A computer-implemented system may include an electromechanical 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 condition or a cardiac outcome, 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 of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.

A system for moving or assisting in movement of a body part of a subject, as well as a rehabilitation system including such a movement assistance system, includes a body part interface configured to be secured to the body part, and a motor-actuated assembly connected to the body part interface to move the body part interface to cause flexion or extension movement of the body part. A force sensing module is configured to measure forces applied between the body part interface and the motor-actuated assembly to ascertain at least one of volitional flexion and volitional extension movement of the body part by the subject, among other functions that may be implemented in movement assistance and rehabilitation systems using the disclosed force sensing module designs.

An exercise apparatus comprising: a frame; first and second vertical guides coupled to the frame; first and second carriages carried on the respective first and second vertical guides, each of the first and second carriages having an upper carriage portion, a lower carriage portion and a carriage locking mechanism operable to lock and release the lower carriage portion to a selected vertical position along the first and second vertical guides; and an exercise bar coupled to the upper carriage portion of the first and second carriages, the exercise bar operable to translate or rotate to actuate the carriage locking mechanism.

A walking training system includes: a tension unit that pulls a leg of a trainee upward and forward; a sensor provided for determining a start timing of a swinging end phase of the leg; and a control unit that reduces a tensile force of the tension unit from the start timing of the swinging end phase.

A wearable device may include a motor, a motor driver circuit, a frame connected to the motor, the frame to be worn on the body of the user to support the body, a processor configured to generate a control signal to control an electrical connection in the motor driver circuit, and a sensor configured to sense a body motion of the user. The processor is further configured to provide an exercise load through the frame according to a speed of the sensed body motion by controlling, based on the speed of the body motion, a changing ratio per time between a first control state in which the electrical connection in the motor driver circuit is a closed loop and a second control state in which the electrical connection in the motor driver circuit is an open loop.

A method for optimizing at least one exercise. An exercise apparatus is configured to enable a user to perform the at least one exercise. The method includes receiving user data. The method includes generating, based on the user data, initial target data. The method includes receiving measurement data associated with one or more sensors. The method includes determining, differential data. The determining is based on one or more differences between the initial target data and the measurement data. The method includes receiving cohort data. The method includes generating, via an artificial intelligence engine and based on the differential data, a machine learning model trained to generate message data based on a difference between the differential data and the cohort data. The method includes transmitting, to an interface associated with a user, a message to the user based on the message data.

A method includes receiving treatment data associated with a user capable of using a treatment device to perform a treatment plan. The method also includes receiving alignment data associated with the user while the user engages in at least one activity and receiving at least one alignment characteristic associated with the user and determining, using at least the at least one alignment characteristic, whether the at least one alignment characteristic correlates with at least one secondary condition of the user. The method also includes generating secondary condition information indicating at least the secondary condition and modifying at least one aspect of the treatment plan in response to receiving, from a healthcare professional, treatment plan input. The treatment plan input includes at least one modification to the at least one aspect of the treatment plan and wherein, further, the treatment plan input is generated based on the secondary condition information.

Rehabilitating an impaired body part of a subject such as a stroke patient includes systems, devices, and methods using an orthosis system configured to attach to the impaired body part and to move or assist in movement of the impaired body part. A control system is configured to operate the orthosis system in a mode in which the orthosis system first allows the subject to move volitionally or attempt to move volitionally the impaired body part in a predefined motion and then operates to move or assist in the predefined motion of the impaired body part. Additional modes of operation include a brain computer interface mode of operation and a mode in which the orthosis system operates in a continuous passive mode of operation comprising a plurality of repetitions of an exercise to move the impaired body part.

The present invention relates to a rehabilitation exercise system for upper and lower limbs, comprising: a rehabilitation exercise device for rehabilitation of arms or legs and an information processing terminal which is connected to the rehabilitation exercise device via a wireless communication network; wherein the rehabilitation exercise device comprises at least one type of sensors which detect a first information; wherein the information processing terminal is configured to transmit a second information to the rehabilitation exercise device via the wireless communication network; wherein the rehabilitation exercise device is configured to control a rehabilitation exercise load based on the first information and the second information. Therefore, it is possible to provide a more efficient rehabilitation by controlling a rehabilitation exercise load of the rehabilitation exercise device based on the first information detected by the rehabilitation exercise device and the second information received from the information processing terminal.

A walking training system according to the present embodiment includes: a treadmill; a load distribution sensor; an imaging device that takes an image of a trainee; a specifying unit that specifies, from the image taken by the imaging device, whether a load detected by a load distribution sensor is a load received from a sole of a right leg of the trainee or a load received from a sole of a left leg of the trainee; and a determination unit that determines, based on a status of a load received from a sole of one leg, out of the right leg and the left leg of the trainee during walking training, in a standing state that is detected by the load distribution sensor, whether the sole of the one leg in the standing state is located within a load detection area of the load distribution sensor.