CROSS-REFERENCE TO RELATED APPLICATION This application is a continuation of U.S. patent application Ser. No. 18/108,954 filed on Feb. 13, 2023, which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/444,056 filed Feb. 8, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/444,045, filed Feb. 8, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/443,146 filed Feb. 3, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/483,045, filed Feb. 3, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/482,659, filed Feb. 1, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/482,656 filed Feb. 1, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/482,097 filed Jan. 30, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/482,109 filed Jan. 30, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/481,660 filed Jan. 26, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/481,053 filed Jan. 23, 2023, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/431,094 filed Dec. 8, 2022, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/423,932 filed Nov. 9, 2022, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/419,781 filed Oct. 27, 2022, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/419,522 filed Oct. 26, 2022, and which claims the benefit of the filing date of United States Provisional Patent Application No. 63,419,455 filed Oct. 26, 2022, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/359,384 filed Jul. 8, 2022, and which claims the benefit of the filing date of U.S. Provisional Patent Application No. 63/309,809 filed Feb. 14, 2022, the disclosures of all of which are hereby incorporated herein by reference in their entirety.
FIELD OF INVENTION The present disclosure relates to implants and methods for tracking implant performance, and particularly to joint implants and methods for tracking joint implant performance.
BACKGROUND OF THE INVENTION Monitoring patient recovery after joint replacement surgery is critical for proper patient rehabilitation. A key component of monitoring a patient's recovery is evaluating the performance of the implant to detect implant dislocation, implant wear, implant malfunction, implant breakage, etc. For example, a tibial insert made of polyethylene (“PE”) implanted in a total knee arthroscopy (“TKA”) is susceptible to macroscopic premature failure due to excessive loading and mechanical loosening. Early identification of improper implant functioning and/or infection and inflammation at the implantation site can lead to corrective treatment solutions prior to implant failure. Data relating to postoperative range of motion and load balancing of the new TKA implants can be critical for managing recovery and identification of a proper replacement solution if necessary.
However, diagnostic techniques to evaluate implant performance are generally limited to patient feedback and imaging modalities such as X-ray fluoroscopy or magnetic resonance imaging (“MRI”). Patient feedback can be misleading in some instances. For example, gradual implant wear or dislocation, onset of infection, etc., may be imperceptible to a patient. Further, imaging modalities offer only limited insight into implant performance. For example, X-ray images will not reveal information related to the patient's range of motion or the amount of stress on the knee joint of a patient recovering from a TKA. Furthermore, the imaging modalities may provide only an instantaneous snapshot of the implant performance, and therefore fail to provide continuous real time information related to implant performance. Therefore, there exists a need for implants and related methods for tracking implant performance.
BRIEF SUMMARY OF THE INVENTION Disclosed herein are joint implants and methods for tracking joint implant performance.
In accordance with an aspect of the present disclosure a joint implant is provided. A joint implant according to this aspect, may include a first implant coupled to a first bone of a joint and a second implant coupled to a second bone of the joint. The first implant may include at least one marker. The second implant may contact the first implant. The second implant may include at least one marker reader to detect a position of the marker to identify positional data of the first implant with respect to the second implant. The second implant may include at least one load sensor to measure load data between the first and second implants. A processor may be operatively coupled to the marker reader and the load sensor. The processor may simultaneously output the positional data and the load data to an external source.
Continuing in accordance with this aspect, the marker may be a magnet and the marker reader may be a magnetic sensor. The magnetic sensor may be a Hall sensor assembly including at least one Hall sensor. The magnet may be a magnetic track disposed along a surface of the first implant. The first implant may include a first magnetic track extending along a medial side of the first implant and a second magnetic track extending along a lateral side of the first implant.
Continuing in accordance with this aspect, the second implant may include a first Hall sensor assembly on a medial side of the second implant and a second Hall sensor assembly on a lateral side of the second implant. The first Hall sensor assembly may be configured to read a magnetic flux density of the first magnetic track and the second Hall sensor assembly configured to read a magnetic flux density of the second magnetic track.
Continuing in accordance with this aspect, a central portion of the first magnetic track may be narrower than an anterior end and a posterior end of the first magnetic track. The first magnetic track may include curved magnetic lines extending across the first magnetic track.
Continuing in accordance with this aspect, the magnetic sensor may be coupled to the load sensor by a connecting element. The connecting element may be a rod configured to transmit loads from the magnetic sensor to the load sensor. The load sensor may be a strain gauge.
Continuing in accordance with this aspect, the joint may be a knee joint. The first implant may be a femoral implant and the second implant may be a tibial implant. The tibial implant may include a tibial insert and a tibial stem. The marker reader and the processor may be disposed within the tibial insert.
Continuing in accordance with this aspect, the positional data may include any of a knee flexion angle, knee varus-valgus rotation, knee internal-external rotation, knee medial-lateral translation, superior-inferior translation, anterior-posterior translation, and time derivatives thereof. The load data may include any of a medial load magnitude, lateral load magnitude, medial load center and lateral load center. The tibial insert may include any of a pH sensor, a temperature sensor and a pressure sensor operatively coupled to the processor. The tibial insert may include a spectroscopy sensor. The tibial insert may be made of polyethylene.
Continuing in accordance with this aspect, the joint implant may include an antenna to transmit the positional data and the load data to an external source. The external source may be any of a tablet, computer, smart phone, and remote workstation.
In accordance with another aspect of the present disclosure, a joint implant is provided. A joint implant according to this aspect, may include a first implant coupled to a first bone of a joint and a second implant coupled to a second bone of the joint. The first implant may include a plurality of medial markers located on a medial side of the first implant, and a plurality of lateral markers located on a lateral side of the first implant. The second implant may contact the first implant. The second implant may include at least one medial marker reader to identify a position of the medial markers and at least one lateral marker reader to identify a position of the lateral markers. The position of the medial markers and the position of the lateral markers may provide positional data of the first implant with respect to the second implant. The second implant may include a medial load sensor to measure medial load data between the first and second implants on a medial side of the joint implant, a lateral load sensor to measure lateral load data between the first and second implants on a lateral side of the joint implant. A processor may be operatively coupled to the medial marker reader, the lateral marker reader, the medial load sensor, and the lateral load sensor. The processor may simultaneously output the positional data, the medial load data, and the lateral load data to an external source.
Continuing in accordance with this aspect, a number of medial markers may be different from a number of lateral markers. The medial markers and the lateral markers may include magnets located at discrete locations on the first implant. The medial marker reader and the lateral marker reader may include a Hall sensor assembly with at least one Hall sensor. The medial load sensor and the lateral load sensor may include piezo stacks.
Continuing in accordance with this aspect, the joint implant may include a battery disposed within the second implant. The joint implant may include a charging circuit disposed within the second implant to charge the battery using power generated by the piezo stacks during loading between the first and second implants.
Continuing in accordance with this aspect, the joint may be a knee joint. The first implant may be a femoral implant and the second implant may be a tibial implant. The tibial implant may include a tibial insert and a tibial stem. The marker reader and the processor may be disposed within the tibial insert. The positional data may include any of a knee flexion angle, knee varus-valgus rotation, knee internal-external rotation, knee medial-lateral translation, anterior-posterior translation, superior-inferior translation, and time derivatives thereof.
Continuing in accordance with this aspect, the medial load data may include a medial load magnitude and a medial load center. The tibial insert may include any of a pH sensor, a temperature sensor, accelerometer, gyroscope, inertial measure unit and a pressure sensor operatively coupled to the processor. The tibial insert may include a spectroscopy sensor.
In accordance with another aspect of the present disclosure, a joint implant system is provided. A joint implant system according to this aspect, may include a first implant coupled to a first bone of a joint, a second implant coupled to a second bone of the joint, and an external sleeve configured to be removably attached to the joint. The first implant may include at least one marker. The second implant may contact the first implant. The second implant may include at least one marker reader to detect a position of the marker to identify positional data of the first implant with respect to the second implant. The second implant may include at least one load sensor to measure load data between the first and second implants. A processor may be operatively coupled to the marker reader and the load sensor. The processor may be configured to simultaneously output the positional data and the load data to an external source.
Continuing in accordance with this aspect, the joint implant system may include a battery to power the marker reader and the processor. The battery may be disposed within the second implant and including a joint implant charging coil. The external sleeve may include an external charging coil to charge the battery. The battery may be configured to be charged by ultrasonic wireless charging or optical charging.
In another aspect of the present disclosure, a method for monitoring a joint implant performance is provided. A method according to this aspect, may include the steps of providing a first implant couplable to a first bone of a joint, providing a second implant couplable to a second bone of the joint, tracking magnetic flux density magnitudes over time using a magnetic sensor, and initiating a warning when a tracked magnetic flux density magnitude is different from a predetermined value. The first implant may include at least one magnetic marker. The second implant may be configured to contact the first implant. The second implant may include at least one magnetic sensor to detect the magnetic flux density of the magnetic marker. The magnetic flux density value may be proportional to a thickness of the second implant.
In accordance with another aspect of the present disclosure, a method for monitoring a joint implant performance is provided. A method according to this aspect, may include the steps of providing a first implant couplable to a first bone of a joint, providing a second implant couplable to a second bone of the joint, tracking a rate of change of a magnetic flux density over time using a magnetic sensor, and initiating a warning when a tracked rate of change of the magnetic flux density exceeds a predetermined value. The first implant may include at least one magnetic marker. The second implant may be configured to contact the first implant. The second implant may include at least one magnetic sensor to detect the magnetic flux density of the magnetic marker. The rate of change of the magnetic flux density may be proportional to a wear rate of the second implant.
In accordance with another aspect of the present disclosure, a method of monitoring implant performance is provided. A method according to this aspect, may include the steps of providing an implant with a first sensor to detect implant temperature, a second sensor to detect a fluid pressure, and a third sensor to detect implant alkalinity, tracking and outputting implant temperature, implant pressure and implant alkalinity over time to an external source using a processor disposed within the implant, and initiating a notification when any of the implant temperature, implant pressure and implant alkalinity, or any combination thereof, exceeds a predetermined value. The implant temperature, implant pressure and implant alkalinity may be related to any of an implant failure and an implant infection. The fluid pressure may be a synovial fluid pressure.
