Photoplethysmogram Analysis and Applications: An Integrative Review

Area of Science:

• Biomedical Engineering
• Physiological Monitoring
• Signal Processing

Background:

• Photoplethysmogram (PPG) technology is expanding beyond clinical settings for everyday physiological monitoring.
• Existing research covers PPG generation, measurement, clinical uses, noise, and signal processing techniques.
• A comprehensive review from an engineering perspective is needed to consolidate current knowledge.

Purpose of the Study:

• To systematically review and synthesize research on photoplethysmogram (PPG) signal processing.
• To examine PPG generation, measurement principles, clinical applications, noise sources, and processing techniques.
• To provide an engineering-focused overview of the current state and future directions in PPG research.

Main Methods:

• Extensive literature search conducted across PubMed, Google Scholar, IEEE, ScienceDirect, and Web of Science databases.
• Inclusion of 118 articles, with exclusion of non-English publications.
• Categorization of research into four main themes: PPG waveform, features and applications, noise, and signal processing.

Main Results:

• Identified key areas: PPG waveform characteristics, feature extraction for clinical applications, common noise types (motion artifact, baseline wander, hypoperfusion), and signal processing steps (preprocessing, peak detection, quality index).
• The application scope of PPG has broadened significantly from clinical environments to mobile and wearable devices.
• Lack of a standardized preprocessing pipeline due to diverse data acquisition methods.

Conclusions:

• The review consolidates current understanding of photoplethysmogram (PPG) technology from an engineering standpoint.
• Machine learning-based methods show promise for addressing challenges in PPG signal processing and standardization.
• Continued research is essential to optimize PPG for reliable physiological monitoring in diverse environments.