PPGSynth: An Innovative Toolbox for Synthesizing Regular and Irregular Photoplethysmography Waveforms

Area of Science:

• Biomedical Engineering
• Digital Health Technologies
• Cardiovascular Signal Processing

Background:

• Photoplethysmography (PPG) is vital in digital health, particularly in smartwatches, for monitoring heart activity.
• PPG signal analysis is crucial for cardiovascular disease research.
• A significant gap exists in publicly available datasets of arrhythmic PPG signals.

Purpose of the Study:

• To develop and provide a publicly accessible toolbox for synthesizing realistic arrhythmic photoplethysmography (PPG) signals.
• To address the scarcity of arrhythmic PPG datasets for research and algorithm development.
• To enable the generation of diverse PPG signal types, including regular and irregular heartbeats.

Main Methods:

• A PPG synthesis model based on two combined Gaussian functions for individual pulse generation.
• Implementation of functionalities to generate regular and three types of irregular heartbeats (compensation, interpolation, reset).
• Inclusion of adjustable parameters for sampling frequency, duration, and noise types (Gaussian, multi-frequency).

Main Results:

• Successful generation of synthesized PPG waveforms with controllable regular and irregular heartbeats.
• Capability to produce large datasets of simulated PPG signals with customizable noise.
• The toolbox allows for the creation of various types of arrhythmic PPG signals as defined by the model.

Conclusions:

• The developed toolbox provides a valuable resource for researchers by generating synthetic arrhythmic PPG data.
• This tool can enhance the testing and validation of algorithms designed for detecting and analyzing arrhythmias.
• The public availability of this PPG synthesis tool facilitates advancements in digital health and cardiovascular monitoring.