How to generate a PPG signal using symmetrical curve fitting method (SCF)? How is it different from Gaussian curve fitting?

I am trying to generate a PPG signal which matches the morphologies of signals from TBME database using SCF method other than adding two Gaussian functions.

Answer 1

[Raghav]

Hi,

Based on your question, I understand that you want to know about generating PPG signal using SCF.

The symmetrical curve fitting (SCF) method is a technique used to generate a photoplethysmography (PPG) signal from a raw PPG signal. This method involves fitting a symmetrical curve to the PPG waveform, which can help to remove noise and other artifacts from the signal.

1. To generate a PPG signal using the SCF method, follow these steps:
2. Acquire a raw PPG signal using a PPG sensor.
3. Pre-process the PPG signal to remove noise and artifacts.
4. Identify the peaks and valleys of the PPG signal
5. Fit a symmetrical curve to the PPG signal using a mathematical function such as a Gaussian or Lorentzian function.
6. Adjust the curve parameters to optimize the fit to the PPG signal.
7. Use the fitted curve to generate a PPG signal that is free from noise and artifacts.

Compared to Gaussian curve fitting, the SCF method involves fitting a symmetrical curve to the PPG waveform rather than a Gaussian function. The main advantage of using a symmetrical curve is that it can better capture the shape of the PPG waveform, which may have different slopes on the rising and falling edges. In contrast, a Gaussian function assumes a symmetrical shape, which may not accurately represent the PPG waveform.

Overall, the SCF method can be an effective technique for generating a clean PPG signal from a raw signal, but it requires careful optimization of the curve parameters to ensure accurate fitting.

Hope it helps

Thanks,

Raghav Bansal