End-to-end design of wearable sensors

Knowledge mapping and research trends of accidental falls in patients with Parkinson's disease from 2003 to 2023: a bibliometric analysis

Background

Recent years have witnessed a rapid growth in research on accidental falls in patients with Parkinson's Disease (PD). However, a comprehensive and systematic bibliometric analysis is still lacking. This study aims to systematically analyze the current status and development trends of research related to accidental falls in patients with PD using bibliometric methods.

Methods

We retrieved literature related to accidental falls in patients with PD published between January 1, 2003, and December 31, 2023, from the Web of Science Core Collection (WoSCC) database. Statistical analysis and knowledge mapping of the literature were conducted using VOSviewer, CiteSpace, and Microsoft Excel software.

Results

A total of 3,195 publications related to accidental falls in patients with PD were retrieved. These articles were authored by 13,202 researchers from 3,834 institutions across 87 countries and published in 200 academic journals. Over the past 20 years, the number of published articles and citations has increased annually. The United States and the United Kingdom have the highest number of publications in this field, while Harvard University and Tel Aviv University are the most influential institutions. The Parkinsonism & Related Disorders journal published the highest number of articles, while the Movement Disorders journal had the highest number of citations. The most prolific author is Bloem, Bastiaan R, while the most cited author is Hausdorff, Jeffrey. The main research areas of these publications are Neurosciences, Biomedical, Electrical & Electronic, and Biochemistry & Molecular Biology. Currently, high-frequency keywords related to accidental falls in patients with PD include risk factors, clinical manifestations, and interventions. Prediction and prevention of accidental falls in such patients is a research topic with significant potential and is currently a major focus of research.

Conclusion

This study used bibliometric and knowledge mapping analysis to reveal the current research status and hotspots in the field of accidental falls in patients with PD. It also points out directions for future research. This study can provide theoretical support and practical guidance for scholars to further conduct related research.

Unraveling the impact of therapeutic drug monitoring via machine learning for patients with sepsis

Clinical studies investigating the benefits of beta-lactam therapeutic drug monitoring (TDM) among critically ill patients are hindered by small patient groups, variability between studies, patient heterogeneity, and inadequate use of TDM. Accordingly, definitive conclusions regarding the efficacy of TDM remain elusive. To address these challenges, we propose an innovative approach that leverages data-driven methods to unveil the concealed connections between therapy effectiveness and patient data, collected through a randomized controlled trial (DRKS00011159; 10th October 2016). Our findings reveal that machine learning algorithms can successfully identify informative features that distinguish between healthy and sick states. These hold promise as potential markers for disease classification and severity stratification, as well as offering a continuous and data-driven "multidimensional" Sequential Organ Failure Assessment (SOFA) score. The positive impact of TDM on patient recovery rates is demonstrated by unraveling the intricate connections between therapy effectiveness and clinically relevant data via machine learning.

Sensing patches for biomarker identification in skin-derived biofluids

In conventional clinical disease diagnosis and screening based on biomarker detection, most analysis samples are collected from serum, blood. However, these invasive collection methods require specific instruments, professionals, and may lead to infection risks. Additionally, the diagnosis process suffers from untimely results. The identification of skin-related biomarkers plays an unprecedented role in early disease diagnosis. More importantly, these skin-mediated approaches for collecting biomarker-containing biofluid samples are noninvasive or minimally invasive, which is more preferable for point-of-care testing (POCT). Therefore, skin-based biomarker detection patches have been promoted, owing to their unique advantages, such as simple fabrication, desirable transdermal properties and no requirements for professional medical staff. Currently, the skin biomarkers extracted from sweat, interstitial fluid (ISF) and wound exudate, are achieved with wearable sweat patches, transdermal MN patches, and wound patches, respectively. In this review, we detail these three types of skin patches in biofluids collection and diseases-related biomarkers identification. Patch classification and the corresponding manufacturing as well as detection strategies are also summarized. The remaining challenges in clinical applications and current issues in accurate detection are discussed for further advancement of this technology (Scheme 1).

Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.

Materials, Structure, and Interface of Stretchable Interconnects for Wearable Bioelectronics

Since wearable technologies for telemedicine have emerged to tackle global health concerns, the demand for well-attested wearable healthcare devices with high user comfort also arises. Skin-wearables for health monitoring require mechanical flexibility and stretchability for not only high compatibility with the skin's dynamic nature but also a robust collection of fine health signals from within. Stretchable electrical interconnects, which determine the device's overall integrity, are one of the fundamental units being understated in wearable bioelectronics. In this review, a broad class of materials and engineering methodologies recently researched and developed are presented, and their respective attributes, limitations, and opportunities in designing stretchable interconnects for wearable bioelectronics are offered. Specifically, the electrical and mechanical characteristics of various materials (metals, polymers, carbons, and their composites) are highlighted, along with their compatibility with diverse geometric configurations. Detailed insights into fabrication techniques that are compatible with soft substrates are also provided. Importantly, successful examples of establishing reliable interfacial connections between soft and rigid elements using novel interconnects are reviewed. Lastly, some perspectives and prospects of remaining research challenges and potential pathways for practical utilization of interconnects in wearables are laid out.

