Systems and methods are described for personalizing a fitness or workout plan based on an athletes past performance. In some aspects, performance metrics from at least two workout sessions performed by a user using exercise equipment, may be obtained, where each workout session includes a plurality of intervals corresponding to one of a number of different intensity levels. The performance metrics over a subset of the intervals may be compared with a prescribed performance of the corresponding interval to generate interval comparisons. Using the interval comparisons, at least one of a length or an intensity level of at least one interval of a future workout session may be modified.

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.

A basketball training apparatus and a method for improving basketball shot making are disclosed. The basketball training apparatus includes a horizontal bar column, one or more brackets and a processing system. The horizontal bar column is configured to be mounted on a vertical structure and includes a plurality of longitudinal members. The one or more brackets are configured to be mounted on the vertical structure for horizontally adjoining the plurality of longitudinal members of the horizontal bar column together. The horizontal bar column is mounted onto the vertical structure using one or more brackets such that an optimum angle trajectory is created for an apex shot. The processing system operates an interactive device connected with the horizontal bar column. The interactive device is configured to track shot data associated with one or more shots performed by a player practicing on the basketball training apparatus.

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.

This present invention relates to a baseball simulation game. The baseball simulation game comprises one or more bays, a microchipped baseball, and a field into which the baseball is hit by a user positioned in the bay. A plurality of targets and catchers, each comprising a sensor for detecting the baseball, are also positioned in the field in spaced apart fashion. The game assigns points to the player, wherein the amount of points assigned depends on what target or catcher is struck by the baseball. The baseball simulation game is capable of being enjoyed by multiple players simultaneously and can be enjoyed at any time of day and is not dependent on the weather.

The present invention relates to a method, system, and non-transitory computer-readable recording medium for supporting photographing of a golf swing. According to one aspect of the invention, there is provided a method for supporting photographing of a golf swing, the method comprising the steps of: (i) determining a user device matched with information on a user who is to perform a golf swing, among a plurality of user devices, with reference to a scenario associated with the golf swing; and (ii) causing a photographing module of the determined user device to photograph the golf swing of the user.

Systems and methods configured to process motion data associated with a user. The systems and methods are configured to receive motion data from a sensor, calculate motion attributes from the data, and classify the motion data using one or more mathematical models. Attributes may be calculated without classifying the motion data into an activity type (such as walking, running, swimming, or any specific or general activity). Attributes may be compared to activity models comprising motion data from several individuals, which may not include the user. Motion data within the models and attributes of the user may be independent of any activity type. Attributes may be compared to select an energy expenditure model from one or more energy expenditure models, which may be selected as a best-match to the one or more motion attributes. An energy expenditure associated with the motion of the user may then be calculated.

Systems and methods configured to process motion data associated with a user. The systems and methods are configured to receive motion data from a sensor, calculate motion attributes from the data, and classify the motion data using one or more mathematical models. Attributes may be calculated without classifying the motion data into an activity type (such as walking, running, swimming, or any specific or general activity). Attributes may be compared to activity models comprising motion data from several individuals, which may not include the user. Motion data within the models and attributes of the user may be independent of any activity type. Attributes may be compared to select an energy expenditure model from one or more energy expenditure models, which may be selected as a best-match to the one or more motion attributes. An energy expenditure associated with the motion of the user may then be calculated.

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.

An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.