Disclosed herein is an implant system for detecting implant condition and related patient condition. The implant system may include a first implant associated with a first bone of a joint and a second implant associated with a second bone of the joint. A manipulator such as an acoustic exciter may be used to impart energy to the first or second bones. The energy may be in the form of an acoustic energy generated by a manipulator such as an acoustic exciter. The energy may cause the first and/or second bones to vibrate. The vibration may be detected by a transducer by identifying a vibration signal of the first and/or second bones. A processor may be operatively coupled to the transducer to output a vibration signature derived from the vibration signal to an external source.
In accordance with an aspect of the present disclosure, an implant system comprises a first implant coupled to a first bone of a joint; a second implant coupled to a second bone of the joint; an acoustic exciter configured to vibrate at least the first or second bones; a transducer to detect a vibration signal of the first implant and the second implant; and a processor operatively coupled to the transducer, the processor configured to output a vibration signature to an external source.
In another aspect, the first implant is a femoral component of a knee implant and the second implant is a tibial component of a knee implant.
In a different aspect, the system further includes an insert located between the femoral component and the tibial component.
In another aspect, the acoustic exciter is an ultrasound exciter.
In a further aspect, the transducer includes first and second transducers, each of the first and second transducers disposed in the tibial insert adjacent a condyle.
In a different aspect, the processor is disposed in the tibial insert.
In another aspect, the processor is configured to wirelessly communicate the vibration signature with the external source.
In a further aspect, the wireless communication is a Bluetooth communication.
In yet another aspect, the system further comprises an analog to digital converter, the converter configured to convert the vibration signal to the vibration signature.
In a different aspect, the vibration signature includes at least one of a response, peak, amplitude, and magnitude of the vibration signal.
In another aspect, a change in the vibration signature over time indicates implant loosening.
In another aspect, a change in the vibration signature over time indicates implant subsidence.
In a further aspect, the external source is any of a computer, tablet, and smartphone.
In a different aspect, the system further comprises a guidance system configured to position the acoustic exciter.
In a further aspect, the guidance system includes an inertial measurement unit.
In another aspect, the inertial measurement unit is located in the first or second implant.
In accordance with another aspect of the present disclosure, a method for monitoring implant movement comprises coupling a first implant to a first bone of a joint; coupling a second implant to a second bone of the joint; sensing a vibration signal emitted through the joint with a sensor positioned in the any of the first or second implants; and outputting a vibration signature from a processor to an external source, the vibration signature converted from the vibration signal.
In another aspect, the coupling steps include coupling the first implant to a femur and coupling the second implant to a tibia.
In a different aspect, the method further comprises a step of vibrating at least one of the first or second bones using an acoustic exciter.
In another aspect, the method further comprises converting the vibration signal to a vibration signature with an analog to digital converter.
In a different aspect, the outputting step includes outputting the vibration signal to a computer.
In another aspect, the outputting step includes outputting the vibration signal at least first time and a second time, the first time being different from the second time.
In a different aspect, the method further comprises creating an alert when a change in vibration signature is detected.
In accordance with another aspect of the present disclosure, a method of monitoring implant position over time comprises coupling a first implant to a first bone of a joint; coupling a second implant to a second bone of the joint, the second implant including an insert contacting the first implant; measuring a reference movement value at a first time; measuring a secondary movement value at a second time; and comparing the reference movement value to the secondary movement value.
In another aspect, the method further comprises measuring transducer data from a transducer embedded in the insert at the first time and at the second time to obtain a first sensor data and a second sensor data respectively.
In a further aspect, the transducer data includes vibration data.
In another aspect, the method further comprises creating an alert when a change between a first and second transducer data exceeds a predetermined value.
In a different aspect, the method further comprises creating an alert when a change between the reference movement value and the secondary movement value exceeds a predetermined value.
In another aspect, the method further comprises comparing at least one of the reference movement value, the secondary movement value, the first sensor data, and the second sensor data with a machine learning algorithm.
In a different aspect, the method further comprises creating an alert when the machine learning algorithm detects a change that exceeds a predetermined value in at least one of the reference movement value, the secondary movement value, the first sensor data, and the second sensor data.
In accordance with another aspect of the present disclosure, a method of measuring joint implant movement over time comprises disposing a first magnet in a first bone of a joint; disposing a second magnet in a second bone the joint; coupling a first implant to the first bone; coupling a second implant to the second bone, the second implant including an insert contacting the first implant; manipulating the joint at a first time such that a first magnetic sensor disposed in the insert registers the first magnet to create first sensor data and a second magnetic sensor disposed in the insert registers the second magnet to create second sensor data; repeating the manipulating movements at a second time; and outputting the first sensor data and the second sensor data from the first time and the second time to an external source.
In another aspect, the method further comprises drilling a hole into a first bone to receive the first magnet and a hole in the second bone to receive the second magnet.
In a different aspect, the method further comprises processing the first and second sensor data with a processor.
In another aspect, the method further comprises outputting the first and second sensor data to the external source with Bluetooth communication.
In a further aspect, the repeating step includes repeating identical manipulating movements of the joint.
In a different aspect, the repeating step includes repeating the manipulating movements at frequent intervals of time.
In another aspect, the magnetic sensor is a Hall sensor.
In a different aspect, the first bone is a femur and the second bone is a tibia.
In a further aspect, the joint is a hip joint.
In another aspect, a change in the first and second sensor data at the second time indicates implant loosening.
In a different aspect, a change in the first and second sensor data at the second time indicates implant subsidence.
In another aspect, the method further comprises comparing the first and second sensor data at the first time with the first and second sensor data at the second time.
In another aspect, the comparing step includes utilizing a finite element analysis model.
In a different aspect, the method further comprises recording the locations of the first and second magnets in the first and second bones.
BRIEF DESCRIPTION OF THE DRAWINGS A more complete appreciation of the subject matter of the present disclosure and the various advantages thereof can be realized by reference to the following detailed description, in which reference is made to the following accompanying drawings:
FIG. 1 is a front view of a knee joint implant according to an embodiment of the present disclosure;
FIG. 2 is a side view of a femoral implant of the knee joint implant of FIG. 1;
FIG. 3A is a bottom view of the femoral implant of FIG. 2;
FIG. 3B is schematic view of encoder tracks of the femoral implant of FIG. 2;
FIG. 4 is a partial view of an encoder read head and a load sensor of a tibial implant of the knee joint implant of FIG. 1;
FIG. 5A is a front view of an antenna of the knee joint implant of FIG. 1;
FIG. 5B is a top view of the antenna of FIG. 5A;
FIG. 6 is a perspective side view of a knee joint implant according to another embodiment of the present disclosure;
FIG. 7 is a perspective front view of a tibial implant of the knee joint implant of FIG. 6;
FIG. 8 is a partial perspective view of an insert of the tibial implant of FIG. 6;
FIG. 9 is a partial top view of the insert of FIG. 8 showing details of various insert components;
FIG. 10 is a perspective side view of the insert of the tibial implant of FIG. 7;
FIG. 11 is a perspective side view of a cover of the insert of FIG. 10;
FIG. 12 are graphs showing magnetic flux density measurements of the implant sensors and knee flexion angles;
FIG. 13 is a graph showing various implant sensor readings of the knee joint implant of FIG. 6;
FIG. 14 is a schematic view of implant sensors of the knee joint implant of FIG. 6 in communication with a processor;
FIG. 15 is a graph showing voltage measurements of the implant sensors;
FIG. 16 is a schematic view of a charging circuit for the knee joint implant of FIG. 6;
FIG. 17A is a graph showing measured voltage of the implant sensors;
FIG. 17B is a graph showing rectified voltage of the implant sensors;
FIG. 18 is a schematic view of a knee joint implant with a charging sleeve according to an embodiment of the present disclosure;
FIG. 19 is a front view of the charging sleeve of the knee joint implant of FIG. 17;
FIG. 20 is a side view of an insert of the knee joint implant of FIG. 17;
FIG. 21 shows top and front views of the insert of FIG. 19;
FIG. 22A is front view of a knee joint implant according to another embodiment of the present disclosure;
FIG. 22B is a side view of the knee joint implant of FIG. 22A;
FIG. 23A is a front view of a tibial implant according to another embodiment of the present disclosure;
FIG. 23B is a top view of an insert of the tibial implant of FIG. 22A;
FIG. 24A is a front view of a tibial implant according to another embodiment of the present disclosure;
FIG. 24B is a top view of an insert of the tibial implant of FIG. 24A;
FIG. 25A is a front view of a tibial implant according to another embodiment of the present disclosure;
FIG. 25B is a top view of an insert of the tibial implant of FIG. 25A;
FIG. 26 is a side view of a knee joint implant according to another embodiment of the present disclosure;
FIG. 27 is a front view of a tibial implant of the knee joint implant of FIG. 26;
FIG. 28 is a schematic side view of a knee joint implant illustrating various measurements according to another embodiment of the present disclosure;
FIG. 29 is a schematic side view of a spinal implant assembly according to another embodiment of the present disclosure;
FIG. 30 is side view of a hip implant according to another embodiment of the present disclosure;
FIG. 31A is a schematic view of a sensor assembly of the hip implant of FIG. 30;
FIG. 31B is a side view of the sensor assembly and an insert of the hip implant of FIG. 31A;
FIG. 31C is a top view of the sensor assembly and the insert of FIG. 31B;
FIG. 32 is a side view of a hip implant according to another embodiment of the present disclosure;
FIG. 33 is a partial top view of the hip implant of FIG. 32;
FIG. 34 is a side view of a hip implant according to another embodiment of the present disclosure;
FIG. 35 is a side view of an electronic assembly of the hip implant of FIG. 34 according to another embodiment of the present disclosure;
FIG. 36 is a side view of an electronic assembly of the hip implant of FIG. 34 according to another embodiment of the present disclosure;
FIG. 37 is a side view of a shoulder implant according to another embodiment of the present disclosure;
FIG. 38 is top view of an insert of the shoulder implant of FIG. 37;
FIG. 39 is a top view of a cup of the shoulder implant of FIG. 37;
FIG. 40 is side view of a shoulder implant according to another embodiment of the present disclosure;
FIG. 41 is a side view of an insert of the shoulder implant of FIG. 40;
FIG. 42 is a flowchart showing steps to determine implant wear according to another embodiment of the present disclosure;
FIG. 43 is a first graph showing implant thickness over time;
FIG. 44 is a second graph showing implant thickness over time;
FIG. 45 is a flowchart showing steps to determine implant wear according to another embodiment of the present disclosure;
FIG. 46 is a flowchart showing for implant data collection according to another embodiment of the present disclosure;
FIGS. 47A and 47B is a flowchart showing steps for patient monitoring according to another embodiment of the present disclosure;
FIG. 48 is a front view of a knee joint implant according to an embodiment of the present disclosure;
FIG. 49 is a perspective view of a tibial implant of the knee joint implant of FIG. 48;
FIG. 50 is a schematic view of a vibration signal being processed by the knee joint implant of FIG. 48;
FIG. 51 is a schematic flowchart view of the processor of FIG. 48;
FIG. 52 is a graph of frequency plotted against amplitude when an implant is detached;
FIG. 53 is a graph of frequency plotted against amplitude when an implant is attached;
FIG. 54 is a graph of two frequencies plotted against two amplitudes;
FIG. 55 is a front view of a knee joint implant according to another embodiment of the present disclosure;
FIG. 56 is a schematic flowchart view of the data stream of the knee joint implant of FIG. 55;
FIG. 57 is a perspective view of a knee joint implant according to another embodiment of the present disclosure, and
FIG. 58 is a schematic flowchart view of the logic used to determine if the implant of FIG. 57 is loose.
