Processing sensed accelerometer data for determination of bone healing

• US 9,445,720 B2
• Filed: 02/23/2007
• Issued: 09/20/2016
• Est. Priority Date: 02/23/2007
• Status: Active Grant

• Current Assignee: Smith & Nephew Incorporated (Smith & Nephew PLC)
• Original Assignee: Smith & Nephew Incorporated (Smith & Nephew PLC)
• Inventors: Janna, Sied W., Wilson, Darren James, Brady, Peter A.
• Primary Examiner(s): EISEMAN, ADAM JARED
• Application Number:
  US12/528,243
• Publication Number:
  US 20100152621A1
• Time in Patent Office: 3,497 Days
• Field of Search: 600/552, 600/553, 600/587, 600/592, 600/594, 600/595, 340/669
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/4504 Bones A61B5/4547 takes precedence
• CPC Class Codes: A61B 5/6807 Footwear
• CPC Class Codes: A61B 5/7257 using Fourier transforms

Abstract

A system (800) for processing accelerometer data is disclosed. The system (800) includes an accelerometer (806), a first processor (810), a power supply (816), and a second processor (804). The accelerometer (806) measures a physiological acceleration parameter. The first processor (810) is operatively connected to the accelerometer (806). The first processor (810) is configured to receive the acceleration parameter from the accelerometer (806) and configured to output machine readable acceleration data. The machine readable acceleration data includes time domain accelerometer data. The power supply (816) is electrically connected to the first processor (810). The second processor (804) is configured to receive the machine readable acceleration data and transform the time domain accelerometer data into frequency domain accelerometer data. The frequency domain accelerometer data may be used to estimate patient healing status.

Claims

1. A system for processing accelerometer data, the system comprising:

a. an accelerometer for measuring a physiological acceleration parameter;

b. a first processor operatively connected to the accelerometer, the first processor configured to receive the acceleration parameter from the accelerometer and configured to output machine readable acceleration data, the machine readable acceleration data comprising time domain accelerometer data;

c. a power supply electrically connected to the first processor; and

d. a second processor configured to;

receive the machine readable acceleration data,

transform the time domain accelerometer data into frequency domain accelerometer data, the frequency domain accelerometer data comprising data about one or more gait cycles,

analyze a bone healing progression based on the frequency domain accelerometer data, and

output a healing number that indicates a percentage of bone healing in the area surrounding the implant,

wherein, to analyze the bone healing progression based on the frequency domain accelerometer data, the second processor is configured to analyze the frequency domain accelerometer to determine a level of bone healing of a subject in an area surrounding the intramedullary nail based on the data about the one or more gait cycles;

wherein the accelerometer and the first processor are located within the intramedullary nail or an intramedullary nail cap.

2. The system according to claim 1, wherein the accelerometer and the first processor are located within a medical implant.

3. The system according to claim 1, wherein the accelerometer and the first processor are located within a wearable device.

4. The system according to claim 1, wherein an antenna is operatively connected to the first processor and the antenna is configured to transmit the machine readable acceleration data.

5. The system according to claim 1, wherein the accelerometer, the first processor, and the second processor are located within the intramedullary nail or the intramedullary nail cap.

6. The system according to claim 1, wherein the accelerometer and the first processor comprise one unit.

7. The system according to claim 4, wherein the antenna and the power supply comprise one unit.

8. The system according to claim 1, further comprising a reader for retrieving accelerometer data.

9. The system according to claim 1, wherein at least one of the first processor and the second processor is part of a computer assisted surgery system.

10. The system according to claim 4, wherein the antenna used to transmit the accelerometer data is also an inductive coupling element used to power the first processor and the accelerometer.

11. The system according to claim 1, wherein the power supply includes at least one of a capacitor, an inductive coupling, a battery, a mechanically driven power generation unit, a piezoelectric device, and an energy scavenging device.

12. The system according to claim 1, wherein the first processor and accelerometer are powered by at least one of a capacitor, an inductive coupling, a battery, a mechanically driven power generation unit, a piezoelectric device, and an energy scavenging device.

13. The system according to claim 1, wherein at least one of the machine readable acceleration data, the time domain accelerometer data, and the frequency domain accelerometer data is communicated under power from at least one of a capacitor, an inductive coupling, a battery, a mechanically driven power generation unit, a piezoelectric device, and an energy scavenging device.

14. The system according to claim 1, wherein the second processor is part of a remote processing system.

15. The system according to claim 14, wherein the remote processing system includes at least one of a display unit and a sound generating unit.

