During a first time period and for a first user, a second user is automatically selected based on competitive data of the first user and competitive data of the second user, and a workout selection is sent to cause a video of a workout to be displayed during a second time period on a smart mirror of the first user and a smart mirror of the second user. During the second time period, a live stream of the first user exercising is displayed at the smart mirror of the second user, and a live stream of the second user exercising is received and displayed at the smart mirror of the first user. During the second time period, a performance score of the first user and a performance score of the second user is displayed at the smart mirrors of the first user and the second user.

An exercise machine monitoring and instruction system for the movement of an element of an exercise machine by an exerciser and providing automated feedback to the exerciser to help improve the exercise in real-time. The exercise machine monitoring and instruction system generally includes an exercise machine having a movable element that moves between a first position and a second position in a reciprocating manner, a sensor that detects a real-time position of the movable element, a processor in communication with the sensor to receive the real-time position data from the sensor related to a position of the movable element and a feedback device in communication with the processor that provides real-time instructions to the exerciser on how to adjust their workout to achieve a desired result.

A method includes capturing, using an Internet of Things (IoT) device, real-time video of a user performing an exercise associated with a first exercise class. Real-time video of the user is displayed, via a display, concurrently with video of an instructor, to provide a visual comparison of the user to the instructor. Image analysis of the real-time video of the user is performed to determine a performance of the user, and a representation thereof is displayed. Biometric data associated with the user is received at the IoT device from a wearable device at multiple points in time. Heart rates are identified based on the biometric data, and scores based on the heart rates are displayed via the display. A recommendation for a second exercise class different from the first exercise class is determined based on a profile of the user, and displayed via the display.

A combat training equipment relates to the technical field of combat training equipment. The existing combat training equipment is not equipped with active attack function, which is not conducive to the trainers to improve their combat level; the new combat training equipment drives the motor to cooperate with the angle box, angle motor, oscillating piece and hanging ball, so as to oscillate at a certain angle. Driven by the angle motor, the oscillating piece can simulate a human arm attacking in the upper, middle, and lower positions. With the help of hanging ball, the trainers can carry out body movement training to improve the reaction capability. The striking mechanism, lamps and speakers on the striking post enable trainers to evade attacks with good coordination. After the trainers make an effective attack, the speakers and lights will give positive feedback respectively, so that the trainers can gradually improve their own strength.

The present disclosure provides a method of providing customized training content and a user terminal for implementing the same for further increasing interest in exercise by providing training content in consideration of the physical ability and characteristics of a user and simultaneously allowing the user to easily know whether the user is exercising with a correct posture and method to continuously exercise at a pace suitable for a level of the user. The user terminal includes a display, a camera, and a controller configured to perform control to acquire information on a reference posture of a trainer appearing in an exercise content through artificial intelligence, to recognize an exercise posture of a user photographed through the camera through artificial intelligence while the exercise content is reproduced, and to adjust a reproduction speed of the exercise content based on the recognized exercise posture of the user.

An intelligent interactive real road simulation training device that simulates the real road grade and slope change while playing video based on the geographic location of the road from the pre-processed video and the speed of the user. With the video playing, the user sees the road moving as the user moves, and the speed of the road moving by is based upon the user's speed on the exercise training equipment. The user also feels the grade and slope change as the road grade and slope changes on the video. The invention can be integrated into any exercise training equipment such as a bicycle trainer or treadmill.

Evaluation value calculation unit calculates, based on time-series changes in exercise information on each of a plurality of users who have exercised in accordance with an exercise menu, an evaluation value of the exercise menu. Evaluation result generation unit compares an evaluation value of an exercise menu with a reference value. The evaluation result generation unit generates results of evaluating the exercise menu based on the results of comparing the evaluation value with the reference value.

A sport training method and system and a head-mounted VR device are disclosed. The method is performed by a head-mounted VR device. The head-mounted VR device is wirelessly connected to a hand-motion tracker and a foot-motion tracker. The method comprises: displaying a virtual demonstrative action; acquiring 6DOF head-motion data, 6DOF hand-motion data and 6DOF foot-motion data of the user; fusing the 6DOF hand-motion data and the 6DOF foot-motion data with the 6DOF head-motion data; calculating motion data of different parts of a human body according to the data that have been fused; and comparing the motion data of the different parts of the human body obtained by the calculation with standard sport training data of the virtual demonstrative action, and if a degree of similarity is greater than a threshold, determining that an action of a human-body part meets a training standard, and if not, displaying a corresponding prompting message in a virtual reality scene to prompt a human-body part whose action is not standard.

A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

An exemplary responsive training device for responding to user interaction with the device can be provided. For example, the responsive training device can be configured with a surface enclosing a compressible body. The responsive training device can further embed at least one sensor configured to sense a deformation of the compressible body and to generate a sensory output to a controller. The responsive training device can also embed a controller configured to control at least one transponder. Furthermore, the exemplary responsive training device can embed at least one transponder configured to provide an audio output and/or a visual output as a function of the sensor output.