DETAILED DESCRIPTION Reference will now be made in detail to the various embodiments of the present disclosure illustrated in the accompanying drawings. Wherever possible, the same or like reference numbers will be used throughout the drawings to refer to the same or like features within a different series of numbers (e.g., 100-series, 200-series, etc.). It should be noted that the drawings are in simplified form and are not drawn to precise scale. Additionally, the term “a,” as used in the specification, means “at least one.” The terminology includes the words above specifically mentioned, derivatives thereof, and words of similar import. Although at least two variations are described herein, other variations may include aspects described herein combined in any suitable manner having combinations of all or some of the aspects described.
As used herein, the terms “load” and “force” will be used interchangeably and as such, unless otherwise stated, the explicit use of either term is inclusive of the other term. Similarly, the terms “magnetic markers” and “markers” will be used interchangeably and as such, unless otherwise stated, the explicit use of either term is inclusive of the other term.
As used herein, the terms “power” and “energy” will be used interchangeably and as such, unless otherwise stated, the explicit use of either term is inclusive of the other term. Similarly, the terms “implant” and “prosthesis” will be used interchangeably and as such, unless otherwise stated, the explicit use of either term is inclusive of the other term. The term “joint implant” means a joint implant system comprising two or more implants. Similarly, the terms “energy generator” and “energy harvester” will be used interchangeably and as such, unless otherwise stated, the explicit use of either term is inclusive of the other term.
In describing preferred embodiments of the disclosure, reference will be made to directional nomenclature used in describing the human body. It is noted that this nomenclature is used only for convenience and that it is not intended to be limiting with respect to the scope of the present disclosure. As used herein, when referring to bones or other parts of the body, the term “anterior” means toward the front part of the body or the face, and the term “posterior” means toward the back of the body. The term “medial” means toward the midline of the body, and the term “lateral” means away from the midline of the body. The term “superior” means closer to the head, and the term “inferior” means more distant from the head.
FIG. 1 is a front view of a knee joint implant 100 according to an embodiment of the present disclosure. Knee joint implant 100 includes a femoral implant 102 located on a femur 106 and a tibial implant 104 located on a tibia 108. Tibial implant 104 has a tibial insert 110 configured to contact femoral implant 102, and a tibial baseplate or tibial stem 112 extending distally into tibia 108. Femoral implant 102 includes a medial encoder track 114 located on a medial side and a lateral encoder track 116 on a lateral side of the femoral implant. While the encoder tracks are shown along a surface of femoral implant 102 in FIG. 1, these tracks can be located within or partially within a femoral implant on the medial and lateral sides thereof in other embodiments. The encoder tracks can be made of various structures, including magnetic tape of varying lengths and magnetic markers positioned at discrete locations. The resolution of the encoder track can be adjusted depending on the required precision of the measured parameters such as joint displacement, joint rotation, joint slip, etc. Tibial insert 110 includes a medial read head 118 and lateral read head 120 to read a magnetic flux density from medial encoder track 114 and lateral encoder track 116, respectively. Medial read head 118 and lateral read head 120 can be any suitable magnetometer configured to detect and measure magnetic flux density, such as a Hall effect sensor. As tibia 108 rotates with reference to femur 106 during knee flexion and extension, medial encoder track 114 and lateral encoder track 116 move along medial read head 118 and lateral read head 120, respectively. This movement causes a change in magnetic flux density which is detected by read heads 118, 120, and can be utilized to measure knee joint implant 100 movement, rotation, speed and range of articulation, motion/activity, joint slip, and other motion related information. The magnetic-mechanic coupling of the read heads with the encoder tracks allows for direct, instantaneous, and continuous measurements of these knee joint implant parameters. A data transmitter such as an antenna 122 located on tibial insert 110 transmits the knee joint implant parameters measured by the read heads via Bluetooth or other similar wireless means to an external source such as a smart phone, tablet, monitor, network, etc. to allow for real time review of the knee joint implant performance.
FIGS. 2-3B illustrate additional details of femoral implant 102, medial encoder track 114 and lateral encoder track 116. As shown in FIG. 2, medial encoder track 114 extends from an anterior portion 126 of femoral implant 102 to a posterior portion 128 of the femoral implant along a track axis 130. Medial encoder track 114 includes a central portion 124 which is narrower than anterior and posterior portions 126, 128 as shown in FIG. 3A. As shown in FIG. 3B, medial encoder track 114 includes arched or curved magnetic lines to compensate for joint rotations in order to maintain uniform readings during a full range of motion of the knee joint. Similarly, lateral encoder track 116 extends from an anterior portion to a posterior portion of the femoral implant and includes a narrow central portion relative to the anterior and posterior portions with arched or curved magnetic lines. The conical profile and curved magnetic lines of the encoder tracks are configured to compensate for joint rotational motion and maintain alignment and coupling between the read heads and the tracks. This maximizes measurement collection and measurement accuracy during a full range of motion of the knee joint. The shape, size and location of the encoder tracks can vary depending on the implant.
FIG. 4 shows details of a medial side of tibial insert 110. Tibial insert 110 includes a medial load sensor 132 in connection with medial read head 118 via a medial connector 134. Medial load sensor 132 is a load measuring sensor such as a strain gauge or piezoelectric sensor configured to measure loads or forces transmitted from medial read head 118 via medial connector 134. Medial connector 134 can be a rigid member such as a connecting rod to transmit loads from medial read head 118 to medial load sensor 132. As shown in FIG. 4, a portion of the medial side of femoral implant 102 directly contacts medial read head 118 to transmit loads (medial side loads), which is then measured by medial load sensor 132. Medial read head 118 is spring-loaded by a medial load spring 136 located below medial load sensor 132 to ensure contact between medial read head 118 and femoral implant 102. Similarly, a lateral side of tibial insert 110 includes a lateral load sensor, a lateral connector, and a lateral load spring. The lateral load sensor is configured to measure lateral loads between femoral implant 102 and tibial implant 104. Measured medial and lateral loads are transmitted via antenna 122 to an external source. Thus, knee joint implant 100 can simultaneously provide knee motion information (rotation, speed, flexion angle, etc.) and knee load (medial load, medial load center, lateral load, lateral load center, etc.) in real time to an external source.
Details of antenna 122 are shown in FIGS. 5A and 5B. Antenna 122 includes screw threads configured to be attached to tibial insert 110. Antenna 122 can include a coax interface to shield knee joint and improve transmission between knee joint implant 100 and the external source. A battery is located adjacent antenna 122 (not shown) to power knee joint implant 100. Antenna 122 can serve as a charging port via radio frequency (RF) or inductive coupling if a rechargeable battery is used. The location of battery and antenna 122 in tibial insert 110 allow for convenient access to remove and replace these components if necessary. Various other sensors such as a temperature sensor, pressure sensor, accelerometer, gyroscope, magnetometer, pH sensor, etc., can be included in knee joint implant 100 as more fully described below.
FIG. 6 is a perspective side view of a knee joint implant 200 according to another embodiment of the present disclosure. Knee joint implant 200 is similar to knee joint implant 100, and therefore like elements are referred to with similar numerals within the 200-series of numbers. For example, knee joint implant 200 includes a femoral implant 202, a tibial implant 204 with a tibial insert 210 and a tibial stem 212. However, knee joint implant 200 includes magnetic medial markers 214 and magnetic lateral markers 216 located at discrete locations along the medial and lateral sides of femoral implant 202, respectively.
