| --- |
| library_name: pytorch |
| tags: |
| - ecg |
| - classification |
| - chronos-2 |
| - ltaf |
| - arrhythmia |
| license: mit |
| --- |
| |
| # LTAF ECG Beat Classifier (N / A / V) |
|
|
| Frozen **Chronos-2** (`amazon/chronos-2`) multivariate encoder + MLP head, |
| trained on the PhysioNet Long-Term Atrial Fibrillation (LTAF) database |
| for per-beat classification. |
|
|
| ## Classes |
|
|
| | Code | Expansion | |
| |------|-----------| |
| | N | Normal sinus-origin beat | |
| | A | Atrial premature contraction (APC / PAC / SVE) | |
| | V | Ventricular premature contraction (PVC / VE) | |
|
|
| `Q` (unclassifiable / paced, ~89 / 9 M in the LTAF subset) is dropped. |
|
|
| ## Input |
|
|
| - `(B, 2, 256)` — 2-lead ECG at **128 Hz**, 2-second window **centered on the R-peak sample** |
| - Per-channel z-scored |
| - LTAF leads: `ECG1`, `ECG2` |
|
|
| ## Checkpoint details |
|
|
| | Field | Value | |
| |---|---| |
| | `num_classes` | 3 | |
| | `class_names` | `["N", "A", "V"]` | |
| | `window_samples` | 256 (2 s @ 128 Hz) | |
| | `n_channels` | 2 | |
| | `chronos_model_id` | `amazon/chronos-2` | |
| | `freeze_encoder` | `true` (only the head's 395,267 params were trained) | |
| | Head | 2-layer MLP: `Linear(1024, 512) → ReLU → Dropout(0.3) → Linear(512, 3)` | |
|
|
| ## Usage |
|
|
| ```python |
| import torch |
| from huggingface_hub import hf_hub_download |
| from src.models.ts_llm.ecg_classifier import EcgRhythmClassifier |
| |
| path = hf_hub_download("rmxjck/ltaf-ecg-beats-classifier", "best_classifier.pt") |
| model = EcgRhythmClassifier.load(path, device="cuda") |
| |
| # x: (B, 2, 256) float32 at 128 Hz, z-scored, centered on R-peak |
| logits = model(x) |
| pred = logits.argmax(-1) # 0=N, 1=A, 2=V |
| ``` |
|
|
| ## Training |
|
|
| Produced by `scripts/train_ecg_classifier.py` in |
| [rmxjck/TSLM-Arena](https://github.com/) on the LTAF-Haystack split |
| (67 train / 8 val / 9 test records, deterministic seed 42). N beats are |
| subsampled per epoch to `negative_k × n_nonN` (default 2.0) to balance |
| the 97 % N / 1.7 % A / 1.5 % V class distribution. |
|
|
| ```bash |
| .venv/bin/python3 scripts/train_ecg_classifier.py \ |
| --label-class beats --epochs 30 --batch-size 128 |
| ``` |
|
|
| ## Not for clinical use |
|
|
| Research artifact only. Not FDA-cleared. Not suitable for triage, |
| diagnosis, or any patient-facing application. |
|
|
