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.

According to an embodiment, a device for recognizing a free weight training motion comprises a depth camera obtaining image information for measuring a user's body information before exercise and obtaining image information including a unique identifier attached to a piece of exercise equipment and motion of each joint of the user and a variation in body surface due to a motion of the body of the user doing exercise using the piece of exercise equipment, a sensor unit measuring a state of the piece of exercise equipment and recognizing the user, and a controller controlling the depth camera and the sensor unit and processing various pieces of information obtained by the depth camera and the sensor unit.

Disclosed are computer-implemented techniques for providing immediate feedback to rowers for training and other activities to improve competitiveness of rowing crews. The techniques include a computing device receiving from a set of stroke unit devices, data that represent changes in acceleration of users' seats corresponding to users' strokes, receiving reference stroke data corresponding to a reference user's stroke, and generating from the received data from the set of stroke unit devices and the received reference strokes data, feedback data that correspond to relative stroke timing differences of each of the users, relative to the reference stroke, and transmitting the generated feedback data to user devices according to a feedback mechanism. Various feedback mechanisms are disclosed including visual, audio and tactical feedback mechanisms.

A system and method for tracking physical activity of a user performing exercise movements and providing feedback and recommendations relating to performing the exercise movements is disclosed. The method includes receiving a stream of sensor data in association with a user performing an exercise movement over a period of time, processing the stream of sensor data, detecting, using a first classifier on the processed stream of sensor data, one or more poses of the user performing the exercise movement, determining, using a second classifier on the one or more detected poses, a classification of the exercise movement and one or more repetitions of the exercise movement, determining, using a third classifier on the one or more detected poses and the one or more repetitions of the exercise movement, feedback including a score for the one or more repetitions, the score indicating an adherence to predefined conditions for correctly performing the exercise movement, and presenting the feedback in real-time in association with the user performing the exercise movement.

A sports training aid comprising a body unit, attachable to a person's body or the person's sports implement, is provided with a positioning sensor module; a feedback stimulator; and a processor. The sports training aid is configured to provide instantaneous feedback on motion faults of a studied sports motion, and the body unit is intended to be attached to a person's body (or a person's sports implement) at a representative location, the location being bound to travel a path representative of the studied sports motion, and the positioning sensor module comprises acceleration sensors and gyro sensors, and the processor is configured to determine a still position corresponding to an event wherein the body unit is determined to be still, to keep track of the sensor module's movements relative to the still position, and to activate the feedback stimulator in real time, upon detection of a sports motion fault.

The techniques described herein relate to methods, apparatus, and computer readable media configured to receive preference data indicative of a user's desired golf ball flight, capture and process time series data of the user while performing a golf swing to generate a time series array of positional values of aspects of the user and/or golf club, process the time series array using a machine learning model to determine data indicative of a predicted ball flight for the captured golf swing, generate data indicative of one or more modifications to the user's golf swing to achieve the desired ball flight instead of the predicted ball flight, generate data indicative of a recommended golf swing for the user to achieve the desired golf ball flight, and generate display data indicative of the recommended golf swing overlaid on second captured time series data of the user.

The learning apparatus includes a data generation unit configured to generate learning data based on rehabilitation data and a learning unit configured to perform machine learning using the learning data. A sensor is provided to detect a plurality of motion amounts in a walking motion of a trainee, and it is evaluated that, when one of the motion amounts matches one of abnormal walking criteria, that the walking motion is an abnormal walking pattern that meets the matched abnormal walking criterion. The data generation unit generates each of the pieces of rehabilitation data before and after a change in the results of evaluation of the abnormal walking pattern as learning data. The learning unit sequentially inputs each of the pieces of rehabilitation data as one data set, thereby performing machine learning.

A method trains a user in performing a motion for an activity. The method employs an AV-equipped portable computing device positioned so that its camera faces the target. The device's processor executes computer processes that include: receiving and processing an output from the camera to determine an initial position of the target; processing the camera's output to determine a series of coordinates corresponding to positions of the target, assumed after the initial position; processing the series of coordinates, against a set of fault rules, to determine presence of a fault in performing the motion, wherein the fault rules relate to the motion based on target position in a real, physical space; and if a fault is determined, causing notification of the user, so as to train the user to perform the activity in a manner free of the fault.

Disclosed herein are an apparatus and method for evaluating a physical activity ability. The apparatus includes one or more processors and executable memory for storing at least one program executed by the one or more processors. The at least one program recognizes the position of a human by analyzing an image input through a camera, identifies the motion of the human by analyzing the sequence of the image, and evaluates the physical activity ability of the human from the motion of the human based on the body segment of the human.

A monitoring system that includes a processor, one or more video cameras, a student monitor, and an instructor monitor. The processor can transmit and receive digital information to and from the video cameras and monitors. The student monitor and the instructor monitor are each also able to communicate digitally with the processor and may each play video as received from the processor. The processor may transmit either a live or recorded video signal to both the student monitor and the instructor monitor, such that the student monitor and the instructor monitor receive and play video simultaneously.