Details of tibial insert 210 are shown in FIGS. 7-11. Tibial insert 210 includes batteries 242 on both medial and lateral sides. Batteries 242 can be solid state batteries, lithium ion batteries, lithium carbon monofluoride batteries, lithium thionyl chloride batteries, lithium ion polymer batteries, etc. As best shown in FIG. 9, Hall sensor assemblies, with each assembly including at least one Hall sensor, are used as a medial marker reader 252 and a lateral marker reader 248 to read medial markers 214 and lateral markers 216, respectively. Each Hall sensor assembly can include multiple Hall sensors arranged in various configurations and orientations. For example, the Hall sensor assembly can include Hall sensors oriented in Cartesian coordinates. As the tibia rotates with reference to the femur during knee flexion and extension, medial markers 214 and lateral markers 216 move along medial marker reader 252 and lateral marker reader 248, respectively. This movement causes a change in magnetic flux density, which is detected by marker readers 252, 248, to measure knee joint implant 200 movement, rotation, speed and range of articulation, motion/activity, joint slip, and other motion related information. The magnetic-mechanic coupling of the marker readers with the markers allows for direct, instantaneous, and continuous measurements of these knee joint implant parameters without the need to process this information via an algorithm or other means. While eight Hall sensor assemblies (four on each side) are shown in this embodiment, other embodiments can have more than eight or less than eight Hall sensor assemblies positioned at various locations. The arrangement of marker readers and markers provide absolute positions of knee joint implant 200 supporting wake-up-and-read kernels. Thus, no inference of movement by data synchronization techniques is required to obtain absolute position data of knee joint implant 200. The number of medial markers 214 can be different from the number of lateral markers 216 to account for variation in signal fidelity between these sides. For example, seven magnetic markers can be provided on the medial side and only four magnet markers can be provided on the lateral side to improve signal fidelity and motion detection precision on the medial side.
As best shown in FIG. 9, three piezo stacks on the medial side serve as medial load sensors 232, and three piezo stacks on the lateral side serve as lateral load sensors 254. The staggered or non-linear arrangement of the three piezo stacks on the medial and lateral sides allow for net load measurements and identification of resultant load centers at the medial and lateral sides. Thus, knee joint implant 200 can simultaneously provide knee motion information (joint rotation, joint speed, joint flexion angle, joint slippage, etc.) and knee load (medial load, medial load center, lateral load, lateral load center, etc.) in real time to an external source. The piezo stacks are configured to generate power from the patient's motion by converting pressure on the piezo stacks to charge batteries 242 as more fully described below. Thus, knee joint implant 200 does not require external charging devices or replacement batteries for the active life of the implant.
Tibial insert 210 includes an infection or injury detection sensor 244. For example, the infection or injury detection can be a pH sensor configured to measured bacterial infection by measuring the alkalinity of synovial fluid to provide early detection of knee joint implant 200 related infection. A temperature and pressure sensor 246 is provided in tibial insert 210 to monitor knee joint implant 200 performance. For example, any increase in temperature and/or pressure may indicate implant-associated infection. Pressure sensor 246 is used to measure synovial fluid pressure in this embodiment. Temperature and/or pressure sensor 246 readings can provide early detection of knee joint implant 200 related infection. Thus, injury detection sensors 244 and 236 provide extended diagnostics with heuristics for first level assessment of infections or injury related to knee joint implant 200. An onboard processor 250 such as a microcontroller unit (“MCU”) is used to read sensors 244 and 236 and process results for transmission to an external source. This data can be retrieved, processed, and transferred by the MCU via antenna 222 continuously, at predefined intervals, or when certain alkalinity, pressure, and/or temperature thresholds, or any combinations thereof, are detected.
The various sensors and electronic components of tibial insert 210 are contained within an upper cover 256 and a lower cover 258 as shown in FIG. 10. The upper and lower covers can be made from a polymer. Antenna 222 is located on an anterior portion of knee joint implant 200 to provide better line of site for transmitting data with less interference. The antenna is fixed inside the polymer covers to provide predictable inductance and capacitance. A cover 260 encloses the sensors and electronic components of tibial insert 210 as shown in FIG. 11. Cover 260 can be a hermetic cover to hermetically seal tibial insert 210. Cover 260 is preferably made of metal and provides radio frequency (“RF”) shielding to the knee joint.
The modular design of knee joint implant 200 provides for convenient maintenance of its components. For example, an in-office or outpatient procedure will allow a surgeon to access the tibia below the patella (an area of minimal tissue allowing for fast recovery) to access component of knee joint implant 200. The electronic components and sensors of knee joint are modular and connector-less allowing for convenient replacement of tibial insert 210 or upgrades to same without impacting the femoral implant or the tibial stem.
Graphs plotting magnetic flux density measurements 310 and knee flexion angles 312 are shown in FIG. 12. Magnetic flux density measurements 310 are generated from the magnetic-mechanic coupling of marker readers 248, 252 with the markers 214, 216 as more fully described above. Graphs 302 and 304 show magnetic flux density (mT) measurements from two Hall sensor assemblies (medial marker reader 252 or lateral marker reader 248) for a first range of motion of the knee joint. Similarly, graphs 306 and 308 show magnetic flux density (mT) measurements from two Hall sensors (medial marker reader 252 or lateral marker reader 248) for a second range of motion of the knee joint. The placement of magnetic markers 214, 216 on the femoral component create a sinusoidal magnetic flux density around femoral implant 202. As the femoral implant 202 rotates around an axis of rotation 201 shown in FIG. 6, the marker readers read sine and cosine waveforms. The magnitude of the sine and cosine waves are interpolated to a near linear knee flexion angle. Placing the individual magnetic markers of medial markers 214 and lateral markers 216 at different separation angles on each condyle of femoral implant 202 creates a phase shift in the measurements from one condyle to the next as the knee rotates. This phase shift can then be used to correct for any rollovers in the interpolated waveform. Thus, marker readers 248, 252 and markers 214, 216 serve as an absolute rotation sensor measuring knee flexion through a full range of motion of knee joint implant 200. In addition to the two Hall sensor assemblies on the lateral and medial side of tibial insert 210, the remaining Hall sensor assemblies of marker readers 248, 252 allow for 6-degrees of freedom movement measurements of knee joint implant 200 as more fully explained below. While an absolute magnetic encoder is disclosed in this embodiment, other embodiments can include a knee joint implant with an incremental magnetic encoder.
FIG. 13 is a graph showing various implant injury detection sensor readings 404 of knee joint implant 200 for early detection of knee joint implant related infection and/or failure. Pressure 408 and temperature 406 are measured using temperature and pressure sensor 246, and alkalinity 410 is measured using pH sensor 244 over time 402. As more fully explained above, alkalinity 410 measurements of joint synovial fluid can indicate bacterial infection to provide early detection of knee joint implant 200 related infection. Increase in pressure 408 and temperature 406 readings may indicate implant-associated infection. Variation or change in synovial fluid pressure 408 may indicate implant malfunction. In addition to predetermined absolute thresholds of the temperature, pressure and alkalinity readings indicating impending infection or implant failure, collective analysis of these readings can offer early detection warning ahead of the failure/infection thresholds. As shown in FIG. 14, a combination of temperature, pressure and alkalinity may indicate early detection of trauma 414 or infection 412. Thus, injury detection sensor readings provide extended diagnostics with heuristics for first level assessment of infections or injury related to knee joint implant 200.
FIG. 14 is a schematic view of piezo stacks of medial load sensors 232 and lateral load sensor 254 in communication with a processor 266. Analog impulses generated by the piezo stacks when subjected to loading are converted to continuous digital signals via analog-to-digital converters 262 and 264 as shown in FIG. 14. The continuous digital signals (voltage) 508 can be serially loaded into a shift register and measured as shown in a graph 500 of FIG. 15. A sampling window 506 is selected to identify a peak reading 508 to detect knee joint motion. For continuous loading case, such as when a patient is standing, additional sensors such as an inertial measurement unit (“IMU”) located in the tibial insert or other locations on knee joint implant 200 can be used to detect or confirm knee joint position. Load data from piezo stacks and IMU measurements can be used to create load and motion profiles for patient-specific or patient-independent analyses.
FIG. 16 is a schematic view of a charging circuit 600 for charging battery 242 of knee joint implant 200. The charging circuit includes a charge circuit 602 connected to a charging coil 606 and piezo stacks of medial load sensors 232 and lateral load sensors 254 via bridge rectifier 604. Charging circuit is configured to direct charge to battery 242 utilizing inputs from one or more piezo stacks from the medial or lateral load sensors. This allows for singular or combined charging using individual or multiple piezo stacks. A minimum voltage output threshold of the piezo stacks can be predetermined to initiate battery charging. For example, when a patient is asleep, low piezo stack pulses will not be used to charge battery 242. Raw piezo stack pulses (voltage 704) as shown in a graph 700 of FIG. 17 over time 706 are rectified by a voltage rectifier 708 to produce a rectified and smoothed voltage output (voltage 704) shown in a graph 702 of FIG. 17B. The rectified and smoothed voltage output from the piezo stacks is used to charge battery 242. Thus, power harvesting from motion of knee joint implant 200 is achieved by using the pulses generated by the piezo stacks.
FIG. 18 is a schematic view of a knee joint implant 800 according to another embodiment of the present disclosure. Knee joint implant 800 is similar to knee joint implant 200, and therefore like elements are referred to with similar numerals within the 800-series of numbers. For example, knee joint implant 800 includes a femoral implant 802, a tibial implant 804 with a tibial stem 812 and a tibial insert 810. However, knee joint implant 800 includes a chargeable implant coil 872 located in tibial insert 810 which can be charged by an external coil 870 contained in an external sleeve 868 as shown in FIG. 18.
External sleeve 868 shown in FIG. 19 includes an outer body 873 made of stretchable fabric or other material. Outer body 873 is configured to be a ready-to-wear pull-on knee sleeve which a patiently can conveniently put on and remove. A kneecap indicator 875 allows the patient to conveniently align sleeve 868 with knee joint implant 800 for proper placement of external coil 870 with reference to implant coil 872 for charging. As shown in FIG. 18, when a patient aligns external sleeve 868 using kneecap indicator 875 and assumes a flexion position, external coil 870 is adjacent to implant coil 872 for proper charging. External sleeve 868 includes a battery 876 and a microcontroller 874 as shown in FIG. 19. Battery 876, which can be conveniently replaced, provides power to external coil 870. In another embodiment, external coil 870 may be charged by an external source not located on sleeve 868.
