4-Stage ECG Segmentation (SEG-4-TCN-SM)
Overview
Section titled “Overview”The following table provides the latest pre-trained model for 4-class ECG segmentation. Below we also provide additional details including training configuration, performance metrics, and downloads.
| NAME | DATASET | FS | DURATION | # CLASSES | MODEL | PARAMS | FLOPS | METRIC |
|---|---|---|---|---|---|---|---|---|
| SEG-4-TCN-SM | LUDB, Synthetic | 100Hz | 2.5s | 4 | TCN | 7K | 2.1M | 86.3% F1 |
- Sensor: ECG
- Location: Wrist
- Sampling Rate: 100 Hz
- Frame Size: 2.5 seconds
Class Mapping
Section titled “Class Mapping”Identify each of the P-wave, QRS complex, and T-wave.
| Base Class | Target Class | Label |
|---|---|---|
| 0-NONE | 0 | NONE |
| 1-PWAVE | 1 | PWAVE |
| 2-QRS | 2 | QRS |
| 3-TWAVE | 3 | TWAVE |
Datasets
Section titled “Datasets”The model is trained on the following datasets:
Model Performance
Section titled “Model Performance”The confusion matrix for the segmentation 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 |