BioSynth-EMG: Physics-Informed Generative Framework for Synthetic Myoelectric Signals
A physics-based synthetic EMG signal generator for training low-latency neural networks in prosthetic control systems.
Features
- Biomechanical Layer: Motor unit firing rate simulation using Poisson distribution
- Electrical Propagation Layer: MUAP generation with Hermite functions
- Realistic Noise: Gaussian noise, power line interference, and movement artifacts
- High Performance: Optimized for GTX 1650 (<1ms generation for 1s signal)
- Dataset Generation: 8-channel EMG with gesture labels and force values
Installation
pip install -r requirements.txt
Usage
from biosynth_emg import BioSynthGenerator
generator = BioSynthGenerator()
data = generator.generate_dataset(num_samples=1000, duration=1.0)
Paper
Based on "BioSynth-EMG: A Physics-Informed Generative Framework for Synthetic Myoelectric Signal Synthesis and Prothetic Control Benchmarking"
1 maintainer
Metadata
1 maintainer
Release files for biosynth-emg 0.1.0
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| biosynth_emg-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 40.4 kB
Release files / biosynth_emg-0.1.0.tar.gz
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