FIG. 20 shows a side view of tibial insert 810 of knee joint implant 800. Tibial insert 810 is made of a polymer or other suitable to facilitate charging of implant coil 872. Implant coil 872 is located within tibial insert 810 at an indent or depression at a proximal-anterior corner of the tibial insert as show in FIG. 20 and FIG. 21 (top and front views of tibial implant 810). The proximal-anterior location of implant coil 872 maximizes access to external coil 870 for efficient and convenient charging.
FIGS. 22A and 22B show a knee joint implant 900 according to another embodiment of the present disclosure. Knee joint implant 900 is similar to knee joint implant 800, and therefore like elements are referred to with similar numerals within the 900-series of numbers. For example, knee joint implant 900 includes a femoral implant 902, a tibial implant 904 with a tibial stem 912 and a tibial insert 910. However, knee joint implant 900 includes a chargeable implant coil 972 located at anterior end of tibial insert 910 which can be charged by an external coil 970 (not shown). An external sleeve as described with reference knee joint implant 900, or another charging mechanism can be used to conveniently charge implant coil 972.
FIG. 23A is a front view of a tibial implant 1004 according to an embodiment of the present disclosure. Tibial implant 1004 is similar to tibial implant 204, and therefore like elements are referred to with similar numerals within the 1000-series of numbers. For example, tibial implant 1004 includes a tibial stem 1012 and a tibial insert 1010. However, tibial insert 1010 includes a charging coil 1072 located around a periphery of the tibial insert 1010 as shown in FIG. 23B. A spectroscopy sensor 1074 in tibial insert 1010 serves as an infection detection sensor for tibial implant 1004. Spectroscopy sensor 1074 is configured to identify the onset of biofilm on tibial implant (or a corresponding femoral implant) to provide early detection of implant related infection.
FIG. 24A is a front view of a tibial implant 1104 according to an embodiment of the present disclosure. Tibial implant 1104 is similar to tibial implant 204, and therefore like elements are referred to with similar numerals within the 1100-series of numbers. For example, tibial implant 1104 includes a tibial stem 1112 and a tibial insert 1110. However, tibial insert 1110 includes an IMU 1176 and five Hall sensor assemblies for each of the medial and lateral marker readers. The arrangement of the Hall sensor assemblies differ from tibial insert 210. Sensor data from IMU 1176 provides additional knee implant joint movement data as more fully explained above. For example, IMU 1176 can detect or confirm knee joint position during continuous loading positions of a patient such as standing. IMU data can reveal, or support measurements related to gait characteristics, stride, speed, etc., of a patient. pH sensor 1144 of tibial insert 1110 is located adjacent to a proximal face of the tibial insert at a central location as shown in FIG. 24B. All sensors of tibial implant 1104 are powered by batteries located in tibial insert 1110.
A tibial implant 1204 according to another embodiment of the present disclosure is shown in FIGS. 25A and 25B. Tibial implant 1204 is similar to tibial implant 204, and therefore like elements are referred to with similar numerals within the 1200-series of numbers. For example, tibial implant 1204 includes a tibial stem 1212 and a tibial insert 1210. However, tibial insert 1210 includes an IMU 1276 and a pressure sensor. Tibial insert 1210 is made of polyethylene and tibial stem 1212 is made of titanium in this embodiment.
FIG. 26 is a side view of a knee joint implant 1300 according to another embodiment of the present disclosure. Knee joint implant 1300 is similar to knee joint implant 200, and therefore like elements are referred to with similar numerals within the 1300-series of numbers. For example, knee joint implant 1300 includes a femoral implant 1302, a tibial implant 1304 with a tibial stem 1312 and a tibial insert 1310. However, battery 1342 of knee joint implant 1300 are located in tibial stem 1312 as best shown in FIG. 27. Locating batteries 1342 in tibial stem provides room for additional sensors in tibial insert 1310. The tibial stem and tibial insert 1310 can be made of polyethylene in this embodiment. Various knee joint implant motion data 1301 collected by magnetic markers and marker readers is shown in FIG. 26. Motion data 1301 can include internal-external rotation, medial-lateral rotation, varus-valgus rotation, etc.
A knee joint implant 1400 according to another embodiment of the present disclosure is shown in FIG. 28. Knee joint implant 1400 is similar to knee joint implant 200, and therefore like elements are referred to with similar numerals within the 1400-series of numbers. For example, knee joint implant 1400 includes a femoral implant 1402, a tibial implant 1404 with a tibial stem 1412 and a tibial insert 1410. However, tibial insert 1410 includes an IMU 1476. Sensor data from IMU 1476 provides additional knee implant joint motion data 1401. Motion data 1401 can include internal-external rotation, medial-lateral rotation, varus-valgus rotation, etc. for reviewing knee joint implant 1400 performance. For example, internal-external rotation measurements exceeding a predetermined threshold can indicate knee joint implant lift-off (instability), medial-lateral rotation measurements exceeding predetermined thresholds can indicate knee joint implant stiffness. Combining these measurements with inputs from the various other sensors of tibial insert 1410 will provide a detailed assessment of knee joint implant 400 performance.
Referring now to FIG. 29, a spinal implant assembly 1500 is shown according to an embodiment of the present disclosure. Spinal implant assembly 1500 includes a spinal implant 1510 such as a plate, rod, etc., secured to first and second vertebrae by a first fastener 1502 and a second fastener 1504, respectively. The first and second fasteners can be screws as shown in FIG. 29. First fastener 1502 includes magnetic flux density detectors such as Hall sensor assemblies 1506 located along a body of the fastener 1502. Second fastener 1504 includes magnetic markers 1508 located along a body of the fastener. Any movement of second fastener 1504 with respect to the first fastener is detected and measured by Hall sensor assemblies 1506. Thus, the first and second fasteners function as an absolute or incremental encoder to detect spinal mobility of a patient during daily activity. As described with reference to the knee joint implants disclosed above, various other sensors such as temperature, pressure, pH, load, etc., can be included in fast fastener 1502 to provide additional measurements related to spinal implant assembly 1500 performance during a patient's recovery and rehabilitation. Ideally, there should be little to no movement between the first and second vertebrae for successful for spinal fusion. Therefore, any movement detected between the first and second fastener may indicate a compromised spinal implant assembly.
FIG. 30 is side view of a hip implant 1600 according to an embodiment of the present disclosure. Hip implant 1600 includes a stem 1602, a femoral head 1604, an insert 1606 and an acetabular component 1608. Magnetic flux density sensors such as Hall sensor assemblies 1626 are located on a flex connect 1628 and placed around femoral head 1604 as shown in FIGS. 31A and 31B. A connector 1622 on flex connect 1628 allows for convenient connection of femoral head 1604 with stem 1602. Magnetic markers 1630 are located on insert 1606 as best shown in FIG. 31C. Any motion of insert 1606 is detected by Hall sensor assemblies 1626 by measuring the change in magnetic flux density. Thus, Hall sensor assemblies 1626 and markers 1630 function as an absolute or incremental encoder to detect hip movement of a patient during daily activity.
Hip implant 1600 includes a charging coil 1610 located on stem 1602 as shown in FIG. 30. Charging coil 1610 charges a battery 1612 via a connector 1624 to power the various sensors located in hip implant 1600. A load sensor 1614 such a strain gauge detects forces between stem 1602 and acetabular component 1608 to monitor and transmit hip loads during patient rehabilitation and recovery. Various electronic components 1616, including sensors described with reference to knee joint implants, are located in stem 1602. A pH sensor 1618 located on stem can measure alkalinity and provide early detection notice of implant related infection. Data from these sensors is transmitted to an external source via an antenna 1620 as described with reference to the knee joint implants disclosed above.
FIG. 32 is a side view of a hip implant 1700 according to another embodiment of the present disclosure. Hip implant 1700 is similar to hip implant 1600, and therefore like elements are referred to with similar numerals within the 1700-series of numbers. For example, hip implant 1700 includes a stem 1702, a femoral head 1704 and an acetabular component (not shown). However, battery 1712 of hip implant 1700 is located away from electric components 1716 as best shown in FIG. 32. Battery 1712 can be conveniently inserted into hip implant 1700 via a slot 1734 as shown in FIG. 33. Similarly, electric components 1716 can be inserted into hip implant 1700 via a slot 1732. This allows for convenient replacements and upgrades to the battery and electric components without disturbing hip implant 1700.
FIG. 34 is a side view of a hip implant 1800 according to another embodiment of the present disclosure. Hip implant 1800 is similar to hip implant 1600, and therefore like elements are referred to with similar numerals within the 1800-series of numbers. For example, hip implant 1800 includes a stem 1802, a femoral head 1804 and an acetabular component (not shown). However, slot 1832 of hip implant 1800 is configured to receive all electronic components structured as a modular electronic assembly 1801 or a sensor assembly. A slot cover 1834 ensures that electronic assembly 1801 is secured and sealed in slot 1832. Thus, hip implant 1800 can be easily provided with replacement or upgrades to the electric components without disturbing hip implant 1800.
A first embodiment of a modular electronic assembly 1801 is shown in FIG. 35. Electronic assembly includes a connector 1822 to connect to femoral head 1804, various electronic components 1816, a battery 1812 and an antenna 1820. Another embodiment of a modular electronic assembly 1801′ is shown in FIG. 36. Electronic assembly 1801′ includes various electronic components 1816′, a battery 1812′, a load sensor such as a strain gauge 1814′ and an antenna 1820′. Electronic assembly 1801′ includes a pH sensor 1818′ to provide early detection of implant related infection.
