2-Class Arrhythmia Classification (ARR-2-EFF-SM)
Overview
The following table provides the latest pre-trained model for 2-class arrhythmia classification. Below we also provide additional details including training configuration, performance metrics, and downloads.
| NAME | DATASET | FS | DURATION | # CLASSES | MODEL | PARAMS | FLOPS | METRIC |
|---|---|---|---|---|---|---|---|---|
| ARR-2-EFF-SM | Icentia11K, PTB-XL, LSAD | 100Hz | 5s | 2 | EfficientNetV2 | 18K | 1.2M | 99.5% F1 |
Input
- Sensor: ECG
- Location: Wrist
- Sampling Rate: 100 Hz
- Frame Size: 5 seconds
Class Mapping
The model is trained on raw ECG data and is able to discern normal sinus rhythm (NSR) from atrial fibrillation (AFIB) and atrial flutter (AFL). The class mapping is as follows:
| Base Class | Target Class | Label |
|---|---|---|
| 0-Normal | 0 | NSR |
| 7-AFIB, 8-AFL | 1 | AFIB |
Datasets
The model is trained on the following datasets:
Model Performance
The confusion matrix on the test set for the model is depicted below.
Downloads
| Asset | Description |
|---|---|
| configuration.json | Configuration file |
| model.keras | Keras Model file |
| model.tflite | TFLite Model file |
| metrics.json | Metrics file |