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.

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.

An exercise machine including a support frame having a handle structure affixed to a base structure is described. The handle structure can provide hand support for a user using the machine. The base structure can provide floor support for the machine. One or more resilient pedaling assemblies may be pivotably coupled with the base structure to guide the exercising movements of the user. Each resilient pedaling assembly may comprise an elastic element to provide torsion force, a foot pad for user foot resting and pivot assemblies rotatably engaged with the elastic element and the foot pad. Movement of the foot pad may cause deformation of the elastic element via the resilient pedaling assemblies. The deformation can induce the torsion force from the elastic element to provide reciprocal foot pedaling effects to the user.

The disclosure relates to a cable tensioning station for providing a defined resistance force for resistance training, including a weight (9), which is arranged movably above a pull element (7, 17) and on which the resistance force is at least dependent, the pull element (7, 17) being guided via at least one coupling roller (18), which is designed to transfer a linear motion of the pull element as a rotary motion to a generator (19) to generate electrical energy, characterised in that the coupling roller (18) is embodied as a freewheel with adjustable blocking effect.

A calf exerciser includes a free standing platform with independent foot braces that pivot and rotate for providing an optimally positioned foot and ankle position for a calf exercise. A handle and locking knob provide one-handed control. A pair of rotating platforms mount to a base, and each rotating platform has a pivot brace that angles left and right. Positioning and locking the foot braces at various positions of rotation and right/left angles provide a selectable, varied position as the calf exercises generally involve an ankle driven force against the foot braces, often bearing on the ball or arch of the foot. A beveled or curved edge with a grip surface further enhances contact with the user's foot.

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.