Sensors measure variables such as position, force, and movement while the system software interprets that information. Actuators then provide controlled assistance or resistance based on the measured performance. This feedback relationship allows the robotic system to guide movement precisely and repeat treatment conditions, supporting consistent practice during rehabilitation.
Software changes the level of assistance or resistance in response to a patient’s performance. A system may therefore support impaired movement when greater guidance is needed or provide resistance when the patient can contribute more actively. This adjustment connects motor performance with treatment intensity and supports individualized rehabilitation rather than a fixed mechanical task.
Assistance can help a patient practice a task-specific movement that remains difficult after neurological or musculoskeletal damage. Resistance provides a way to challenge movement when the patient can perform more of the task independently. Because both inputs are controlled by the robotic system, treatment can remain precise and repeatable while task demands change.
Robotic therapy brings together biomechanics, control systems, human-machine interaction, and rehabilitation science. Biomechanics relates the device to human movement, control systems regulate assistance or resistance, and human-machine interaction addresses how a person engages with the system. Their integration helps engineers connect mechanical performance with rehabilitation goals and patient-specific treatment.
The system measures the patient’s movement using position, force, and movement sensors, then applies controlled assistance or resistance through its actuators. Software adjusts the task according to observed performance while the patient practices intensive, task-specific movements. Throughout the session, the system can record quantitative information that supports assessment of progress.
Robotic therapy may support rehabilitation after stroke, spinal cord injury, or musculoskeletal damage, especially when impaired motor function limits movement practice. Its ability to deliver intensive, task-specific training makes it relevant when repeated exercise and controlled task difficulty are important. Recorded measurements also allow researchers to examine recovery using quantitative progress data.
In addition to guiding or resisting movement, these systems record quantitative measures of performance. Such data can help track changes in motor function over the course of rehabilitation and support evidence-based recovery strategies. For engineering research, the measurements also connect sensor outputs and control settings with observed patient performance.