A training system, kit, and method including a weighted wearable equipment, e.g. gloves, having a sensor (e.g. accelerometers, gyroscopes, photoelectric sensors, position sensors, tilt sensors, pressure sensors, temperature sensors, blood pressure sensors, heart rate monitors, and SpO2 sensors) and including a weight enhancement (e.g. weight bodies in closed pockets); a non-weighted wearable equipment of the same type as the weighted wearable equipment, the non-weighted wearable equipment having a sensor and. not including a weight enhancement; and a training application in functional communication with each of the weighted wearable equipment and the non-weighted wearable equipment and having a data processor that includes instructions for: analyzing data received from the sensor of each of the weighted wearable equipment and the non-weighted wearable equipment and generating predictive information derived from exercise training data from the sensors.

An American style football including an inflatable bladder, a cover surrounding the bladder, a battery carried by the football, and a light emitter. The light emitter is carried by the football and is electrically connected to the battery. At least a portion of the cover transmits light from the light emitter.

Systems, methods, and computer-readable mediums for operating an electromechanical device are disclosed. The system includes, in one example, the electromechanical device, a patient portal, and a computing device. The computing device is configured to receive user data relating to a user, and receive treatment data relating to treatment plans and outcomes. The computing device is also configured to generate a prehabilitation plan by using a machine learning model to process the user data and the treatment data. The computing device is further configured to select, for the electromechanical device, an electromechanical device configuration that enables exercises of the prehabilitation plan to be performed by the user such that performance improves an area of the user's body. The computing device is also configured to enable the electromechanical device to implement the electromechanical device configuration.

There is provided a health promotion system using a wireless and ropeless jump rope. When a plurality of users use a plurality of wireless and ropeless jump rope apparatuses, each wireless and ropeless jump rope apparatus transmits each user's weight, the number of jumps made by the user and the time of using the wireless and ropeless jump rope to an external health promotion server. The health promotion server analyzes the user's weight, the number of jumps made by the user and the time of using the wireless and ropeless jump rope as transmitted and provides an instructor with the information of the number of jumps made by the user and the analyzed health-relevant data. The instructor who receives the information of the number of jumps made by the user and the analyzed health-relevant data is able to improve the health of the user.

A golf ball with embedded electronics to allow proximity to be tracked and to monitor golfer performance is disclosed. The golf ball comprises a processor connected to an accelerometer, communications circuitry, a spin detector, and memory, wherein the processor stores accelerometer data from the accelerometer and rotation data regarding rotation of the spin detector in the memory. The processor converts the data regarding the rotation of the spin detector into a rotation speed and a rotation direction, said rotation speed determined by a frequency of the data, and said rotation direction determined by a magnitude of the data. The communications circuitry is configured to communicate the accelerometer data, the rotation direction, and the rotation speed to a central interrogator for analysis of a golfer's performance.

The present application is directed to a method for use in a system implementing a reference golf club, one or more sensors associated with the reference golf club, and a computing device. The method comprises receiving from the one or more sensors, by the computing device, swing data relating to a swing of the reference golf club, analyzing, by the computing device, the swing data to determine recommended shaft parameter values for each of a plurality of shaft parameters using an algorithm, accessing, by the computing device, a shaft database comprising actual shaft parameter values for each of the plurality of shaft parameters for each of a plurality of shafts, determining, by the computing device, at least one shaft from the plurality of shafts based, at least in part, on a comparison between the recommended shaft parameter values and the actual shaft parameter values, transmitting, by the computing device, information relating to the at least one shaft; and displaying, by the computing device, the information on a display of the computing device.

Disclosed is a technical training garment configured for use with modular, interchangeable biomechanics units and or resistance modules. The garment may provide resistance to movement throughout an angular range of motion and or tracks a variety of biomechanical parameters such as stride length, stride rate, angular velocity and power expended by the wearer. The garment may be low profile, and worn by a wearer as a primary garment or beneath or over conventional clothing or athletic uniform. The device may be worn as a supplemental training and or diagnostic tool during conventional training protocols, or as a biomechanics or biometric data capture device during competition.

An electronic device monitors accelerations using a motion sensor. The electronic device determines a current motion state based on the accelerations. The electronic device identifies a plurality of applications that subscribe to a motion state identification service and notifies a subset of the applications of the current motion state, the subset meeting notification criteria associated with the current motion state.

A device for upper-limb rehabilitation, which assists a user in exercising the arm for rehabilitation, has a connector, a placing unit movably connected to the connector, and a driving unit configured to move the connector, wherein when a user places the arm on the placing unit and moves the placing unit, the driving unit is operated to move the connector along the placing unit, so as to enlarge a work space in which the user is capable of moving the arm.

This disclosure relates to systems, media, and methods for quantifying and monitoring exercise parameters and/or motion parameters, including performing data acquisition, analysis, and providing scientifically valid, clinically relevant, and/or actionable diagnostic feedback. Disclosed embodiments may receive real-time sensor data from a motion sensor or sensors mounted on a user and/or equipment while a user performs a test motion. Disclosed embodiments may also calculate a test motion profile based on the real-time sensor data, the test motion profile describing a multi-dimensional representation of the test motion performed by the user or computed motion profiles. Disclosed embodiments may include comparing the test motion profile to a template motion profile to determine a deviation amount for the test motion profile indicating how the test motion deviated from the template motion profile. Still further embodiments may correlate test motion profiles over time with health indicators.