A palm-supported finger rehabilitation training device comprises a mounting base, a finger rehabilitation training mechanism mounted on the mounting base, and a driving mechanism for driving the finger rehabilitation training mechanism; wherein the finger rehabilitation training mechanism comprises four independent and structurally identical combined transmission devices for finger training corresponding to a forefinger, a middle finger, a ring finger and a little finger of a human hand, respectively, and the mounting base is provided with a supporting surface capable of supporting a human palm; wherein each combined transmission device for finger training comprises an MP movable chute, a PIP fingerstall, a DIP fingerstall and a connecting rod transmission mechanism; a force sensor is provided to acquire force feedback information to determine and control force stability, and a space sensor is provided to acquire space angle information to control space positions of fingers in real time.

An agility trainer apparatus that provides a robotic system that applies forces laterally to a harness worn by a person during walking so as to provide highly controllable interventions targeting locomotor stability.

When controlling load torque of a drive unit on the basis of a biological signal detected from a subject's lower limb parts, adjustments are made to a hybrid ratio of voluntary control to generate running torque and a rotational speed of a crank according to the subject's intention and autonomous control to generate assisting power for the subject's pedaling motion on the basis of a rotation angle of the crank.

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.

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.

A computer-implemented system may include a rowing 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 a processing device 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 rowing machine to implement the one or more exercises.

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.

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.

Exercise robot suitable for rehabilitation and methods of its operation are provided. In particular a method in which the exercise robot learns an exercise movement on the basis of movements conducted by the aid of a human assistant holding the leg of a patient and moving the leg with muscular form to conduct an exercise movement. The rehabilitation robot actively accompanies the exercise movement in an active compliance mode and records the movement so as to determine an exercise movement stored in the control unit of the device. The rehabilitation robot can then produce the determined exercise in an exercise mode.

Device (100) for assisting with mobilizing a joint (3) comprising a first and a second guiding element, the first flexible guiding element (102) being positioned on one of the segments (4), having a first pair of cable passages arranged on the side of the rear face (52) and on the side of the front face (54), the second flexible guiding element (104) being positioned on the other of the segments (5), having a first pair of cable passages, arranged on the side of the rear face (52) and on the side of the front face (54), the second guiding element further comprising a pair of anchoring points arranged on the side of the front face (52) and on the side of the rear face (54), a flexible support part on which a pair of actuators (M11, M12) associated with a pair of winders are arranged, to cause the associated winder to turn in the winding direction and the unwinding direction, and a pair of cables (C11, C12) extending from the winders, up to the anchoring points of the second guiding element, passing through the cable passages of the first pair of cable passages of the first and second guiding elements.