Disclosed herein are examples of user-paced exercise equipment, as well as related circuitry, methods, and computer-readable media. For example, disclosed herein is a user-paced treadmill, including a belt, a motor coupled to the belt, and control circuitry communicatively coupled to the motor. The control circuitry may be configured to change a velocity of the belt based at least in part on a body velocity and a leg swing velocity of a user of the user-paced treadmill.

A motorized treadmill includes a base, an endless belt movable relative to the base for allowing a user to exercise thereon, a motor coupled to the endless belt for driving the endless belt to rotate, a current sensor coupled to the motor, and a controller in communication with the motor and the current sensor. The current sensor is configured to detect a motor current of the motor when using the motorized treadmill. The controller is configured to analyze fluctuations of the motor current to determine whether objects or children interfere with rotation of the endless belt. When the current sensor detects a current change not associated with the user of the motorized treadmill, the controller determines that the endless belt is interfered by objects or children and stops operation of the motor to slow or stop rotation of the endless belt.

Among other things, a processor executes instructions to: update, in real time during a current instance of an exercise activity by a subject competitor, a graphical user interface displayed on a display device, the display device being included in a first exercise machine operated by the subject competitor or included in a mobile electronic device. The graphical user interface includes: a ranking of the subject competitor and a second competitor based on (i) a projected performance metric of the subject competitor over a predefined scope of the exercise activity compared to (ii) a historical performance metric of the second competitor over the predefined scope of the exercise activity in a previous instance of the exercise activity, an illustration of a margin between the historical performance metric of the second competitor and the projected performance metric for the subject competitor, and an illustration of the projected performance metric.

A motorized treadmill provided for allowing a user to perform a programed workout. The motorized treadmill includes a base, an endless belt movable relative to the base for allowing a user to exercise thereon, a motor coupled to the endless belt for driving the endless belt to rotate, a signal receiver, and a controller in communication with the motor and the signal receiver. The signal receiver is configured to receive a weight training signal when the user performs the programed workout with free weight equipment. The controller is configured to transmit validated exercise use data when the user is engaging the endless belt. When the signal receiver receives the weight training signal from the free weight equipment, the controller will determine that the user is not engaging the endless belt and stops transmitting the validated exercise use data.

A method and system using sensors and a deep neural network to control a treadmill based on user movement on the treadmill. Training data is collected to improve performance in a variety of typical as well as atypical treadmill activities to provide data with which to train a neural network for the task of controlling the treadmill. The method and system includes one or more sensors that obtain user movement and position data while the user is on the treadmill. A command unit (CU) stores the pre-trained neural network and receives the user movement and position data obtained by the one or more sensors. The CU determines the motion commands to provide to the treadmill based on the real-time data received from the sensor(s) and processed through the pre-trained neural network. A motion control processor (MCP) that controls power the treadmill motors receives the command data sent from the CU and controls the functions of the treadmill based on the motion command data which correlates to the inferred user movement.

A kinesitherapy apparatus includes a measuring instrument, a pedaled rotational mechanism, a rotating electrical machine configured to apply an assist load, which is a regenerative load or a power running load, to the pedaled rotational mechanism, and a motion control device. The motion control device performs power running operation of the rotating electrical machine so that a minus assist load is generated in a warm-up period. In a ramp loading period following the warm-up period, the motion control device raises the assist load from the minus assist load, and calculates an anaerobic threshold based on time-series data of oxygen uptake and carbon dioxide emission that are obtained via the measuring instrument.

An exercise machine includes a processor, a display, a deck, and a belt rotatable about the deck. The machine also includes a sensor operably connected to the processor and configured to detect a performance parameter associated with a belt of the exercise machine. In implementations described herein, the performance parameter may be disregarded when it is determined that a user is not on the belt.

Disclosed herein are examples of user-paced exercise equipment, as well as related circuitry, methods, and computer-readable media. For example, disclosed herein is a user-paced treadmill, including a belt, a motor coupled to the belt, and control circuitry communicatively coupled to the motor. The control circuitry may be configured to change a velocity of the belt based at least in part on a body velocity and a leg swing velocity of a user of the user-paced treadmill.

Among other things, a processor executes instructions to (a) during a current instance of an exercise activity having a predefined scope and being performed by a subject competitor on a machine, compute a first performance metric for the subject competitor using performance data from the subject competitor's performance of a lesser scope than the predefined scope of the current instance of the exercise activity, the first performance metric being normalized to reflect a hypothetical performance over the predefined scope, (b) receive performance data representing an historical performance during a previous instance of the exercise activity by at least one other competitor on a machine, and (c) present to the subject competitor comparative data based on the first performance metric and on a second performance metric for the historical performance by at least one other competitor that is based on the received performance data and that reflects performance of the at least one other competitor of a scope of the previous instance that is substantially the same as the predefined scope.