Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence

S Shuwen Chen S Shicheng Fan Z Zheng Qiao Z Zixiong Wu B Baobao Lin (Department of Biomedical Engineering National University of Singapore Singapore 117583 Singapore) Z Zhijie Li (Molecular Medicine Program, The Hospital for Sick Children) M Michael A. Riegler M Matthew Yu Heng Wong (School of Clinical Medicine University of Cambridge Cambridge CB2 1TN UK) A Arve Opheim (Sunnaas Rehabilitation Hospital Bjoernemyr 1453 Norway) O Olga Korostynska (Department of Mechanical Electronic and Chemical Engineering (MEK) Faculty of Technology Art and Design TKD Oslo Metropolitan University OsloMet Oslo 0166 Norway) K Kaare Magne Nielsen (Department of Life Science and Health Faculty of Health Sciences Oslo Metropolitan University OsloMet Oslo 0130 Norway) T Thomas Glott (Sunnaas Rehabilitation Hospital Bjoernemyr 1453 Norway) A Anne Catrine T. Martinsen (Sunnaas Rehabilitation Hospital Bjoernemyr 1453 Norway) V Vibeke H. Telle‐Hansen (Intelligent Health Faculty of Health Sciences and Faculty of Technology Art and Design Oslo Metropolitan University OsloMet Oslo 0130 Norway) C Chwee Teck Lim (Department of Biomedical Engineering, National University of Singapore)

Abstract

Abstract Intelligent wearable sensors, empowered by machine learning and innovative smart materials, enable rapid, accurate disease diagnosis, personalized therapy, and continuous health monitoring without disrupting daily life. This integration facilitates a shift from traditional, hospital‐centered healthcare to a more decentralized, patient‐centric model, where wearable sensors can collect real‐time physiological data, provide deep analysis of these data streams, and generate actionable insights for point‐of‐care precise diagnostics and personalized therapy. Despite rapid advancements in smart materials, machine learning, and wearable sensing technologies, there is a lack of comprehensive reviews that systematically examine the intersection of these fields. This review addresses this gap, providing a critical analysis of wearable sensing technologies empowered by smart advanced materials and artificial Intelligence. The state‐of‐the‐art smart materials—including self‐healing, metamaterials, and responsive materials—that enhance sensor functionality are first examined. Advanced machine learning methodologies integrated into wearable devices are discussed, and their role in biomedical applications is highlighted. The combined impact of wearable sensors, empowered by smart materials and machine learning, and their applications in intelligent diagnostics and therapeutics are also examined. Finally, existing challenges, including technical and compliance issues, information security concerns, and regulatory considerations are addressed, and future directions for advancing intelligent healthcare are proposed.

Article Details

Volume / Issue Vol. 37, Issue 21
Published May 01, 2025
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (15)

S

Shuwen Chen

S

Shicheng Fan

Z

Zheng Qiao

Z

Zixiong Wu

B

Baobao Lin

Department of Biomedical Engineering National University of Singapore Singapore 117583 Singapore

Z

Zhijie Li

Molecular Medicine Program, The Hospital for Sick Children

M

Michael A. Riegler

M

Matthew Yu Heng Wong

School of Clinical Medicine University of Cambridge Cambridge CB2 1TN UK

A

Arve Opheim

Sunnaas Rehabilitation Hospital Bjoernemyr 1453 Norway

O

Olga Korostynska

Department of Mechanical Electronic and Chemical Engineering (MEK) Faculty of Technology Art and Design TKD Oslo Metropolitan University OsloMet Oslo 0166 Norway

K

Kaare Magne Nielsen

Department of Life Science and Health Faculty of Health Sciences Oslo Metropolitan University OsloMet Oslo 0130 Norway

T

Thomas Glott

Sunnaas Rehabilitation Hospital Bjoernemyr 1453 Norway

A

Anne Catrine T. Martinsen

Sunnaas Rehabilitation Hospital Bjoernemyr 1453 Norway

V

Vibeke H. Telle‐Hansen

Intelligent Health Faculty of Health Sciences and Faculty of Technology Art and Design Oslo Metropolitan University OsloMet Oslo 0130 Norway

C

Chwee Teck Lim

Department of Biomedical Engineering, National University of Singapore