A gait evaluation apparatus that evaluates a training gait of a paralyzed patient suffering from paralysis in a leg includes an acquisition unit configured to acquire a plurality of motion amounts of a paralyzed body portion according to a gait motion and an evaluation unit configured to evaluate that the gait motion is an abnormal gait in a case where at least one of the motion amounts acquired by the acquisition unit meets any one of a plurality of abnormal gait criteria set in advance. The abnormal gait criteria include at least two or more first criteria, which are criteria relevant to motion amounts of different parts of the paralyzed body portion, or at least two or more second criteria, which are criteria relevant to motion amounts of the same part of the paralyzed body portion in different directions.

A body harness system includes a body harness having a first portion for providing resting position to a user. The body harness includes a plurality of belts with offset buckles connected to the body of the first portion, for supporting body of the user. A first pair of shoulder straps are connected at a first end and an undercarriage support is connected at a second end of the first portion. An abdominal support is connected to the undercarriage support via abdominal support connection straps. The undercarriage support runs from the second end of the first portion to the abdominal support, for supporting the user's groin area. The body harness system includes an elastic cord support system connected to one or more attachment rings, for controlling at least one of initial bodyweight offset, amount of bodyweight resistance, and maximum allowable downward stop for each user.

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.

An adjustable knee ankle foot orthosis for unloading weight from a knee joint afflicted with osteoarthritis, thus reducing pain and improving mobility, comprising: an upper and lower frame connected by an unloading hinge assembly, optionally comprising a sensor and processor allowing for remote or automatic control of brace tension. In embodiments, the brace includes a user mechanism that is capable of adjusting a tensioning element while the brace is being worn. In other embodiments, electronic motors, sensors, and indicators may be included in the brace to improve brace performance and user interaction.

The present invention discloses a system for assisting a mobility-impaired individual or a patient. The system includes a track that mounts to a ceiling or wall of a structure such as a home. The track receives a sliding mechanism. The sliding mechanism connects to a strap hanging arrangement. The strap hanging arrangement connects to a vest. The vest connects to a leg support mechanism. The mobility-impaired individual wears the vest and the leg support mechanism. The sliding mechanism includes a lift strap for adjusting the height of the strap hanging arrangement thereby allowing the mobility-impaired individual to be placed in a sitting position or standing position. The mechanically driven mechanism moves along the track allowing the mobility-impaired individual to move around the structure.

An acquisition unit acquires a classification result obtained by classifying training assistants by performing a cluster analysis based on first rehabilitation data about rehabilitation performed by the trainee by using the rehabilitation support system, the first rehabilitation data including at least assistant data indicating a training assistant and index data indicating a degree of recovery of the trainee. A learning unit generates a learning model, the learning model being configured to input second rehabilitation data including at least the action data indicating an assisting action performed by the training assistant to assist the trainee and output the action data for suggesting a next action to be performed by the training assistant. The learning unit generates the learning model by using, as teacher data, the second rehabilitation data for which pre-processing has been performed based on the classification result.

A walking training device according to the present embodiment includes: a robot leg attached to one leg of a trainee; a treadmill; a load distribution sensor that detects a distribution of a load received from a sole of the trainee riding on the belt of the treadmill; and a walking state determination unit that determines whether the one leg has switched from a standing state to a swinging state based on a state of increase in a load detected by the load distribution sensor and received from another leg of the trainee performing walking training; and a control unit that starts bending control for the swinging state of the robot leg when the walking state determination unit determines that the one leg has switched from the standing state to the swinging state.

A processing system capable of educating a training assistant, who assists a trainee when the trainee performs rehabilitation by using a walking training apparatus, in order to enable the training assistant to appropriately assist the trainee is provided. The processing system includes a determination unit and an output unit. The determination unit determines an adjustment-required parameter, the adjustment-required parameter being, among parameters that can be adjusted in a walking training apparatus, a parameter of which a frequency of adjustments by a training assistant who assists a trainee performing walking training in the walking training apparatus or by an assistant in a hospital other than the training assistant is lower than an adjustment criterion. The output unit outputs parameter information indicating the adjustment-required parameter and effect information indicating an adjustment effect that is obtained when the adjustment-required parameter is adjusted.

A learning unit of a learning system generates a learning model, the learning model being configured to input rehabilitation data about rehabilitation and predict feedback control to be performed, the rehabilitation being performed by a trainee using a rehabilitation support system. The rehabilitation support system performs the feedback control based on motivation information of the trainee. The rehabilitation data includes at least training data including the motivation information of the trainee and feedback information indicating the feedback control. The learning unit generates the learning model by using, as teacher data, the rehabilitation data that is obtained when the motivation information is one that causes such a change that the motivation of the trainee is improved.

The rehabilitation training system includes: an evaluation unit configured to evaluate rehabilitation training performed by a trainee; a storage unit configured to store a plurality of evaluation comments regarding the evaluation; a reception unit configured to receive, from an authorized training assistant, designation of an evaluation comment that is restricted from being presented to a specific trainee among the plurality of evaluation comments; a selection unit configured to select an evaluation comment to be presented to the specific trainee from the plurality of evaluation comments based on the evaluation for the rehabilitation training of the specific trainee that is performed by the evaluation unit and the designation; and a presentation unit configured to present the evaluation comment selected by the selection unit.