Lower limb loading assessment systems and methods

• US 10,405,780 B2
• Filed: 02/18/2015
• Issued: 09/10/2019
• Est. Priority Date: 03/25/2014
• Status: Active Grant

• Current Assignee: IMeasureU Limited (Oxford Metrics PLC)
• Original Assignee: IMeasureU Limited (Oxford Metrics PLC)
• Inventors: Finch, Mark, Besier, Thor Franciscus
• Primary Examiner(s): Hindenburg, Max F
• Application Number:
  US15/128,808
• Publication Number:
  US 20180020950A1
• Time in Patent Office: 1,665 Days
• Field of Search: None
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/1036 Measuring load distribution, e.g. podologic studies
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1124 Determining motor skills
• CPC Class Codes: A61B 5/6829 Foot or ankle
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G01P 15/18 in two or more dimensions

Abstract

A lower loading assessment system having at least one motion sensor mounted to a subject'"'"'s lower limb that is configured to sense the tibial shockwaves experienced by the lower limb as the subject performs a repetitive physical activity involving repetitive footstrikes of the lower limb with a surface. The motion sensor comprises an accelerometer that is configured to sense acceleration data in at least three axes and generate representative acceleration data over a time period associated with the physical activity. The acceleration data represents a series of discrete tibial shockwaves from the discrete footstrikes. A data processor receives the tibial shockwave data and processes that to generate output feedback data comprising data to assist the subject to minimize future loading in their lower limbs.

Claims

1. A lower limb loading assessment system comprising:

at least one wearable motion sensor releasably securable to a subject'"'"'s lower limb that is configured to sense the tibial shockwaves experienced by the lower limb as the subject performs a repetitive physical activity involving repetitive footstrikes of the lower limb with a surface, the wearable motion sensor comprising an accelerometer that is configured to sense acceleration data in at least three orthogonal axes and generate representative multi-axis acceleration data over a time period associated with the physical activity, the wearable motion sensor generating tibial shockwave data comprising the generated multi-axis acceleration data which represents a series of discrete tibial shockwaves from the discrete footstrikes; and

a data processor that is configured to receive and convert the tibial shockwave data comprising the multi-axis acceleration data sensed by the wearable motion sensor into resultant acceleration magnitude data, and wherein the data processor is configured to process the resultant acceleration magnitude data to generate output feedback data comprising data to assist the subject to minimize future loading in their lower limbs.

2. The lower limb loading assessment system according to claim 1 wherein the data processor is further configured to extract or calculate one or more variables from the received tibial shockwave data or resultant acceleration magnitude data and compare the or each variable to a predetermined threshold or thresholds, and provide feedback data in the form of a real-time alert signal if one or more of the thresholds is exceeded by its associated variable.

3. The lower limb loading assessment system according to claim 2 wherein the data processor is configured to extract peak shock variables representing the peak resultant acceleration magnitude data associated with each discrete footstrike.

4. The lower limb loading assessment system according to claim 3 wherein the data processor is configured to generate a real-time alert signal if any peak shock variables exceed a predetermined threshold.

5. The lower limb loading assessment system according to claim 3 wherein the data processor is configured to calculate an average peak shock variable representing the average of the extracted peak shock variables, and wherein the data processor is configured to generate a real-time alert signal if the average peak shock variable exceeds a predetermined threshold.

6. The lower limb loading assessment system according to claim 2 wherein the data processor is configured to generate footstrike pattern variables representing the footstrike pattern associated with each footstrike as defined by the profile of the resultant acceleration magnitude data for a period associated with each discrete footstrike, and generate a real-time alert signal if any of the footstrike pattern variables exceed a predetermined footstrike pattern threshold.

7. The lower limb loading assessment system according to claim 2 wherein the data processor is configured to generate footstrike pattern variables representing the footstrike pattern associated with each footstrike as defined by the profile of the acceleration data in three axes for a period associated with each discrete footstrike, and generate a real-time alert signal if any of the footstrike pattern variables exceed a predetermined footstrike pattern threshold.

8. The lower limb loading assessment system according to claim 6 wherein the data processor is configured to generate the footstrike pattern variables based on tibial shockwave data for each discrete footstrike between heelstrike and toe-off time locations.

9. The lower limb loading assessment system according to claim 2 wherein the system further comprises one or more feedback devices mounted to or carried by the user that are triggered by in response to a generated real-time alert signal.

10. The lower limb loading assessment system according to claim 9 wherein the feedback devices comprise any one or more of the following:

tactile feedback devices, audible feedback devices, and/or visual feedback devices.

11. The lower limb loading assessment system according to claim 1 wherein the data processor is configured to process the tibial shockwave data to generate feedback data in the form of data indicative of a session load stimulus.

12. The lower limb loading assessment system according to claim 1 wherein the data processor is configured to receive tibial shockwave data from a plurality of activity sessions of the subject from a single day, and generate feedback data in the form data indicative of a daily load stimulus.

13. The lower limb loading assessment system according to claim 1 wherein the data processor is configured to identify the time locations of the heelstrikes associated with each footstrike, and generate feedback data in the form of cadence representing the average time between heelstrikes.

14. The lower limb loading assessment system according to claim 1 wherein the data processor is configured to:

receive tibial shockwave data from a plurality of separate activity sessions,

convert the 3-axes acceleration data of the tibial shockwave data into resultant acceleration magnitude data,

extract peak shock values representing the peak resultant acceleration magnitude associated with each discrete footstrike of the tibial shockwave data of each of the separate activity sessions,

calculate the average peak resultant acceleration magnitude for each of the separate activity sessions based on the extracted peak shock values, and

generate feedback data representing the calculated average peak resultant acceleration magnitude for each separate activity session.

15. The lower limb loading assessment system according to claim 14 wherein the subject is wearing a different type of footwear in each separate activity session, and the data processor is configured to receive or associate unique identification data relating to each different type of footwear used by the subject with the respective tibial shockwave data of each activity session, and the feedback data generated comprises data representing the calculated average peak resultant acceleration magnitude of each separate activity session linked with the unique identification data relating to the footwear used in the activity session.

16. The lower limb loading assessment system according to claim 14 wherein the data processor is further configured to compare the calculated average peak resultant acceleration magnitude associated with each activity session and generate further feedback data identifying the activity session having the lowest peak resultant acceleration magnitude.

17. The lower limb loading assessment system according to claim 1 wherein the accelerometer is a 3-axis accelerometer.

18. The lower limb loading assessment system according to claim 1 wherein the data processor is communicatively coupled to the wearable motion sensor over a data link.

19. The lower limb loading assessment system according to claim 1 wherein the data processor is onboard the wearable motion sensor.

20. The lower limb loading assessment system according to claim 1 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb between the femoral epicondyle and medial malleolus.

21. The lower limb loading assessment system according to claim 1 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region of the lower ⅓

^rd of the tibia.

22. The lower limb loading assessment system according to claim 1 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region of the medial part of the tibia.

23. The lower limb loading assessment system according to claim 22 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region adjacent and above the medial malleolus of the tibia.

24. The lower limb loading assessment system according to claim 1 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region adjacent and above the lateral malleolus of the tibia.

26. The lower limb loading assessment system according to claim 7 wherein the data processor is configured to generate the footstrike pattern variables based on tibial shockwave data for each discrete footstrike between heelstrike and toe-off time locations.

25. An electronic system for assessing the loading on a subject'"'"'s lower limb as the subject performs a repetitive physical activity involving repetitive footstrikes of the lower limb with a surface, the system comprising a data processor configured to:

receive tibial shockwave data comprising sensed multi-axis acceleration data from at least one wearable motion sensor releasably secured to the subject'"'"'s lower limb that comprises an accelerometer that is configured to sense and generate multi-axis acceleration data in at least three orthogonal axes, the sensed multi-axis acceleration data representing a series of discrete tibial shockwaves from the discrete footstrikes;

convert the tibial shockwave data comprising the multi-axis acceleration data into resultant acceleration magnitude data;

process the resultant acceleration magnitude data; and

generate output feedback data comprising data to assist the subject to minimize future loading in their lower limbs.

27. The electronic system according to claim 25 wherein the data processor is further configured to extract or calculate one or more variables from the received tibial shockwave data or resultant acceleration magnitude data, compare the or each variable to a predetermined threshold or thresholds, and generate feedback data in the form of a real-time alert signal if one or more of the thresholds is exceeded by its associated variable.

