Example of simple AI(Artificial Neural Network) Application On ECG Data

I think AI can be applied in signal processing to process data such as ECG and gait data.

The words I type in Grok to generate the graphs are as below: 

Can you generate python code to draw a graph of raw ECG data and another graph where artificial neural network is perform on the raw data to recognize the real pattern of the ECG data, label the graph

Explanation from Grok
I'll provide Python code to visualize raw ECG data and apply a simple artificial neural network (ANN) to process the data, attempting to recognize patterns (e.g., denoising or feature enhancement). The ANN will be basic, as ECG pattern recognition typically requires domain-specific preprocessing and labeled data for tasks like QRS detection or arrhythmia classification. Since no specific ECG dataset is provided, I'll generate synthetic ECG-like data for demonstration. The code will include two labeled plots: one for raw ECG data and one for the ANN-processed output.Assumptions

• We'll use numpy to generate synthetic ECG data mimicking a periodic signal with P, QRS, and T waves.
• The ANN will be a simple feedforward neural network (using tensorflow/keras) trained to denoise or reconstruct the ECG signal.
• We'll add noise to the raw data to simulate real-world conditions and train the ANN to recover the clean signal.
• Libraries required: numpy, matplotlib, tensorflow.