Described herein are to frameworks and methodologies configured to enable real-time adaptive delivery of skills training data based on monitoring of user performance data. Embodiments of the invention have been particularly to enable real-time control over a performance instruction user interface (for example in terms of rate), and/or control over delivery of media data (for example in terms of rate and/or pan/zoom position).

An exercise management device using a hula hoop having a device for measuring spinning direction and exercise amount includes: an annular body part; a sensor unit including a gyro sensor, an acceleration sensor, and a gravity sensor; a hula hoop including a control unit including a MICOM for receiving and analyzing a data value detected by the sensor unit to calculate and obtain exercise information, a communication unit having a Bluetooth chip for transmitting the exercise information or the data value, and a power unit for switching on/off the control unit; and a wireless communication device having a dedicated program for receiving the exercise information or the data value transmitted from the communication unit and displaying the exercise information.

The present disclosure relates to systems and methods for elastic delivery, processing, and storage for wearable devices based on system resources. For example, a wearable apparatus may have at least one battery; at least one sensor configured to measure at least one property associated with a user of the wearable apparatus; at least one memory storing measurements from the at least one sensor and instructions; at least one transmitter configured to send data to a device remote from the wearable apparatus; and at least one processor configured to execute the instructions to: receive, from the at least one battery, an indicator of a charge; and based on the received indicator, sending a command to the at least one sensor to operate in a low-power mode or a high-power mode, the low-power mode having. a lower sampling rate than the high-power mode.

A Kinect-based auxiliary training system for basic badminton movements, includes a data collection module, a movement feature extraction and recognition module, and a movement standard degree analysis and guidance module. The data collection module is provided with a Kinect v2 somatosensory device for monitoring athletes in real time, and collecting 3D coordinate data of 25 joint points of athletes' whole body. The movement feature extraction and recognition module is provided for establishing a standard template, and obtaining a similarity between the movement data and the standard template. The movement standard degree analysis and guidance module is provided for determining a category of the current movement of the user to be tested according to the similarity, and further analyzing whether the current movement of the user to be tested meets a standard according to a threshold range of the bone included angle set by a technology evaluation rule.

A method for generating feedback to a user practicing a skill comprises: providing a local platform for acquiring physical parameter data pertaining to motion and position of the user and motion and position of a golf club and a golf ball struck by the golf club during a golf swing by the user; transmitting via a network at least a portion of the physical parameter data of the motion and position of the golf club and the golf ball struck by the golf club during the golf swing and the physical parameter data associated with the motion and position of the user during the golf swing from the local platform to a machine learning analysis engine as input information; entering the input information into a machine learning model, the machine learning model having a set of rules and statistical techniques to learn patterns from the input data, and a model which is trained by using evolving training sets, wherein an initial training sets is formed from selected professional golf players physical and swing characteristics and are classified and used to train the machine learning model and resulting learned weighting factors are feedback and used to refine a model prediction, the machine learning model determining a user's skill deficiencies and providing correction suggestions; and providing a correction suggestion to the user.

The invention discloses a computer automatic golf swinging form training method, which uses a computer to automatic analyzing a golf swinging form of a golf trainee, comprising: (A) a step of capturing a golf trainee video using an electrical motion capture sensor and/or an optical image capture sensor to capture a golf trainee dynamic swinging form video; (B) a step of retrieving golf trainee form frame; (C) a step of retrieving reference golfer form frame using a processor to automatically retrieve, from the memory, a reference golfer form frame; and (D) a step of automatic comparing frame and providing comparing result automatically comparing the golf trainee form frame and the reference golfer form frame.

A system, method, and device are disclosed for creating a simulation that seamlessly switches or dissolves between see through Augmented Reality (AR) and Virtual Reality (VR) thereby creating a mixed reality environment. The mixed reality environment switching or dissolving between AR and VR (or vice-versa) automatically based on predefined rules. The system, method, and device enabling the use of existing real world devices (e.g., sports equipment) displaying the real world devices in both AR and VR modes.

A system and method for analyzing and improving the performance of a body motion of an animal or human subject requires instrumenting a subject with inertial sensors, monitoring a body motion of interest, converting sensor data into motion data and animation, comparing the motion data with existing data for motion related performance parameters, providing a real-time, information rich, animation and data display of the results in color coded displays; and based on the results prescribing a training regime with exercises selected from a library of standardized exercises using standardized tools and training aids.

A training aid stimulator for providing fast perceptive feedback is disclosed. The training aid stimulator includes a first skin electrode and a second skin electrode both for making electrical contact to the body of a user, a charging module, a discharge module connected to one or more of the skin electrodes for a feedback discharging, and a processor for controlling the charging of a capacitor equivalent to a predetermined first voltage level, wherein the processor further being connected to the discharge module for controlling a feedback discharge of the capacitor equivalent. The stimulator comprises a voltage measurement module for measuring the level of charge of the capacitor equivalent, and the processor is configured for keeping the stimulator ready to discharge by repeatedly measuring the level of charge and by providing a maintenance charging when the voltage over said capacitance equivalent is at or below a predetermined second voltage level.

A method includes receiving motion data of a user in an environment with respect to a plurality of instances of a first action by the user, determining a kinematic movement based on receiving the motion data, analyzing the kinematic movement using a neural network, obtaining a plurality of outcome types with respect to the first action of the user, correlating the kinematic movement with the at least one indication of the outcome type with respect to the first action, classifying an outcome of the first action as at least one of the plurality of outcome types, determining which of the kinematic movements of the user result in the at least one of the plurality of outcome types, and providing instructions to the user to alter the determined kinematic movements of the user that result in the at least one of the plurality of outcome types.