<ul><li>Upper limb myoelectric prostheses often use pattern recognition control systems translating EMG signals into movements.</li><li>Users struggle with producing distinct EMG patterns for reliable classification as prosthesis movement complexity increases.</li><li>A new 3D visual interface, the Reviewer, provides real-time insight into PR algorithm behavior, improving control performance and reducing cognitive load.</li><li>Study shows participants using the Reviewer achieved higher completion rates and improved PR performance compared to conventional visualization, enhancing myoelectric control training.</li></ul>

Visual Feedback of Pattern Separability Improves Myoelectric Decoding Performance of Upper Limb Prostheses

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