Model Zoo
A number of pre-trained models are available for download to use in your own project. These models are trained on the datasets listed below and are available in Keras and TensorFlow Lite flatbuffer formats.
Signal Denoising Task
The following table provides the latest performance and accuracy results for denoising models.
NAME | DATASET | FS | DURATION | MODEL | PARAMS | FLOPS | METRIC |
---|---|---|---|---|---|---|---|
DEN-TCN-SM | Synthetic, PTB-XL | 100Hz | 2.5s | TCN | 3.3K | 1.0M | 18.1 SNR |
DEN-TCN-LG | Synthetic, PTB-XL | 100Hz | 2.5s | TCN | 6.3K | 1.8M | 19.5 SNR |
DEN-PPG-TCN-SM | Synthetic | 100Hz | 2.5s | TCN | 3.5K | 1.1M | 92.1% COS |
Signal Segmentation Task
The following table provides the latest performance and accuracy results for ECG segmentation models.
NAME | DATASET | FS | DURATION | # CLASSES | MODEL | PARAMS | FLOPS | METRIC |
---|---|---|---|---|---|---|---|---|
SEG-2-TCN-SM | LUDB, Synthetic | 100Hz | 2.5s | 2 | TCN | 2K | 0.42M | 96.6% F1 |
SEG-4-TCN-SM | LUDB, Synthetic | 100Hz | 2.5s | 4 | TCN | 7K | 2.1M | 86.3% F1 |
SEG-4-TCN-LG | LUDB, Synthetic | 100Hz | 2.5s | 4 | TCN | 10K | 3.9M | 89.4% F1 |
SEG-PPG-2-TCN-SM | Synthetic | 100Hz | 2.5s | 2 | TCN | 4K | 1.43M | 98.6% F1 |
Rhythm Classification Task
The following table provides the latest performance and accuracy results for rhythm classification models.
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 |
ARR-4-EFF-SM | LSAD | 100Hz | 5s | 4 | EfficientNetV2 | 27K | 1.6M | 95.9% F1 |
Beat Classification Task
The following table provides the latest performance and accuracy results for beat classification models.
NAME | DATASET | FS | DURATION | # CLASSES | MODEL | PARAMS | FLOPS | METRIC |
---|---|---|---|---|---|---|---|---|
BC-2-EFF-SM | Icentia11k | 100Hz | 5s | 2 | EfficientNetV2 | 28K | 1.8M | 97.7% F1 |
BC-3-EFF-SM | Icentia11k | 100Hz | 5s | 3 | EfficientNetV2 | 41K | 2.1M | 92.0% F1 |
Reproducing Results
Each pre-trained model has a corresponding configuration.json
file that can be used to reproduce the model and results.
To reproduce a pre-trained rhythm model with configuration file configuration.json
, run the following command:
To evaluate the trained rhythm model with configuration file configuration.json
, run the following command: