A groundbreaking development in wearable health technology has emerged from Zhejiang University, where researchers have engineered a novel computationally-assisted wearable system capable of continuous cortisol monitoring. This device, termed the Continuous Wearable System for Cortisol Continuous Monitoring (CWSCCM), elegantly integrates cutting-edge molecular imprinting chemistry, advanced organic bioelectronics, and innovative sweat stimulation techniques to enable real-time, non-invasive stress assessment. This advance signifies a pivotal step toward continuous, personalized stress management with profound implications for medicine and wellness.
Cortisol, a central biomarker of stress, fluctuates throughout the day following a circadian rhythm and is intricately linked with psychological states, metabolic health, and chronic diseases. Traditional cortisol sensing methods rely heavily on invasive sampling procedures such as venipuncture combined with sophisticated laboratory techniques like liquid chromatography-tandem mass spectrometry (LC-MS/MS) or immunoassays. These methods are not optimized for frequent or daily monitoring due to their invasiveness, complexity, and requirement of specialized facilities. The CWSCCM addresses these critical limitations by capitalizing on sweat as a biofluid matrix, leveraging iontophoresis to stimulate sweat secretion, and employing an electrochemical biosensor that faithfully transduces cortisol concentrations into electrical signals.
At the heart of this wearable system lies a molecularly imprinted polymer (MIP) specifically engineered to recognize cortisol molecules with high fidelity. The team utilized density functional theory (DFT) computations to systematically screen a set of monomer candidates, aiming to maximize binding affinity and selective recognition toward cortisol. Pyrrole emerged as the optimal monomer, balancing strong molecular interactions with favorable electrochemical properties. This computationally informed molecular design transcends traditional trial-and-error approaches, facilitating precise receptor fabrication. The MIP layer’s regenerability is particularly notable; by applying a mild negative potential, the receptor surface is electrically reset, enabling repeated sensing cycles without the need for chemical washing or sensor replacement. This on-site electrical regeneration offers an unprecedented combination of reusability and real-time responsiveness.
Complementing the recognition element is an organic electrochemical transistor (OECT) that serves as the signal transducer. By engineering channel geometries with optimized width-to-length (W/L) ratios, the research delineated that a ratio of 40 yields peak transconductance, approximately 1.8 millisiemens, which translates to an 85-fold amplification over conventional electrochemical sensors. This enhancement significantly boosts signal-to-noise ratios, reduces power consumption, and streamlines scalable manufacturing via screen printing techniques. The OECT operates in depletion mode, maintaining stable performance even after integration with the MIP, thereby sustaining reliable electrical characteristics critical for continuous in-situ monitoring.
Detection sensitivity and selectivity were rigorously evaluated using a spectrum of physiologically relevant fluids. The biosensor exhibited a robust, concentration-dependent response to cortisol in phosphate-buffered saline, artificial sweat, and human saliva. The limit of detection attained was as low as 0.36 nanomolar in sweat, affirming the system’s capability to detect physiologically pertinent cortisol levels. This sensitivity is coupled with high selectivity against structurally related steroid hormones and potential interfering substances typical in sweat matrices. Benchmarking against enzyme-linked immunosorbent assay (ELISA) results confirmed analytical accuracy, further certifying the device’s reliability for clinical and consumer applications.
The wearable system architecture incorporates a screen-printed iontophoretic sweat stimulator that noninvasively induces sweat secretion directly from the skin. A vertical microfluidic chamber is integrated for precise sweat sample capture and channeling toward the sensing region. The entire assembly is encapsulated within a 3D-printed soft polymer housing providing mechanical protection and shielding the electronics from moisture-induced degradation. This holistic device design facilitates stable operation over prolonged periods, permitting continuous cortisol monitoring throughout waking hours.
Extensive on-body trials validated the CWSCCM’s efficacy in capturing real-time cortisol dynamics. The device successfully recorded circadian fluctuations in cortisol levels between early morning and late evening in human subjects, mirroring known endocrine rhythms. Additionally, acute cortisol elevations following aerobic exercise were detected, demonstrating the system’s responsiveness to physiological stressors. Data transmitted wirelessly to a mobile application provided a convenient interface for continuous health tracking and stress management.
This innovation opens new frontiers in personalized healthcare by enabling closed-loop biofeedback systems. The seamless integration of computational chemistry, advanced bioelectronics, and flexible wearable forms sets a new standard for real-world biomarker monitoring. Continuous cortisol measurement empowers users and clinicians alike to gain unprecedented insight into stress-related health. Potential applications extend beyond wellness into chronic disease management, mental health therapy, and adaptive drug delivery, heralding a future where therapeutic interventions are dynamically guided by real-time biochemical data.
The researchers’ multidisciplinary approach underscores the power of combining theoretical computations with scalable manufacturing strategies to produce robust, high-performance biosensors. The employment of density functional theory for receptor optimization exemplifies how modern computational tools can accelerate the development of functional biointerfaces. Likewise, the adoption of screen-printed organic electrochemical transistors illustrates how organic electronics can revolutionize biological signal detection, blending sensitivity with practicality.
As wearable devices become increasingly central to digital health ecosystems, innovations like the CWSCCM highlight the importance of non-invasive, continuous monitoring technologies that harmonize user comfort with scientific rigor. The electrical regeneration feature addresses one of the longstanding challenges in continuous sensing—sensor fouling and loss of sensitivity—thereby extending device longevity and measurement accuracy. This capability is expected to catalyze wider adoption of biosensing platforms in daily life.
Moving forward, the integration of such wearable biosensors with artificial intelligence and cloud computing could enable personalized stress prediction and intervention protocols. Real-time data analytics derived from continuous cortisol tracking have the potential to uncover new correlations between stress patterns and health outcomes, fueling preventive medicine initiatives. Furthermore, miniaturization and cost-reduction strategies may broaden accessibility, making these sophisticated health monitors ubiquitous companions in the quest for optimal well-being.
In conclusion, the CWSCCM developed by Zhejiang University researchers exemplifies a paradigm shift in biosensing technology, marrying molecular design, organic electronics, and wearable systems to unlock continuous, actionable insights into human stress physiology. This innovation not only bridges the gap between laboratory diagnostics and everyday health monitoring but also paves the way for personalized, closed-loop healthcare solutions that respond intelligently to the body’s biochemical signals in real time.
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Subject of Research: Continuous Cortisol Monitoring Using Wearable Biosensors
Article Title: Wearable System Enables Continuous Cortisol Monitoring for Stress Management
Web References: http://dx.doi.org/10.1016/j.scib.2025.03.060
Image Credits: ©Science China Press
Keywords
Life sciences, Applied sciences and engineering, Health and medicine
