In some aspects, the disclosure is directed to methods and systems for body tracking systems and augmented reality interfaces. These systems provide an augmented reality application that enables a user to accurately perform physical therapy or training exercises at home and enable real time monitoring and communication between the user and a remote physician or trainer. Using motion tracking capabilities of depth cameras and/or multiple camera setups, the system can create a real time three dimensional model that mirrors or guides the patient's movements and can show the patient how to properly perform an exercise with dynamic interactive feedback. The tracking capabilities further provide physicians with detailed measurements as well as tracking improvements or degradations over time, and guide positions may be adjusted to provide further instruction or training as necessary.

A system includes wearable devices positioned on a subject in different locations. Each wearable device includes motion sensors that measure the subject's movement in three dimensions. The motion sensors generate raw sensory data as the subject performs a physical movement. A data filter is selected based on a condition of the subject and a designated movement corresponding to the physical movement, and used to convert the raw sensory data into formatted data. A level of compliance of the physical movement with a movement model for the designated movement is determined by applying comparative modeling techniques to the formatted data and the movement model. Real-time feedback is delivered dynamically to the subject by the wearable devices during the performance of the physical movement based on the level of compliance. The movement model can be generated, and the comparative modeling techniques can be selected, based on the condition of the subject.

Systems and methods for motion capture and analysis are described. The system may include a motion sensor unit configured to capture data associated with movement of an object. The motion sensor unit is configured to be directly or indirectly coupled to the movement object at a first location. The system also includes a processor to process the captured data to determine one or more values and to translate the data and/or values to correspond to a second location on the movement object located away from the first location. The data and/or values, including translated data and/or values, may be transmitted by wireless transmitter and displayed by a display unit.

The system automatically or partly automatically coaches and assesses a non-putting golf swing to increase the strength or distance of the swing. Increases are coached in the components of energy generated across specific individual joints of the player's body during the downswing. Increases are also coached in the efficiency at which the generated energy is transmitted to the clubhead. Fast or near-instantaneous feedback is provided to the player, based on measured changes in the components of energy generated in the specific individual joints and on the efficiency at which the generated energy is transmitted to the clubhead. Changes in 3D positions of the player's body segments or joints are tracked by inertial sensors or optical sensors and used in the calculation of the components of energy generated across the specific individual joints utilising an artificial intelligence system.

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 athletic training system has a data recording system and a data engine. The data recording system 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 is configured to receive data associated with the recorded athletic competition event. The data engine processes the data and displays the data as a replay of the event in animated form.

Disclosed herein is a system for testing motor skills involved in locomotor, non-locomotor, and manipulative activities. The system utilizes joint data created by a motion sensor during a subject's performance of an activity to determine the subject's motor skill proficiency for that activity. The system compares the subject's joint data to benchmark data to detect one or more phases of the activity. Based on the comparison, the system also determines the subject's proficiency in the particular motor skill tested. The system is embodied in a computer-implemented application that provides various user interfaces for navigating through the user interfaces, accessing a database of the system, testing a subject's motor skills, analyzing a subject's proficiency, and facilitating practice of motor skills.

A system includes wearable devices positioned on a subject in different locations. Each wearable device includes motion sensors that measure the subject's movement in three dimensions. The motion sensors generate raw sensory data as the subject performs a physical movement. A data filter is selected based on a condition of the subject and a designated movement corresponding to the physical movement, and used to convert the raw sensory data into formatted data. A level of compliance of the physical movement with a movement model for the designated movement is determined by applying comparative modeling techniques to the formatted data and the movement model. Real-time feedback is delivered dynamically to the subject by the wearable devices during the performance of the physical movement based on the level of compliance. The movement model can be generated, and the comparative modeling techniques can be selected, based on the condition of the subject.

A training method on a strength exercise machine is usable by a user to perform a strength exercise, as a series of repetitions, for training the power generable by the user in at least one first workload regimen. In case a determined or detected power peak value is either higher than or equal to a stored maximum-power reference value, the steps of updating the stored target power value as a function of the generated power peak value determined or detected, updating the stored maximum-power reference value to the determined or detected power peak value, and resetting a counter variable value are performed. In case the determined or detected power peak value is lower than the stored reference maximum power value, a step of incrementing the stored counter variable value is performed. The method is performed for each further repetition of the first workout series.

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.