A force measurement system and a motion base used therein is disclosed herein. The force measurement system includes a force measurement assembly configured to receive a subject, a motion base for displacing the force measurement assembly, and one or more data processing devices operatively coupled to the force measurement assembly and an actuation system of the motion base. The motion base includes a support structure; a displaceable carriage coupled to the force measurement assembly; and an actuation system, the actuation system including one or more actuators operatively coupling the displaceable carriage to the support structure, the one or more actuators configured to displace the displaceable carriage with the force measurement assembly relative to the support structure, the displaceable carriage being suspended below a portion of the support structure.

The present invention can accurately (precisely) measure the quantity of exercise of a bicycle rider, by comprising: a case which can rotate about a spindle; a top plate which is connected to the case by a pivot shaft and can rotate about the pivot shaft; a displacement generating assembly which is disposed in the case and is connected to the case and the top plate so as to generate displacement according to the rotation of the top plate; and a sensing unit which is connected to the displacement generating assembly so as to sense the displacement.

An Internet of Thing (IoT) device includes a camera coupled to a processor; and a wireless transceiver coupled to the processor. Blockchain smart contracts can be used with the device to facilitate secure operation.

An exercise equipment system with a movable support that is movable in a lateral direction, a sensor adapted to generate a lateral tilt signal, and a processor for generating a left or right turn output signal to a ride simulation in response to tilting of the exercise equipment during use. The exercise equipment may be a cycle mounted to a base. The processor may further filter out small magnitude sensor signals generated through left or right tilting that occurs during cycling, which are not indicative of a turn. The system may also include a display for visualizing a ride simulation of one or more network connected cycle avatars that are individually controlled with a lean-to-steer system.

A timing device is provided herein. The timing device includes a housing defining an aperture in a surface thereof. An elongated member is extendable from the housing. A wheel is attached to an interior surface of the housing. An encoder is operably coupled to the wheel and is configured to calculate a rotational velocity of the wheel. A controller is configured to calculate a linear velocity of the elongated member based on the rotational velocity of the wheel.

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 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 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.

An automatic ball launcher includes a ball feed control system that includes a meter wheel with radially-spaced ribs or grooves to selectively block and pass balls to the flywheels of the launcher. The meter wheel rotates to selectively block and release a single ball to pass at a time. The controller of the launcher can be programmed to stop the meter wheel when a ball has been metered by monitoring the current at peak of the motor driving the meter wheel. A meter-event can be determined to have occurred when the current of the drive motor drops to a trough by a pre-set magnitude following a rise to a peak value. A remote control can be provided for the user to operate the launching machine and adjust a plurality of parameters.

In some aspects, the disclosure is directed to methods and systems for body tracking systems and augmented reality interfaces. These systems provide an augmented reality application that enables a user to accurately perform physical therapy or training exercises at home and enable real time monitoring and communication between the user and a remote physician or trainer. Using motion tracking capabilities of depth cameras and/or multiple camera setups, the system can create a real time three dimensional model that mirrors or guides the patient's movements and can show the patient how to properly perform an exercise with dynamic interactive feedback. The tracking capabilities further provide physicians with detailed measurements as well as tracking improvements or degradations over time, and guide positions may be adjusted to provide further instruction or training as necessary.