Implant With Sensor Diagnostics
Disclosed herein are joint implants and methods for tracking joint implant performance. A joint implant includes a first implant coupled to a first bone of a joint and a second implant coupled to a second bone of the joint. The second implant includes at least one of a first sensor configured to measure a first type of data, and a processor operatively coupled to the at least one of the first sensor. The process outputs the first type of data to a network to be compared with data received from other joint implants. One of the joint or the implant is determined to be in a first state based on a comparison of the first type of data to a set of predetermined values formed based on the data received from the other joint implants. The predetermined values are adapted to change with the addition of new data.
This application is a continuation of United States Pat. Application No. 18/108,954 filed on Feb. 13, 2023, which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/444,056 filed Feb. 8, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/444,045, filed Feb. 8, 2023, and which claims the benefit of the filing date of United States Provisional Pa.t Application No. 63/443,146 filed Feb. 3, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/483,045, filed Feb. 3, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/482,659, filed Feb. 1, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/482,656 filed Feb. 1, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/482,097 filed Jan. 30, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/482,109 filed Jan. 30, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/481,660 filed Jan. 26, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/481,053 filed Jan. 23, 2023, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/431,094 filed Dec. 8, 2022, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/423,932 filed Nov. 9, 2022, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/419,781 filed Oct. 27, 2022, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/419,522 filed Oct. 26, 2022, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63,419,455 filed Oct. 26, 2022, and which claims the benefit of the filing date of United States Provisional Pat. Application No. 63/359,384 filed Jul. 8, 2022, and which claims the benefit of the filing date of United States Provisional Pat. 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 INVENTIONThe 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 INVENTIONMonitoring 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 INVENTIONDisclosed 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 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 second implant may include a first sensor configured to measure a first type of data, and a processor operatively coupled to the first sensor. The processor may output the first type of data to a network. One of the joint or the implant may be determined to be in a first state based on a comparison of the first type of data to a set of predetermined values. The predetermined values may be adapted to change with the addition of new data.
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 any of a pH sensor, a temperature sensor, a Hall sensor, a pressure sensor, an optical sensor, and a blood sensor operatively coupled to the processor. The tibial implant may include a tibial insert and a tibial stem. The tibial insert may be made of polyethylene.
Continuing in accordance with this aspect, the processor may output the data to an external source connected to the network. The joint implant may further comprise a transmitter to transmit the first type of data to the external source.
Continuing in accordance with this aspect, the external source may be any of a tablet, computer, smart phone, and remote workstation. A battery may be disposed within the second implant. A charging circuit may be disposed within the second implant to charge the battery using power generated by piezo stacks.
Continuing in accordance with this aspect, the joint may be a hip joint. The first implant may be a hip insert and the second implant may be a femoral head.
Continuing in accordance with this aspect, the joint may be a shoulder joint. The first implant may be a glenoid sphere and the second implant may be a shoulder insert.
Continuing in accordance with this aspect, the joint implant may include at least one of a second sensor configured to measure a second type of data. The joint implant may include a plurality of the first sensor and a plurality of the second sensor. The processor may output the first and second types of data to the network.
Continuing in accordance with this aspect, the data received from other joint implants may include data measured by a sensor. The data received from the other joint implants may include determinations of a state of the respective joint or a state of the respective implant as determined by a user.
Continuing in accordance with this aspect, the addition of new data may include the first type of data output by the processor of the joint implant. The addition of new data may include the data received from the other joint implants. The addition of new data may include a determination of a state of one of the other joint implants based on a type of data output from the respective one of the joint implants as determined by a user.
Continuing in accordance with this aspect, the joint implant may be configured to initiate a warning when the joint implant is determined to be in the first state. The first state may be any one of inflamed, infected, or injured
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 and contacting the first implant. The second implant may include a first sensor configured to measure a first type of data, a second sensor configured to measure a second type of data, and a processor operatively coupled to the at least one of the first and second sensors. The joint implant may be operatively coupled to a network of joint implants. The processor may output the first and second types of data to the network to determine a state of the joint implant based on data received in the network from other joint implants. The joint implant may be configured to initiate an alert when the joint implant is determined to be in a first state.
