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Electro-Stimulation System with Artificial-Intelligence-Based Auricular-Triggered Algorithm to Support Facial
Katharina Steiner1,2, Marius Arnz3,4, Gerd Fabian Volk3,4,5
1Department of Medical Engineering, University of Applied Sciences Upper Austria, 4020 Linz, Austria.
Diagnostics (Basel, Switzerland)
|October 16, 2024
Summary
This study developed an AI-powered system to help patients with facial palsy regain facial movements like smiling and blinking. The system uses auricular muscle signals to control electrical stimulation, improving quality of life.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Rehabilitation Technology
Background:
- Facial palsy significantly impairs quality of life, causing difficulties with smiling and eyelid closure.
- Chronic facial palsy with synkinesis presents persistent functional challenges for patients.
- A closed-loop electro-stimulation system offers a potential solution for restoring facial muscle function.
Purpose of the Study:
- To develop and evaluate an artificial intelligence (AI)-based closed-loop electro-stimulation system for facial palsy.
- To enable naturalistic facial movements such as eye closure, blinking, and smiling.
- To improve functional recovery and quality of life for individuals with facial palsy.
Main Methods:
- Utilized an AI-based auricular-triggered algorithm to classify intended facial movements.
- Employed surface electromyography (EMG) of extrinsic auricular muscles for movement classification.
- Delivered targeted surface electrical stimulation to activate appropriate facial muscles based on AI classification.
Main Results:
- Evaluated the system with 17 patients suffering from facial synkinesis.
- Assessed system performance using a simulation with previously recorded patient data.
- Achieved a median macro F1-score of 0.602 for facial movements on the synkinetic side.
Conclusions:
- The AI-based auricular-triggered system demonstrates potential in supporting facial movements for patients with unilateral chronic facial palsy and synkinesis.
- The developed system achieved a median macro F1-score of 0.602, indicating effective classification and stimulation.
- This technology offers a promising avenue for restoring function and enhancing the quality of life for individuals affected by facial palsy.
