Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, an exercise program comprising a first user energy score, wherein the method comprises generating, by the artificial intelligence engine, the exercise program including an exercise plan including a plurality of exercises. Each respective exercise is associated with user energy consumption metrics based at least on a metabolic equivalent of task (MET) value, and based on the user energy consumption metrics, the first user energy score is associated with the exercise program. The method includes receiving data pertaining to a plurality of users. The data includes physical activity goals the plurality of users desires to achieve. The method includes determining second user energy scores for the physical activity goals, and based on the first and second user energy scores, assigning, by the artificial intelligence engine, at least a subset of the plurality of users to the exercise program.

The present invention relates to a safety system for treadmills. The safety system includes at least one load/weight sensor and a small switch disposed within the base of the treadmill. The system also includes a comparator for comparing the weight of a user standing on the treadmill, and an input weight of the user displayed on a dashboard of the treadmill. The safety system allows the treadmill to activate only when the weight of the user is equal or more than the selected weight on the dashboard. The system can be integrated into a treadmill during manufacturing or can be retrofitted to existing treadmills. The system also controls various variables such as speed, duration and inclination of the treadmill.

Fight training equipment includes a training equipment body; a liner fixed inside the training equipment body; at least one telescopic arm fixed in the liner through a first elastic member; a pop-up device or a winding device arranged in the liner, a pop-up channel matched with each arm in a one-to-one correspondence manner being arranged between the liner and the training equipment body so that the arm extends from the liner to the outside of the training equipment body through the pop-up channel under the action of the pop-up device and is withdrawn to the middle part of the liner through the pop-up channel under the action of the first elastic member, or the arm is withdrawn from the outside of the equipment body to the middle part of a liner body through the pop-up channel under the action of the winding device and extends to the outside of the equipment body through the pop-up channel under the action of the first elastic member; an arm control assembly arranged on the training equipment body; and a drive device connected with the pop-up device or the winding device, the arm control assembly being connected with the pop-up device or the winding device through the drive device.

Embodiments provide functionality for determining fitness level of an individual using a fitness testing unit. In one such embodiment, an individual is instructed, via a graphical user interface (GUI) of a fitness testing unit, to perform a series of exercise activities. In turn, via the fitness testing unit, baseline heart rate, maximum heart rate, and recovery heart rate are captured while the individual is performing the series of exercise activities. Then, a fitness level of the individual is determined using an age of the individual and the captured baseline heart rate, maximum heart rate, and recovery heart rate.

A computer-implemented method includes running a training program for a user wearing a virtual reality (VR) headset; and, while running the training program: monitoring activity of the user; presenting video images in a display of the VR headset corresponding to the activity of the user; and based on said monitoring, modifying at least one aspect of said training program.

A walking training system includes a treadmill, a center-of-gravity position detection unit that detects a center-of-gravity position of a trainee from a load received from a sole of the trainee on a belt of the treadmill, a posture detection unit that detects a posture of the trainee, a center-of-gravity position estimation unit that estimates the center-of-gravity position of the trainee from the detected posture of the trainee, a determination unit that determines whether a difference between the detected center-of-gravity position and the estimated center-of-gravity position exceeds a predetermined value, and a notification unit that sends, when the determination unit determines that the difference exceeds the predetermined value, a notification notifying that whether the difference exceeds the predetermined value.

An intelligent system that automatically adjusting optimal rehabilitation intensity or exercise volume with personalized exercise prescription, comprising: upload the physiological information data measured by registered members to a cloud data integration server through the Internet; an expert diagnostic unit, which can download and use the member's physiological information data from the cloud data integration server. After the diagnosis, a personalized exercise prescription is issued and uploaded to the cloud data integration server; a rehabilitation fitness equipment unit can download the exercise prescription from the cloud data integration server to control and automatically adjust the optimal rehabilitation intensity or exercise volume; after being diagnosed by experts such as doctors, rehabilitators or fitness coaches, the optimal parameter values of a continuously updated artificial intelligence exercise prescription can be used to improve the efficacy of personal rehabilitation or exercise fitness.

In an information processing device, at least one processor is configured to derive, based on a first model generated with as an input a first indicator expressing first exercise information of a subject acquired in a first period, and as an output a second indicator expressing second exercise information, first estimation data expressing the second indicator relative to first indicator specified in the first period, the second exercise information being different than the first exercise information of the subject, the second indicator having correlation with the first indicator; derive, based on a second model generated with as an input the first indicator acquired in the second period, and as an output the second indicator, second estimation data expressing the second indicator relative to the first indicator specified in the second period; and present the first estimation data and the second estimation data in a mutually comparable manner on a presenter.

An exercise system includes a workout server. An active workout session is created for a user on the workout server. An exercise information is collected for a user at a first exercise device and a second exercise device. The exercise information is tracked to the active workout session and maintained on the workout server. This allows a user to maintain a workout session across multiple devices.

A system for a quantitative detection of a movement. The system includes a signal emitter and two signal receivers, positioned in series, along a first axis parallel to a second axis of movement of a reflective marker provided on a moving object. The reflective marker is configured to reflect a signal emitted by the signal emitter towards the two signal receivers. The two receivers have a signal reception coverage such that allows existence of a reflective marker position, on the second axis, in which the reflective marker of a given size is recognized simultaneously by the two signal receivers.