An embodiment of the present invention provides a moving bike device including: a memory configured to store distance information and altitude information; a content implementation unit configured to adjust a reproduction state of content in response to a speed of a wheel depending on pedaling of a user; a controller configured to calculate a road slope from the distance information and the altitude information, and to calculate a travel distance depending on the pedaling of the user; and a road slope implementation unit configured to adjust strength of a brake in proportion to the road slope corresponding to the travel distance.

An electronic device and method for data-driven assistance for users involved in physical activities is provided. The electronic device receives first sensor data associated with a movement pattern of one or more parts of a body of a user and receives first information associated with a location where the user performs the physical activity. The electronic device determines one or more first indicators which are likely to have affected the user or the performance of the user in the physical activity. Thereafter, the electronic device generates presentation data based on an application of a first machine learning model on the determined one or more first indicators and the received first information. The generated presentation data includes one or more improvement suggestions for the user in relation to the physical activity. The electronic device controls a display device to display the presentation data.

Disclosed are an electronic device for generating workout types and a method of operating the electronic device. According to an embodiment, an electronic device includes: a memory and at least one processor connected to the memory, wherein the at least one processor is configured to: acquire a workout type name in response to a request for adding a workout type, recommend at least one data type based on the workout type name, generate a new workout type corresponding to the workout type name based on a data type selected from among the at least one recommended data type, and acquire workout measurement information corresponding to the selected data type in response to execution of the new workout type.

A system and method for targeted neurological treatment using brainwave entrainment therapy with passive treatment that allows for targeted treatment of particular areas of the brain, particular neurological functions, particular neurological states, and combinations of areas, functions, and states. The system and method receive gait parameters for an individual and compare those against a database of historical gait data to determine if an onset neurodegenerative condition is present, and applies a brainwave entrainment therapy responsive to the determination of the condition. The system and method receive a neurological assessment identifying areas of the brain or neurological functions to be treated, select one or more treatment modalities and frequencies, select a treatment regimen, and apply brainwave entrainment using a treatment regimen while the subject engages in dual-task activities selected to stimulate the areas of the brain, neurological functions, or neurological states to be treated, enhanced, or altered.

Computing device enhanced training environment system comprising a computing device, I/O subsystem for permitting a user to enter at least one attribute of the training or of the trainee, a plurality of sensors for generating sensory information, a training environment in which a training activity takes place, a database containing training related information. The computing device enhanced training environment system configured for at least one of the following: design a training program for a plurality of users, monitor training program performance, monitor training performance, instruct a user about the training, determine and/or set difficulty level in training apparatus.

Systems and methods for adjusting resistance on an exercise cycle having a frame and a flywheel include calibration, homing and auto-follow routines. A resistance apparatus comprising an actuator is configured to selectively position the resistance apparatus relative to the flywheel, wherein a distance between the resistance apparatus to the flywheel corresponds to resistance applied to the flywheel. Control components are configured to control operation of the resistance system in response to instructions, and a computing device is configured to output media for an exercise class to a user, the exercise class comprising one or more target resistance ranges corresponding to a segment of the exercise class. The computing device is further configured to selectively implement auto-follow logic configured to determine a target resistance value for a current segment of the exercise class and instruct the control components to adjust the resistance system to the target resistance value.

The information generation device stores a model that is generated based on a user information relating to a user, a motion information relating to a motion of each part of a body of the user, and an evaluation report including a comment and an exercise program created by a specialist. The information generation device creates an exercise program for each part of one user, from the user information of the one user and the motion information of each part of the body of the one user based on the model, and also creates a comment indicating a basis of creating the exercise program for each part for the one user. Then, the information generation device presents an evaluation report including the exercise program for each part and the comment indicating the basis.

A platform models and correlates physical activities based on users' interactions with a simple grip-metaphor design, enabling multi-dimensions actionable information to improve the health, performance and well-being of connected grip users within like-minded communities. For example, the platform captures multi-dimensional datasets generated from activities of each of a plurality of users on the online human internet of thing platform, where the activities include physical interactions with connected grips systems connected to the online human internet of thing platform. The platform then filters the captured multi-dimensional datasets into a plurality of categories and scores the filtered multi-dimensional data by the human internet of thing platform. Finally, the platform generates a multi-dimensional information modeling for each user based on the scored multi-dimensional data.

Various embodiments of the present disclosure provide a method and an apparatus for providing personal coach for user's exercise in an electronic device. According to various embodiments of the present disclosure, an electronic device may include sensor circuitry and a processor, wherein the processor may be configured to determine at least one activity information which satisfies a designated condition among one or more activity information previously obtained in relation to a user motion, to determine a first exercise intensity for the user, based at least on variation of the at least one activity information over time, to determine a second exercise intensity by adjusting the first exercise intensity, based at least on a previous target of exercise of the user, and to provide guide information associated with the second exercise intensity. Various embodiments are feasible.