55 results about "Exercise activity" patented technology

A training program recommendation system may monitor a user while the user is performing an assessment exercise activity. An exercise chatbot may present the user with an assessment query. The assessment query may request exercise information for the user. A training program recommendation system may apply a health assessment model to the exercise information to determine a health parameter and a user scaling factor. A training program recommendation system may apply a recommendation model to the health parameter and a user response to the assessment query. The recommendation model generates a training program recommendation for the user based at least in part on at least one of the health parameter or the user scaling factor. The training program recommendation includes a training program. A training program recommendation system may provide the training program recommendation to the user.

An exercise recommendation system may receive exercise information for a user. An exercise recommendation system may, based on the exercise information, identify a missed exercise activity. An exercise recommendation system may, based on the missed exercise activity and using an exercise chatbot, present the user with a query, the query including a request for additional information related to the missed exercise activity. An exercise recommendation system may receive a response to the query. An exercise recommendation system may apply a recommendation model to the response to generate an exercise recommendation.

Various systems and methods that enhance an exercise or other physical activity performed by a user are described. In some embodiments, a repetition counting systems can track, monitor, count, or determine a number of repetitions of movements performed by a user during an exercise activity or other activity. For example, the repetition counting system can utilize classification or matching techniques to determine that a certain number of repetitions of a given movement or exercise are performed by the user.

A risk analysis system is configured to collect and monitor sensor data associated with a user to generate an insurance policy or recommend products / services that may be better suited for the user based on the user's gameplay data, fitness data, streaming data, outdoor activity data, location data, etc. The risk analysis system is configured to correlate all the sensor data and control operations of devices to discourage behavior that may increase risk of an accident or other suitable insurance liabilities.

Athletic performance monitoring and tracking may provide multiple ways in which to track athletic movement and activity. Workouts may also be tagged with various parameters including mood, weather, terrain, athletic equipment, friends used and the like. Workout information may be shared to social messaging and networking outlets. Workout information shared may include map information including images of maps, interactive maps, links to maps, route information and the like and / or combinations thereof. Additionally or alternatively, an application may be configured to execute within a context of a social networking system to facilitate athletic activity data transfer and generation of workout entries in the social networking site.

A fitness tracking system can include at least one processor and non-transitory memory storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations including receiving, from one or more wearable devices having sensors for detecting motion of a user, first data characterizing raw motion of a user during an exercise activity, determining, using a first artificial intelligence (AI) model, based on the first data, a readiness metric associated with the exercise activity, determining, using a second AI model, based on the readiness metric, an exercise plan for the user, and providing second data characterizing the exercise plan.

The buffer element may include a texture layer and a second layer disposed over the texture layer. The texture layer includes a plurality of protrusions extending upwardly from a surface of the texture layer. The second layer may include a plurality of recesses, each configured to receive a respective projection of the texture layer. The protrusions of the textured layer form a surface texture on the upper surface of the second layer when a load pressure is applied to the upper surface of the second layer (e.g., by a foot of a user). The cushioning elements may be used to form part of garments, accessories, athletic equipment, and / or articles of footwear, and may be configured to accommodate specific foot anatomy of a user, and / or may be customized to support a user's foot while performing an athletic activity.

An apparatus for configuring a wearable device for exercise tracking includes a data storage unit for storing sensor data generated by a sensor arrangement in the wearable device based on sensed movement of the wearable device and optical movement data including representations of an individual obtained from an image-based monitoring system; and a processing unit configured to: execute a movement tracker model on the sensor data to determine a first exercise activity and an associated first confidence indicator; execute an optical tracker model on the optical movement data to determine a second exercise activity and an associated second confidence indicator; process the movement tracker model based on the first confidence indicator and the second confidence indicator.

1. Name of the product in this design: Grip Strength Playground Ball. 2. Purpose of this design: For exercise activities of children aged three and above. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

A system for automatically monitoring activity on an athletic activity area is provided. The network device includes artificial intelligence configured to automatically identify objects and gestures from video received from cameras disposed at the activity area. The artificial intelligence automatically edits the video based on objects and gestures identified from the video and generates a video file including predetermined objects and gestures. The artificial intelligence may generate a video including each trial completed by a particular athlete and may provide the video automatically to the player or a third party.

In some examples, an electronic device detects initiation of an exercise activity associated with a user of the electronic device. In some examples, in response to detecting the initiation of the exercise activity, the electronic device activates an image compilation capture mode of operation in which one or more images for formulating a compilation of the one or more images corresponding to the exercise activity are captured, including capturing one or more portions of a physical environment. In some examples, while the image compilation capture mode of operation is active, the electronic device visually detects a first object in the one or more captured portions of the physical environment. In some examples, in accordance with a determination that the first object satisfies one or more criteria, the electronic device generates a first event associated with formulating a first compilation of one or more images corresponding to the exercise activity.

Disclosed herein is a device for continuous physiological monitoring as well as systems and methods for interpreting data from such a device. The systems and methods may include automatically detecting, assessing, and analyzing exercise activity, physical recovery states, sleep states, and the like. The acquisition of continuous physiological data may facilitate automated recommendations concerning changes to sleep, recovery time, exercise routines, and the like.

An athletic parameter measurement device associated with a first user may include a display, a processor associated with the display, and an athletic parameter measurement sensor. During the athletic activity, the device may detect, using the sensor, athletic activity of the first user. A plurality of video segments, captured by video sources, may correspond to the athletic activity and may be reconstructed to generate a video replay. Video segments of the plurality of video segments may be selected to maximize an image of the user.

Methods and systems are described for real-time coaching and guidance using a virtual assistant that interacts with a user. A user can receive feedback inferences provided substantially in real-time after a video sample is collected from the user's device. Neural network architectures and layers can be used to determine motion patterns and temporal aspects of the video sample, as well as to detect the activity of the foreground user despite background noise. The methods and systems can have various capabilities, including but not limited to real-time feedback on the exercise activity performed, exercise score, calorie estimation, and repetition count.

An exercise recommendation system may receive exercise information for a user. An exercise recommendation system may, based on the exercise information, identify a missed exercise activity. An exercise recommendation system may, based on the missed exercise activity and using an exercise chatbot, present the user with a query, the query including a request for additional information related to the missed exercise activity. An exercise recommendation system may receive a response to the query. An exercise recommendation system may apply a recommendation model to the response to generate an exercise recommendation.

The present invention relates to the technical field of auxiliary training equipment and proposes a user data analysis method based on a wearable device, comprising: collecting electrocardiogram (ECG) data of an exercise user during training to obtain an ECG sequence, an ECG waveform sequence, and a quasi-period; determining a frequency curve, obtaining an extreme value pair of the frequency curve, and then obtaining a frequency extreme value disorder coefficient; obtaining a fundamental frequency shift coefficient of the ECG data, and then obtaining an intra-cluster fundamental drift deviation coefficient, obtaining a first correlation coefficient, obtaining an ECG waveform quasi-period deviation coefficient, and then obtaining an ECG waveform disturbance distortion index; obtaining a first particle number of the ECG data, denoising the ECG sequence based on the first particle number, obtaining a denoised ECG sequence, and implementing intelligent analysis of exercise activity data based on the wearable device based on the denoised ECG sequence. The present invention aims to solve the problem of being unable to dynamically adjust the denoising of training data based on the exercise state of the exercise user, resulting in poor denoising effect.

System and method for creating an exercise plan for a user based on a goal state of a digital twin of the user. A baseline state of the digital twin is created based on a first 3D model of the user and first physiological data of the user. Using a machine-learning model, an exercise plan for the user, comprising one or more motion profiles, is created that most likely effectuates a goal state of the digital twin from the baseline state of the digital twin. Electronic exercise equipment is configured to physically manifest the one or more motion profiles during exercise activity of the user, and data is acquired by the electronic exercise equipment based on the exercise activity.

The present invention relates to a system (100) for detecting, analyzing and processing movement and impact data during an exercise activity. The system (100) has a first control module (10) configured to process input data and communicate with an external device. Also, at least one second control module (20) configured to be positioned on a user's body and / or on an impact surface (30). The second control module (20) detects at least one parameter associated with the movement, impact, or force of a user or an object, generate data corresponding to the detected parameter, and transmit the generated data to the first control module (10). An impact surface (30) configured to receive an impact during an exercise activity. The at least one second control module (20) is arranged on the impact surface to detect the impact.

Systems and methods that enhance an exercise activity are described. In some embodiments, the systems and methods personalize certain time-based content for users / members to enhance their experience when exercising or navigating a connected fitness platform. For example, the systems and methods may utilize machine learning models to determine or predict a likelihood of engagement of timely content by users and ranks the content or provides recommendations to the users in response to the determined predictions.

Among other things, a processor executes instructions to: update, in real time during a current instance of an exercise activity by a subject competitor, a graphical user interface displayed on a display device, the display device being included in a first exercise machine operated by the subject competitor or included in a mobile electronic device. The graphical user interface includes: a ranking of the subject competitor and a second competitor based on (i) a projected performance metric of the subject competitor over a predefined scope of the exercise activity compared to (ii) a historical performance metric of the second competitor over the predefined scope of the exercise activity in a previous instance of the exercise activity, an illustration of a margin between the historical performance metric of the second competitor and the projected performance metric for the subject competitor, and an illustration of the projected performance metric.

The invention relates to the field of physical exercise, in particular to a community physical exercise device which comprises a plurality of supporting legs, a supporting frame is arranged between the tops of the supporting legs, a first supporting plate is arranged on one side of the supporting frame, a sliding assembly is installed on the inner wall of a placing hole, and a stretching assembly is installed on the supporting frame. The limiting assembly is mounted on the sliding assembly through a mounting block, the extension assembly is mounted on the sliding assembly through a first moving rod, and a second moving rod moves to drive the first moving rod and a moving column to move, so that exercise activities such as forward bending of a sitting body can be achieved, and a second supporting plate is pulled to drive a limiting rod and a limiting column to move; the second supporting plate is fixed and limited, the angle of the second supporting plate is adjusted, the most comfortable angle is found, a connecting column and a blocking column are arranged at the bottom of the arc-shaped plate, and therefore the device can complete exercise activities such as sitting body forward bending and the like and can also complete exercise activities such as sit-ups and the like.

Athletic performance monitoring and tracking may provide multiple ways in which to track athletic movement and activity. Workouts may also be tagged with various parameters including mood, weather, terrain, athletic equipment, friends used and the like. Workout information may be shared to social messaging and networking outlets. Workout information shared may include map information including images of maps, interactive maps, links to maps, route information and the like and / or combinations thereof. Additionally or alternatively, an application may be configured to execute within a context of a social networking system to facilitate athletic activity data transfer and generation of workout entries in the social networking site.

A console for an exercise device includes a translational mechanism and a rotational mechanism. During operation, a component of the exercise device may prevent rotation or at least partially obscure the user's view of the display. The translational mechanism may move the console out of the way of the component so that the console may be moved and the display visible to the user when performing an exercise activity while dismounted from the exercise device.

A console for an exercise device includes a translational mechanism and a rotational mechanism. During operation, a component of the exercise device may prevent rotation or at least partially obscure the user's view of the display. The translational mechanism may move the console out of the way of the component so that the console may be moved and the display visible to the user when performing an exercise activity while dismounted from the exercise device.

Disclosed are a method and apparatus for providing a guide for analyzing an exercise video through a user terminal. The method for providing a guide for analyzing an exercise video through a user terminal, according to an embodiment of the present invention, may comprise the steps of: receiving an input of selecting a first exercise item that a user wants to exercise, from an exercise item selection page of an application for analyzing an exercise video executed on the user terminal; providing the user terminal with guide information for measuring a record of the user on the first exercise item; receiving, from the user terminal in real time, an exercise video obtaining by photographing the appearance of the user performing the first exercise item, and measuring the record of the user on the first exercise item; and if the measurement of the record on the first exercise item is completed, storing a result of the measurement in user information about the user.

We provide the system. [Solution] A means of obtaining user physical condition information from a device for collecting activity data, A data analysis means for processing the aforementioned physical condition information, A program generation means that generates an optimal exercise program for the user based on the information processed by the data analysis means, A means of presenting the generated exercise program to the user, A system that includes a feedback mechanism to provide real-time feedback on the user's exercise activities.

A monitoring system configured to monitor the motion of a piece of athletic equipment may include: one or more memory devices configured to store a file and including a buffer; a motion sensor configured to couple to the piece of athletic equipment; and one or more processors. The one or more processors may: sample motion data from the motion sensor at a sampling rate; save the sampled motion data in the buffer; save at least a portion of the sampled motion data in the file separate from the buffer at a saving rate that depends upon a variability of the sampled motion data; and alter the saving rate separately from the sampling rate based on at least one of an impact to the piece of athletic equipment or movement of the piece of athletic equipment by the individual during the course of an athletic activity.

An exercise bicycle having various enhanced or updated features or components is described. For example, the exercise bicycle may include various enhanced brake or braking structures, such as brake locks and brakes having thermal sensing components. The brake, or resistance mechanism, may perform thermal sensing (e.g., measuring a temperature at or around the brake) when the bicycle in being used during an exercise activity, and adjust or modify certain captured parameters (e.g., a resistance applied to a flywheel of the brake and / or a performance output or power level) based on the measured temperature.

Athletic activity monitoring methods and systems are disclosed. In one embodiment, a sensor module is physically coupled to an object during an athletic activity conducted by a user. An athletic activity monitoring method for use with the sensor module includes detecting movement of the object; determining an initial spatial orientation of the object; and determining a change in the spatial orientation of the object. The method further includes wirelessly transmitting data relating to the change in spatial orientation to a computer, where the computer is remotely located from the user during the athletic activity; wirelessly receiving activity metric data from the remote computer, where the activity metric data is based on the transmitted data relating to the change in spatial orientation; and providing an output to the user that conveys an activity metric.