3-Class Beat Classification (BEAT-3-EFF-SM)
Overview
Section titled “Overview”The following table provides the latest pre-trained model for 3-class beat classification. Below we also provide additional details including training configuration, performance metrics, and downloads.
| NAME | DATASET | FS | DURATION | # CLASSES | MODEL | PARAMS | FLOPS | METRIC |
|---|---|---|---|---|---|---|---|---|
| BC-3-EFF-SM | Icentia11k | 100Hz | 5s | 3 | EfficientNetV2 | 41K | 2.1M | 92.0% F1 |
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
Section titled “Class Mapping”The model is able to distinguish between normal sinus rhythm (NSR), premature/ectopic atrial contractions (PAC), and premature/ectopic ventricular contractions (PVC). The class mapping is as follows:
| Base Class | Target Class | Label |
|---|---|---|
| 0-NSR | 0 | NSR |
| 1-PAC | 1 | PAC |
| 2-PVC | 2 | PVC |
Dataset
Section titled “Dataset”The model is trained on the following datasets:
Model Performance
Section titled “Model Performance”The confusion matrix for the model is depicted below.
Downloads
Section titled “Downloads”| Asset | Description |
|---|---|
| configuration.json | Configuration file |
| model.keras | Keras Model file |
| model.tflite | TFLite Model file |
| metrics.json | Metrics file |