A computer-implemented method is disclosed. The method includes determining whether one or more messages have been received from at least one of an electromechanical machine, a sensor, and an interface. Then 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.

An interactive exercise method includes streaming exercise content to an interactive video system for display via a mirror, the exercise content including a depiction of an instructor performing a repetitive movement. A video stream of a user performing the repetitive movement is received, via a camera of the interactive video system, and the user is detected in the video stream. The user or a body portion thereof is tracked in the video stream as the user performs the repetitive movement. The method also includes generating a measure of a difference between a form of the user performing the repetitive movement and a predetermined form for the repetitive movement. A corrective movement is displayed to the user, via the display and during the display of the instructor performing the repetitive movement, based on the measure, to conform the form of the user to the predetermined form for the repetitive movement.

In one aspect, the invention features a barbell including a first end portion, a second end portion, and a middle portion, where the middle portion is couplable to the first end portion and the second end portion. The middle portion includes a male coupling extending from a first end of the middle portion, the male coupling providing a first coupling mechanism that engages with a corresponding female coupling of the first end portion, and a female coupling providing a second coupling mechanism that engages with a corresponding male coupling of the second end portion.

A stationary exercise device comprises pedals mounted via cranks to opposite sides of a drive wheel; a flywheel with a magnetic rim coupled to the drive wheel; a brake with a motor and one or more permanent magnets mounted for movement relative to the magnetic rim; a measuring unit for measuring at least one of the drive force applied via the drive wheel and the related torque; a measuring device for measuring cadence; and a command module. The command module uses measurements from the measuring unit and the measuring device to calculate a performance parameter and compares the performance parameter against a predetermined performance profile. The command module also can control the motor to move the permanent magnets relative to the magnetic rim to adjust the braking force applied and thereby adjust the performance parameter to conform with the performance profile.

A method for optimizing at least one exercise is provided. The method includes receiving user data. The user data includes biometric attribute data associated with a user of an exercise device. The method includes generating at least one interval, the at least one interval including at least duration data and target power data each associated with the exercise. The method includes during the at least one interval, receiving measurement data associated with at least one of the user and the exercise device. The method includes calculating, based on the measurement data and the user data, energy data associated with an expended energy of the user during the at least one interval, the energy data including quantity data and source information each associated with at least one energy source. The method includes generating, via an artificial intelligence engine, a machine learning model trained to identify the at least one energy source.

A seated treadmill has a structure with a front portion and a rear portion. A front roller is rotatably mounted on the front portion of the structure, a rear roller is rotatably mounted on the rear portion of the structure, and a belt circumscribes the front and rear rollers. The front and rear rollers are much closer together than prior art treadmills, typically about 10-30 inches. The treadmill may further include a remote control for controlling operation of the treadmill, and a shutoff switch in the event that too much force is placed upon the treadmill, such as if the user attempts to stand on the treadmill.

Disclosed is system and method for measuring the tension of a tennis net, and, alternatively or in addition, for determining if a service let occurs via the measuring of the net tension. The disclosed embodiments measure a force exerted on the center-strap or the singles stick by the net. In these embodiments, the measured force provides an accurate reflection of the tension of the net.

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.

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.

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.