Abstract: A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Abstract: Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. For example, a method may include receiving, from one or more of an electromechanical machine, a sensor, and a computing device, data associated with a user that uses the electromechanical machine to perform a treatment plan. The method may include, based on one or more correlations of one or more indicators included in the data, generating, using an artificial intelligence engine, a unique data signature associated with a life-threatening event of the user. The unique data signature is generated when the one or more indicators satisfy a respective urgent threshold level, and the one or more indicators include a pain measurement and a measurement of revolutions per minute. Based on the unique data signature associated with the one or more life-threatening events, the method may include performing one or more preventative actions.

Abstract: A method includes receiving user data for a user capable of operating an electromechanical device. The user data comprises health history data related to one or more health indicators of the user. The method further includes generating a health improvement plan by using a machine learning model to process the user data. The health improvement plan includes an exercise session to be performed on the electromechanical device. The method further includes providing the health improvement plan to one or more user portals. The method further includes selecting, for the electromechanical device, a device configuration that corresponds to the health improvement plan. The device configuration includes mode data related to one or more modes the electromechanical device is capable of operating during the exercise session. The method further includes providing the device configuration to the electromechanical device such that the device configuration may be implemented on the electromechanical device.

Abstract: Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. For example, a method may include using, inter alia, objective data to optimize treatment plans to support user progression during rehabilitation for the purpose of assisting in determining AI-driven interventions by using machine learning to generate at least one data signature. In some embodiments, a method may perform AI-driven interventions via optimization of treatment plans in order to support user progression during rehabilitation by performing, based on data signatures related to medically-associated events, selective data injection. Some other embodiments use evidence-based research to enable AI and machine learning to select and modify treatment plans in real-time at scale. Further, the improved rehabilitation infrastructure enables, via pain management, user compliance with treatment plans.

Abstract: A computer-implemented system includes an assistant interface for providing remote medical assistance to aid a patient in performing various aspects of a rehabilitation regimen for a body part comprising a joint, a bone, or a muscle group. The assistant interface is configured to communicate, via a network connection, a telemedicine signal with the patient interface. The telemedicine signal is configured to control the patient interface and/or a treatment apparatus configured to be manipulated by the patient to perform the rehabilitation regimen. The patient interface and the treatment apparatus are at a patient location geographically separate from a location of the assistant interface. The telemedicine signal includes one or more of an audio signal, an audiovisual signal, an interface control signal for controlling a function of the patient interface, and/or an apparatus control signal for changing an operating parameter of the treatment apparatus.

Abstract: A computer-implemented system may include a rowing machine, an interface comprising a display configured to present information pertaining to the treatment plan, and at least one processing device configured to receive, from sensors, measurements associated with the user, wherein the measurements are received while the user performs the treatment plan; determine, via machine learning models, content items to present to the user, wherein the determining is based on the measurements and one or more characteristics of the user; and while the user performs the treatment plan using the rowing machine, cause presentation of the content items on the interface, wherein the content items comprise at least information related to a state of the user, and the state of the user is associated with the measurements, the characteristics, or some combination thereof.

Abstract: A smart exercise device includes an interface comprising a smart mirror configured to present information pertaining to a treatment plan being performed by a user while the user interacts with the smart exercise device. A processing device is configured to cause the smart exercise device to perform one or more functions related to the treatment plan, such as cause one or more preventative actions to be performed based on whether the processing device receives one or more messages, cause one or more content items to be presented to the user on the interface, assign the treatment plan to the smart exercise device based on a determined eligibility of the user, and implement the treatment plan to reduce a probability of a cardiac intervention for the user.

Abstract: A system for measuring an angle of a joint of a user includes a center hub, a first arm, a second arm, a magnet, and a sensor. The center hub includes a first hub and a second hub. The first arm is configured for attachment to a first limb portion of the user at a first outer end and to the first hub at a first inner end. The second arm is configured for attachment to a second limb portion of the user at a second outer end and to the second hub at a second inner end, wherein the first hub is pivotally coupled to the second hub. The magnet is coupled to the second hub. The sensor is disposed in the center hub and configured to detect a rotation of the magnet.

Abstract: Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, an alignment plan capable of enabling, during a treatment session, the aligning of a user's body. The method comprises generating machine learning models trained to identify alignment plans. The method also comprises receiving treatment data that comprises a first position of the user's body, aspects of a treatment plan, and one or more attributes of the user. The method further comprises generating the alignment plan by using the machine learning models. The generating is based on at least the aspects of the treatment plan and at least one of the one or more attributes of the user. The alignment plan may comprise a target position of the user's body and one or more elements for adjusting the user's body from the first position to the target position. The method also comprises transmitting the plan to a computing device.

Abstract: A method is disclosed for generating an improved exercise plan for a user to perform using at least an exercise machine. The method includes receiving data pertaining to the user. The data includes a physical activity goal the user desires to achieve and the physical activity goal includes levels of attainment to achieve. The method includes generating, by an artificial intelligence engine, the improved exercise plan. The improved exercise plan includes a set of exercises to be performed by the user to achieve the levels of attainment associated with the physical activity goal. The artificial intelligence engine uses at least one data source configured to include information pertaining to one or more exercises and at least one of the levels of attainment associated with the physical activity goal. The method includes transmitting the improved exercise plan to a computing device.

