Methods for treating fluid overload in a subject comprise shifting fluids directly and non-invasively from an interstitial compartment of the subject to skin of the subject through controlled local sweating. Methods of the invention allow for removal of excess fluid from the interstitial compartment of the subject and treat fluid overload in the subject. Sweat stimulation systems comprise a chamber and first and second relative humidity sensors. The chamber is sized to fit around a body part of a subject, comprises an inlet and an outlet, and is configured such that air flows through the chamber from the inlet to the outlet. The first relative humidity sensor is operably located inside the inlet, and the second relative humidity sensor is operably located proximate the outlet.

In one embodiment, a method is disclosed. The method includes, while the patient uses the treatment apparatus, controlling, based on a treatment plan for a patient, a treatment apparatus. The method includes receiving, by a processing device, data from an electronic device, wherein the data comprises one of a position of a body part of the patient or a force exerted by the body part. The method includes storing, via the processing device, the data for the patient in a computer-readable medium. The method includes causing, via a processing device, presentation of a user interface on a patient interface. The user interface comprises an adjustment confirmation control, and the adjustment confirmation control is configured to solicit a response regarding the patient's comfort level with the one of the position of the body part or the force exerted by the body part.

A system and method for generating and implementing a barcode is provided, wherein the system includes a data generation device configured to receive data and generate barcode data response to the received data, a barcode generation device, configured to receive the barcode data and generate a barcode responsive to the received barcode data, a display device, configured to display the barcode and a barcode receiving device, configured to receive the barcode and operate in response to the barcode.

This application describes a mobile cycling apparatus which may be easily installed in transportation terminals (and/or other locations) to provide people with an opportunity to exercise. The mobile cycling apparatus described herein may mounted proximate existing seating in the transportation terminals. In some examples, the mobile cycling apparatus may be coupled to the seating, such as a beam seating platform, and/or tables proximate a chair. In some examples, the mobile cycling apparatus may be directly coupled to the floor or other substantially horizontal surface. In some examples, the mobile cycling apparatus may be detachably coupled to a surface (e.g., seating, table, floor, etc.). In such examples, the mobile cycling apparatus may be moved between locations in the transportation terminal.

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.

A computer-implemented system may include an electromechanical 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 condition or a cardiac outcome, 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 of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.

A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.

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.

An exercise device includes a foot support portion pivotably connected to a leg support portion and having a neutral position relative to a pivot axis. The support portion is configured to rotate about the neutral pivot axis in a first direction away from the neutral position and in a second direction away from the neutral position. The second direction is opposite the first direction. The exercise device also includes a resistance mechanism configured to exert a force on the foot support portion about the pivot axis opposite to the respective first and second directions of rotation of the foot support portion about the pivot axis.