PROPORTIONAL ELECTROMYOGRAPHIC CONTROL OF A BIONIC ARM IN A PARTICIPANT WITH CHRONIC HEMIPARESIS, MUSCLE SPASTICITY,...

Area of Science:

• Biomedical Engineering
• Neurorehabilitation
• Robotics

Background:

• Stroke is a leading cause of disability, often resulting in hemiparesis.
• Current assistive exoskeletons lack fine motor control, offering only binary (on/off) functionality.
• Electromyographic (EMG) signals are crucial for controlling prosthetic and robotic devices.

Purpose of the Study:

• To investigate the feasibility of proportional EMG control for a bionic arm in a stroke patient with hemiparesis.
• To assess the performance of state-of-the-art EMG control algorithms with weak and spastic muscle activity.
• To compare control using paretic versus healthy arm EMG signals.

Main Methods:

• A case study involving one hemiparetic stroke patient using an EMG-controlled bionic arm.
• The participant performed a virtual target-touching task, grasping and extending.
• EMG data was collected from both the paretic and healthy arms for comparison.

Main Results:

• Proportional control was achieved for grasping with the paretic arm, despite reduced EMG signal-to-noise ratio.
• Extension task performance and EMG signal-to-noise ratio significantly decreased for the paretic arm.
• The participant successfully completed the task using EMG from the paretic arm, indicating potential for functional control.

Conclusions:

• State-of-the-art EMG control can provide proportional force regulation for assistive devices in some stroke patients with hemiparesis.
• Functional motor control information remains present in EMG signals despite hemiparesis.
• Further research with diverse patient populations is needed to validate and advance upper-limb exoskeleton control.