An activity tracking device for tracking and incentivizing personal goals. One embodiment of the activity tracking device is formed as a fitness smart watch with sliders for tracking water and fruit/vegetable intakes, and with the typical smart watch features, including a pedometer, heart-rate monitor, altimeter, stop watch, vibrating notifications, alerts, etc. Another embodiment of the activity tracking device is formed as a band that would have no automated tracking, however users could choose from different bands for tracking their goals for various activities like drinking enough water, fruit and vegetable intake, daily exercises, meditation breaks during the day and more. A preferred embodiment of the activity tracking device is formed as a computer device having computer application thereon that provides a method of tracking and incentivizing personal goals and provides a plurality of electronic touch screen pages that are adapted to allow a user to create goal monitoring electronic pages that allows the user to input data correlating to the progression towards personal goals, and to which graphic images are created to provide the percent of completion of their goals.

Systems, methods, and computer-readable mediums for operating an electromechanical device are disclosed. The system includes, in one example, the electromechanical device, a patient portal, and a computing device. The computing device is configured to receive user data relating to a user, and receive treatment data relating to treatment plans and outcomes. The computing device is also configured to generate a prehabilitation plan by using a machine learning model to process the user data and the treatment data. The computing device is further configured to select, for the electromechanical device, an electromechanical device configuration that enables exercises of the prehabilitation plan to be performed by the user such that performance improves an area of the user's body. The computing device is also configured to enable the electromechanical device to implement the electromechanical device configuration.

A system may comprise one or more monitoring devices that may communicate with a mobile device or a wearable device worn by a user of a sporting apparatus. The system may enable motion data specific to motion of the sporting apparatus to be conveniently captured and transmitted, and displayed on the wearable device. The system may include functionality to permit disablement of the motion detecting, transmission, and/or displaying functions at times when such functions are not permitted to be used, and to record the date, time, and location when such functions have been disabled to permit verification thereof by a governing body or sporting organization. The system may further include a learning module enabling monitored motion of the object to be correlated to monitored motion of the user such that predictive motion of the sporting object based only on monitored motion of the user may be obtained and displayed.

A computer-implemented system may include a stair-climbing machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and processing structure configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac-related event; generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability that a cardiac intervention will occur; and transmit the treatment plan to cause the stair-climbing machine to implement the one or more exercises.

A wireless play communication system enables communications between a coach and a player. The system includes a coach communication device mounted in a first carrying device that is adapted to be carried by the coach, and a player communication device mounted in a second carrying device that is adapted to be carried by the player. An input mechanism of the coach communication device enables a coach to input a signal. Actuation of a pitch plus button functions to transmit the signal from the coach communication device to the player communication device, while also updating a pitch tracker which tracks the number of pitches thrown by the player. The pitch count is displayed on a pitch count display.

A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Systems including an elliptical machine and a processing device. The processing device may be configured to receive, before or while a user operates the elliptical machine, one or more messages pertaining to the user or a use of the elliptical machine by the user. The processing device may be also configured to determine whether the one or more messages were received by the processing device. In response to determining that the one or more messages were not received by the processing device, the processing device may be configured to determine, via one or more machine learning models, one or more actions to perform. The one or more actions may include at least one of initiating a telecommunications transmission, stopping operation of the elliptical machine, and modifying one or more parameters associated with the operation of the elliptical machine.

A computer-implemented system may include a rowing machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac-related event; generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability that a cardiac intervention will occur; and transmit the treatment plan to cause the rowing machine to implement the one or more exercises.

A computer-implemented system includes a processing device configured to receive a plurality of user and blood vessel characteristics associated with a user, generate a selected set of user and blood vessel characteristics, determine, based on the selected set of the user and blood vessel characteristics, a probability that angiogenesis will occur, and generate, based on the probability and the selected set of the user and blood vessel characteristics, a treatment plan that includes one or more exercises directed to modifying the probability that angiogenesis will occur, and a treatment apparatus configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

A computer-implemented system includes one or more processing devices configured to receive user information associated with a user, generate a selected set of the user information, determine, based on the selected set of the user information, at least one of a first probability of surviving one or more procedures and a second probability indicating an improvement, resulting from the one or more procedures, in quality-of-life metrics for the user, generate, based on the at least one of the first probability and the second probability and on the selected set of the user information, one or more recommendations of whether the user should undergo the one or more procedures, and generate, based on the one or more recommendations, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability.