Method and system for real time interactive dynamic alignment of prosthetics

• US 8,452,458 B2
• Filed: 05/05/2008
• Issued: 05/28/2013
• Est. Priority Date: 05/03/2007
• Status: Active Grant

• Current Assignee: Motek BV
• Original Assignee: Motek BV
• Inventors: Even-Zohar, Oshri
• Primary Examiner(s): Ali, Mohammad
• Assistant Examiner(s): WHITTINGTON, ANTHONY T
• Application Number:
  US12/598,462
• Publication Number:
  US 20100131113A1
• Time in Patent Office: 1,849 Days
• Field of Search: 700/98, 700/117, 700/279, 623/24, 607/2
• US Class Current: 700/279
• CPC Class Codes: A61B 2090/061 for measuring dimensions, e.g. length
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/25 User interfaces for surgical systems
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for
• CPC Class Codes: A61F 2/60 Artificial legs or feet or parts thereof
• CPC Class Codes: A61F 2/70 electrical
• CPC Class Codes: A61F 2/76 Means for assembling, fitting or testing prostheses, e.g. for measuring or balancing, e.g. alignment means
• CPC Class Codes: A61F 2002/705 Electromagnetic data transfer for implantable prostheses A61F2250/0002
• CPC Class Codes: A61F 2002/7695 Means for testing non-implantable prostheses for testing implantable prostheses A61F2240/008; for implanting artificial joints A61F2/468

Abstract

An objective method and system for dynamic analysis of prosthesis-bound subjects for determining optimal prosthesis alignment adjustments consists of a motion detection system, motion database, blending engine and algorithms, and a graphical user interface with suitable program controls whereby manual, semi-automatic, or fully automated analysis of a prosthesis-equipped subject'"'"'s motion performance can be done in real time to determine objectively the optimal adjustments for the subject'"'"'s prosthesis in a precise clinical protocol context.

Claims

1. A computer-based system for dynamic alignment of a prosthetic limb for a human subject configured therewith, the computer-based system comprising:

a measurement system for obtaining a patient human motion capture record of a prosthesis-equipped human subject in motion;

a motion database comprising a plurality of reference human motion capture records that correspond with a plurality of known prosthetic alignment errors;

a motion blending engine configured for blending said reference human motion capture records, said blending including at least one of weighting and combining said reference capture records, to produce a predicted human motion capture record; and

a computer configured for comparing the predicted human motion capture record with the patient human motion capture record, said computer being configured to calculate from the comparison a prosthesis alignment error correction for the prosthesis-equipped subject.

2. The system of claim 1, further comprising a graphic user interface in communication with the computer for visually displaying the calculated prosthesis alignment error correction.

3. The system of claim 1, further comprising a prosthesis alignment adjustment mechanism in communication with the computer for receiving and responding to the calculated prosthesis alignment error correction.

4. The system of claim 1, said measurement system for obtaining human motion data comprising a human motion detection system for monitoring motion of said subject, said human motion detection system being linked for communicating the human motion data in real time to said human motion database and hence to said blending engine.

5. The system of claim 4, said human motion detection system comprising at least one motion sensor external to the prosthesis.

6. The system of claim 4, said human motion detection system comprising at least one motion sensor integrated with the prosthesis.

7. The system according to claim 4, said human motion detection system comprising an instrumented treadmill.

8. The system according to claim 3, said human motion database, blending engine, computer, and prosthesis alignment adjustment mechanism being integrated with the prosthesis.

9. The system according to claim 1, the computer being linked with the motion database whereby the patient human motion capture record and the calculated prosthesis alignment error correction for the subject may be recorded therein as a said human motion with known prosthetic alignment error.

10. The system according to claim 1, further comprising a computer program comprising a Virtual Character module, a Motion Designer module, a Video Control module, and a Motion Database module.

11. A method for computing a prosthetic alignment error correction in real time for a prosthesis-equipped human subject, said method comprising:

collecting a patient human motion capture record from the prosthesis-equipped human subject in motion;

comparing in real time the patient human motion capture record with a plurality of reference human motion capture records that correspond with known prosthetic alignment errors to determine matching records;

blending said reference human motion capture records into blended data that approximates the patent human motion capture record, said blending including at least one of weighting and combining a plurality of said reference human motion capture records; and

computing in real time from said blended data a computed prosthesis alignment error correction.

12. The method according to claim 11, further comprising:

outputting said computed prosthesis alignment error correction to a graphic user interface.

13. The method according to claim 11, further comprising:

outputting said computed prosthesis alignment error correction to an alignment adjustment mechanism in said prosthesis.

14. The method according to claim 11, said collecting motion data comprising using a camera-based human motion detection system to monitor the subject in motion.

15. The method according to claim 11, said collecting human motion data comprising using sensors integrated with the prosthesis, said sensors outputting the human motion data of the subject in motion to a human motion database and hence to a blending engine.

16. The method according to claim 11, said method comprising using a human motion detection system for the collecting, linked to a human motion database for the comparing, linked to a human motion blending engine for the blending, linked to a computer for the computing, wherein the method is conducted in real time.

17. The method according to claim 12, said collecting human motion data comprising using an instrumented treadmill upon which the subject moves, linked to a human motion database.

18. A computer system for dynamic alignment of prosthetic limbs for a prosthesis-equipped human subject, the computer system comprising:

a human motion detection system for monitoring the prosthesis-equipped human subject while in motion, the output of which is real time patient human motion data;

a human motion database configured for comparing the real time patient human motion data with a database of reference human motion capture records corresponding with known prosthetic alignment errors, and selecting reference human motion capture records from the database based on matching prosthetic alignment errors;

a human motion blending engine configured for blending the selected reference human motion capture records in real time into blended data that approximates the real time patient human motion data, said blending including at least one of weighting and combining a plurality of said reference human motion capture records; and

a computer receiving the blended data from the blending engine, said computer being configured to calculate in real time a dynamic prosthesis alignment error for the prosthesis-equipped subject from the blended data and to visually display in real time the dynamic prosthesis alignment error on a graphic user interface.

19. A method for determining alignment adjustments for the prosthesis of a prosthesis-equipped human subject, said method comprising:

collecting patient human motion data from the prosthesis-equipped human subject in motion;

comparing the patient human motion data to a database of reference human motion capture records corresponding with known prosthetic alignment errors to identify related capture records;

blending the related capture records to create blended data that approximates the patient human motion data, said blending including at least one of weighting and combining a plurality of said related capture records;

computing from the blended data the prosthetic alignment error of the subject in motion; and

utilizing the computed prosthetic alignment error of the subject in motion for determining a corrective adjustment to the prosthesis.

20. The method of claim 19, said method being conducted with a computer-based system in real time, the corrective adjustments being outputted to a GUI.