A measurement system includes a motion capture system comprising at least one motion capture device configured to detect the motion of one or more body portions of a system user and generate output data; a sensory output device, the sensory output device configured to generate sensory feedback for delivery to the system user; and at least one data processing device operatively coupled to the motion capture system and the sensory output device, the at least one data processing device further configured to determine, by utilizing a trained neural network, one or more poses and/or movements of the one or more body portions of the system user from the motion capture output data, and to provide sensory feedback to the system user, by means of the sensory output device, as to conformity of the one or more poses and/or movements to one or more reference poses and/or movements.

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 recommendation method based on an exercise status of a user includes an electronic device obtaining first exercise data of a user after running an exercise application. The first exercise data is used to reflect a type of exercise that is being performed by the user. The method further includes the electronic device determining a first exercise scenario corresponding to the first exercise data. The method further includes the electronic device obtaining first recommended content corresponding to the first exercise scenario. The method further includes the electronic device displaying the first recommended content in a display interface of the exercise application, or the electronic device playing the first recommended content when running the exercise application.

Systems and methods for evaluating the efficacy of entertaining elements during physical and cognitive therapeutic sessions are disclosed. The system is comprised of a means for providing visual and auditory information, and prompting a patient to perform physical and cognitive tasks of varying difficulty. The system is further comprised of a means of tracking the patient's movements to provide feedback to the patient and assess the performance of the patient's movements. Prompted movements are designed to provide therapeutic mental, behavioral, and physical health benefits to the patient, and may increase or decrease in difficulty based on prior assessments of a patient's movements. Entertaining elements are introduced in the visual and auditory information and assessed for their impact on the patient's performance of the movements.

An athletic training system (200) has a data recording system (202) and a data engine (204). The data recording system (202) is configured to record an athletic competition event. The event may have a first team of players competing against a second team of players. The data engine (204) is configured to receive data associated with the recorded athletic competition event. The data engine (204) processes the data and displays the data as a replay of the event in animated form.

A training determination device includes: a determination unit configured to determine a training type, based on exercise data obtained when a user has performed a running training; a storage unit configured to store training history information in which the training type determined by the determination unit is associated with time information for performed training and a moving distance during the performed training; a calculation unit configured to perform at least two types of different calculation for a cumulative total of the moving distance for each training type, based on the training history information stored in the storage unit; and a display controller configured to display an image indicating the cumulative total of the moving distance for each training type calculated by the calculation unit.

The present disclosure relates to systems and methods for balance index determination. For example, a wearable apparatus may have at least one gyroscope configured to measure angular velocity about a first axis; at least one inertial measurement device (IMU) configured to measure deviation along a second axis and a third axis; at least one memory storing instructions; and at least one processor configured to execute the instructions to: receive angular velocity measurements over a period of time from the at least one gyroscope; receive deviations from the second axis and from the third axis over the period of time from the at least one IMU; weight the deviations based on directions associated with the deviations; and generate a composite balance index based on the angular velocity measurements, the weighted deviations from the second axis, and the weighted deviations from the third axis.

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.

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.

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.