A fatigue relief method using smart footwear and an operation method for a user terminal are provided. The fatigue relief method using smart footwear comprises: receiving the provision of pressure data or acceleration data measured while a user wears smart footwear and performs an exercise, wherein the smart footwear has at least one pressure sensor or acceleration sensor and a tactile element, which are installed therein; estimating the fatigue of the user by using the provided pressured data or acceleration data; selecting one of a plurality of vibration solutions on the basis of the estimated fatigue; and allowing the tactile element of the smart footwear to vibrate according to the selected vibration solution.

A fatigue measurement method includes obtaining a face video of a target object, processing the facial video to obtain a plurality of quasi-heart rates and a plurality of quasi-vibration frequencies, selecting a target heart rate from the plurality of quasi-heart rates and a target vibration frequency from the plurality of quasi-vibration frequencies, detecting the target heart rate and the target vibration frequency, and determining, according to the detection result, that the target object is in a fatigue state. The quasi-heart is obtained through one or more of a region of interest (ROI) between eyebrows and an ROI of chin, and the quasi-vibration frequency obtained through one or more of an ROI of eyes and an ROI of mouth.

The present disclosure contains embodiments of an apparatus, system and method designed to facilitate learning or efficient multitasking involving movement and solar energy where users' movement devices process or respond to different stimuli to facilitate users moving while learning, working, or participating in a simulation. In some embodiments this may be accomplished with the aid of a circular treadmill, spherical walkway, or combinable modular trackpads that may be linked to allow a user to lay the apparatus in a path suited for a plurality of environments. The embodiments of the disclosure involve the user moving while processing information and receiving feedback, assistance related to that movement, processing, or any combination thereof while combining the motion of the movement device with the feedback loop sent from sensor relays a user may receive an optimal experience for learning while moving. Some embodiments make efficient use of solar energy for classroom education management.

In one embodiment, a method for generating a message to a friend of a user is provided, comprising: processing activity data of a first user measured by an activity monitoring device to update a value of an activity metric for the first user; identifying a change in an inequality relationship between the value of the activity metric for the first user and a value of the activity metric for a second user; in response to identifying the change in the inequality relationship, prompting the first user to generate a message to the second user.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

A method of determining a CRF level for a user of a fitness tracking system includes receiving activity data from at least one activity sensor carried by the user during a number of workouts, the activity data including distance data for each of the number of workouts, and then generating workout data based on the activity data. The method further includes storing the workout data in a memory, the memory further including demographic data for the user. When the an attribute of the workout data is less than a threshold number, the method includes determining a first CRF level for the user based on a first CRF model. When the attribute of the workout data is greater than the threshold number, the method includes determining a second CRF level for the user based on a second CRF model, and displaying the first and second CRF levels.

Embodiments are disclosed for an electrical bicycle detector for energy expenditure estimation. In an embodiment, a method comprises: determining heart rate energy expenditure of a user wearing or holding the device; determining work rate energy expenditure of a user wearing or holding the device; determining a probability that the user is riding an electrical bike based on the heart rate energy expenditure and the work rate energy expenditure; determining whether or not the probability meets a condition corresponding to a threshold probability; and in accordance with the probability meeting the condition corresponding to the threshold probability: adjusting the work rate energy expenditure; and generating fitness data based at least on the adjusted work rate energy expenditure.

Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, an alignment plan capable of enabling, during a treatment session, the aligning of a user's body. The method comprises generating machine learning models trained to identify alignment plans. The method also comprises receiving treatment data that comprises a first position of the user's body, aspects of a treatment plan, and one or more attributes of the user. The method further comprises generating the alignment plan by using the machine learning models. The generating is based on at least the aspects of the treatment plan and at least one of the one or more attributes of the user. The alignment plan may comprise a target position of the user's body and one or more elements for adjusting the user's body from the first position to the target position. The method also comprises transmitting the plan to a computing device.

The present invention relates to a device, system and method for generating information on musculoskeletal recovery of a subject. To enable the generation of additional information on recovery of a subject to better avoid over-fatigue, injuries and overuse fractures, the device (10) comprises a sensor input (11) configured to receive a motion parameter and/or motion signal related to motion of the subject performing an activity; a processor (12) configured to determine from the motion parameter and/or motion signal a measure of impact load, determine from the measure of impact load a measure of musculoskeletal damage, and determine from the measure of impact load information on musculoskeletal recovery indicating to which extent the musculoskeletal damage recovers over time; and an output (13) configured to output the determined information on musculoskeletal recovery.

A method includes causing display, during a first time period and via a first set of multiple smart mirrors, of live video depicting at least one user associated with the first set of multiple smart mirrors, without displaying a workout video. The method also includes causing display, during a second time period following and mutually exclusive of the first time period, and via a second set of multiple smart mirrors, of a workout video and a representation of at least one user associated with the second set of smart mirrors. The method also includes causing display, during a third time period following and mutually exclusive of the second time period, and via a third set of multiple smart mirrors, of live video depicting at least one user associated with the third set of multiple smart mirrors.