Excerpt:
How real-time signal processing and adaptive algorithms improve intuitive prosthetic control.
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Content:
Introduction
Modern prosthetic hardware has evolved significantly over the past decade. Lightweight materials, modular components, and embedded systems have improved durability and comfort. However, intuitive control remains one of the biggest technical challenges.
At TRYZMEY, we focus on translating EMG signals into precise and reliable movement through adaptive control systems.
The Challenge of EMG Signal Variability
Electromyographic (EMG) signals are inherently noisy and inconsistent. Muscle fatigue, electrode placement, and environmental factors all affect signal stability.
Traditional fixed algorithms often struggle to maintain performance under changing conditions.