Abstract: 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.

Abstract: Systems, methods, and computer-readable media for assigning remote monitoring sessions. The system includes an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while performing a treatment plan. The one or more sensors are configured to determine measurements of one or more vital signs associated with the user. The one or more processing devices are configured to receive a request to conduct a monitored session of the user performing the treatment plan. The one or more processing devices are also configured to determine whether conducting the monitored session with a computing device will violate one or more remote monitoring rules. The one or more processing device are further configured to initiate the monitored session by displaying the measurements on a display of the computing device while the user performs the treatment plan.

Abstract: A computer-implemented system includes an interface comprising a display configured to display interface presentation data pertaining to a user using an electromechanical machine to perform a treatment plan and one or more processing devices configured to receive selected measurement information associated with the user and treatment plan information associated with the treatment plan, generate the interface presentation data based on the selected measurement information and the treatment plan information, and enable the interface to present, in a portion of the display, the interface presentation data for the user. The portion of the display includes one or more graphical elements that present, in real-time or near real-time, at least one type of the selected measurement information and the treatment plan information.

Abstract: A computer-implemented system includes an interface comprising a display configured to display interface presentation data pertaining to a plurality of users each using a respective electromechanical machine to perform a treatment plan and one or more processing devices configured to receive selected measurement information associated with each of the plurality of users, generate the interface presentation data based on the selected measurement information; and enable the interface to present, in respective portions of the display, the interface presentation data for each of the plurality of users.

Abstract: Computer-implemented systems, computer-implemented methods, and tangible, non-transitory computer-readable media for detecting abnormal heart rhythms of a user performing treatment plan with an electromechanical machine. The system includes, in one embodiment, an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while the user is performing a treatment plan. The one or more sensors are configured to determine one or more measurements associated with the user. The one or more processing devices are configured to receive, from the one or more sensors while the user performs the treatment plan, the one or more measurements associated with the user. The one or more processing devices also configured to determine, using one or more machine learning models, a probability that the one or more measurements indicate that the user satisfies a threshold for a condition associated with an abnormal heart rhythm.

Abstract: A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on the attribute data and a first health issue of the user, a selected set of the attribute data, the first health issue corresponding to a first long-term care health issue of the user, determine, based on the selected set of the attribute data, a first probability associated with treating the first health issue, generate, based on the first probability, a treatment plan that includes one or more exercises directed to modifying the first probability, and modify, based on at least one of the first probability and a second probability, the treatment plan. The second probability is associated with treating a second health issue of the user. A treatment apparatus is configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

Abstract: A smart exercise device includes an interface comprising a smart mirror configured to present information pertaining to a treatment plan being performed by a user while the user interacts with the smart exercise device. A processing device is configured to cause the smart exercise device to perform one or more functions related to the treatment plan, such as cause one or more preventative actions to be performed based on whether the processing device receives one or more messages, cause one or more content items to be presented to the user on the interface, assign the treatment plan to the smart exercise device based on a determined eligibility of the user, and implement the treatment plan to reduce a probability of a cardiac intervention for the user.

Abstract: A treadmill comprises a pair of rollers and a belt coupled to and extending between the pair of rollers. The belt encircles a support platform suspended between the pair of rollers. A motor is operatively coupled to one of the pair of rollers to rotate the one of the pair of rollers such that rotation of the rollers causes the belt to rotate around the support platform suspended between the pair of rollers. The treadmill further comprises a processing device configured to cause the treadmill to perform an action associated with a use of the treadmill by the user based on whether the processing device receives certain messages; cause content items to be presented to the user; assign the treatment plan to the treadmill based on a determined eligibility of the user; and implement the treatment plan to reduce a probability of a cardiac intervention for the user.

Abstract: The embodiments set forth a technique implemented by a computing device. The technique includes the steps of (1) receiving one or more characteristics associated with a user, wherein the one or more characteristics comprise personal information, performance information, measurement information, cohort information, familial information, comorbidity information, healthcare professional information, or some combination thereof; (2) determining, based on the one or more characteristics, one or more conditions of the user, wherein the one or more conditions pertain to cardiac health, pulmonary health, bariatric health, oncologic health, cardio-oncologic health, or some combination thereof; (3) based on the one or more conditions, identifying, using one or more trained machine learning models, one or more subgroups to present via the display, wherein the one or more subgroups represent different partitions of the one or more characteristics; and (4) presenting, via the display, the one or more subgroups.

Abstract: A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

Abstract: A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on a pulmonary condition of the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, a first probability of improving a pulmonary condition of the user subsequent to at least one of a pulmonary procedure being performed on the user, a pulmonary treatment being performed on the user, and a pulmonary diagnosis, and generate, based on the first probability, a treatment plan that includes one or more exercises directed to modifying the first probability. A treatment apparatus is configured to enable implementation of the treatment plan.

Abstract: A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on at least one of a first bariatric procedure to be performed on the user and a second bariatric procedure already performed on the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, at least one of a first probability of being eligible for the first bariatric procedure to be performed on the user and a second probability of improving a bariatric condition of the user subsequent to the second bariatric procedure being performed on the user, and generate, based on the at least one of the first probability and the second probability, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability, and a treatment apparatus configured for implementation of the treatment plan.

Abstract: A computer-implemented system includes one or more processing devices configured to receive comorbidity information that includes a plurality of comorbidities or comorbidity-related conditions associated with a user, generate a selected set of the comorbidity information, determine, based on the selected set of the comorbidity information, respective probabilities of a plurality of different outcomes related to the comorbidity information, and generate, based on the respective probabilities and the selected set of the comorbidity information, a treatment plan comprising one or more exercises directed to changing the respective probabilities. A treatment apparatus is configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

Abstract: A computer-implemented system includes one or more processing devices configured to receive user information associated with a user, generate a selected set of the user information, determine, based on the selected set of the user information, at least one of a first probability of surviving one or more procedures and a second probability indicating an improvement, resulting from the one or more procedures, in quality-of-life metrics for the user, generate, based on the at least one of the first probability and the second probability and on the selected set of the user information, one or more recommendations of whether the user should undergo the one or more procedures, and generate, based on the one or more recommendations, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A computer-implemented system includes a processing device configured to receive a plurality of user and blood vessel characteristics associated with a user, generate a selected set of user and blood vessel characteristics, determine, based on the selected set of the user and blood vessel characteristics, a probability that angiogenesis will occur, and generate, based on the probability and the selected set of the user and blood vessel characteristics, a treatment plan that includes one or more exercises directed to modifying the probability that angiogenesis will occur, and a treatment apparatus configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

Abstract: 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.