A Robot based Hybrid Lower-Limb System for Assist-As-Needed
Rehabilitation of Stroke Patients: Technical Evaluation and Clinical
Feasibility
Abstract
Background: Although early rehabilitation is important following a
stroke, severely affected patients have limited options for intensive
rehabilitation as they are often bedridden. To create a system for early
rehabilitation of lower extremities in severely affected patients, we
have combined the robotic manipulator ROBERT® and EMG-triggered FES and
developed a novel user-driven Assist- As-Needed (AAN) control approach.
The method is based on a state machine that can detect user movement
capability and provide different levels of assistance, as required by
the patient (no support, FES only, and simultaneous FES and mechanical
support).
Methods: To technically validate the system, we tested 10 able-bodied
participants who were instructed to perform specific behaviors to
trigger the desired system states while conducting knee extension and
ankle dorsal flexion exercise. In addition, the system was tested on two
stroke patients to establish the clinical feasibility.
Results: The technical validation showed that the state machine
correctly detected the participants’ behavior and activated the target
AAN state in more than 96% of the exercise repetitions. The clinical
feasibility test showed that the system successfully recognized the
patients’ movement capacity and activated assistive states according to
their needs, providing the minimal level of support required to perform
the exercise successfully.
Conclusions: The system was technically validated and preliminarily
proven clinically feasible. The present study shows that the novel
system can be used to deliver exercises with a high number of
repetitions while engaging the participants’ residual capabilities
through an effective AAN strategy.