Your AI-powered scientific assistant for EMG and motor unit research. Ask questions about motor unit physiology, HDsEMG methods, decomposition algorithms, and more.
MUchat is trained on scientific literature and methodological resources in the field of EMG and motor unit research.
Recruitment, rate coding, synchronization, motor unit types, size principle, and neuromuscular adaptations.
High-density surface EMG recording techniques, electrode configurations, signal processing, and best practices.
Blind source separation, convolutive models, spike sorting, template matching, and validation methods.
MUchat can help with conceptual questions, methodological guidance, and technical troubleshooting.
"What is the size principle and how does it affect motor unit recruitment?"
"How do I set up an HDsEMG grid for recording the vastus lateralis?"
"What are the main differences between CKC and gradient convolution decomposition?"
"How can I validate my motor unit decomposition results?"
Get quick answers while learning the field and designing your experiments.
Troubleshoot recording issues and understand signal processing steps.
Quick reference for methods and literature when writing papers or reviewing.
MUchat is here to help you navigate the complex world of EMG and motor unit research.
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