Cardiac signal quality check and feature extraction pipeline using morphological features for stress level estimation

An electronic device comprising:

• a sensor;
• at least one memory;
• at least one processor operatively connected with the sensor and the at least one memory, the at least on processor configured to:
• receiving, from the sensor, a photoplethysmography (PPG) signal about a user;
• divide the received PPG signal into a first set of waveforms;
• check qualities of the first set of waveforms and generate a second set of waveforms based on the checked qualities of the first set of waveforms;
• extract a plurality of morphological features of each waveform of the second set of waveforms and calculate a plurality of time/amplitude factors based on the extracted plurality of morphological features;
• estimate, using an artificial intelligence model, a stress level of the user, based on the calculated plurality of time/amplitude factors;
• and
• provide the estimated stress level to the user.

A computer-implemented method comprising:

• receiving, from a sensor of an electronic device, a photoplethysmography (PPG) signal about a user;
• determining whether a noise of the PPG signal is equal to or higher than a threshold;
• based on a determination that the noise of the PPG signal is equal to or higher than the threshold, dividing the received PPG signal into a first set of waveforms;
• checking qualities of the first set of waveforms and generating a second set of waveforms based on the checked qualities of the first set of waveforms;
• extracting a plurality of morphological features of each waveform of the second set of waveforms and calculating a plurality of time/amplitude factors based on the extracted plurality of morphological features;
• estimating, using an artificial intelligence model, a stress level of the user, based on the calculated plurality of time/amplitude factors;
• and
• providing the estimated stress level to the user.