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RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

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Contactless Vital Sign Monitoring: A Review Towards Multi-Modal Multi-Task Approaches.

Ahmad Hassanpour¹, Bian Yang¹

¹Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU), 2815 Gjovik, Norway.

Sensors (Basel, Switzerland)

|August 14, 2025

Summary

This summary is machine-generated.

Contactless vital sign monitoring uses advanced AI and multi-modal sensing to assess health without physical touch. This technology integrates various sensors and learning methods for accurate, efficient, and privacy-conscious remote patient assessment.

Keywords:

contactless monitoring multi-modal sensing multi-task learning remote health monitoring vital sign sensing

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Area of Science:

Biomedical Engineering
Artificial Intelligence in Healthcare
Remote Sensing Technologies

Background:

Contactless vital sign monitoring offers a non-invasive approach to healthcare assessment.
The field is rapidly evolving with advancements in sensing technologies and AI.

Purpose of the Study:

To comprehensively review the state-of-the-art in contactless vital sign monitoring.
To emphasize multi-modal sensing and multi-task learning paradigms.
To analyze current technologies, challenges, and future directions.

Main Methods:

Systematic categorization of technologies by sensing modality (vision, radar, thermal, ambient).
Analysis of multi-modal sensor fusion techniques (signal, feature, decision, deep learning).
Exploration of multi-task learning frameworks for enhanced accuracy and efficiency.

Main Results:

AI has transformed the field from single-modality to sophisticated multi-modal systems.
Multi-modal fusion and multi-task learning improve vital sign extraction.
Key challenges include environmental robustness, variability, fusion complexity, and privacy.

Conclusions:

Contactless vital sign monitoring is a rapidly advancing field with significant potential.
Future directions include novel sensing, advanced fusion, new applications, and privacy preservation.
This review serves as a holistic reference for researchers and practitioners.