A computer-implemented method is disclosed. The method includes determining a maximum target heart rate for a user using an electromechanical machine to perform a treatment plan, wherein the electromechanical machine is configured to be manipulated by the user while the user is performing the treatment plan. The method includes receiving, via an interface, an input pertaining to a perceived exertion level of the user, wherein the interface comprises a display configured to present information pertaining to the treatment plan. Based on the perceived exertion level and the maximum target heart rate, the method includes determining an amount of resistance for the electromechanical machine to provide via one or more pedals physically or communicatively coupled to the electromechanical machine. While the user performs the treatment plan, the method includes causing the electromechanical machine to provide the amount of resistance.

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.

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.

In a first aspect, a method is provided that includes the steps of (1) providing a monitor for determining a level of exercise performance performed by an exerciser and for outputting a signal representative of the performance level; (2) using the monitor to measure a level of exercise performance performed by an exerciser; (3) outputting from the monitor a signal representative of the performance level; (4) providing a video game having a character, the video game inputting and being responsive to the performance level signal output by the monitor, the video game using the performance level signal to control a performance level of the video game character; and (5) while the exerciser is not exercising, controlling a performance level of the video game character based on a performance level signal output by the monitor.

A system and method for a mixed or virtual reality-enhanced stationary exercise bicycle, comprising a stationary bicycle device, a belt-like attachment, and a mechanical arm attachment attached to the base of a stationary bike, used for measuring and determining user position for virtual or mixed reality-enhanced software.

A system and method for a mixed or virtual reality-enhanced stationary exercise bicycle, comprising a stationary bicycle device, a belt-like attachment, and a mechanical arm attachment attached to the base of a stationary bike, used for measuring and determining user position for virtual or mixed reality-enhanced software.

Techniques for configuring an exercise machine to operate according to a predefined workout regimen are described. The exercise machine includes exercise apparatus portion that is controlled and configured at least in part by a computing system portion. The computing system receives an operator selection of a selected predefined workout regimen, and operator data including at least operator gender, operator height and operator age and the computing system retrieves parameter data to configure an exercise instruction that is part of the selected workout regimen. The parameter data is retrieved from a database that stores at least range of motion data and maximum weight data searchable by a cohort, e.g., gender/height cohorts or gender/age cohorts and converts the retrieved parameter data into settings data to configure corresponding portions of the exercise apparatus according to the configured exercise instruction.

A physical exercise apparatus includes a frame, a seat, an arm, and a pair of cycling hand pedals. The seat is supported by the frame and is configured to support a user in an at least partially supine position. The arm is movably attached to a first portion of the frame and coupled with a linearly movable resistance load. The pair of cycling hand pedals is attached to a second portion of the frame and is independently movable from the arm so that the user can cycle the pair of cycling hand pedals while separately moving the arm with a portion of his or her lower body.

An exercise machine may include a frame with foot pedals mounted thereon and a seat having an inflatable bladder whereby the user may undertake a cardiovascular workout and a core workout of abdominal and back muscles.

A stationary bicycle includes a lever arm that is pivotable about a pivot axis. A biasing device rotatably biases the lever arm about the pivot axis. The lever arm is swept through a horizontal plane when rotated about the pivot axis. A user rotates the lever arm against the bias while pedaling to preload the body for a desired therapeutic effect.