Thermal Imaging for Contactless Cardiorespiratory and Sudomotor Response Monitoring

2026-02-12

Technology Category

• Computer Vision: Video Understanding & Activity Analysis
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Kernel Methods

Application Category

• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Thermal infrared imaging captures skin temperature changes driven by autonomic regulation and can potentially provide contactless estimation of electrodermal activity (EDA), heart rate (HR), and breathing rate (BR). While visible-light methods address HR and BR, they cannot access EDA, a standard marker of sympathetic activation. This paper characterizes the extraction of these three biosignals from facial thermal video using a signal-processing pipeline that tracks anatomical regions, applies spatial aggregation, and separates slow sudomotor trends from faster cardiorespiratory components. For HR, we apply an orthogonal matrix image transformation (OMIT) decomposition across multiple facial regions of interest (ROIs), and for BR we average nasal and cheek signals before spectral peak detection. We evaluate 288 EDA configurations and the HR/BR pipeline on 31 sessions from the public SIMULATOR STUDY 1 (SIM1) driver monitoring dataset. The best fixed EDA configuration (nose region, exponential moving average) reaches a mean absolute correlation of $0.40 \pm 0.23$ against palm EDA, with individual sessions reaching 0.89. BR estimation achieves a mean absolute error of $3.1 \pm 1.1$ bpm, while HR estimation yields $13.8 \pm 7.5$ bpm MAE, limited by the low camera frame rate (7.5 Hz). We report signal polarity alternation across sessions, short thermodynamic latency for well-tracked signals, and condition-dependent and demographic effects on extraction quality. These results provide baseline performance bounds and design guidance for thermal contactless biosignal estimation.

Problem

• thermal imaging
• contactless monitoring
• electrodermal activity
• heart rate
• breathing rate

Innovation

• thermal imaging
• contactless biosignal monitoring
• electrodermal activity (EDA)
• orthogonal matrix image transformation (OMIT)
• autonomic nervous system