In accordance with an aspect of the present disclosure, a system for detecting the state of a joint implant is provided. A system according to this aspect, may include a joint implant. The joint implant 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 contacting the first implant. The second implant may include at least one of a first sensor configured to measure a first type of data, and a processor operatively coupled to the at least one of the first sensor, and a device operatively coupled to the processor. The device may have a network adapted to receive data from the processor and at least a second source, process the data from the processor and the second source, and output a state of the joint based on the data from the processor and the data from the second source.
Continuing in accordance with this aspect, the joint implant may be a first joint implant. The second source may include a second joint implant including at least one of a first sensor configured to measure a first type of data.
Continuing in accordance with this aspect, the second source may include a determination of a state of a joint based on data provided by sensors of a joint implant as determined by a user. The device may define a predetermined range of values and determines that the joint is in a first state when the data is within the predetermined range. The device may initiate a warning when the first type of data is outside of the predetermined range of values. The joint may be determined to be any one of injured, infected, or inflamed when the data is outside of the predetermined range of values. The predetermined range may be adapted to change upon receipt of data from a joint implant or the determination of the state by the user.
Continuing in accordance with this aspect, the at least one of the first sensor may include any one of a temperature sensor, a pressure sensor, a pH sensor, an optical sensor, and a blood sensor. The blood sensor may measure data on pathogens present in the joint. The blood sensor may measure a glucose level in the joint.
Continuing in accordance with this aspect, at least one of the first sensor may measure the first type of data upon activation by a user.
In accordance with an aspect of the present disclosure, a method for monitoring an implant performance is provided. A method according to this aspect, may include the steps of providing a joint implant with a first sensor configured to measure a first type of data, tracking and outputting the first type of data over time to a network using a processor disposed within the implant, comparing the first type of data to a set of data received into the network from other implants, determining a state of the implant based on the comparison of the first type of data with the set of data received from other implants, and initiating a warning from the implant when the implant is determined to be in a first state.
Continuing in accordance with this aspect, the first state may be any one of the joint being inflamed, infected, or injured.
Continuing in accordance with this aspect, the first type of data may be compared to a predetermined value designated according to the set of data received into the network from the other implants. The predetermined value may include a range of predetermined values. The implant may be determined to be in the first state when the first type of data falls outside of the range of predetermined values. The predetermined value may be adapted to change when a new set of data from an implant is received in the network.
In accordance with an aspect of the present disclosure, a method for monitoring an implant performance is provided. A method according to this aspect, may include the steps of coupling a first implant to a first bone of a joint, coupling a second implant to a second bone of the joint, tracking and outputting the first type of data to an external source using a processor disposed within the implant, comparing the first type of data to a predetermined value formed based on a set of data obtained from other joint implants, and determining a state of the implant. The second implant may be configured to contact the first implant. The second implant may include a first sensor to measure a first type of data such that the implant may be determined to be in a first state when the first type of data is different than the predetermined value. The range of predetermined values may be adapted to change when new data is provided to the set of data.
Continuing in accordance with this aspect, the new data may include a first type of data measured by a first sensor of an implant. The new data may include a determination of a state of an implant as determined by a user.
Continuing in accordance with this aspect, the method may further comprise initiating an alert to a user when the implant is determined to be in the first state. The first state may be one of the joint being inflamed, infected, or injured.
Continuing in accordance with this aspect, the predetermined value may include a range of predetermined values. The implant may be determined to be in the first state when the first type of data is outside of the range of predetermined values.
Continuing in accordance with this aspect, the first sensor may be any one of a temperature sensor, a pressure sensor, a pH sensor, an optical sensor, and a blood sensor.
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:
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.
Details of antenna 122 are shown in
Details of tibial insert 210 are shown in
As best shown in
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
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
In addition to the sensors described above, particularly with reference to knee joint implants 100 or 200, it is contemplated that the implant may include any type and any number of sensors useful for detecting signs of infection, inflammation, injury, etc. within the knee joint. For example, knee joint implant 200 may include an optical sensor capable of measuring the turbidity of the synovial fluid, and/or a blood sensor or analyzer capable of capturing data on pathogens present in the joint, which may allow for a more accurate treatment in the case of infection. Still further, the blood analyzer may include other functions such as glucose analysis, which may be useful for cases of diabetes in joint replacement.
