A system includes a treatment apparatus configured to implement a treatment plan for rehabilitation to be performed by a user and a processing device configured to receive attribute data associated with the user; generate, based on the rehabilitation, selected attribute data; determine, based on the selected attribute data, the rehabilitation, and a rehabilitation goal associated with the rehabilitation, one or more probabilities of attaining the rehabilitation goal within respective one or more numbers of rehabilitation sessions to be performed by the user using the treatment apparatus; provide, based on the one or more probabilities, an indication of the one or more numbers of rehabilitation sessions; and generate, based on a selected number of rehabilitation sessions from among the one or more numbers of rehabilitation sessions, the treatment plan. The treatment plan includes one or more exercises directed to attaining the rehabilitation goal within the selected number of rehabilitation sessions.

In one embodiment, a computer-implemented system includes an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan. The treatment plan includes a high-intensity interval training (HIIT) session. A processing device is configured to initiate, using the electromechanical machine, the HIIT session, receive, via one or more sensors, one or more measurements pertaining to the electromechanical machine, determine whether the one or more measurements exceed one or more of one or more corresponding thresholds, and in response to determining that the one or more measurements exceed one or more of the one or more corresponding thresholds, modify the treatment plan to cause operation of the electromechanical machine to be modified.

A wearable device such as a garment is disclosed, having at least one sensor, for sensing a parameter. Electronics are provided for processing the sensed parameter, and for providing feedback. Feedback may be in the form of proprioceptive tactile or audible feedback, or in the form of an adjustment of a performance parameter of the wearable device. In one implementation, the processor is configured to activate an effector to provide feedback to the wearer to make a body position correction to bring the position into alignment with predetermined body position reference data.

Systems and methods provide feedback to at least one participant in a field of play. A performance analysis device determines performance information of each participant in the field of play, where the performance information is based upon at least one of determined location, speed, path, acceleration and biometrics of said each participant. At least one output device provides real-time feedback to the at least one participant based upon the performance information. The real-time feedback comprises performance information of the at least one participant and/or performance information of one or more other participants in the field of play.

Embodiments of the invention provide apparatus, systems, and methods wherein pre-event and post-event analyte concentration readings associated with an event are collected and processed to determine a numerical delta. The numerical delta may be displayed on a visual display to aid in a ready determination of the affect that the event (alone or in combination with medication and/or insulin dosages) had on the analyte concentration levels. Medication and/or insulin dosages may be displayed alongside the numerical delta to gauge immediate relationships between numerical delta, dosage, and/or an associated event. Apparatus and systems for calculating and displaying the numerical delta are described, as are other aspects.

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.

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 includes one or more processing devices configured to receive attribute data associated with a user, generate, based on at least one of a first bariatric procedure to be performed on the user and a second bariatric procedure already performed on the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, at least one of a first probability of being eligible for the first bariatric procedure to be performed on the user and a second probability of improving a bariatric condition of the user subsequent to the second bariatric procedure being performed on the user, and generate, based on the at least one of the first probability and the second probability, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability, and a treatment apparatus configured for implementation of the treatment plan.

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.

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.