FIG. 37 is a side view of a reverse shoulder implant 1900 according to an embodiment of the present disclosure. Shoulder implant 1900 includes a stem 1902, a cup 1904, an insert 1906 and a glenoid sphere 1908. Magnetic flux density sensors such as Hall sensor assemblies 1922 are located on insert 1906 as shown in FIG. 38. A connector 1920 on cup 1904 as shown in FIG. 39 allows for attachment of the cup to insert 1906. Magnetic markers 1910 are located on glenoid sphere 1908 as best shown in FIG. 37. Any motion of glenoid sphere 1908 is detected by Hall sensor assemblies 1922 by measuring the change in magnetic flux density. Thus, Hall sensor assemblies 1922 and markers 1910 function as an absolute or incremental encoder to detect shoulder movement of a patient during daily activity.
Shoulder implant 1900 includes a battery 1914 and an electronic assembly 1912 located within cup 1904. A pH sensor 1916 is located on cup 1904 to measure alkalinity and provide early detection notice of implant related infection. An antenna 1918 located on insert 1906 is provided to transmit sensor data to an external source to monitor and transmit shoulder implant 1900 performance during patient rehabilitation and recovery. Various electronic components of electronic assembly 1912, including sensors described with reference to knee joint implants, are located in cup 1904.
FIG. 40 is a side view of a reverse shoulder implant 2000 according to another embodiment of the present disclosure. Shoulder implant 2000 is similar to shoulder implant 1900, and therefore like elements are referred to with similar numerals within the 2000-series of numbers. For example, shoulder implant 2000 includes a stem 2002, a cup 2004 and an insert 2006. However, electronic assembly 2012, battery 2014 and pH sensor 2018 are located in insert 2006 as shown in FIG. 41. Thus, only a single component—i.e., the cup, of shoulder implant 2000 can be replaced or upgraded to make changes to sensor collection and transmission of the shoulder implant performance data.
FIG. 42 is a flowchart showing steps of a method 2100 to determine implant wear according to an embodiment of the present disclosure. While method 2100 is described with reference to a knee joint implant below, method 2100 can be applied to any implant with sensors described in the present disclosure, including all of the implants disclosed above. In a first step 2102, the initial thickness of the knee joint implant (such as thickness of the tibial insert) is recorded. This can be obtained by measuring the tibial insert prior to implantation, or measured based on the magnetic flux density generated by the magnetic markers as measured by the Hall sensor assemblies. Once the knee joint implant is implanted, periodic measurements of tibial insert thickness are determined in a step 2104 by evaluating the magnetic flux density. As the polyethylene housing of tibial insert degrades over time, the distance between the markers and Hall sensor assemblies are reduced as measured in a step 2106. This results in increased magnetic flux density values, which are used to estimate tibial insert wear in a step 2108.
The decision to replace the tibial insert can be based on a rate of wear threshold 2206 as shown in graph 2200 of FIG. 43 in a step 2110, or a critical thickness value 2308 as shown in graph 2300 of FIG. 44 in a step 2112. Graph 2200 plots tibial insert thickness 2202 over time 2204. A change in slope 2206 denotes the rate of wear of tibial insert. When slope 2206 exceeds the predetermined rate of wear threshold, notification to replace the tibial insert is triggered in a step 2114. Graph 2300 plots tibial insert thickness 2302 over time 2304. When the tibial insert thickness is less than a predetermined critical thickness value 2308, a notification 2310 is triggered to replace the tibial insert in step 2114.
FIG. 45 is a flowchart showing steps of a method 2400 to determine implant wear according to another embodiment of the present disclosure. While method 2400 is described with reference to a knee joint implant below, method 2400 can be applied to any implant with sensors described in the present disclosure, including all of the implants disclosed above. In a first step 2402, a knee angle of a patient with the knee joint implant is measured. The knee is then placed in full extension in a step 2404. Hall sensor amplitudes are measured in a step 2408. This process is repeated over time to track the Hall sensor amplitude. These values are then compared with initial Hall sensor amplitude values obtained when the knee implant joint template was implanted (obtained by performing steps 2412 to 2418). As the Hall sensor amplitudes are directly related to a distance between the markers and the marker readers—i.e., a tibial insert thickness, a difference between the initial Hall sensor amplitudes and current Hall sensor amplitudes from step 2408 represent wear of the tibial insert in a step 2420. When a predetermined minimum implant thickness is reached in a step 2420, a notification to replace the tibial insert is triggered in a step 2422.
FIG. 46 is a flowchart showing steps of a method 2500 for implant data collection according to an embodiment of the present disclosure. While method 2500 is described with reference to a knee joint implant below, method 2500 can be applied to any implant with sensors described in the present disclosure, including all of the implants disclosed above. In a first step 2502, a patient is implanted with a knee joint implant. The knee joint implant is in a low-power mode (to conserve battery power) until relevant activity is detected (steps 2504 and 2506). Once the relevant activity is identified by the sensor(s) of the knee joint implant (step 2508), the implant shifts to a high-power mode. Relevant activity to trigger the high-power mode can be patient-specific, and may include knee flexion speed, gait, exposure to sudden impact loads, temperature thresholds, alkalinity levels, etc. Upon identifying the relevant activity and switching over to the high-power mode, various sensors in the knee joint implant record and store sensor measurements on the device (step 2512). This data can be transferred from the patient to a home station when the patient is in the vicinity of the home station or a smart device (step 2514). The data is then transferred from the home station or the smart device to the cloud to be reviewed and analyzed by software, virtual machines and/or by experts (steps 2518, 2520). Relevant information for patient rehabilitation and recovery uncovered from the sensor data is sent back to the patient (steps 2523, 2522) via a client portal. Thus, method 2500 preserves and extends battery life of the knee joint implant by shifting the implant from low-power to high-power mode when required, and shifting the implant back to the low-power mode to conserve energy during other periods.
In some examples, the relevant patient information may be that the knee joint and knee joint implant are in a healthy state, or alternatively that the knee joint is in an infected state. If the knee joint is determined to not be in a healthy state, the clinician can then take steps to review the condition more closely and prepare a plan for treatment if necessary. After review, the clinician can input the state of the joint as determined by the clinician so that the confirmed diagnosis is then associated with the data provided by the joint implant. The diagnosis data combined with corresponding sensor data is then stored in the cloud and henceforth considered in the software's future determinations of the state of a joint and joint implant. In some examples, the software is adapted to adjust and further refine its parameters and/or thresholds used in determining the state of an implant upon receipt of the diagnosis data.
FIGS. 47A and 47B shows steps of a method 2600 for patient monitoring according to an embodiment of the present disclosure. While method 2600 is described with reference to a knee joint implant below, method 2600 can be applied to any implant with sensors described in the present disclosure, including all of the implants disclosed above. After installing the knee joint implant, various sensors within the sensor are activated (steps 2624, 2626) to track and monitor patient rehabilitation and recovery (step 2628). When the tracked data indicates that the desired recovery parameters are achieved, some of the sensors in the knee joint implant are deactivated or turned to a “sleep mode” (step 2616). For example, the recovery target can be a desired range of motion of the knee joint. Once a patient exhibits the desired knee flexion-extension range, some of the sensors on the knee joint implant can be turned off. Alternatively, peer data can be used to identify recovery thresholds (step 2612). If the recovery threshold or milestones are not achieved, the knee joint implant continues to charge and use all sensors (step 2608). Some sensors in the knee joint implant will be periodically used even after achieving the recovery milestones to monitor for early identification of improper implant performance (step 2610, 2618, 2620). For example, after turning off the magnetic readers upon achieving the desired flexion-extension range of motion, the pH or temperature sensors can be used to periodically measure alkalinity and temperature to identify infection or implant failure. Upon identification of an anomalous condition, the knee joint implant can be configured to fully recharge and turn on the previously turned off sensors to provide additional implant performance measurements (step 2624). A surgeon can customize the sensor readings and frequency based on the observed condition (steps 2626 and 2628). Additional rehabilitation steps for patient recovery can be provided to the patient at this point. The impact of the new rehabilitation steps can be monitored and compared with peers to observe patient recovery (steps 2636-2642).
FIG. 48 is a front view of a knee joint implant 7900 according to an embodiment of the present disclosure. Knee joint implant 7900 includes a femoral implant 7902 located on a femur 7906 and a tibial implant 7904 located on a tibia 7908. Tibial implant 7904 has a tibial insert 7910 configured to contact femoral implant 7902, and a tibial baseplate or tibial stem 7912 extending distally into tibia 7908. Tibial insert 7910 includes at least one transducer, e.g., a medial transducer 7914 and a lateral transducer 7916, each configured to read analog knee implant parameters, such as vibration, magnetic flux density, etc. An analog to digital converter 7918 is configured to convert the analog knee implant parameter data to digital data (FIG. 50). A processor 7920 analyzes and stores the digital data, which a data transmitter, such as an antenna 7936 located on tibial insert 7910, transmits to an external source 7926 like a smart phone, tablet, monitor, network, etc. to allow for real time review of the knee joint implant performance.
FIG. 49 illustrates additional details of tibial implant 7904 and tibial insert 7910. Tibial insert 7910 includes a tibial stem 7912 and tibial tray 7922 to receive tibial insert 7910. Tibial insert 7910 extends in a tray-like fashion in a superior direction away from the tibia and toward the femur. Tibial insert 7910 is preferably enclosed on all sides to protect the components within the insert, but may be accessed through an opening (not shown) or hinged region (not shown) to analyze, remove, or replace components within tibial insert 7910.
Continuing with FIG. 49, tibial insert 7910 includes a pair of transducers, e.g., a medial transducer 7914 and a lateral transducer 7916. Each transducer 7914, 7916 is positioned adjacent a respective condyle 7928, 7930 such that each transducer determines knee implant parameters based on a reading from separate condyles. Each transducer 7914, 7916 may be a standard type of transducer known in the art that can detect a vibration signal. For example, the transducers may be a strain gauge, accelerometer, microphone sensor, eddy-current sensor, or other sensor type known in the art. Transducers 7914, 7916 are configured to determine a vibration parameter of each respective condyle when an acoustic exciter 7932 emits a signal through a patient's knee. Thus, a transducer may be selected that is compatible with the type of acoustic exciter 7932 used in a particular implantation. For example, in an embodiment where the acoustic exciter 7932 is an ultrasound machine, the transducers 7914, 7916 may be microphone sensors. It is envisioned that other transducer types may be implemented with other acoustic exciters. Transducers 7914, 7916 may be secured to tibial insert 7910 using conventional securement means known in the art, such as fasteners or friction fits. In an alternative embodiment, transducers 7914, 7916 may be positioned in a medial encoder track (not shown) extending around a medial side of insert 7910 and/or a lateral encoder track (not shown) extending around a lateral side of the insert 7910. Tibial insert 7910 may further include additional transducers, such as Hall sensors 7943 and infection or injury detection sensors 7945.