As noted above, the data measured and gathered by the various sensors are read by the processor 250, such as an MCU, to process and transfer the measurements to an external source 5845 via the antenna 222. Processor 250 can send data in packets arranged by data types. For example, data packets containing Hall sensor position, IMU gyro, accelerometer, pH, pressure, temperature, etc. can be each transmitted under unique IDs. The type of data and frequency of measurement can be defined by a physician via a platform such as OrthoLogIQ, and sent over the air to the implant by a paired mobile device. During normal operation, the processor can be configured to run a particular task (such as a list of measurements assigned by a physician) at a defined rate (the frequency). The data can then be stored in local FRAM. The processor can then go to sleep until it is woken up by a timer interrupt to read, make readings, store data in memory, and return to sleep status as scheduled. Data upload can be during a defined period (primary) or on first chance (secondary). As shown in
Some of the content stored in the neural network 5854 of the cloud 5850 includes, as described above, a set of data from each knee joint implant 200. Each set of data may include several types of data. That is, a first type of data may be obtained from a first type of sensor (e.g., temperature readings may be obtained from a temperature sensor, or pH readings may be obtained from a pH sensor). From such readings of each type and/or set of data, a clinician makes a diagnosis of the state of the knee joint or knee joint implant 200, either based on the set of data or on other factors (such as information provided by the patient), or a combination thereof. The clinician’s diagnosis includes the determination of the knee joint or knee joint implant 200 being in any one of a variety of states, such as a healthy state, an infected state, an inflamed state, an injured state, or the like. The diagnosis may be manually entered into the external source 5845 by the clinician and thereby associated with the corresponding set of data in the neural network 5854.
After a first set of data from a first knee joint implant 200 in a first user 5840 is provided in the neural network 5854 with an associated diagnosis of the state of the knee joint implant 200 or knee joint, such a process may be repeated for a second set of data from a second knee joint implant 200 in a second user 5840, and may continue thereafter for any number of patients and sets of data which the cloud 5850 is capable of holding. As shown in
Upon determining the state of a knee joint or a knee joint implant 200, the software 5860 may then initiate an alert or a warning, depending on the type of state it has determined the knee joint or implant 200 to be in. For example, if the knee joint or implant 200 is determined by the software 5860 to be in an infected state, the software 5860 initiates a warning notifying the clinician of the patient state, or notifying the client of the same through the client portal 5856. In some scenarios, such an alert is provided prior to the patient’s feeling of pain or discomfort and therefore prior to a clinician’s diagnosis would have occurred had the knee joint implant 200 not provided the alert. It is contemplated that the processor 250 of the implant 200 may communicate with the external source when prompted or activated by the patient (e.g., in the patient’s home) or by the clinician (e.g., in the clinician’s office). It is also contemplated that the processor 250 may communicate with the external source 5845 automatically when within a certain proximity of the external source 5845, allowing the software 5860 to issue a warning to the client portal 5856 even when unsuspected by the patient. In some examples, the client portal 5856 is accessible through the external source 5845. In further examples, if the software 5860 determines that the knee joint and the knee joint implant 200 are in a healthy state, the software 5860 may issue a notice to the patient/clinician indicating such condition (e.g., when the patient or clinician activates communication between the implant 200 and the external 5845 source), or the implant 200 may issue nothing at all.
The set of data of each patient implant 200 stored in the neural network 5854 of the cloud 5850 will remain in the neural network 5854 for as long as permitted by the clinician. However, it is also contemplated that the software 5860 may be capable of detecting an outlier set of data based on an associated diagnosis or manual input from the clinician, and the software 5860 may be capable of disregarding such outliers from its interpretations or removing such data from the neural network 5854 altogether. Generally, with each additional set of data from each patient implant 200 that is added to the neural network 5854, the software 5860 uses artificial intelligence to update its reference points and further refine its ability to detect the state a joint or joint implant 200. For example, with each addition of a new set of data from an implanted implant 200 determined to be in a healthy state, or a new set of data from an implanted implant 200 determined to be in an infected state, etc., the software 5860 may modify its predetermined values or the predetermined ranges of values which it uses to determine the state of a knee joint or implant 200, thereby further enhancing its accuracy of detection with each addition of new data. Therefore, the software 5860 is able to draw conclusions from an aggregate of data history stored within the neural network 5854, and the knowledge base of the neural network 5854 continuously improves over time.
