Photoplethysmography for Measuring Cognitive Load in XR Environments: A Systematic Review

Abstract

Photoplethysmography (PPG) is a low-cost, low-power biosensing technology with growing applications in education, particularly for monitoring cognitive load in eXtended Reality (XR) learning environments. Measuring cognitive load is critical for preventing overload and optimising immersive learning, yet existing approaches such as self-reports or Electroencephalography (EEG) are often intrusive, costly or impractical for real-time use. This systematic review is the first to synthesize a decade of research (2015–2025) on the use of PPG for cognitive load measurement in XR. Twenty-three studies were identified and analysed according to PRISMA guidelines, with attention to sensor placement, integration with other modalities, research design, and analysis methods. Our findings show that PPG provides a reliable, portable, and scalable alternative to traditional physiological sensors. It is increasingly combined with EEG, Electrocardiography (ECG), and Galvanic Skin Response (GSR) to improve accuracy. However, most implementations rely on placement on the wrist and fingertips, leaving head-mounted integration for seamless XR use largely unexplored. Therefore, this review highlights research gaps in sensor placement, multimodal fusion, and real-time signal processing. It outlines promising directions such as headset-embedded PPG and machine learning–based feature extraction. By consolidating current evidence, this review provides a roadmap for researchers, XR developers, and educators seeking to leverage physiological monitoring for adaptive, learner-centered XR systems.

keywords: cognitive load, extended reality, photoplethysmography