Study on the Establishment Process of Muscle Synergy Based on Cosine Similarity
Summary
This study reveals a "building-stability-weakening" process in muscle synergy establishment. Extracting synergy patterns from stable segments of data significantly reduces calculation time for non-negative matrix factorization (NMF), improving exoskeleton control.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Robotics
Background:
- Muscle synergy is crucial for motor intention recognition in rehabilitation exoskeleton control.
- Non-negative matrix factorization (NMF) for synergy extraction is computationally intensive, limiting real-time application.
- Existing methods face challenges with long calculation times and low effectiveness due to large datasets.
Purpose of the Study:
- To investigate the muscle synergy establishment process.
- To propose an optimized method for faster synergy pattern extraction.
- To enhance the real-time control capabilities of rehabilitation exoskeletons.
Main Methods:
- Extracted synergy matrices from complete single-cycle and segmented electromyography (EMG) signals.
- Analyzed cosine similarity variations between segmented and complete single-cycle synergy matrices.
- Identified a
- building-stability-weakening
- process in muscle synergy establishment.
Main Results:
- Muscle synergy exhibits a
- building-stability-weakening
- pattern during establishment.
- Extracting synergy modes from "stable" data segments yields results comparable to using complete single-cycle data.
- Reduced data usage via segmented extraction significantly optimizes NMF calculation time.
Conclusions:
- Optimized NMF for muscle synergy extraction by utilizing partial data from stable segments.
- Improved real-time performance for synergy mode extraction, crucial for motion intention recognition.
- The proposed method holds significant implications for advancing rehabilitation exoskeleton control systems.
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