Acoustic exciter 7932 may be a unique ultrasound machine or other exciter configured to send a readable signal. In other embodiments, acoustic exciter 7932 may be a commonly available ultrasound machine that analyzes the harmonics of bone resonance. Acoustic exciter 7932 may be placed at various locations relative to the patient to achieve a desired result. Typically, placing exciter 7932 close to bone will yield the clearest signal that is less affected by soft tissue artefact. Often, it is desirable to place exciter close to a portion of bone in which the bone is close to the surface of the overlying skin. Examples of such places include the anterior portion of the tibia and the medial and lateral sides of the knee epicondyles.
Each of transducers 7914, 7916 is configured to detect and output a vibration signal 7950, shown in FIG. 48, when an acoustic exciter 7932 emits a pulse through a patient's knee. Due to the transducers' location in tibial insert 7910, the transducers can detect the vibration signal 7950 for both the medial and lateral sides of the entire knee implant 7900 and any bone cement used to secure the implant. The vibration signal 7950 can then be remeasured at various time intervals after the initial implantation to detect a change in vibration signal that could indicate implant loosening, subsidence, implant damage, or other signs of implant detachment. This method is advantageous over other detachment detection methods as the patient's leg does not require excessive manipulation in ways that could further harm a patient or provide false readings due to human error.
FIGS. 50-51 illustrate a processor system 7920 for processing the vibration signal experienced in the knee implant 7900. An onboard processor 7920 is also positioned within tibial insert 7910. Processor 7920 may be any processor known in the art, and preferably includes an arithmetic and logical unit (ALU) (not shown), a control unit such as a microcontroller 8002, and a memory unit (not shown). In order for processor 7920 to receive analog data from transducers 7914, 7916, the vibration signal 7950 is converted from analog to digital form by an analog to digital converter 7918. Such a converter may be any converter known in the art and may have any architecture type known in the art. After conversion, the vibration signal 7950 may be referred to as a vibration signature 7960.
FIG. 51 illustrates a series of operations in flowchart form the processor 7920 may make to determine whether the implant has detached from its original, implanted position, implant subsidence, or implant damage. Processor 7920 may receive multiple streams of data. A first data stream 8006 may be initiated with input data samples from transducers 7914, 7916 being stored in a buffer 8010. The first data stream 8006 may then be transformed using fast Fourier transformations 8012 or other transformation types known in the art. A second buffer 8014 may then store the transformed data. A peak detector 8016 may then determine the maximum vibration value for the first data stream 8006. A second data stream 8008 may include a set of threshold vibration values 8026 that were stored in memory just after initial implantation. The microcontroller 8002 may then compare the measured data from the first data stream 8006 to the threshold stored data in the second data stream 8008. Result data 8018 may then be released from processor 7920 and emitted to an external source 7926. The result data 8018 may be emitted by a transmitter, such as a Bluetooth transmitter 7940 or other wireless communication types known in the art. An antenna 7936 may be positioned in or on tibial insert 7910 to aid in the data transmission process. Antenna 7936 includes may include screw threads configured to be attached to tibial insert 7910. Antenna 7936 can include a coax interface to shield knee joint and improve transmission between knee joint implant 7900 and the external source. A battery 7941 may be located adjacent antenna 7936 to power the various components of knee joint implant 7900. Antenna 7936 can serve as a charging port via radio frequency (RF) or inductive coupling if a rechargeable battery is used. The location of battery 7941 and antenna 7936 in tibial insert 7910 allow for convenient access to remove and replace these components if necessary.
FIGS. 52-53 illustrate graph outputs from the data computed by microcontroller 8002 as it compares the values from data streams 8006, 8008. The output data ideally includes response, peak, and magnitude data of the signal under various frequencies. From this data, a peak amplitude 8020 may correspond to a given frequency and thus create a signature of the implant, bone, cement, or the system of the implant, bone, and cement. The graphs may chart the amplitude in decibels along the y-axis and the frequency in kHz along the x-axis. The peak amplitudes 8020 at various frequencies may then be recorded and compared to previous values. The peak amplitude 8020 as a function of the frequency is the signature of the implant and the patient's bone density at the time of implantation. Thus, a change in amplitude over time may indicate a loss of connection between the implant and the bone. An operator or external computer program may then analyze the data and graphs over a given time period to determine if the implant has shifted from its original position. For example, FIG. 52 depicts a graph with a nearly constant amplitude of around −60 dB for various frequencies. Alternatively, FIG. 53 depicts a graph with a peak amplitude that varies at different frequencies. If the nature—i.e., pattern of the signal, varies over time, it may be indicative of implant loosening, detachment, or subsidence.
A method of using the system described in FIGS. 48-52 is provided herein. First a patient undergoes a total knee arthroscopy and a knee implant including a femoral implant 7902, a tibial implant 7904, and a tibial insert 7910 are implanted in the patient's knee. The tibial insert 7910 includes a pair of transducers 7914, 7916, one transducer positioned within insert 7910 and corresponding to a medial condyle 7928 and one positioned within insert 7910 and corresponding to a lateral condyle 7930, as is depicted in FIG. 49. After the operation and once any bone cement has hardened, an operator may activate an acoustic exciter 7932 located external to the patient's body such that the acoustic exciter 7932 sends a pulse through the patient's knee at various frequencies. For example, the exciter 7932 may provide a fixed input of 0 dB for each 1 kHz, 3 kHz, and 5 kHz signal to the transducer. The initial vibration readings post-operation (or after the patient has had the time to properly heal), provide a threshold value that act as a baseline for determine the implant's position, as the implant likely experienced minimal shift post-operation. Subsequent readings may be taken at time intervals after the threshold readings are taken. For example, a patient may be tested annually. After the threshold readings have been collected, they may be stored in the processor's memory system as vibration signatures 7960 such that they can later be compared with measured values.
As the acoustic exciter 7932 emits a pulse through the patient's knee, the pulse transfers a vibration energy through the bone and through the implant structure. Thus, transducers 7914, 7916 located in tibial insert 7910 are configured to detect the vibration energy being transferred from the femur 7906 and tibia 7908 to the knee implant 7900. Further, because each transducer 7914, 7916 is positioned adjacent a condyle 7928, 7930, each transducer 7914, 7916 can provide specific data relating to a medial and lateral side of the patient's knee.
The transducers 7914, 7916, are preferably vibration-detecting transducers such as strain gauges, accelerometers, microphone sensors, or the like. Each transducer 7914, 7916 is configured to read a vibration signal being transmitted between bone, bone cement, and the knee implant 7900. Transducers 7914, 7916 record the vibration signal as an analog signal, which is then passed through an analog to digital converter 7918 to a microcontroller 8002. The vibration signal is passed through a series of buffers 8010, 8014 and is then transformed using fast Fourier transformations 8012 or other transformation types known in the art. The data then moves through a peak detector 8016 to determine peak amplitudes of the vibration signatures 7960. Finally, the data is compared to the stored threshold data to determine if a delta occurs over time. This delta is subsequently stored as a DC offset in non-volatile RAM in the processor's memory system. Alternatively, the measured data may be compared against a previously measured data. Incoming data into the processor 7920 may be compensated by the offset to read 0 dB by the transducer at each frequency. Thus, various noises can be filtered from the system when the acoustic exciter 7932 is oriented at different positions relative to the patient.
Several methods may be implemented to filter noise throughout the system. First, positioning acoustic exciter 7932 in a clearly defined position relative to the patient can limit noise based at least on the tissue thickness and distance between the bone and the tissue. Various instrumentation, such as inertial measurement units (including inertial measurement units in the implant), may be used to ensure the exciter 7932 is in the same location for repeated tests. The same instrumentation may also be used to ensure that the patient and the patient's extremities are in the same position for repeated tests. Second, multiple vibration profiles may be taken at various poses and average profiles may be created to ensure the algorithm is resistant to bias from a single measurement. Finally, false positives or other abnormal changes in signal readings can be remeasured to confirm accuracy.
Once the processor 7920 has finished comparing the measured data to the threshold data or to previously measured data, the processor 7920 outputs the data using wireless communication technology, such as Bluetooth, to an external source 7926 (FIG. 48). The external source 7926 may be a computer program configured to further analyze and present the data. For example, the data may be prepared as graphs as illustrated in FIGS. 52-54. The graphs may chart the amplitude in decibels along the y-axis and the frequency in kHz along the x-axis. The peak amplitudes 8020 at various frequencies may then be recorded and compared to previous values. The peak amplitude 8020 as a function of the frequency is the signature of the implant 7900 and the patient's bone density at the time of implantation. Thus, a change in amplitude over time may indicate a loss of connection between the implant and the bone, implant subsidence or other implant defect. As illustrated in FIG. 54, because each transducer 7914, 7916 measures data corresponding to a condyle, it is foreseeable that each condyle may have a different vibration signature. The difference between the medial and lateral condyle vibration signals may also be used to determine the amount of variation and the direction the implant is shifting. Thus, a graph may be created that shows the difference between each condyle's vibration signature.
