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 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 support structure has a base with a top and recesses. Inserts are mounted in respective ones of the recesses. Each insert has a protrusion that extends from the insert. The inserts are reversible and invertible. The inserts include: a first configuration where the protrusions extend above the top of the base and are located in a first position; a second configuration where the protrusions extend above the top of the base and are located in a second position that differs from the first position; and a third configuration where the protrusions extend into the recesses below the top of the base such that the inserts are flush with the top of the base.

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 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: This disclosure relates to methods of making novel dissolving wood pulps by processes comprising acid prehydrolysis, pulping, and a multi-stage bleaching process comprising oxidation with a catalyst and peroxide under acidic conditions, as well as to products made therefrom having a combination of medium-purity, low viscosity, and improved reactivity, filterability, and/or clogging that can be used as a substitute for traditional high-purity dissolving pulps in a wide variety of applications.

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 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.

Abstract: A sound emitting device can include electrically powered components that emit sound. In addition, the device can have a sensor capable of detecting movement of the device, and an electrically powered circuit. When the sensor is activated, the circuit can send a signal to the device to cause the device to emit sound. An attachment device can couple the device to a person, animal, bicycle, other device or a combination thereof.

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 method is disclosed for using an artificial intelligence engine to perform a control action. The control action is based on one or more measurements from a wearable device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive the one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the control action to be performed. The method includes receiving the one or more measurements from the wearable device being worn by a user, determining whether the one or more measurements indicate, during an interval training session, that one or more characteristics of the user are within a desired target zone, and responsive to determining that the one or more measurements indicate the one or more characteristics of the user are not within the desired target zone during the interval training session, performing the control action.

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 is disclosed for using an artificial intelligence engine to onboard a user for an exercise plan. The method includes generating a machine learning model trained to receive as input onboarding data associated with a user and an onboarding protocol and, based on the onboarding data and the onboarding protocol, output an exercise plan. While a user performs an exercise using the exercise device, the method includes receiving the onboarding data associated with the user. The method includes determining, by the machine learning model using the onboarding data and the onboarding protocol, a fitness level of the user. The onboarding protocol includes exercises with tiered difficulty levels, the onboarding protocol increases a difficulty level for a subsequent exercise when an exercise is completed, and based on a completion state of a last exercise performed, the fitness level is determined. The method includes selecting a difficulty level for each exercise.

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.