ForeverBlue816/PhysioWave
[NeurIPS 2025] PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
This project provides pre-trained models and tools to interpret complex physiological data like ECG and EMG signals. It takes raw heart or muscle activity recordings and helps classify them for various medical or research applications, identifying patterns such as arrhythmias or gestures. Medical researchers, clinicians, and biosignal processing engineers can use this to analyze and understand physiological signals more effectively.
181 stars.
Use this if you need to accurately classify patterns in physiological signals (like ECG for heart conditions or EMG for muscle activity) using robust, pre-trained models.
Not ideal if you're working with non-physiological time-series data or if you require real-time, low-latency analysis on embedded devices.
Stars
181
Forks
25
Language
Python
License
MIT
Category
Last pushed
Oct 20, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ForeverBlue816/PhysioWave"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
iver56/audiomentations
A Python library for audio data augmentation. Useful for making audio ML models work well in the...
Rikorose/DeepFilterNet
Noise supression using deep filtering
torchsynth/torchsynth
A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.
marl/openl3
OpenL3: Open-source deep audio and image embeddings
archinetai/audio-data-pytorch
A collection of useful audio datasets and transforms for PyTorch.