A system that comprises a memory device storing instructions, and a processing device communicatively coupled to the memory device. The processing device executes the instructions to: receive user data obtained from records associated with a user; generate a modified treatment plan based on the user data; and send, to a treatment apparatus accessible to the user, the modified treatment plan, wherein the modified treatment plan causes the treatment apparatus to update at least one operational aspect of the treatment apparatus, and update at least one operational aspect of at least one other device communicatively coupled to the treatment apparatus.

A method for generating an exercise session for a user using an exercise machine is disclosed herein. The method includes receiving a plurality of inputs, wherein the plurality of inputs comprise an indication of a level of pain of the user and a range of motion of a body part of the user. The method also includes determining, based on the plurality of inputs, an exercise level of the user, generating, using a machine learning model, the exercise session for the user by selecting, based on the exercise level of the user, one or more exercises to be performed by the user using an exercise machine, and causing initiation of the exercise session on the exercise machine and a virtual coach executed by a computing device associated with the exercise machine to provide instructions pertaining to the exercise session.

A method is disclosed for generating an improved exercise plan for a user to perform using at least an exercise machine. The method includes receiving data pertaining to the user. The data includes a physical activity goal the user desires to achieve and the physical activity goal includes levels of attainment to achieve. The method includes generating, by an artificial intelligence engine, the improved exercise plan. The improved exercise plan includes a set of exercises to be performed by the user to achieve the levels of attainment associated with the physical activity goal. The artificial intelligence engine uses at least one data source configured to include information pertaining to one or more exercises and at least one of the levels of attainment associated with the physical activity goal. The method includes transmitting the improved exercise plan to a computing device.

A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

A method for protecting healthcare information associated with an individual may include receiving at least a first electronic medical record associated with the individual and generating a patient identifier associated with the individual. The method may also include generating, using the patient identifier and at least a portion of the first electronic medical record, at least one protected electronic medical record corresponding to the first electronic medical record. The patient identifier may be associated with at least one characteristic of the individual. The method may also include providing, at least at a healthcare provider interface, at least one of the patient identifier and at least a portion of the at least one protected electronic medical record.

Proposed are an aquatic exercise apparatus and a method for exercising aimed at improving mobility of a user by exercising in water. The apparatus consists of base support and a balance board, which is connected to the base support via a resilient body that allows tilting of the balance board in any direction and a mechanism that provides free rotation of the balance board. Exercising in water allow people with mobility deficits to perform exercises without a fear of falling, decreasing pain, and improving cardiovascular return.

A method is disclosed for generating a treatment plan to modify an attribute of a user, wherein the attribute of the user is associated with an attribute of an occupational task. The method includes receiving data associated with the user, wherein the data comprises the modified attribute of the user and the attribute of the occupational task; accessing a database comprising data associated with exercises associated with the modified attribute of the user and the attribute of the occupational task; and generating, via an artificial intelligence engine, the treatment plan comprising an exercise of the exercises associated with the modified attribute of the first user and the attribute of the occupational task, wherein the artificial intelligence engine generates the treatment plan comprising the exercise based on the data associated with the user and the data associated with the exercises.

A method includes receiving data pertaining to a user that uses a treatment apparatus to perform a treatment plan. The data includes characteristics of the user, the treatment plan, and a result of the treatment plan. The method includes assigning the user to a cohort representing people having similarities to the characteristics of the user. The method includes receiving second data pertaining to a second user, the second data comprises characteristics of the second user. The method includes determining whether at least some of the characteristics of the second user match with at least some of the characteristics of the user, assigning the second user to the first cohort, and selecting, via a trained machine learning model, the treatment plan for the second user, and controlling, based on the treatment plan, the treatment apparatus while the second user uses the treatment apparatus.

A method includes receiving first data pertaining to a first user using a treatment apparatus to perform a treatment plan, wherein the first data comprises an attribute of the first user and an occupational task associated with the first user; receiving second data pertaining to a second user, wherein the second data comprises an attribute of the second user and an occupational task associated with the second user; determining whether an attribute and occupational task of the second user matches an attribute and occupational task of the first user; and responsive to determining that the attribute and the occupational task of the second user matches the attribute and occupational task of the first user, predicting, via an artificial intelligence engine, an estimate of when the second user performing the treatment plan would be capable of performing the occupational task associated with the second user.

A method includes receiving treatment data pertaining to a user capable of using a treatment device to perform a treatment plan and receiving activity data pertaining to the user while the user engages in at least one activity. The method also includes generating treatment information using the treatment data and the activity data and writing to an associated memory, for access by a healthcare professional, the treatment information. The method also includes modifying at least one aspect of the treatment plan in response to receiving, from the healthcare professional, treatment plan input including at least one modification to the at least one aspect of the treatment plan.