Tyler R. Ray

Advances in wearable sensing technology are driving a new era of personalized health monitoring. In contrast to the hard, rigid form factors of conventional wearable sensors, these emerging skin-interfaced systems support high-quality physiological measurements across biophysical, biochemical, and kinematic signals of interest. These platforms enable continuous monitoring of complex physiological processes with unprecedented detail as a result of a seamless, conformal skin interface and advanced wireless communications capabilities. These platforms integrate flexible materials, miniaturized electronics, and wireless communication to provide detailed physiological data during daily activities. This review examines how skin-interfaced wearables are advancing patient care, remote monitoring, and large-scale health studies. We highlight critical barriers to clinical adoption including interpreting data, validating devices, and integration into health care systems. Key opportunities include sustainable manufacturing, point-of-care fabrication, and development of disease-specific digital biomarkers. By addressing these challenges through collaboration among engineers, clinicians, and data scientists, wearable sensors can expand patient access to advanced physiological monitoring and transform personalized medicine.

Acoustic forces offer a powerful, contact-free modality for manipulating particles and fluids within microfluidic lab-on-a-chip systems. However, realizing the full potential of acoustic manipulation has been constrained by conventional cleanroom-based fabrication methods. Typically formed from high-acoustic-impedance materials like silicon or glass, these processes yield devices with limited design complexity owing to the planar channel geometries inherent in micromachining. Here, we introduce a class of polymer-based acoustofluidic platforms fabricated using micro-digital light processing (μDLP) 3D printing. In contrast to micromachining, this additive manufacturing approach enables complex, truly three-dimensional (3D) microfluidic architectures in a monolithic device form factor. We demonstrate strategies to overcome challenges associated with low-acoustic-impedance polymer resins and establish design rules based on precise control over channel and surrounding material dimensions (e.g., wall thicknesses) to achieve robust acoustofluidic functions including efficient sharp-edge-based mixing and effective particle focusing using a bulk acoustic wave resonance mode. By leveraging the design freedom provided by additive manufacturing, we fabricated an integrated, monolithic device driven by a single piezoelectric element that sequentially performs acoustic mixing and focusing within spatially distinct regions enabled by engineered variations in the 3D channel structure. This work establishes μDLP additive manufacturing as a key enabler for next generation acoustofluidic platforms by demonstrating how true 3D architectural control over channel geometry can yield integrated, multifunctional polymer acoustofluidic devices with an expanded functional design space.

Enzyme-mimicking nanomaterials (nanozymes) promise robust alternatives to biological catalysts for continuous health monitoring, yet achieving sufficient catalytic activity remains challenging. Here, multimetallic medium-entropy oxide (MEO) nanoparticles incorporating five transition metals (Fe, Co, Mn, Ni, Cu) demonstrate exceptional dual-mode biosensing capabilities. A facile, one-pot microwave-assisted synthesis process yields nanoparticles (12 nm diameter, configurational entropy of 1.41 R) with abundant oxygen vacancies and mixed-valence states that serve as highly active catalytic centers. When integrated with graphene oxide, the MEO creates a robust platform for nonenzymatic electrochemical detection of the stress hormone cortisol, achieving a low limit of detection (LOD) of 1.9 nM and a high sensitivity of 46.5 ± 1.9 μA μM^-1 cm^-2. The material also exhibits powerful peroxidase-like activity, enabling dual-mode colorimetric sensing. This system provides a "signal-on" response for hydrogen peroxide (H₂O₂) detection with a LOD of 2.2 μM and a selective "signal-off" response for glutathione (GSH) quantification (LOD: 0.01 μM) through an inhibitory binding mechanism. Mechanistic studies establish that the versatile catalytic performance originates from the synergistic interplay between M(II)/M(III) redox cycling, superoxide radical generation at oxygen vacancies, and efficient electron transfer. The entropy-stabilized structure maintains 92% of its activity over 20 days without refrigeration. These findings establish multimetallic entropy engineering as a powerful strategy for creating stable, high-performance nanozymes suitable for wearable biosensors and point-of-care diagnostics.

