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 that includes receiving treatment data associated with a user capable of using a treatment device to perform a treatment plan. The method also includes receiving user related data (URD) associated with the use and receiving alignment data associated with the user while the user engages in at least one activity. The method also includes identifying, based on at least the treatment data, the URD, and the alignment data, at least one alignment characteristic associated with the user and modifying at least one aspect of the treatment plan in response to receiving, from a healthcare professional, treatment plan input including at least one modification to the at least one aspect of the treatment plan.

A method for updating a treatment plan. The treatment plan is associated with a user using a treatment apparatus to perform the treatment plan. The method includes receiving first data associated with a first diagnosis of the user. The method includes generating, based on the first data, an initial treatment plan to be performed on the treatment apparatus by the user. The method includes receiving second data associated with a first attribute of the user. The method includes generating, via an artificial intelligence engine, a machine learning model trained to generate an updated treatment plan based on the initial treatment plan and the second data.

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.

An intelligent health strap. A detection and analysis method comprises: acquiring multiple groups of pulse data collected by multiple pulse sensors (11); and according to the multiple groups of pulse data, using a calculation method for analysis to obtain physical sign information (12). An intelligent health wrist strap and an intelligent health ankle strap having multiple pulse sensors are used for performing pulse monitoring and analysis, displaying multiple types of pulse physical sign information, and transmitting data to an external device, so that a user can conveniently monitor changes of individual physiological status, and the intelligent health wrist strap and the intelligent health ankle strap can provide massage and health-care for wrists and ankles.

A mobile walker has a frame, at least two wheels which are embodied and arranged on the frame to move the mobile walker around on a ground surface, at least one hand grip embodied and arranged on the frame to be used by a user of the mobile walker as a support and pushing aid, at least one measured value recording unit embodied and programmed to record at least one vital parameter of the user, and a processor unit which is connected communicatively to the measured value recording unit and which is embodied and programmed to assess the recorded vital parameter and/or transmit the same to a control center arranged separately from the mobile walker.

A computer-implemented method for facilitating cardiac rehabilitation among eligible users is disclosed. The method includes the steps of (1) receiving health information associated with one or more users; (2) for each user of the one or more users: determining, based on health information associated with the user, a respective eligibility of the user for cardiac rehabilitation; (3) determining, based on the respective eligibilities, that at least one user of the one or more users is eligible for cardiac rehabilitation; (4) generating a treatment plan for the at least one user, where the treatment plan pertains to a cardiac rehabilitation that is specific to the at least one user; and (5) assigning the treatment plan to at least one electromechanical machine to enable the user to perform the cardiac rehabilitation.

A computer-implemented method is disclosed. The method includes determining whether one or more messages have been received from at least one of an electromechanical machine, a sensor, and an interface. Then the one or more messages may pertain to at least one of a user and a usage of the electromechanical machine by the user. The electromechanical machine may be configured to be manipulated by the user while the user is performing a treatment plan. The method also includes, responsive to determining that the one or more messages have not been received, determining, using one or more machine learning models, one or more preventative actions to perform. The method also includes causing the one or more preventative actions to be performed.

Disclosed are devices and methods for mitigating insulin resistance in a human subject by contacting one or more regions of the neck, the supraclavicular, and the interscapular regions of the human subject with a part of a cooling device, wherein the part of the cooling device has a temperature at about 15 or less Celsius degrees; cooling the one or more regions of the neck, the supraclavicular, and the interscapular regions of the human subject for a cooling period of at least 15 minutes; and performing previous two steps daily for about 14 or more days. The devices and methods may also be used to preventing, delaying or treating type 2 diabetes in a human subject or activating brown fat without incurring a sympathetic nerve-mediated cold feeling in a human subject.

A computer-implemented method for (1) receiving one or more characteristics of a user, wherein the one or more characteristics comprise personal information, performance information, measurement information, or some combination thereof, (2) generating, using one or more trained machine learning models, a treatment plan for the user, wherein the treatment plan is generated based on the one or more characteristics of the user, and the treatment plan comprises: (i) a dietary plan that is tailored to manage one or more medical conditions associated with the user, and (ii) an exercise plan comprises one or more exercises associated with the one or more medical conditions, and (3) presenting, via a display device, at least a portion of the treatment plan comprising the dietary plan.