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.

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

Abstract: A system for rehabilitation is disclosed. The system for rehabilitation includes one or more electronic devices comprising one or more memory devices storing instructions, one or more network interface cards, and one or more sensors, wherein the one or more electronic devices are coupled to a user. The system for rehabilitation further includes one or more processing devices operatively coupled to the one or more memory devices, the one or more network interface cards, and the one or more sensors. The one or more processing devices are configured to execute the instructions to receive information from the one or more sensors. The one or more processing devices are further configured to execute the instructions to transmit the information to a computing device controlling an electromechanical device, via the one or more network interface cards.

Abstract: A system includes a treatment apparatus configured to implement a treatment plan for rehabilitation to be performed by a user and a processing device configured to receive attribute data associated with the user; generate, based on the rehabilitation, selected attribute data; determine, based on the selected attribute data, the rehabilitation, and a rehabilitation goal associated with the rehabilitation, one or more probabilities of attaining the rehabilitation goal within respective one or more numbers of rehabilitation sessions to be performed by the user using the treatment apparatus; provide, based on the one or more probabilities, an indication of the one or more numbers of rehabilitation sessions; and generate, based on a selected number of rehabilitation sessions from among the one or more numbers of rehabilitation sessions, the treatment plan. The treatment plan includes one or more exercises directed to attaining the rehabilitation goal within the selected number of rehabilitation sessions.

Abstract: A computer-implemented system includes an electromechanical machine and a processing device communicatively coupled to motors. The processing device executes instructions to receive data comprising a treatment plan, wherein the treatment plan includes one or more prescribed exercises for a user to perform using the electromechanical machine; generate, based on the data and certain criteria, a motion profile for an assembly of the electromechanical machine, wherein the motion profile comprises a movement shape of one or more portions of the electromechanical machine; execute a transformation function to implement, using the electromechanical machine, a desired virtual apparatus model, wherein, to implement the desired virtual apparatus model, the transformation function maps the motion profile to one or more coordinates in a domain; and control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine.

Abstract: A method is disclosed for using an artificial intelligence engine to perform a control action. The control action is based on one or more measurements from a wearable device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive the one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the control action to be performed. The method includes receiving the one or more measurements from the wearable device being worn by a user, determining whether the one or more measurements indicate, during an interval training session, that one or more characteristics of the user are within a desired target zone, and responsive to determining that the one or more measurements indicate the one or more characteristics of the user are not within the desired target zone during the interval training session, performing the control action.

Abstract: A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan, and a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; identify at least one aspect of the treatment data pertaining to the user associated with a first treatment device mode of the treatment device; and, in response to a determination that the at least one aspect of the treatment data is correlated with at least one second condition of the user, generate second condition information indicating at least the second condition.

Abstract: 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.

Abstract: Systems, methods, and computer-readable mediums for modifying, by an artificial intelligence engine, a treatment plan for optimizing patient outcome and pain levels during treatment sessions. The system includes, in one implementation, a treatment apparatus, a patient interface, and a computing device. The treatment apparatus is configured to be manipulated by a patient while the patient performs the treatment sessions. The computing device is configured to receive the treatment plan for the patient and treatment data pertaining to the patient. The computing device is also configured to receive patient input from the patient interface correlating with the pain levels of the patient. The computing device is further configured to use the treatment plan, the treatment data, and the patient input to generate at least one threshold. Responsive to an occurrence of exceeding the at least one threshold, the computing device is configured to modify the treatment plan.

Abstract: A pedal assembly for electromechanical exercise or rehabilitation of a user is disclosed and can include pedals to engage appendages of a user. A spindle supports each pedal and has a spindle axis. A pedal arm assembly is located between the spindle and a rotational axle of the equipment. The pedal arm assembly is radially offset from the spindle axis to define a range of radial adjustability for the pedal relative to the rotational axle. The pedal arm assembly can include an electrically-actuated coupling assembly to adjust the radial position of the pedal in response to a control signal, and regulate motion of the user engaged with the pedals.

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.

Abstract: A pedal assembly for electromechanical exercise or rehabilitation of a user is disclosed and can include pedals to engage appendages of a user. A spindle supports each pedal and has a spindle axis. A pedal arm assembly is located between the spindle and an axle. The pedal arm assembly is radially offset from the spindle axis to define a range of adjustability for the pedal relative to the axle. The pedal arm assembly can include an electrically-actuated coupling assembly to adjust the position of the pedal in response to a control signal, and regulate motion of the user engaged with the pedals.

Abstract: A computer-implemented system includes a treatment apparatus configured to implement a treatment plan while the treatment apparatus is being manipulated by a user and a processing device configured to receive a plurality of risk factors, each of the plurality of risk factors being associated with one or more medical events or outcomes for a user; generate a set of the risk factors; determine, based on the set of the risk factors and measurement information associated with the user, one or more individual probabilities that the one or more medical events or outcomes will occur while the treatment apparatus is being manipulated by the user; and perform, based on the one or more individual probabilities, one or more corrective actions associated with the one or more medical events or outcomes.

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. Each of the respective portions comprises a graphical element that presents, in real-time or near real-time, at least one type of the selected measurement information.

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 computer-implemented system for a remote examination is disclosed. The computer-implemented system includes a treatment device, a master console, a user interface, and a control system. The treatment device comprises one or more slave sensors and a slave pressure system, the treatment device configured to be manipulated while a patient performs a treatment plan. The master console comprises a master device. The user interface comprises an output device configured to present telemedicine information associated with a telemedicine session. The control system comprises one or more processing devices operatively coupled to the master console and the treatment device.

Abstract: A computer-implemented system for a remote examination is disclosed. The computer-implemented system includes a treatment device, a master console, a user interface, and a control system. The treatment device comprises one or more slave sensors and a slave pressure system, the treatment device configured to be manipulated while a patient performs a treatment plan. The master console comprises a master device. The user interface comprises an output device configured to present telemedicine information associated with a telemedicine session. The control system comprises one or more processing devices operatively coupled to the master console and the treatment device.

Abstract: 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.

Abstract: A system for rehabilitation is disclosed. The system for rehabilitation includes a monitoring device that includes a memory device storing instructions and a network interface card. The monitoring device is configured to detect information from a body part of a user. The system for rehabilitation further includes one or more processing devices operatively coupled to the monitoring device. The one or more processing devices are configured to execute the instructions to receive configuration information specified in a treatment plan for rehabilitating the body part of the user. The one or more processing devices are configured to execute the instructions for receiving the information from the monitoring device. The one or more processing devices are further configured to execute the instructions to transmit the configuration information and the information to a computing device controlling an electromechanical device, via the network interface card.

Abstract: A system includes an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan. The system also includes a computing device configured to: receive treatment data pertaining to the user who uses the electromechanical machine to perform the treatment plan; and modify at least one aspect of the treatment plan in response to receiving treatment plan input including at least one modification to the at least one of the at least one aspect and any other aspect of the treatment plan; and control, based on the modification, the operation of the electromechanical machine.