Abstract: A rehabilitation and exercise system can include a base. A static device can be coupled to the base and configured to provide isometric exercise for a user by receiving static force from the user to facilitate at least one of osteogenesis or muscle hypertrophy for the user. In addition, a dynamic device can be coupled to the base and configured to provide a dynamic exercise for the user by being moved by the user to facilitate at least one of osteogenesis and muscle hypertrophy for the user.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of one or more pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the exercise device to modify the resistance of the one or more pedals. The method includes receiving the one or more measurements from a sensor associated with the one or more pedals of the exercise device, determining whether the one or more measurements satisfy a trigger condition, and responsive to determining that the one or more measurements satisfy the trigger condition, transmitting the control instruction to the exercise device.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. 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 control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

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 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 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 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 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 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 system, method and apparatus for exercise and rehabilitation includes a frame coupled to a base and having a top end. An arm having a proximal end can be coupled to the top end of the frame. A distal end of the arm is opposite the proximal end. The arm is movable in a first degree of freedom between a retracted position and an extended position relative to the frame. Handles are coupled to the arm adjacent the distal end and movable in a second degree of freedom relative to the arm. The handles are manipulated by a user for exercise and rehabilitation.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. 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 control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

Abstract: Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, an exercise plan for a user to perform. The method comprises receiving data pertaining to the user and generating user energy consumption metrics for a plurality of exercises. Each of the user energy consumption metrics is generated for a respective one of the plurality of exercises based at least on a metabolic equivalent of task (MET) value for the respective one of the plurality of exercises and user fitness test results. The method also includes generating the exercise plan based at least on the user energy consumption metrics and a user energy score. The exercise plan includes at least a subset of the plurality of exercises to be performed by the user to attempt to achieve the user energy score. The method further includes transmitting the exercise plan to a computing device.

Abstract: A multidimensional exercise control system is disclosed herein. In one embodiment, a control system of an exercise machine comprises a memory device storing instructions, a user interface for presenting a video game with an avatar, and a processing device operatively coupled to the memory device and the user interface. The processing device is configured to execute the instructions to receive sensor data from a sensor operatively coupled to an exercise machine, wherein the sensor data comprises one or more measurements; responsive to the one or more measurements, cause the avatar to change a position in the video game; compare the one or more measurements to a target threshold; determine whether the one or more measurement exceed the target threshold; and responsive to determining that the one or more measurements exceed the target threshold, cause the user interface to present a modification to the video game.

Abstract: A method for generating an exercise session for a user using an exercise machine is disclosed herein. The method includes receiving a plurality of inputs, wherein the plurality of inputs comprise an indication of a level of pain of the user and a range of motion of a body part of the user. The method also includes determining, based on the plurality of inputs, an exercise level of the user, generating, using a machine learning model, the exercise session for the user by selecting, based on the exercise level of the user, one or more exercises to be performed by the user using an exercise machine, and causing initiation of the exercise session on the exercise machine and a virtual coach executed by a computing device associated with the exercise machine to provide instructions pertaining to the exercise session.

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 system and method for intelligent self-calibration of target load thresholds for users of exercise machines is disclosed herein. In one embodiment, a method includes determining, by one or more processing devices, a bone geometry of a bone in a portion of a body of a user, where said portion is going to be exercised by the user performing an exercise on an exercise machine. The method also includes determining, using the bone geometry, a strain on the bone in the portion of the body of the user such that the strain triggers osteogenesis, determining a target load threshold to be added by the user to the exercise machine during the exercise to achieve the strain that triggers osteogenesis, and, while the user performs the exercise on the exercise machine, causing the target load threshold to be represented on a user interface of a computing device.

Abstract: An exercise system includes two or more exercise machines coupled together. Each exercise machine can include a modular exercise machine offering one or more unique exercise functions. To vary or change the exercise system, the exercise machines may decouple from each other and couple to a different exercise machine. Examples of the exercise machines include osteogenic, muscular hypertrophy and cardiovascular devices. These exercise systems enable modifications to the exercise machines for user rehabilitation. The exercise machines can monitor other exercise machines and provide feedback to a user through a computer display.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. 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 control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.