28. The electronic system according to claim 27 wherein the data processor is further configured to extract peak shock variables representing the peak resultant acceleration magnitude data associated with each discrete footstrike.

29. The electronic system according to claim 28 wherein the data processor is further configured to generate a real-time alert signal is any peak shock variables exceed a predetermined threshold.

30. The electronic system according to claim 28 wherein the data processor is further configured to calculate an average peak shock variable representing the average of the extracted peak shock variables, and generate a real-time alert signal if the average peak shock variable exceeds a predetermined threshold.

31. The electronic system according to claim 27 wherein the data processor is further configured to generate footstrike pattern variables representing the footstrike pattern associated with each footstrike as defined by the profile of the resultant acceleration magnitude data for a period associated with each discrete footstrike, and generate a real-time alert signal if any of the footstrike pattern variables exceed a predetermined footstrike pattern threshold.

32. The electronic system according to claim 27 wherein the data processor is further configured to generate footstrike pattern variables representing the footstrike pattern associated with each footstrike as defined by the profile of the acceleration data in three axes for a period associated with each discrete footstrike, and generate a real-time alert signal if any of the footstrike pattern variables exceed a predetermined footstrike pattern threshold.

33. The electronic system according to claim 31 wherein the data processor is configured to generate the footstrike pattern variables based on tibial shockwave data for each discrete footstrike between heelstrike and toe-off time locations.

34. The electronic system according to claim 27 wherein the data processor is configured to trigger one or more feedback devices mounted to or carried by the user in response to a generated real-time alert signal.

35. The electronic system according to claim 34 wherein the feedback devices comprise any one or more of the following:

tactile feedback devices, audible feedback devices, and/or visual feedback devices.

36. The electronic system according to claim 25 wherein the data processor is configured to process the tibial shockwave data to generate feedback data in the form of data indicative of a session load stimulus.

37. The electronic system according to claim 25 wherein the data processor is configured to receive tibial shockwave data from a plurality of activity sessions of the subject from a single day, and generate feedback data in the form data indicative of a daily load stimulus.

38. The electronic system according to claim 25 wherein the data processor is configured to identify the time locations of the heelstrikes associated with each footstrike, and generate feedback data in the form of cadence representing the average time between heelstrikes.

39. The electronic system according to claim 25 wherein the data processor is configured to:

receive the tibial shockwave data from a plurality of separate activity sessions, convert the 3-axes acceleration data of the tibial shockwave data into resultant acceleration magnitude data;

extract peak shock values representing the peak resultant acceleration magnitude associated with each discrete footstrike of the tibial shockwave data of each of the separate activity sessions;

calculate the average peak resultant acceleration magnitude for each of the separate activity sessions based on the extracted peak shock values; and

generate feedback data representing the calculated average peak resultant acceleration magnitude for each separate activity session.

40. The electronic system according to claim 39 wherein the subject is wearing a different type of footwear in each separate activity session, and the data processor is configured to receive or associate unique identification data relating to each different type of footwear used by the subject with the respective tibial shockwave data of each activity session, and the feedback data generated comprises data representing the calculated average peak resultant acceleration magnitude of each separate activity session linked with the unique identification data relating to the footwear used in the activity session.

41. The electronic system according to claim 39 wherein the data processor is further configured to compare the calculated average peak resultant acceleration magnitude associated with each activity session and generate further feedback data identifying the activity session having the lowest peak resultant acceleration magnitude.

42. The electronic system according to claim 25 wherein the accelerometer is a 3-axis accelerometer.

43. The electronic system according to claim 25 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb between the femoral epicondyle and medial malleolus.

44. The electronic system according to claim 25 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region of the lower third of the tibia.

45. The electronic system according to claim 25 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region of the medial part of the tibia.

46. The electronic system according to claim 45 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region adjacent and above the medial malleolus of the tibia.

47. The electronic system according to claim 25 wherein the wearable motion sensor is releasably securable to the subject'"'"'s lower limb in the region adjacent and above the lateral malleolus of the tibia.

48. The electronic system according to claim 32 wherein the data processor is configured to generate the footstrike pattern variables based on tibial shockwave data for each discrete footstrike between heelstrike and toe-off time locations.