A computer-implemented system includes a treatment device configured to be manipulated by a user while the user performs a treatment plan, a patient interface, and a computing device configured to: receive treatment; write to an associated memory, configured to be accessed by an artificial intelligence engine, treatment data, the artificial intelligence engine being configured to use at least one machine learning model to, using the treatment data, generate at least one of a treatment scheduling output prediction and an appointment output; receive, from the artificial intelligence engine, the at least one of the treatment scheduling output prediction and the appointment output; and selectively modify, using the at least one of the treatment scheduling output prediction and the appointment output, the at least one aspect of the treatment plan.

A pedal assembly for an exercise and rehabilitation device can include a disk having an axis of rotation. A central aperture can be formed in the disk along the axis. Spokes can extend radially from adjacent the central aperture toward a perimeter of the disk. The disk can be formed from a first material. In addition, a crank can be coupled to one of the spokes of the disk. The crank can have a hub concentric with the central aperture. Pedal apertures can extend along a radial length of the crank. The crank can be formed from a metallic material that differs from the first material. A pedal having a spindle can be interchangeably and releasably mounted to the pedal apertures in the crank.

In one embodiment, a computer-implemented system includes treatment apparatuses configured to be manipulated by patients while performing an exercise session, patient interfaces associated with the plurality of patients, and a server computing device configured to receive first characteristics pertaining to the patients, and initiate a virtual shared session on the patient interfaces associated with the patients. The virtual shared session includes at least a set of multimedia feeds, and each multimedia feed of the set of multimedia feeds is associated with one or more of the patients. During the virtual shared session, the server computing device may present a first layout including the set of multimedia feeds, the first characteristics, or some combination thereof.

A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan, a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session, 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 at least one measurement pertaining to the user associated with a first treatment device mode of the treatment device; determine whether the at least one aspect of the measurement correlates with a secondary condition of the user; and, in response to a determination that the at least one aspect of the at least one measurement is correlated with the at least one secondary condition of the user, generate secondary condition information indicating at least the secondary condition.

A computer-implemented system includes a treatment device configured to be manipulated by a user while the user performs a treatment plan, a patient interface, and a computing device configured to: receive treatment; write to an associated memory, configured to be accessed by an artificial intelligence engine, treatment data, the artificial intelligence engine being configured to use at least one machine learning model to, using the treatment data, generate at least one of a treatment scheduling output prediction and an appointment output; receive, from the artificial intelligence engine, the at least one of the treatment scheduling output prediction and the appointment output; and selectively modify, using the at least one of the treatment scheduling output prediction and the appointment output, the at least one aspect of the treatment plan.

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.

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.

An exercising apparatus for exercising at least one limb, having a supporting frame and at least one crank which is arranged on a rotation shaft assigned to the supporting frame, and having at least one limb support which can be fastened to the at least one crank at different radial distances from the rotation shaft. A detector is provided for detecting the radial distance of the at least one limb support from the rotation shaft. The invention further relates to a limb support and to a method for determining the force acting on a limb support of an exercising apparatus.

A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan, a patient interface. and a computing device configured to: receive treatment data pertaining to the user who uses the treatment device to perform the treatment plan; identify at least one enhanced component using the treatment data; generate an enhanced environment using the at least one enhanced component and the treatment plan; output at least one aspect of the enhanced environment to at least one of the patient interface and another interface; receive subsequent treatment data pertaining to the user; and selectively modify at least one of the enhanced environment and at least one of the at least one aspect of the treatment plan and any other aspect of the treatment plan using the subsequent treatment data.

In one embodiment, a computer-implemented system includes a treatment apparatus configured to be manipulated by a user while performing an exercise session, patient interfaces associated with users, and a server computing device configured to receive treatment data pertaining to the user, determine whether at least one characteristic of the user matches at least one second characteristic of a second user, where the second user belonging to a cohort. Responsive to determining the at least one characteristic of the user matches the at least one second characteristic of the second user, the server computing device is configured to assign the user to the cohort and select, via a trained machine learning model, a treatment plan for the user. Responsive to transmitting a signal to the patient interfaces of users in the cohort, the server computing device enables the patient interfaces to establish the virtual shared session between the patient interfaces.