I'm conducting research on photoplethysmography (PPG) signals obtained from smartwatches worn on the wrist. The main goal is to analyze the PPG waveform and extract key fiducial points and derivatives.

However, most existing open-source libraries, such as pyPPG, seem to be primarily oriented towards analyzing finger PPG signals.

I'm looking for recommendations on the best open-source libraries or tools specifically designed for working with wrist-based PPG signals. The key features I'm interested in are:

1. Preprocessing and filtering of the raw PPG signal

2. Detecting and extracting main fiducial points (e.g., peaks, onsets, dichrotic notches)

3. Calculating derivatives of the PPG waveform

4. Handling potential challenges specific to wrist-based PPG, such as motion artifacts or lower signal quality compared to finger PPG

If you have experience in this domain, I would greatly appreciate your insights and recommendations on the most suitable open-source libraries or any tips for adapting existing tools for wrist PPG analysis.

Thank you in advance for your help!