External sleeve 868 shown in
A tibial implant 1204 according to another embodiment of the present disclosure is shown in
A knee joint implant 1400 according to another embodiment of the present disclosure is shown in
Referring now to
Hip implant 1600 includes a charging coil 1610 located on stem 1602 as shown in
A first embodiment of a modular electronic assembly 1801 is shown in
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.
The decision to replace the tibial insert can be based on a rate of wear threshold 2206 as shown in graph 2200 of
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 5850 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.
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.
Claims
1. A joint implant comprising:
- a first implant coupled to a first bone of a joint; and
- a second implant coupled to a second bone of the joint, the second implant including: a first sensor configured to measure a first type of data; and a processor operatively coupled to the first sensor; wherein the processor outputs the first type of data to a network, and
- wherein one of the joint, the first implant or the second implant is determined to be in a first state based on a comparison of the first type of data to a set of predetermined values, and
- wherein the predetermined values are adapted to change with the addition of new data.
2. The joint implant of claim 1, wherein the joint is a knee joint, the first implant is a femoral implant and the second implant is a tibial implant.
3. The joint implant of claim 2, wherein the tibial implant includes any of a pH sensor, a temperature sensor, a Hall sensor, a pressure sensor, an optical sensor, and a blood sensor operatively coupled to the processor.
4. The joint implant of claim 3, wherein the tibial implant includes a tibial insert and a tibial stem, and wherein the tibial insert is made of polyethylene.
5. The joint implant of claim 1, wherein the processor outputs the data to an external source connected to the network, and the joint implant further comprises a transmitter to transmit the first type of data to the external source.
6. The joint implant of claim 1, further comprising a battery disposed within the second implant.
7. The joint implant of claim 1, wherein the joint is a shoulder joint, the first implant is a glenoid sphere and the second implant is a shoulder insert.
8. The joint implant of claim 1, further comprising at least one of a second sensor configured to measure a second type of data.
9. The joint implant of claim 8, wherein the joint implant includes a plurality of the first sensor and a plurality of the second sensor.
10. The joint implant of claim 9, wherein the processor outputs the first and second types of data to the network.
11. The joint implant of claim 1, wherein the addition of new data includes the first type of data output by the processor of the joint implant.
12. The joint implant of claim 11, wherein the addition of new data includes the data received from other joint implants.
13. The joint implant of claim 1, wherein the joint implant is configured to initiate a warning when the joint implant is determined to be in the first state.
14. The joint implant of claim 11, wherein the first state is any one of inflamed, infected, or injured.
15. A joint implant comprising: wherein the joint implant is configured to initiate an alert when the joint implant is determined to be in a first state.
- a first implant coupled to a first bone of a joint; and
- a second implant coupled to a second bone of the joint and contacting the first implant, the second implant including: a first sensor configured to measure a first type of data; a second sensor configured to measure a second type of data; and a processor operatively coupled to the at least one of the first and second sensors;
- wherein the joint implant is operatively coupled to a network of joint implants; and
- wherein the processor outputs the first and second types of data to the network to determine a state of the joint implant based on data received in the network from other joint implants, and
16. The joint implant of claim 15, wherein the data received from other joint implants includes data measured by a sensor.
17. The joint implant of claim 15, wherein the data received from the other joint implants includes determinations of a state of the respective joint or a state of the respective implant as determined by a user.
18. A system for detecting a state of a joint implant comprising:
- a joint implant including: a first implant coupled to a first bone of a joint; a second implant coupled to a second bone of the joint and contacting the first implant, the second implant including: at least one of a first sensor configured to measure a first type of data; and a processor operatively coupled to the at least one of the first sensor; and
- a device operatively coupled to the processor, the device having a network adapted to receive data from the processor and at least a second source, process the data from the processor and the second source, and output a state of the joint based on the data from the processor and the data from the second source.
19. The system of claim 18, wherein the joint implant is a first joint implant, and wherein the second source includes a second joint implant including at least one of a first sensor configured to measure a first type of data.
20. The system of claim 18, wherein the second source includes a determination of a state of a joint based on data provided by sensors of a joint implant as determined by a user.
Type: Application
Filed: Apr 6, 2023
Publication Date: Sep 28, 2023
Inventors: Carlos O. Alva (Boynton Beach, FL), Matthias Verstraete (Chaam), Ezra S. Johnson (Reeds Spring, MT)
Application Number: 18/131,594