Hands-On Deep Learning for IoT

Use case one

We used an LSTM five-layered architecture for the ECG data classification, as shown in the following diagram:

We can train and test the model by running the LSTM_ECG.py file available in the chapter's code folder named use-case-1 subfolder:

python LSTM_ECG.py

For the ECG data in the remote patient-management system, we also tested and validated a CNN model. The following diagram presents the CNN architecture we used for the ECG dataset. As we can see, the CNN architecture consists of four convolutional layers:

We can train and ...