The present invention relates to systems, methods, and apparatus that facilitate exercise in vehicles. In particular, the present invention provides active exercise in passenger and navigation areas in vehicles by incorporating force sensors in the environment surrounding the passenger and/or navigator in the vehicle. The present invention applies the principles of isometric training and interacts with a remote or on-board computer platform to track, measure and provide instruction to the passage and/or navigator engaged in such isometric training.

An isokinetic oscillation exercise device of an elongated flexible blade having a first and second end and a grip portion coupled to a middle portion of the elongated flexible blade. End caps coupled to said first and second ends adapted to storage. Further, a method is disclosed of manufacturing an isokinetic oscillation exercise device that provides a flexible elongated flexible blade, a grip portion injection molding, a pliable ring injection moldings, and end caps injection molding; slides the pliable rings on the elongated flexible blade separated by a length of the grip portion, overmolds a first-shot of the grip portion over the pliable rings, overmolds a second-shot of the grip portion to the first-shot of the grip portion to the elongated flexible blade, seals the first-shot to the second-shot of the grip portion against the pliable rings; and attaches the end caps to the elongated flexible blade.

During a first time period and for a first user, a second user is automatically selected based on competitive data of the first user and competitive data of the second user, and a workout selection is sent to cause a video of a workout to be displayed during a second time period on a smart mirror of the first user and a smart mirror of the second user. During the second time period, a live stream of the first user exercising is displayed at the smart mirror of the second user, and a live stream of the second user exercising is received and displayed at the smart mirror of the first user. During the second time period, a performance score of the first user and a performance score of the second user is displayed at the smart mirrors of the first user and the second user.

A movement tracking device that includes a housing, a rotatable spool secured within the housing, a rotary sensor in operable communication with the spool, and a conductive wire configured to be repeatedly unspooled from and respooled onto the rotatable spool. The conductive wire has a distal end extendable from the housing. The movement tracking device also includes a plurality of resonators and a processor in communication with the plurality of resonators and the rotary sensor. The plurality of resonators are disposed in or on the housing and positioned about the conductive wire. Each of the plurality of resonators is configured to create one or more magnetic fields through which the conductive wire extends. The processor is configured to receive information from the plurality of resonators and the rotary sensor and determine a position of the conductive wire.

Methods and systems for real-time generation of ball shot analytics are disclosed. The methods and systems perform steps for ball and posture detection, ball and posture flow generation, shot event identification and classification, and shot analytics generation based on identified shot events and shooter posture flow. Embodiments of the present invention use computer vision techniques to enable a resource-limited mobile device such as a smartphone to conduct the aforementioned steps. Therefore, the present invention may be implemented using a processor on a single mobile computing device. Also disclosed are benefits of the new methods, and alternative embodiments of implementation.

A method includes capturing, using an Internet of Things (IoT) device, real-time video of a user performing an exercise associated with a first exercise class. Real-time video of the user is displayed, via a display, concurrently with video of an instructor, to provide a visual comparison of the user to the instructor. Image analysis of the real-time video of the user is performed to determine a performance of the user, and a representation thereof is displayed. Biometric data associated with the user is received at the IoT device from a wearable device at multiple points in time. Heart rates are identified based on the biometric data, and scores based on the heart rates are displayed via the display. A recommendation for a second exercise class different from the first exercise class is determined based on a profile of the user, and displayed via the display.

A user-specific workout can be generated by adjusting transform parameters of a user-agnostic training profile to conform to a user boundary specifying a user's ability to perform work. The user-agnostic training profile can be defined in a training space, specifying a power curve in a time domain whereas the user boundary can be defined in a boundary space, specifying amounts of user-produced work in a time window size domain. A training boundary can be generated based on the user-agnostic training profile by determining the largest area under the user-agnostic training profile power curve for various time window sizes, where each largest area under the user-agnostic training profile power curve produces a data point for the training boundary for that window size domain value. The training boundary can be transformed based on the user boundary, causing corresponding transformations to the user-agnostics training profile, converting it to a user-specific workout.

Evaluation value calculation unit calculates, based on time-series changes in exercise information on each of a plurality of users who have exercised in accordance with an exercise menu, an evaluation value of the exercise menu. Evaluation result generation unit compares an evaluation value of an exercise menu with a reference value. The evaluation result generation unit generates results of evaluating the exercise menu based on the results of comparing the evaluation value with the reference value.

A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

Methods, systems and devices are provided for motion-activated display of messages on an activity monitoring device. In one embodiment, method for presenting a message on an activity monitoring device is provided, including the following method operations: downloading a plurality of messages to the device; detecting a stationary state of the device; detecting a movement of the device from the stationary state; in response to detecting the movement from the stationary state, selecting one of a plurality of messages, and displaying the selected message on the device.