Once the processor 7920 has compared and analyzed the input data, it determines result data 8018 corresponding to overall implant detachment. This result data 8018 may include a change in amplitude over time and a direction of change, the direction corresponding to at least one of the medial and lateral directions. The processor 7920 then sends the result data 8018 to a transmitter which transmits the data to an external source 7926. The external source may be a computer, smartphone app, or other electronic source configured to show data. The external source 7926 ideally may provide recommendations for patients experiencing implant detachment. Machine learning may be implemented to provide said recommendations or create alerts if the implant becomes detached.
FIG. 55 illustrates another embodiment of detecting implant detaching. In this embodiment, knee joint implant 8100 is similar to knee joint implant 7900, and therefore like elements are referred to with similar numerals within the 8100-series of numbers. Knee joint implant 8100 includes a femoral implant 8102 located on a femur 8106 and a tibial implant 8104 located on a tibia 8108. Tibial implant 8104 has a tibial insert 8110 configured to contact femoral implant 8102, and a tibial baseplate or tibial stem 8112 extending distally into tibia 8108 (not shown). Tibial insert 8110 includes at least one transducer, e.g., a medial transducer 8114 and a lateral transducer 8116, each configured to read analog knee implant parameters, such as vibration or magnetic flux density. An analog to digital converter 8118 (not shown) is configured to convert the analog knee implant parameter data to digital data. A processor 8120 analyzes and stores the digital data, which a data transmitter, such as an antenna 8136 located on tibial insert 8110, transmits to an external source 8126 like a smart phone, tablet, monitor, network, etc. to allow for real time review of the knee joint implant performance
FIG. 56 illustrates a flowchart of the method steps for using implant 8100. Unlike the previous embodiment, the method of detecting implant detachment does not involve the use of an acoustic exciter. Rather, the method includes the steps of performing a TKA in a patient and implanting a knee implant 8100 including the above-mentioned components. After implantation, the patient undergoes a range of movement test to determine baseline movement data 8140 that can later be compared to other movement data. For example, the patient may perform an anterior-posterior drawer test to determine a range of motion. Alternatively, patients may perform other tests or potentially random range of motion tests as long as patient has a large range of motion. The transducers 8114, 8116 may be the same types of transducers mentioned above to detect vibration. Unlike the method where the patient remains stationary and a vibration signature is created from an acoustic exciter, this method requires a patient to move and create the patient's own vibration signature 7960. Accordingly, transducers 8114, 8116 may detect a vibration signature 7960 as the patient's knee is manipulated, and that data may be processed similarly to the data in the method.
After the baseline movement data 8140 is determine post-operation, a patient may perform identical range of motion tests at given time intervals to determine a new data point 8142 after potential loosening has occurred. For example, a patient may undergo a range of motion test annually, and the tenth annual test may indicate implant detachment compared to the reference movement data 8140. Accordingly, it is imperative that each resulting data gained from each range of motion test is properly stored in a memory system to ensure that results can be compared over a long time period.
Machine learning may be implemented to compare the data over time and provide recommendations for patients. As such, manual comparison may not be required to detect implant detachment. A database (not shown) of movements and average vibration responses for various patients may first be created. This database ideally includes information from patients of all ages, all body types, all knee operations performed, all range of movement tests performed, and the like. The machine learning algorithm may then extract feature data 8146 from the database and compare that feature data to similar feature data 8144 measured in a particular patient's range of movement test. An example of feature data 8146 is a reference vibration amplitude recorded when a patient undergoes an anterior drawer test under a maximum range of motion. This feature data 8146 may then be compared to the patient's measured vibration amplitude 8144 recorded from an anterior drawer test to determine if implant detachment is present. The machine learning algorithms may use classifier algorithms such as random forest or support vector algorithms to compare and contrast the data 8148. Alternatively, other algorithm types capable of comparing and contrasting data may be utilized to determine if implant loosening 8150 has taken place.
Similar graphs to those shown in FIGS. 52-54 may also be created using the previous method. Thus, an external source 8126 such as a computer or smartphone app may show the graphs and allow a clinician to interpret the data to the patient. The external source 8126 may also create alerts such as an audio alert or a visual alert when implant detachment is detected.
FIGS. 57-58 illustrates another embodiment of detecting implant detachment. In this embodiment, knee joint implant 8200 is similar to knee joint implant 7900, and therefore like elements are referred to with similar numerals within the 8200-series of numbers. Knee joint implant 8200 includes a femoral implant 8202 located on a femur 8206 and a tibial implant 8204 located on a tibia 8208. Tibial implant 8204 has a tibial insert 8210 configured to contact femoral implant 8202, a tibial baseplate and a tibial stem 8212 extending distally into tibia 8208. Tibial insert 8210 includes at least one Hall sensor, e.g., a medial Hall sensor 8214 and a lateral Hall sensor 8216, each configured to read knee implant parameters, such as magnetic flux density. An analog to digital converter 8218 may be configured to convert the analog knee implant parameter data to digital data. A processor 8220 analyzes and stores the digital data, which a data transmitter, such as an antenna located on tibial insert 8210, transmits to an external source 8226 like a smart phone, tablet, monitor, network, etc. to allow for real time review of the knee joint implant performance.
Continuing with FIG. 57, at least one magnet 8228 and at least one magnet 8230 are placed in the femur 8206 and tibia 8208, respectively. In such a configuration, the magnets 8228, 8230 may be detected by Hall sensors 8214, 8216 to provide a knee implant parameter correlating to the distance and strength of a magnetic field between the magnets 8228, 8230 and Hall sensors 8214, 8216. Additionally, other magnets 8232 may be placed within femoral implant 8202 to allow the Hall sensors in the tibial implant to track the position of the femoral implant. Magnets 8228, 8230 may be placed in predrilled holes in bone and may be oriented perpendicular to magnets in the knee implant 8200, such that the magnetic field generated by magnets 8228, 8230 is different from magnets 8232 in the femoral implant. Magnet 8228 in femur 8206 may be placed in a position that is not along the flexion-extension axis of the knee. Thus, the orientation of the magnets 8228, 8230—being different from magnets 8232—provide magnetic field readings and vibration signatures that are different from magnets 8232.
FIG. 58 depicts a flowchart method 8238 for determine implant detachment, loosening, or subsidence. First, a patient undergoes a TKA procedure. During the TKA procedure, a clinician may drill holes into femur 8206 and tibia 8208 to place magnets 8228, 8230 in an optimal location to be recognized by Hall sensors 8214, 8216 in tibial insert 8210. Kinematic motion of the knee with magnets 8228, 8230 is recorded in a step 8242, and inputted into a computer program that utilizes finite element analysis (FEA) to generate magnetic data in many knee poses for various training kinematics models. This computer program may further utilize machine learning, similar to the machine learning in the previous method, and thus will not be described again for sake of brevity. A clinician may also manipulate the patient's leg during surgery and collect and record the corresponding movement data during said movements. This movement data may provide a reference point for future movement tests.
First, the tibia 8208 may be tested to determine if the tibial implant 8204 is loose. In one configuration, the tibia 8208 may be manipulated in positions where the femoral bone magnet 8228 is arranged at a point furthest from Hall sensors 8214, 8216 such that it will not interfere with the magnetic field of the tibia 8208. However, in other configurations, the magnets within the femur 8206 and tibia 8208 may be placed at different distances from Hall sensors 8214, 8216, and the operating algorithm may account for any resulting magnetic field overlap or interaction. The tibia 8208 may be manipulated with anterior/posterior motions or other motions generated by the FEA modules that pass the embedded magnet 8232 by the corresponding Hall sensor 8214, 8216. This movement will generate a magnetic flux density, which can be recorded by Hall sensor 8214, 8216 and processed by processor 8220 using methods 8244 similar to those described herein. If the magnitude of the magnetic signal from the embedded tibial magnet 8230 changes through the same motion over time, for example, five years after surgery, the change could be indicative of tibial implant loosening 8248, but could also be indicative of the tibial insert 8210 moving relative to the implanted magnet. Thus, the femoral implant 8202 may also be tested to determine if loosening has occurred.
To test the femoral implant 8202 for implant loosening 8250, a clinician may manipulate femur 8206 through a predetermined set of movements, such as flexion and extension. The movements may ideally allow the implanted magnet 8228 in femur 8206 to pass by Hall sensors 8214, 8216. This movement may be repeated multiple times and a vibration signature 7960 from each movement may be recorded and stored using similar methods 8246 to those described herein. Likewise, a clinician may prescribe poses that generate maximum magnetic fields from the femoral magnet 8228, such that the magnetic field may be recorded and stored in the processor's memory system. In one embodiment, changes in the vibration signature or the magnetic field over time may indicate implant detachment. In another embodiment, regression models may be used for pose estimation. The regression models may manifest knee implant 8200 positions relative to magnets 8228, 8230 as noise artifacts as the Hall sensors 8214, 8216 pass near magnets 8228, 8230. In yet another embodiment, an acoustic exciter may provide vibration pulses through a patient's leg such that the vibration may cause the magnetic fields between the implanted magnets 8228, 8230 to change. If the change in magnetic field changes over time for similar vibration frequencies, implant loosening may have occurred.
While a knee joint implant, hip implant, shoulder implant and a spinal implant are disclosed above, all or any of the aspects of the present disclosure can be used with any other implant such as an intramedullary nail, a bone plate, a bone screw, an external fixation device, an interference screw, etc. Although, the present disclosure generally refers to implants, the systems and method disclosed above can be used with trials to provide real time information related to trial performance. While sensors disclosed above are generally located in the tibial implant (tibial insert) of the knee joint implant, the sensors can be located within the femoral implant in other embodiments. Sensor shape, size and configuration can be customized based on the type of implant and patient-specific needs.
Furthermore, although the invention disclosed herein has been described with reference to particular features, it is to be understood that these features are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications, including changes in the sizes of the various features described herein, may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention. In this regard, the present invention encompasses numerous additional features in addition to those specific features set forth in the paragraphs below. Moreover, the foregoing disclosure should be taken by way of illustration rather than by way of limitation as the present invention is defined in the examples of the numbered paragraphs, which describe features in accordance with various embodiments of the invention, set forth in the paragraphs below.