Background: As large language models (LLMs) become increasingly accessible to the public, patients are turning to these tools for medical guidance — including in highly specialized fields like interventional neuroradiology. Despite their growing use, the safety, completeness, and reliability of LLM-generated information in subspecialty medicine remain unclear. Methods: Five publicly available LLMs — ChatGPT, Gemini, Claude, Perplexity, and DeepSeek — were prompted with four neurointerventional patient-facing clinical questions spanning ischemic stroke, hemorrhagic stroke, venous disorders, and procedural device use. Each model was queried three times per question to generate unique responses. Eight blinded raters scored each response on accuracy, completeness, safety, and actionability using Likert scales. Plagiarism analyses were also performed. Results: DeepSeek consistently outperformed other LLMs in accuracy, completeness, and actionability across four prompts, while Gemini frequently ranked worse, including in plagiarism levels. ChatGPT performed well in accuracy. Physicians were more critical than non-physicians across accuracy, completeness, and safety, whereas non-physicians rated actionability significantly lower. Overall, LLMs were rated relatively high (median of >4 on a 5-point scale) in medical safety, suggesting low risk of overtly harmful advice. Conclusion: Recent-generation LLMs offer medically safe, though often incomplete or imprecise, information in response to patient-oriented neurointerventional queries. Including non-physician raters revealed valuable differences in perception that are relevant to how patients may interpret LLM outputs. As benchmark frameworks like HealthBench improve LLM evaluation, inclusion of lay perspectives and subspecialty contexts remains essential. Responsible use by clinicians and ongoing patient education will be critical as LLM use in healthcare expands.

Enzyme-mimicking nanomaterials (nanozymes) promise robust alternatives to biological catalysts for continuous health monitoring, yet achieving sufficient catalytic activity remains challenging. Here, multimetallic medium-entropy oxide (MEO) nanoparticles incorporating five transition metals (Fe, Co, Mn, Ni, Cu) demonstrate exceptional dual-mode biosensing capabilities. A facile, one-pot microwave-assisted synthesis process yields nanoparticles (12 nm diameter, configurational entropy of 1.41 R) with abundant oxygen vacancies and mixed-valence states that serve as highly active catalytic centers. When integrated with graphene oxide, the MEOs serve as a robust platform for non-enzymatic electrochemical detection of the stress hormone cortisol, achieving a low limit of detection (LOD) of 1.9 nM and a high sensitivity of 46.5 ±1.9 A M-1 cm-2. The material also exhibits powerful peroxidase-like activity, enabling dual-mode colorimetric sensing. This system provides a "signal-on" response for hydrogen peroxide (H₂O₂) detection with a LOD of 2.2 µM and a selective "signal-off" response for glutathione (GSH) quantification (LOD: 0.01 µM) through an inhibitory binding mechanism. Mechanistic studies establish that the versatile catalytic performance originates from a synergy between M(II)/M(III) redox cycling, the generation of superoxide radicals at oxygen vacancies, and efficient electron transfer. The entropy-stabilized structure maintains 92% activity over 20 days without refrigeration. These findings establish multimetallic entropy engineering as a powerful strategy for creating stable, high-performance nanozymes suitable for wearable biosensors and point-of-care diagnostics.

Acoustic forces offer a powerful, contact-free modality for manipulating particles and fluids within microfluidic lab-on-a-chip systems. However, realizing the full potential of acoustic manipulation has been constrained by conventional cleanroom-based fabrication methods. Typically formed from high-acoustic-impedance materials like silicon or glass, these processes typically yield devices with limited design complexity owing to the planar channel geometries inherent in micromachine. Here, we introduce a class of polymer-based acoustofluidic platforms fabricated using micro-digital light processing (µDLP) 3D printing. In contrast to micromachining, this additive manufacturing approach enables complex, truly three-dimensional (3D) microfluidic architectures in a monolithic device form factor. We demonstrate strategies to overcome challenges associated with low-acoustic-impedance polymer resins and establish design rules based on precise control over channel and surrounding material dimensions (e.g., wall thicknesses) to achieve robust acoustofluidic functions including efficient sharp-edge-based mixing and effective particle focusing using a bulk acoustic wave resonance mode. By leveraging the design freedom provided by additive manufacturing, we fabricated an integrated, monolithic device driven by a single piezoelectric element that sequentially performs acoustic mixing and focusing within spatially distinct regions enabled by engineered variations in the 3D channel structure. This work establishes µDLP additive manufacturing as a key enabler for next generation acoustofluidic platforms by demonstrating how true 3D architectural control over channel geometry can yield integrated, multifunctional polymer acoustofluidic devices with an expanded functional design space.

