A ski resort safety system and method. A ski resort comprises a piste (300). The ski resort safety system comprises: an anti-collision suit (1), wherein the anti-collision suit (1) is worn by a skier and comprises an inflation device (100) and a control device (200), the inflation device (100) is configured to inflate the anti-collision suit (1) under the control of the control device (200), and the control device (200) is configured to detect the condition of the skier, and when the skier encounters a danger, trigger the inflation device (100) to inflate the anti-collision suit (1), and is configured to transmit a danger signal when detecting the dangerous condition of the skier; and relay devices (301), wherein the relay devices (301) are arranged along the piste (300) at a certain interval so as to receive the danger signal, and transmit a trigger signal to other skiers (2′) on the piste (300). By triggering the anti-collision suits (1) of other skiers (2′) located below an out-of-control skier (2), the out-of-control skier (2) per se can be protected, and other skiers (2′) are also effectively prevented from being accidently damaged.

Described herein are various embodiments of differential air pressure systems and components for differential air pressure systems. The air pressure systems comprise a chamber for receiving at least a portion of a user's body. Pressure in the chamber can be changed to adjust force on the user's body. Described herein are various methods and related structures for sealing a user into a pressurizable chamber. Also described herein are various methods and related structures for changing the shape and/or height of the chamber. Described herein are various types and configurations of chambers and support structures for chambers. Also described herein are various methods and related systems for treating various conditions using the differential air pressure systems, including but not limited to obesity, cardiac disease, multiple sclerosis, cerebral palsy, or Down Syndrome.

A computer-implemented system includes a treatment device configured to be manipulated by an individual while the individual performs a treatment plan, a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session, and a computing device configured to: identify two or more types of healthcare providers to participate during the telemedicine session in the treatment plan associated with the individual; identify at least one healthcare provider associated with each of the two or more types of the healthcare providers; identify, based on schedules of the identified at least one healthcare provider, one or more available time slots for each respective healthcare provider; identify a first time slot of the available time slots; generate, based on the first time slot, a schedule event; and communicate the schedule event to each of the identified healthcare providers.

A computer-implemented system comprising a treatment apparatus, a patient interface, and a processing device is disclosed. The processing device is configured to receive treatment data pertaining to the user during the telemedicine session, wherein the treatment data comprises one or more characteristics of the user; determine, via one or more trained machine learning models, at least one respective measure of benefit one or more exercise regimens provide the user, wherein the determining the respective measure of benefit is based on the treatment data; determine, via the one or more trained machine learning models, one or more probabilities of the user complying with the one or more exercise regimens; and transmit the treatment plan to a computing device, wherein the treatment plan is generated based on the one or more probabilities and the respective measure of benefit the one or more exercise regimens provide the user.

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.

An exercise support apparatus is capable of supporting exercise taken by a patient during blood purification treatment and includes an estimation generating device that generates an estimation representing a circulating-blood-volume rate of change regarding a circulating blood volume that is estimated to be observed after the exercise is started, the estimation being generated after the blood purification treatment is started and from a continuous measurement of the circulating-blood-volume rate of change as regarding changes in circulating blood volume that is conducted before the exercise is started; a calculating device that calculates a difference between a measured value of the circulating-blood-volume rate of change that is acquired after the exercise during the blood purification treatment is started and a value of the estimation generated by the estimation generating device; and a first monitoring device that monitors whether the difference or ratio calculated by the first calculating device is over a predetermined threshold.

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.

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.