Biomimetic NMES controller for arm movements supported by a passive exoskeleton.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Technology

Background:

• The MUNDUS project aims to create an assistive platform for daily upper limb function recovery.
• Developing effective control strategies for neuroprosthetics is crucial for restoring arm reaching and hand function.

Purpose of the Study:

• To design a biomimetic controller for modulating neuromuscular electrical stimulation (NMES) for reaching movements.
• To support arm function using a passive exoskeleton and a novel NMES controller.
• To validate the controller's ability to replicate human movement patterns.

Main Methods:

• Experimental campaign on healthy subjects to record kinematics and EMG signals during reaching movements.
• Principal Component Analysis (PCA) on EMG data to identify stereotyped muscular strategies.
• Development of a time-delay artificial neural network controller mapping kinematics to EMG activations for NMES timing.
• Testing the feedforward controller on two healthy subjects for accuracy in reaching target positions.

Main Results:

• Movement kinematics were highly stereotyped with low trajectory errors (<5°).
• PCA revealed that a few components (<5) explained over 85% of EMG signal variance, indicating a consistent muscular strategy.
• The biomimetic controller accurately reproduced observed movement patterns and stimulation levels.
• The feedforward controller demonstrated good accuracy in reaching target positions.

Conclusions:

• Healthy subjects exhibit stereotyped kinematic and muscular strategies during reaching movements.
• A biomimetic NMES controller based on artificial neural networks can effectively replicate these natural movement patterns.
• The developed controller shows promise for assistive neuroprosthetics, with future integration of feedback control planned to enhance robustness.