Abstract: Computer-implemented systems, computer-implemented methods, and tangible, non-transitory computer-readable media for detecting abnormal heart rhythms of a user performing treatment plan with an electromechanical machine. The system includes, in one embodiment, 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 the user is performing a treatment plan. The one or more sensors are configured to determine one or more measurements associated with the user. The one or more processing devices are configured to receive, from the one or more sensors while the user performs the treatment plan, the one or more measurements associated with the user. The one or more processing devices also configured to determine, using one or more machine learning models, a probability that the one or more measurements indicate that the user satisfies a threshold for a condition associated with an abnormal heart rhythm.

Abstract: A computer-implemented system may include an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac condition or a cardiac outcome, generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.

Abstract: Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, treatment plans for optimizing a user outcome. The method comprises receiving attribute data associated with a user. The attribute data comprises one or more symptoms associated with the user. The method also comprises, while the user uses a treatment apparatus to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by the artificial intelligence engine configured to use one or more machine learning models, a second treatment plan for the user. The generating is based on at least the attribute data associated with the user and the measurement data associated with the user. The second treatment plan comprises a description of one or more predicted disease states of the user. The method also comprises transmitting, to a computing device, the second treatment plan for the user.

Abstract: A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.

Abstract: A computer-implemented system includes an electromechanical machine and a processing device communicatively coupled to motors. The processing device executes instructions to receive first data comprising information pertaining to motion of one or more pedals of the electromechanical machine, wherein the motion is associated with one or more users performing one or more treatment plans; receive second data comprising information pertaining to one or more characteristics of the one or more users performing the treatment plan, wherein the characteristics comprise performance information, measurement information, personal information, or some combination thereof; identify one or more correlations between at least some of the first data and at least some of the second data; and generate, based on the one or more treatment plans and the one or more correlations, one or more motion profiles for an assembly of the electromechanical machine.

Abstract: In one embodiment, a computer-implemented system includes an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan. The treatment plan includes a high-intensity interval training (HIIT) session. A processing device is configured to initiate, using the electromechanical machine, the HIIT session, receive, via one or more sensors, one or more measurements pertaining to the electromechanical machine, determine whether the one or more measurements exceed one or more of one or more corresponding thresholds, and in response to determining that the one or more measurements exceed one or more of the one or more corresponding thresholds, modify the treatment plan to cause operation of the electromechanical machine to be modified.

Abstract: A system includes a treatment apparatus configured to implement a treatment plan for rehabilitation to be performed by a user and a processing device configured to receive attribute data associated with the user; generate, based on the rehabilitation, selected attribute data; determine, based on the selected attribute data, the rehabilitation, and a rehabilitation goal associated with the rehabilitation, one or more probabilities of attaining the rehabilitation goal within respective one or more numbers of rehabilitation sessions to be performed by the user using the treatment apparatus; provide, based on the one or more probabilities, an indication of the one or more numbers of rehabilitation sessions; and generate, based on a selected number of rehabilitation sessions from among the one or more numbers of rehabilitation sessions, the treatment plan. The treatment plan includes one or more exercises directed to attaining the rehabilitation goal within the selected number of rehabilitation sessions.

Abstract: A method is disclosed for using an artificial intelligence engine to present a user interface capable of presenting the progress of a user in domains. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a user interface that causes icons to dynamically change position on the user interface. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the exercise device. The method includes presenting, on a computing device associated with the exercise device, sections of the user interface, wherein the sections are each related to a separate domain comprising the domains and wherein, based on the measurements, each section includes the icons placed.

Abstract: A machine includes a body with an arm having a proximal end and a distal end. The proximal end is pivotally mounted to the body, and the distal end is free to move relative to the body. A carriage is slidably mounted to the arm for movement along a length of the arm. A pedal assembly is rotatably coupled to the carriage for movement with the carriage along the length of the arm. The pedal assembly supports a foot of a user of the machine. Motors are mounted to the body and spaced apart from each other and spaced apart from the distal end of the arm. Cables are coupled to respective ones of the motors and to the carriage. A control system selectively extends and retracts the cables with the motors to cause the pedal assembly to move in prescribed pedaling patterns relative to the body.

Abstract: A method and system for implementing an exercise protocol for osteogenesis and/or muscular hypertrophy are disclosed. A method may include initiating, based on the exercise protocol, a warmup session for a first exercise, where the warmup session specifies applying a first target load threshold for a first period of time. The method includes determining the warmup session is complete after the first period of time elapses. Responsive to determining the warmup session is complete, the method includes initiating, based on the exercise protocol, a resting session specifying not applying loads for a second period of time. The method includes determining the resting session is complete after the second period of time elapses. Responsive to determining the resting session is complete, the method includes initiating, based on the exercise protocol, an exercise session specifying applying a second target load threshold for a third period of time.

