Abstract: Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. For example, a method may include receiving, from one or more of an electromechanical machine, a sensor, and a computing device, data associated with a user that uses the electromechanical machine to perform a treatment plan. The method may include, based on one or more correlations of one or more indicators included in the data, generating, using an artificial intelligence engine, a unique data signature associated with a life-threatening event of the user. The unique data signature is generated when the one or more indicators satisfy a respective urgent threshold level, and the one or more indicators include a pain measurement and a measurement of revolutions per minute. Based on the unique data signature associated with the one or more life-threatening events, the method may include performing one or more preventative actions.

Abstract: Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. For example, a method may include using, inter alia, objective data to optimize treatment plans to support user progression during rehabilitation for the purpose of assisting in determining AI-driven interventions by using machine learning to generate at least one data signature. In some embodiments, a method may perform AI-driven interventions via optimization of treatment plans in order to support user progression during rehabilitation by performing, based on data signatures related to medically-associated events, selective data injection. Some other embodiments use evidence-based research to enable AI and machine learning to select and modify treatment plans in real-time at scale. Further, the improved rehabilitation infrastructure enables, via pain management, user compliance with treatment plans.

Abstract: A method may include receiving objective information associated with a user that uses the at least one medical device during execution of a treatment plan, and based on the objective information, generating, using one or more terms defined in at least one medical terminology database, at least one input prompt. The method may also include providing, to an at least artificial intelligence engine configured to provide one or more predictions indicating one or more treatment interventions, the at least one input prompt. The method may also include receiving at least one prediction indicating one or more treatment interventions, and controlling, while the user uses the at least one medical device, and based on at least one aspect of the one or more treatment interventions indicated by the at least one prediction, the at least one medical device.

Abstract: Systems and methods include receiving a plurality of sets of data corresponding to respective users of a plurality of users undergoing rehabilitation treatment. Each of the sets of data includes sensor data obtained while the respective users perform respective treatment plans. The plurality of sets of data is stored as objective information in a queryable data format. The method further includes receiving first sensor data associated with the performance of a first treatment plan. The first treatment plan corresponds to a standardized treatment plan assigned to the user, and the first sensor data correlates with the objective information. The method further includes predicting, based on the objective information and the first sensor data, a likelihood of the first user achieving a rehabilitation goal, generating, based on the objective information, the first sensor data, and the likelihood of the first user achieving the rehabilitation goal, a second treatment plan.

Abstract: In some embodiments, a method may include receiving, from an electromechanical machine, a sensor, and a computing device, data associated with a user that uses the electromechanical machine to perform a treatment plan, correlating, using an artificial intelligence engine, at least two of a pain measurement, an indication of medication utilization, and a measurement of revolutions per minute to generate a unique data signature associated with a treatment gap associated with the treatment plan performed by the user. Based on the unique data signature, generating, using the artificial intelligence engine, alternative treatment plans for the user, based on a threshold compliance level associated with each of the alternative treatment plans, selecting an alternative treatment plan from the alternative treatment plans, and controlling, while the user uses the electromechanical machine and based on the alternative treatment plan, the electromechanical machine.

Abstract: Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. The method includes receiving data associated with a user that uses a electromechanical machine to perform a treatment plan. The method also includes generating, using an artificial intelligence engine, a unique data signature associated with a regression of the user's condition. The unique data signal is generated when an indicator in the data satisfies a threshold indicator level. The method further includes generating, using the artificial engine and based on the unique data signature associated with the regression of the user's condition, a modified treatment plan that modifies a parameters or activity associated with at least one of the pain measurement, the measurement of revolutions per minute, and the session pedaling time. The method also includes controlling, while the user uses the electromechanical machine and using the modified treatment plan, the electromechanical machine.