Passive reach and grasp with functional electrical stimulation and robotic arm support

Area of Science:

• Biomedical Engineering
• Neurorehabilitation
• Robotics

Background:

• Restoring arm and hand function is vital for stroke survivors' independence.
• Current rehabilitation methods may not fully address complex motor deficits.
• Integrated systems offer potential for enhanced functional recovery.

Purpose of the Study:

• To assess the technical feasibility of a combined robotics and functional electrical stimulation (FES) system.
• To support reach, grasp, and release movements during object manipulation tasks.
• To evaluate system performance in both healthy and stroke subjects.

Main Methods:

• An integrated system combining a 3D robotic manipulator for reach and Model Predictive Control (MPC) based FES for grasp/release was developed.
• Subjects (stroke and healthy) performed passive reach, grasp, move, and release tasks with the system.
• System performance was quantified by task success rates.

Main Results:

• Healthy subjects achieved 33%-87% success in complete grasp, move, and release tasks.
• Severe chronic stroke subjects showed low success rates (<25%) for hand opening, with no complete movements.
• The system successfully moved passive arms and hands for pick-and-place tasks, but robot positioning accuracy was critical.

Conclusions:

• The integrated robotic and FES system demonstrates potential for post-stroke rehabilitation.
• Improvements in robot positioning accuracy and control are needed for optimal performance.
• Adaptive support reduction based on patient performance could facilitate motor relearning.