A system and non-intrusive method for exercise posture detection are provided. The system includes a mat, at least one sensor matrix comprising one or more sensors and configured to generate an electrical signal upon making a contact by the user with the mat, a plurality of sensor lines, a plurality of power lines and a processing subsystem. The processing subsystem includes a data acquisition module configured to extract a first set of data, to extract a second set of data; a data processing module to process the first set of data and the second set of data, to concatenate the first set of data and the second set of data to get a final set of data, to compare the final set of data with a pre-defined set of posture data, to determine the posture of the at least one exercise.

Devices, systems, and methods are provided for performing volume and intensity-based activity evaluations. A method may include determining, by a device, a heart rate. The method may include determining, based on the heart rate, a motion threshold amount for a time period. The method may include determining motion data. The method may include comparing the motion data to the motion threshold for the time period. The method may include determining, based on the comparison of the motion data to the motion threshold for the time period, an activity intensity level associated with the heart rate and the motion data. The method may include determining, based on the activity intensity level, an activity score. The method may include sending data indicating the activity score for presentation at a second device.

A scoring method executed by a processor, includes: acquiring sensor data obtained by measuring a competitor in a scoring competition; extracting joint information of the competitor, based on an analysis result of the sensor data; acquiring an evaluation item and an evaluation index that correspond to the joint information of the competitor, based on a rule in which a posture specified by a series of joint motions and joint angles, the evaluation item, and the evaluation index for performance evaluation are associated with each other; and evaluating a success or failure of a skill and a degree of perfection of the skill in a performance of the competitor, based on the analysis result, the evaluation item, and the evaluation index.

Aspects relate to systems, methods, and apparatuses relating 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.

The present disclosure generally relates to managing user interfaces associated with physical activities. The user interface displays a scrollable list of affordances associated with physical activities. The affordances may contain physical activity and heart rate information. A user can launch a physical activity tracking function or an interface to change a workout metric using an affordance. Users can also control the music that is played in response to selecting a workout. Further, the interface can be used to compose a reply message to a received message that contains workout information. The interfaces can show a graph that includes heart data when the user's heart rate meets a heart rate alert criteria.

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 tmining 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 tmining 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.

An exercise instruction apparatus for guiding a user to perform a fitness exercise includes a control unit and a display device. The control unit is configured to control a video imagery displayed by the display device. The video imagery shows an instructor image and a user image simultaneously. The instructor image demonstrates movements of the fitness exercise and the user image presented in a mirror image is a real-time image of the user standing in front of the display device. The control unit is configured to adjust at least one image parameters such as brightness, transparency or contrast of at least one of the instructor image and the user image. The image parameter that is adjusted for the instructor image may be a different parameter than the image parameter that is adjusted for the user image. The instructor image may be overlapped on the user image, and the user can adjust the transparency of at least one of the first image and the second image.

Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, treatment plans for optimizing a user outcome. The method comprises receiving attribute data associated with a user. The attribute data comprises one or more symptoms associated with the user. The method also comprises, while the user uses a treatment apparatus to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by the artificial intelligence engine configured to use one or more machine learning models, a second treatment plan for the user. The generating is based on at least the attribute data associated with the user and the measurement data associated with the user. The second treatment plan comprises a description of one or more predicted disease states of the user. The method also comprises transmitting, to a computing device, the second treatment plan for the user.

An information processing system includes an electronic apparatus including a detector that detects one or more pieces of data indicating an exercise type of a user, the electronic apparatus being attached to an in-use shoe used by the user, and an information processing device including an identification part that identifies the exercise type of the user based on the one or more pieces of data detected by the detector and an output part that outputs applicable shoe information about an applicable shoe corresponding to the type identified by the identification part.

In general, a computing device disposed in a cardio exercise machine receives data related to a fitness level of a user. The computing device selects a workout program based at least in part on the data. The operations of the cardio exercise machine are controlled based at least in part on the workout program. The computing device generates visual feedback based on at least one of the user's operation of the cardio exercise machine and the selected workout program measured against performance criteria.