Intelligent joint prosthesis
Medical devices coupled to a sensor, and systems including such devices, can generate data and analysis based on that data, which may be used to identify and/or address problems associated with the implanted medical device, including incorrect placement of the device, unanticipated degradation of the device, and undesired movement of the device. Also provided are medical devices coupled to a sensor, and devices and methods to address problems that have been identified with an implanted medical device.
1. A method for identifying a clinical or subclinical condition associated with an implant in a patient, the method comprising:
a. monitoring a first motion of the implant during a first monitoring session based on a first sensor signal generated by a sensor which is directly coupled to the implant, to provide a first monitoring-session data for the first motion comprising a first motion mode derived from a filtered first sensor signal;
b. monitoring a second motion of the implant during a second monitoring session based on a second sensor signal generated by the sensor, to provide a second monitoring-session data for the second motion comprising a second motion mode derived from a filtered second sensor signal; and
c. comparing the first motion mode to the second motion mode, to provide a comparison that is indicative of a clinical or subclinical condition associated with the implant.
2. The method of claim 1 wherein the clinical or subclinical condition is a loosening of the implant, optionally due to periprosthetic lucency or periprosthetic osteolysis.
3. The method of claim 1 wherein the clinical or subclinical condition is a malalignment or a realignment of the implant.
4. The method of claim 1 wherein the clinical or subclinical condition is deformation of the implant.
5. The method of claim 1 wherein the patient is asymptomatic for the condition, and the comparison of the first motion mode and second motion mode indicates that the condition has occurred between the first and second monitoring sessions.
6. The method of claim 1 wherein the patient is asymptomatic for loosening of the implant, and the comparison of the first motion mode and second motion mode indicates that the implant has loosened between the first and second monitoring sessions.
7. The method of claim 1 wherein the patient is asymptomatic for realignment of the implant, and comparison of the first motion mode and second motion mode indicates that the implant has changed alignment between the first and second monitoring sessions.
8. The method of claim 1 wherein the patient is asymptomatic for deformation of the implant, and comparison of the first motion mode and second motion mode indicates that the implant has deformed between the first and second monitoring sessions.
9. The method of claim 1 wherein the implant is an intelligent implant.
10. The method of claim 1 wherein the implant is selected from a knee implant, a hip implant and a shoulder implant.
11. The method of claim 1 wherein the comparison is indicative of a status of the patient.
12. The method of claim 1 wherein the implant has been located within the patient for at least 10 weeks prior to the first monitoring session.
13. The method of claim 1 wherein the implant has changed alignment over a period of at least 2 weeks.
14. The method of claim 1 wherein the implant has loosened over a period of at least two weeks.
15. The method of claim 1 wherein the implant has deformed over a period of at least two weeks.
16. The method of claim 1 further comprising monitoring a plurality of subsequent motions of the implant during a corresponding plurality of subsequent monitoring sessions using the sensor, to provide a corresponding plurality of subsequent monitoring-session-data, wherein the first monitoring session, the second monitoring session, and the plurality of subsequent monitoring sessions occur over a time period, wherein the total number of monitoring sessions over the time period corresponds to a frequency that is related to a telemedicine code for the clinical or subclinical condition.
17. The method of claim 1 further comprising monitoring a plurality of subsequent motions of the implant during a corresponding plurality of subsequent monitoring sessions using the sensor, to provide a corresponding plurality of subsequent monitoring-session-data, wherein the first monitoring session, the second monitoring session, and the plurality of subsequent monitoring sessions occur over a time period, wherein the total number of monitoring sessions over the time period corresponds to a frequency that allows a doctor to qualify for payment under a telemedicine insurance code.
18. The method of claim 1 further comprising monitoring a plurality of subsequent motions of the implant during a corresponding plurality of subsequent monitoring sessions using the sensor, to provide a corresponding plurality of subsequent monitoring-session-data, wherein the first monitoring session, the second monitoring session, and the plurality of subsequent monitoring sessions occur over a time period, wherein the total number of monitoring sessions over the time period corresponds to a frequency that allows a doctor to qualify for full payment under a telemedicine insurance code.
19. The method of claim 1 , wherein:
the first motion mode is a first gait-frequency motion mode derived by filtering the first sensor signal to obtain a gait-frequency representation of the first sensor signal; and
the second motion mode is a second gait-frequency motion mode derived by filtering the second sensor signal to obtain a gait-frequency representation of the second sensor signal.
20. The method of claim 19 , wherein:
the sensor has a three-dimensional coordinate system;
the first gait-frequency motion mode is based on an amplitude associated with each of the three dimensions of the coordinate system; and
the second gait-frequency motion mode is based on an amplitude associated with each of the three dimensions of the coordinate system.
21. The method of claim 1 , wherein:
the first motion mode is a first non-gait-frequency motion mode derived by filtering the first sensor signal to obtain a non-gait-frequency representation of the first sensor signal; and
the second motion mode is a second non-gait-frequency filtered representation of the second sensor signal derived by filtering the second sensor signal to obtain a non-gait-frequency representation of the second sensor signal.
22. The method of claim 21 , wherein:
the sensor has a three-dimensional coordinate system;
the first non-gait-frequency motion mode is represented by an amplitude associated with each of the three dimensions of the coordinate system; and
the second non-gait-frequency motion mode is represented by an amplitude associated with each of the three dimensions of the coordinate system.
23. The method of claim 1 , wherein:
the first monitoring-session data for the first motion further comprises at least one first discontinuity motion mode based on a detection of a discontinuity in the first sensor signal; and
the second monitoring-session data for the second motion further comprises at least one second discontinuity motion mode based on a detection of a discontinuity in the second sensor signal.