This invention relates to a load sensor device system, and more particularly to a load sensor device system for measuring physical exercise strength and effort, that provides load measurements for effort load deployed while a person performs physical fitness exercises using extensible functional resistance exercise apparatus and provides real time load data that can be tracked to demonstrate effectiveness of exercise training over a period of time using the sensor device and system.

An information recording apparatus includes a processor. The processor obtains index information representing a lapse situation after a start of movement. The processor obtains either of a time elapsed from the start of movement and a distance passing from a start point of movement. The processor controls, by using either of the elapsed time and the passing distance, to obtain the index information to, as either of a lapse of time from the start of movement and the distance passing from the start point of movement increases, decrease a frequency of obtainment of the index information at the start of movement or from the start point of movement. The processor records the obtained index information.

A system and method for implementing a virtual fitness application are disclosed. Embodiments may be built for various platforms, including web browsers and mobile phones. One embodiment uses pose estimation to count the repetitive motions of a fitness activity (e.g., running). In one embodiment, to count the repetitive motions, a repetitive motion counting process is used that is based on computing differences of Y-coordinates of key points of the user. The repetitive motion counting process includes selecting a proper pose of the user; computing one or more delta values (corresponding to Y-coordinate changes of the key points); and counting a given user movement as a repetitive motion based on a function (e.g., average) of the delta values. One embodiment uses the pose estimation and repetitive motion count results to provide a gamified experience, for example, a leaderboard, a stats report, instant visual feedback, badges, coins, and a social experience.

A training system operates to provide an online training system that includes an instructional portion, a performance portion and a results report. A trainer can create training modules and/or training programs and then launch a training program in which one or more users, utilizing a user system, can participate. A training program consists of one or more training modules. Each training module is configured to first run in a demonstration mode, in which the operator streams a demonstration of the physical activity required by the training module to one or more user systems. Users can thus view the demonstration of the physical activity on the user systems. The training module then enters a trial or trial mode in which each of the participants then engage in performing the physical activity. The user systems present a video/graphical display to show various performance criteria of the training module. The user systems also include a camera that is configured to monitor the activity of the user weighed against the performance criteria. Once the trial mode is completed, the data gathered by the user system cameras is then analyzed and evaluated and presented back to the participants.

Disclosed are techniques for leveraging machine learning to generate posture adjustment values for specific body postures of a player to improve loop drive techniques, such as in table tennis. Video clips of a player hitting a ball with a loop drive technique are analyzed to determine values for specific body postures and qualities of the ball after being hit. A machine learning model is generated to analyze relationships between body posture values and ball qualities. Upon receiving a video clip of a live session of a player hitting a ball using a loop drive technique, the machine learning model is used to generate adjustment values for body postures of the player to impart improved loop drive qualities to the ball, such as faster topspin.

A non-limiting example training instrument comprises a hollow main body formed of an aluminum alloy. The main body is constituted by two gripping portions opposite to each other with a space therebetween and a coupling portion coupling the two gripping portions. A load sensor is arranged in the coupling portion inside the main body. The load sensor is a load cell, a strain gauge affixed to an interior of the main body, and a part of the main body to which the strain gauge is affixed functions as a strain body. Therefore, if a user applies a force so as to bring the two gripping portions close to each other or a force so as to move the two gripping portions away from each other, a load thereof is detected by the load sensor.

A method includes causing display, during a first time period and via a first set of multiple smart mirrors, of live video depicting at least one user associated with the first set of multiple smart mirrors, without displaying a workout video. The method also includes causing display, during a second time period following and mutually exclusive of the first time period, and via a second set of multiple smart mirrors, of a workout video and a representation of at least one user associated with the second set of smart mirrors. The method also includes causing display, during a third time period following and mutually exclusive of the second time period, and via a third set of multiple smart mirrors, of live video depicting at least one user associated with the third set of multiple smart mirrors.

The exercise management system includes a storage device for storing user personal information; a processor including hardware for determining a resistance exercise content and an aerobic exercise content based on the user personal information; and a communication interface for acquiring motion information indicating motion of the user when exercise instructions are given based on the resistance exercise content, and vital information indicating vitals of the user when the exercise instructions are given based on the aerobic exercise content. Based on the motion information and the vital information, the processor performs a process of presenting performance result information of resistance exercise and aerobic exercise performed by the user on a user terminal device, or another terminal device.

A method, an electronic apparatus and a recording medium for automatically configuring a plurality of sensing devices, applicable to an electronic apparatus having at least one sensor and a communication device, is provided. In the method, a first sensing data is detected by using the at least one sensor. A plurality of second sensing data is respectively received from the plurality of sensing devices by using the communication device. The first sensing data and each of the second sensing data are analyzed to obtain a moving pattern of the electronic apparatus and each of the sensing devices. A position on a user's body of each of the sensing devices is configured by comparing the moving patterns with at least one movement model.

Systems and methods are disclosed for generating a 3D avatar using a biomechanical analysis of observed actions with a focus on representing actions through computer-generated 3D avatars. Physical quantities of biomechanical actions can be measured from the observations, and the system can analyze these values, compare them to target or optimal values, and use the observations and known biomechanical capabilities to generate 3D avatars.