Real-Time Health Monitoring Using Smart Wearable Spectroscopy Sensors With AI
A newly published review in the journal Advanced Materials explores how intelligent wearable sensors, powered by smart materials and machine learning, are changing healthcare into a decentralized, personalized, and predictive modeling system. An international team of researchers highlights emerging technologies that promise earlier diagnosis, improved therapy, and continuous health monitoring—anytime, anywhere.
Close up view of microchip spectrum sensor embedded in skin © BoOm
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Imagine a world where your shirt tracks your vital signs, your watch detects early signs of disease, and your smartphone alerts your doctor before symptoms even appear. This is no longer science fiction. In a recent review published in Advanced Materials, a team of international researchers presents an in-depth analysis of how intelligent wearable sensors—enhanced by smart materials and artificial intelligence (AI)—are poised to change global healthcare systems in a dramatic way (1,2).
The study, titled "Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence," was authored by Shuwen Chen, Shicheng Fan, Zheng Qiao, and others. The authors represent Oslo Metropolitan University in Norway and the National University of Singapore (1).
Merging Materials and Machine Learning
The review presents a comprehensive overview of how smart materials—such as self-healing polymers, responsive substances, and metamaterials—are redefining the physical capabilities of wearable sensors. These materials endow sensors with greater flexibility, durability, and sensitivity, enabling real-time measurement of vital signs and biochemical markers without disrupting daily life (1).
However, the authors emphasize that raw data alone is insufficient. To turn sensor input into actionable healthcare insights, AI and machine learning (ML) models are essential. When paired with these advanced materials, ML algorithms can analyze massive volumes of physiological data to detect patterns, diagnose conditions, and even forecast health crises before they occur (1). Such systems could monitor for the onset of viral infections and help monitor future pandemic crises (1,2).
Spectroscopy Meets AI in Wearable Design
A particularly innovative aspect of the study is the integration of spectroscopic techniques—traditionally confined to labs—into compact, wearable platforms. Photodiodes and light-responsive materials, such as azobenzene-based liquid crystal polymers, are embedded in smart wearables to detect ultraviolet (UV) exposure, glucose levels, and more. These sensors operate like mini spectrometers, converting optical signals into electrical data streams that AI algorithms interpret in real time (1,2).
For instance, one example cited in the paper involves wearable broadband UV dosimeters using miniaturized photodiode arrays. These devices, small enough to fit on a fingernail, precisely monitor solar exposure and support therapies like photodynamic treatment (1).
Challenges in Clinical Adoption
Despite the promise, the authors note several practical challenges. Ensuring data integrity, minimizing calibration errors, and preventing environmental interference remain top priorities. AI models must also avoid biases due to unrepresentative training data. For example, a model trained on young users might yield inaccurate results when applied to elderly populations, potentially leading to misdiagnosis (1,2).
Additionally, the review underscores the need for demand-driven innovation—developing materials based on real-world healthcare needs, not vice versa. This includes tailoring smart materials for specific sensing conditions, such as non-invasive glucose monitoring or drug metabolism tracking (1).
Future of Personalized, Patient-Centric Care
As wearable devices become smarter and more autonomous, the fusion of smart materials and ML holds the key to truly personalized medicine. These devices will no longer just monitor; they will recommend, alert, and even adapt in real-time based on a user’s health profile (1).
Looking ahead, the authors advocate for user-friendly design, regulatory clarity, improved power solutions, and enhanced cybersecurity. By addressing these areas, wearable technologies could shift the healthcare paradigm—from hospital-centric treatment to proactive, continuous care delivered through intelligent devices worn and tracked every day (1).
This forward-looking review paper charts a bold future where health monitoring is seamless, diagnostics are predictive, and care is truly individualized. By marrying smart materials with artificial intelligence, wearable sensors are not just gadgets—they are becoming essential spectroscopy tools in reshaping how healthcare is delivered worldwide (1,2).
References
(1) Chen, S.; Fan, S.; Qiao, Z.; Wu, Z.; Lin, B.; Li, Z.; Riegler, M. A.; Wong, M. Y. H.; Opheim, A.; Korostynska, O.; Nielsen, K. M. Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence. Adv. Mater. 2025, n/a, 2500412. DOI: 10.1002/adma.202500412
(2) Khan, B.; Khalid, R. T.; Wara, K. U.; Masrur, M. H.; Khan, S.; Khan, W.; Amara, U.; Abdullah, S. Reshaping the Healthcare World by AI-Integrated Wearable Sensors Following COVID-19. Chem. Eng. J. 2025, n/a, 159478. DOI: 10.1016/j.cej.2025.159478
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