in the substantially vertical direction determined from said data collected using said detector with a threshold value, to indicate a near fall event when each said movement parameter value related to the movement parameter in the substantially vertical direction exceeds an associated threshold value, and

electronically storing a count of a near fall event in a memory, if a predetermined combination of comparisons indicate a near fall event.

31. A method of gait data collection according to claim 30, the method comprising:

electronically recording a magnitude of said near fall event.

32. A method of gait data collection according to claim 30, wherein said predetermined combination of movement parameters is a majority of said plurality of movement parameters;

and

electronically counting comprises electronically counting at least a near fall event if said majority of said plurality of comparisons indicates a near fall event.

33. A method of determining gait irregularity, including near fall events, in an event of which a user recovers from a momentary loss of balance, the method comprising:

electronically collecting movement data using a single detector configured to measure acceleration of the user'"'"'s body, said movement data including a measure of maximum acceleration, said detector configured to be located at a single location on the user'"'"'s body, wherein said collected movement data is collected by said single detector, wherein said single location is a torso of the body,

using a processor in communication with said detector, electronically extracting an indicator indicating a loss of control from said data collected at the single location on the user'"'"'s body, wherein said indicator indicating the loss of control includes at least one movement parameter value which exceeds a threshold value, wherein said electronically extracting an indicator comprises comparing said measure of maximum acceleration with said threshold value to identify near fall events during the gait, wherein said movement parameter value relates to a movement parameter in a substantially vertical direction,

electronically storing a count of at least a near fall event, in a memory, if said indicator indicates said loss of control, and

electronically recording a date or time for said near fall event, in said memory.

34. A method of gait data collection according to claim 33, wherein said counting of at least a near fall event provides a quantitative measure of effectiveness of therapeutic interventions.

35. A method according to claim 33, wherein said counting of at least a near fall event provides quantifiable parameters for assessing a person.

36. A method for assisting a person'"'"'s gait while walking, comprising:

(a) using a sensor configured to be located at a single location on the person'"'"'s torso, electronically detecting, based on time derivation of gait movements, near fall events during the gait; and

(b) electronically providing periodic gait regulating cueing signals indicating a suggested gait pace while walking, responsive to said detecting near fall events, wherein said suggested gait pace includes at least one of an indication and a prompt of a regular pace for the gait;

wherein said gait movements are collected using the sensor;

wherein said electronically detecting is using a processor in communication with said sensor;

wherein said electronically providing is by a user interface.

37. A method according to claim 36, wherein the signals are at least one of audible, tactile or visual.

38. A method of gait data collection according to claim 36, wherein said cueing signals prompt the person to recover a proper gait.

39. The method according to claim 36, wherein said periodically electronically providing is based on a proper gait of a healthy person.

40. The method according to claim 36, wherein said suggested gait pace is based on intervals where the person'"'"'s gait is determined to be proper.

41. An apparatus for assisting a person'"'"'s gait while walking, comprising:

(a) a sensor operatively connected to the person'"'"'s torso and responsive to movement of said person during the gait;

(b) a processor adapted to receive movement data from said sensor and to process said movement data to detect near fall events during the movement during the gait; and

(c) at least one device operable to provide periodic cuing signals responsive to detected near fall events during the gait, wherein said cuing signals include at least one signal indicating a suggested gait pace to adjust the gait and to stabilize the gait while walking, wherein said suggested gait pace includes at least one of an indication and a prompt of a regular pace for the gait.

42. A device according to claim 41, wherein the signals are at least one of audible, tactile or visual.

43. A device according to claim 41, wherein said processor is adapted to process said movement data to detect a gait irregularity.

44. A device according to claim 41, wherein said cuing signals are selected from audible messages, audible ticks, vibrations, audible prompts, auditory stimulation, and visual stimulation.

45. The device according to claim 41, wherein said cuing signals include at least one of rhythmic tones, rhythmic alarm lights, and rhythmic indications on a display.

46. Apparatus according to claim 41, wherein said cuing signals are based on behavior detected or assessed in healthy persons.

47. Apparatus according to claim 41, wherein said suggested gate pace is based on intervals where the person'"'"'s gait is determined to be proper.