Abstract: A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on a pulmonary condition of the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, a first probability of improving a pulmonary condition of the user subsequent to at least one of a pulmonary procedure being performed on the user, a pulmonary treatment being performed on the user, and a pulmonary diagnosis, and generate, based on the first probability, a treatment plan that includes one or more exercises directed to modifying the first probability. A treatment apparatus is configured to enable implementation of the treatment plan.

Abstract: A treadmill comprises a pair of rollers and a belt coupled to and extending between the pair of rollers. The belt encircles a support platform suspended between the pair of rollers. A motor is operatively coupled to one of the pair of rollers to rotate the one of the pair of rollers such that rotation of the rollers causes the belt to rotate around the support platform suspended between the pair of rollers. The treadmill further comprises a processing device configured to cause the treadmill to perform an action associated with a use of the treadmill by the user based on whether the processing device receives certain messages; cause content items to be presented to the user; assign the treatment plan to the treadmill 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 computer-implemented system includes a treatment apparatus configured to implement a treatment plan while the treatment apparatus is being manipulated by a user and a processing device configured to receive a plurality of risk factors, each of the plurality of risk factors being associated with one or more medical events or outcomes for a user; generate a set of the risk factors; determine, based on the set of the risk factors and measurement information associated with the user, one or more individual probabilities that the one or more medical events or outcomes will occur while the treatment apparatus is being manipulated by the user; and perform, based on the one or more individual probabilities, one or more corrective actions associated with the one or more medical events or outcomes.

Abstract: A computer-implemented system includes an electromechanical machine and a processing device communicatively coupled to motors. The processing device executes instructions to receive data comprising a treatment plan including one or more prescribed exercises for a user to perform using the electromechanical machine; generate, based on the data, a motion profile for an assembly of the electromechanical machine, wherein the assembly is coupled to a carriage to enable movement along a length of an arm, wherein the carriage is coupled to each cable of the first set of cables; execute a transformation function to implement a desired virtual apparatus model using the electromechanical machine, wherein, to implement the desired virtual apparatus model, the transformation function maps the motion profile to one or more coordinates in a domain; and control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine.

Abstract: Systems, methods, and computer-readable media for improving cardiovascular health such that the need for a cardiac intervention is mitigated. The system includes one or more processing devices and an electromechanical machine. The one or more processing device are configured to receive a plurality of risk factors associated with a cardiac-related event for a user. The one or more processing device are also configured to generate a selected set of the risk factors. The one or more processing device are further configured to determine, based on the selected set of the risk factors, a probability that a cardiac intervention will occur. The one or more processing device are also configured to generate, based on the probability and the selected set of the risk factors, a treatment plan including exercises directed to reducing the probability that the cardiac intervention will occur. The electromechanical machine is configured to implement the treatment plan.

Abstract: A computer-implemented method is disclosed. The method includes determining whether one or more messages have been received while a user performs a treatment plan. The one or more messages may pertain to at least one of a user and a usage of the electromechanical machine by the user. The electromechanical machine may be configured to be manipulated by the user while the user is performing a treatment plan. The method also includes, responsive to determining that the one or more messages have not been received, determining, using one or more machine learning models, one or more preventative actions to perform. The method also includes causing the one or more preventative actions to be performed.

Abstract: A computer-implemented method for facilitating cardiac rehabilitation among eligible users is disclosed. The method includes the steps of (1) receiving health information associated with a user; (2) determining, based on the health information, whether the user is eligible for cardiac rehabilitation, wherein the cardiac rehabilitation uses an electromechanical machine; and (3) in response to determining the user is eligible for cardiac rehabilitation, generating a treatment plan for the user, wherein the treatment plan pertains to a cardiac rehabilitation that is specific to the user, and the treatment plan comprises use of the electromechanical machine.

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: A computer-implemented method is disclosed. The method includes determining a maximum target heart rate for a user using an electromechanical machine to perform a treatment plan, wherein the electromechanical machine is configured to be manipulated by the user while the user is performing the treatment plan. The method includes receiving, via an interface, an input pertaining to a perceived exertion level of the user, wherein the interface comprises a display configured to present information pertaining to the treatment plan. Based on the perceived exertion level and the maximum target heart rate, the method includes determining an amount of resistance for the electromechanical machine to provide via one or more pedals physically or communicatively coupled to the electromechanical machine. While the user performs the treatment plan, the method includes causing the electromechanical machine to provide the amount of resistance.

Abstract: A computer-implemented method for facilitating cardiac rehabilitation among eligible users is disclosed. The method includes the steps of (1) receiving health information associated with one or more users; (2) for each user of the one or more users: determining, based on health information associated with the user, a respective eligibility of the user for cardiac rehabilitation; (3) determining, based on the respective eligibilities, that at least one user of the one or more users is eligible for cardiac rehabilitation; (4) generating a treatment plan for the at least one user, where the treatment plan pertains to a cardiac rehabilitation that is specific to the at least one user; and (5) assigning the treatment plan to at least one electromechanical machine to enable the user to perform the cardiac rehabilitation.