Abstract: A method includes receiving treatment data pertaining to a user capable of using a treatment device to perform a treatment plan and receiving activity data pertaining to the user while the user engages in at least one activity. The method also includes generating treatment information using the treatment data and the activity data and writing to an associated memory, for access by a healthcare professional, the treatment information. The method also includes modifying at least one aspect of the treatment plan in response to receiving, from the healthcare professional, treatment plan input including at least one modification to the at least one aspect of the treatment plan.

Abstract: Systems, methods, and computer-readable media for assigning remote monitoring sessions. The system includes an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while performing a treatment plan. The one or more sensors are configured to determine measurements of one or more vital signs associated with the user. The one or more processing devices are configured to receive a request to conduct a monitored session of the user performing the treatment plan. The one or more processing devices are also configured to determine whether conducting the monitored session with a computing device will violate one or more remote monitoring rules. The one or more processing device are further configured to initiate the monitored session by displaying the measurements on a display of the computing device while the user performs the treatment plan.

Abstract: A method may include receiving objective information associated with a user that uses the at least one medical device during execution of a treatment plan, and based on the objective information, generating, using one or more terms defined in at least one medical terminology database, at least one input prompt. The method may also include providing, to an at least artificial intelligence engine configured to provide one or more predictions indicating one or more treatment interventions, the at least one input prompt. The method may also include receiving at least one prediction indicating one or more treatment interventions, and controlling, while the user uses the at least one medical device, and based on at least one aspect of the one or more treatment interventions indicated by the at least one prediction, the at least one medical device.

Abstract: A computer-implemented system includes one or more processing devices configured to receive user information associated with a user, generate a selected set of the user information, determine, based on the selected set of the user information, at least one of a first probability of surviving one or more procedures and a second probability indicating an improvement, resulting from the one or more procedures, in quality-of-life metrics for the user, generate, based on the at least one of the first probability and the second probability and on the selected set of the user information, one or more recommendations of whether the user should undergo the one or more procedures, and generate, based on the one or more recommendations, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability.

Abstract: Systems, methods, and computer-readable mediums for operating an electromechanical device are disclosed. The system includes, in one example, the electromechanical device, a patient portal, and a computing device. The computing device is configured to receive user data relating to a user, and receive treatment data relating to treatment plans and outcomes. The computing device is also configured to generate a prehabilitation plan by using a machine learning model to process the user data and the treatment data. The computing device is further configured to select, for the electromechanical device, an electromechanical device configuration that enables exercises of the prehabilitation plan to be performed by the user such that performance improves an area of the user's body. The computing device is also configured to enable the electromechanical device to implement the electromechanical device configuration.

Abstract: A computer-implemented system for processing medical claims is disclosed. The computer-implemented system includes a medical device configured to be manipulated by a user while the user performs a treatment plan; a patient interface associated with the medical device, the patient interface comprising an output configured to present telemedicine information associated with a telemedicine session; and a processor. The processor is configured to, during the telemedicine session, receive device-generated information from the medical device; generate a first biometric signature; using the device-generated information, generate a second biometric signature; using the first and second biometric signatures, generate a signature comparison; using the signature comparison, generate a signature indicator; and transmit the signature indicator.

Abstract: A method is disclosed. The method may include, while the patient uses the treatment apparatus, controlling, based on a treatment plan for a patient, a treatment apparatus. The method may include receiving, by a processing device, data from an electronic device, wherein the data comprises a measurement pertaining to performance of a treatment plan by a patient using a treatment apparatus, a characteristic pertaining to the patient, or both. The method may include storing, via the processing device, the data for the patient in a computer-readable medium. The method may include using a privacy-enhancing technology (PET) engine to control access to personally identifiable information (PII) associated with the patient.

Abstract: A system and method for improving completion of an exercise is disclosed herein. In one embodiment, a method of a control system to improve compliance with an exercise plan for an exercise machine includes receiving one or more load measurements from one or more load cells of the exercise machine. The method also includes comparing the one or more load measurements to one or more target thresholds, and determining whether the one or more load measurements exceed the one or more target thresholds. Responsive to determining that the one or more load measurements exceed the one or more target thresholds, the method also includes causing a user interface to present an indication that the one or more target thresholds have been exceeded and an exercise is complete, wherein the exercise is included in the exercise plan.

Abstract: Systems and methods include receiving a plurality of sets of data corresponding to respective users of a plurality of users undergoing rehabilitation treatment. Each of the sets of data includes sensor data obtained while the respective users perform respective treatment plans. The plurality of sets of data is stored as objective information in a queryable data format. The method further includes receiving first sensor data associated with the performance of a first treatment plan. The first treatment plan corresponds to a standardized treatment plan assigned to the user, and the first sensor data correlates with the objective information. The method further includes predicting, based on the objective information and the first sensor data, a likelihood of the first user achieving a rehabilitation goal, generating, based on the objective information, the first sensor data, and the likelihood of the first user achieving the rehabilitation goal, a second treatment plan.

Abstract: A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.