22. The system according to claim 1, wherein, to analyze the healing progression based on the frequency domain accelerometer data, the second processor is configured to identify a portion of the frequency domain accelerometer data corresponding to the one or more gait cycles.

23. The system according to claim 1, wherein to analyze the healing progression based on the frequency domain accelerometer data, the second processor is configured to:

identify data corresponding to a step point and a stride point; and

analyze the healing progression based on the data corresponding to the step point and the stride point.

24. The system according to claim 1, wherein, to analyze the healing progression based on the frequency domain accelerometer data, the second processor is configured to identify a gait characteristic using the frequency domain accelerometer data.

25. The system according to claim 24, wherein the gait characteristic is one of a stride amplitude, a step amplitude, a stride frequency, and a step frequency.

26. The system according to claim 1, wherein, to analyze the healing progression based on the frequency domain accelerometer data, the second processor is configured to determine the normalcy of an activity of the subject based on the frequency domain accelerometer data.

27. The system according to claim 1, wherein, to determine the level of healing based on the data about the one or more gait cycles, the second processor is configured to generate a gait normalcy metric based on an amplitude or an area of the frequency domain accelerometer data corresponding to the one or more gait cycles.

16. A method of determining the healing progression status of a subject having an intramedullary implant, the method comprising:

executing instructions stored on one or more machine-readable memory devices with one or more processors, wherein at least one of the one or more processors is operatively connected to an accelerometer that is operatively connected to the subject, wherein executing the instructions causes the one or more processors to perform the steps of;

a) collecting accelerometer data from the accelerometer;

b) retrieving the collected accelerometer data, the accelerometer data having a time domain component;

c) transforming the time domain accelerometer data into frequency domain accelerometer data, the frequency domain accelerometer data comprising data about one or more gait cycles;

d) analyzing the frequency domain accelerometer data for bone healing progression of the subject in an area surrounding the intramedullary implant, wherein analyzing the frequency domain accelerometer data comprises determining a level of bone healing of the subject in the area surrounding the intramedullary implant based on the data about the one or more gait cycles; and

e) outputting a healing number that indicates a percentage of bone healing in the area surrounding the intramedullary implant.

18. The method according to claim 16, wherein analyzing the frequency domain accelerometer data for bone healing progression of the subject in an area surrounding the intramedullary implant comprises:

comparing the level of bone healing to a previous level of bone healing.

19. The method according to claim 18, wherein:

the collected accelerometer data is collected over a first time period; and

the previous level of bone healing is based on accelerometer data for a time period that occurs before the first time period.

20. The method according to claim 16, wherein analyzing the frequency domain accelerometer data for bone healing progression of the subject in an area surrounding the intramedullary implant comprises:

generating a bone healing metric based on the frequency domain accelerometer data; and

comparing the bone healing metric to a threshold level derived from healing data for multiple patients.

17. A system for processing accelerometer data, the system comprising:

a) an accelerometer for measuring a physiological acceleration parameter;

b) a first processor operatively connected to the accelerometer, the first processor configured to receive the acceleration parameter from the accelerometer and configured to output machine readable acceleration data, the machine readable acceleration data comprising time domain accelerometer data;

c) a power supply electrically connected to the first processor; and

d) a second processor configured to;

receive the machine readable acceleration data,

transform the time domain accelerometer data into frequency domain accelerometer data, and

analyze a bone healing progression of a patient in an area surrounding an implant based on the frequency domain accelerometer data,

wherein, to analyze the bone healing progression based on the frequency domain accelerometer data, the second processor is configured to;

extract, from the time domain acceleration data, multiple discrete data sets;

identify, based on the frequency domain accelerometer data corresponding to the multiple discrete data sets, a subset of the multiple discrete data sets that each comprise data about one or more gait cycles; and

determine a level of bone healing of the patient in the area surrounding the implant based on the subset of the multiple discrete data sets that each comprise data about one or more gait cycles;

wherein, to determine the level of healing based on the data about the one or more gait cycles, the second processor is configured to;

measure an area under particular regions of curves representing the frequency domain accelerometer data corresponding to the subset of discrete data sets; and

determine the level of bone healing of the patient in the area surrounding the implant based on the measured area.

21. The system according to claim 17, wherein the frequency domain accelerometer data indicates activity of a patient;

and

wherein, to analyze the healing progression based on the frequency domain accelerometer data, the second processor is configured to analyze the healing progression of the patient based on the activity of the patient indicated by the frequency domain accelerometer data.