2-Class Beat Classification (BEAT-2-EFF-SM)
Overview
The following table provides the latest pre-trained model for 2-class beat classification task. Below we also provide additional details including training configuration, performance metrics, and downloads.
| NAME | DATASET | FS | DURATION | # CLASSES | MODEL | PARAMS | FLOPS | METRIC |
|---|---|---|---|---|---|---|---|---|
| BC-2-EFF-SM | Icentia11k | 100Hz | 5s | 2 | EfficientNetV2 | 28K | 1.8M | 97.7% F1 |
Input
The model is trained on 5-second, raw ECG frames sampled at 100 Hz.
- Sensor: ECG
- Location: Wrist
- Sampling Rate: 100 Hz
- Frame Size: 5 seconds
Class Mapping
The model is able to classify normal sinus rhythm (NSR) and premature atrial/ventricular contractions (PAC/PVC). The class mapping is as follows:
| Base Class | Target Class | Label |
|---|---|---|
| 0-NSR | 0 | NSR |
| 1-PAC, 2-PVC | 1 | PAC |
Datasets
The model is trained on the following datasets:
Model Performance
The confusion matrix for 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 |