Persistent disparities exist in access to state‐of‐the‐art healthcare disproportionately affecting underserved and vulnerable populations. Advances in wearable sensors enabled by additive manufacturing (AM) offer new opportunities to address such disparities and enhance equitable access advanced diagnostic technologies. Additive manufacturing provides a pathway to rapidly prototype bespoke, multifunctional wearable sensors thereby circumventing existing barriers to innovation for resource‐limited settings imposed by the need for specialized facilities, technical expertise, and capital‐intensive processes. This review examines recent progress in the additive manufacture of wearable platforms for physiological health monitoring. Supported by an initial overview of relevant techniques, representative examples of 3D printed wearable sensors highlight the potential for measuring clinically‐relevant biophysical and biochemical signals of interest. The review concludes with a discussion of the promise and utility of additive manufacturing for wearable sensors, emphasizing opportunities for expanding access to vital healthcare technology and addressing critical health disparities.

Recent advances in skin-interfaced wearable sweat sensors enable the noninvasive, real-time monitoring of biochemical signals associated with health and wellness. These wearable platforms leverage microfluidic channels, biochemical sensors, and flexible electronics to enable the continuous analysis of sweat-based biomarkers such as electrolytes, metabolites, and hormones. As this field continues to mature, the potential of low-cost, continuous personalized health monitoring enabled by such wearable sensors holds significant promise for addressing some of the formidable obstacles to delivering comprehensive medical care in under-resourced settings. This Perspective highlights the transformative potential of wearable sweat sensing for providing equitable access to cutting-edge healthcare diagnostics, especially in remote or geographically isolated areas. It examines the current understanding of sweat composition as well as recent innovations in microfluidic device architectures and sensing strategies by showcasing emerging applications and opportunities for innovation. It concludes with a discussion on expanding the utility of wearable sweat sensors for clinically relevant health applications and opportunities for enabling equitable access to innovation to address existing health disparities.

High entropy oxides (HEOs) are a class of materials that have garnered significant attention in recent years due to their potential use as catalysts in energy-related applications[1]. These materials are derived from high entropy compounds, which consist of equimolar or near equimolar ratios of multiple primary elements and have configurational entropy in the formation of a single-phase structure. The cocktail effect of HEOs gives rise to various catalytically active sites due to the synergistic interaction of the different elements, and lattice distortion during the formation of a single-phase solid solution results in the generation of abundant oxygen vacancies, which enhances the adsorption activity of HEOs and improves their catalytic performance[2]. HEOs can also be cost-efficient by utilizing low-cost transition metal elements as their active centers. Despite their widespread use as catalysts, the application of HEOs in electrocatalysis for molecule monitoring and early diagnosis remains largely unexplored. Cortisol, a glucocorticoid hormone that regulates many aspects of metabolism, stress, and immune response, is closely related to various diseases and disorders[3]. Current methods for noninvasive monitoring of cortisol relies upon immunological assays and typically limited to labor-intensive and time-consuming laboratory techniques. As a consequence, detecting cortisol in a label-free manner that is low cost and offers significant sensor stability and high sensitivity is desirable for many emerging applications, particularly for on-body monitoring. Here, we present work that examines the catalytic activities of HEOs as nanozymes for the electrocatalysis of cortisol. The electrochemical cortisol sensor is based on a novel one-pot microwave-assisted reaction synthesized (Fe, Co, Mn, Ni, Cu) Ox. The catalytic mechanism of electrochemical sensors depends on the formation of various valence metal redox species pairs, where the higher valence state oxidizes cortisol species present on the electrode surface, accompanied by a reduced lower valence state. The one-pot microwave-assisted synthesized HEOs exhibited ultra-high catalytic activity towards cortisol species as measured by cyclic voltammetry and chronoamperometry. Experimental results show a superior sensing performance including a detection limit as low as 0.5 µM (s/N=3), a good linear detection range between 0.01 ~ 4.01 µM, and a sensitivity of 46.5 µA µM-1 cm-2. References: [1] Y. Pan, J.-X. Liu, T.-Z. Tu, W. Wang, and G.-J. Zhang, “High-entropy oxides for catalysis: a diamond in the rough,” Chem. Eng. J., p. 138659, 2022. [2] D. Feng et al., “Holey lamellar high-entropy oxide as an ultra-high-activity heterogeneous catalyst for solvent-free aerobic oxidation of benzyl alcohol,” Angew. Chem., vol. 132, no. 44, pp. 19671–19677, 2020. [3] B. Wang et al., “Wearable aptamer-field-effect transistor sensing system for noninvasive cortisol monitoring,” Sci. Adv., vol. 8, no. 1, p. eabk0967, 2022.