An ultraflexible energy harvesting-storage system for wearable applications

The swift progress in wearable technology has accentuated the need for flexible power systems. Such systems are anticipated to exhibit high efficiency, robust durability, consistent power output, and the potential for effortless integration. Integrating ultraflexible energy harvesters and energy storage devices to form an autonomous, efficient, and mechanically compliant power system remains a significant challenge. In this work, we report a 90 µm-thick energy harvesting and storage system (FEHSS) consisting of high-performance organic photovoltaics and zinc-ion batteries within an ultraflexible configuration. With a power conversion efficiency surpassing 16%, power output exceeding 10 mW cm-2, and an energy density beyond 5.82 mWh cm-2, the FEHSS can be tailored to meet the power demands of wearable sensors and gadgets. Without cumbersome and rigid components, FEHSS shows immense potential as a versatile power source to advance wearable electronics and contribute toward a sustainable future.

War, emotions, mental health, and artificial intelligence

During the war time dysregulation of negative emotions such as fear, anger, hatred, frustration, sadness, humiliation, and hopelessness can overrule normal societal values, culture, and endanger global peace and security, and mental health in affected societies. Therefore, it is understandable that the range and power of negative emotions may play important roles in consideration of human behavior in any armed conflict. The estimation and assessment of dominant negative emotions during war time are crucial but are challenged by the complexity of emotions' neuro-psycho-physiology. Currently available natural language processing (NLP) tools have comprehensive computational methods to analyze and understand the emotional content of related textual data in war-inflicted societies. Innovative AI-driven technologies incorporating machine learning, neuro-linguistic programming, cloud infrastructure, and novel digital therapeutic tools and applications present an immense potential to enhance mental health care worldwide. This advancement could make mental health services more cost-effective and readily accessible. Due to the inadequate number of psychiatrists and limited psychiatric resources in coping with mental health consequences of war and traumas, new digital therapeutic wearable devices supported by AI tools and means might be promising approach in psychiatry of future. Transformation of negative dominant emotional maps might be undertaken by the simultaneous combination of online cognitive behavioral therapy (CBT) on individual level, as well as usage of emotionally based strategic communications (EBSC) on a public level. The proposed positive emotional transformation by means of CBT and EBSC may provide important leverage in efforts to protect mental health of civil population in war-inflicted societies. AI-based tools that can be applied in design of EBSC stimuli, like Open AI Chat GPT or Google Gemini may have great potential to significantly enhance emotionally based strategic communications by more comprehensive understanding of semantic and linguistic analysis of available text datasets of war-traumatized society. Human in the loop enhanced by Chat GPT and Gemini can aid in design and development of emotionally annotated messages that resonate among targeted population, amplifying the impact of strategic communications in shaping human dominant emotional maps into a more positive by CBT and EBCS.

A Highly Stretchable, Conductive, and Transparent Bioadhesive Hydrogel as a Flexible Sensor for Enhanced Real-Time Human Health Monitoring

Real-time continuous monitoring of non-cognitive markers is crucial for the early detection and management of chronic conditions. Current diagnostic methods are often invasive and not suitable for at-home monitoring. An elastic, adhesive, and biodegradable hydrogel-based wearable sensor with superior accuracy and durability for monitoring real-time human health is developed. Employing a supramolecular engineering strategy, a pseudo-slide-ring hydrogel is synthesized by combining polyacrylamide (pAAm), β-cyclodextrin (β-CD), and poly 2-(acryloyloxy)ethyltrimethylammonium chloride (AETAc) bio ionic liquid (Bio-IL). This novel approach decouples conflicting mechano-chemical effects arising from different molecular building blocks and provides a balance of mechanical toughness (1.1 × 106 Jm-3), flexibility, conductivity (≈0.29 S m-1), and tissue adhesion (≈27 kPa), along with rapid self-healing and remarkable stretchability (≈3000%). Unlike traditional hydrogels, the one-pot synthesis avoids chemical crosslinkers and metallic nanofillers, reducing cytotoxicity. While the pAAm provides mechanical strength, the formation of the pseudo-slide-ring structure ensures high stretchability and flexibility. Combining pAAm with β-CD and pAETAc enhances biocompatibility and biodegradability, as confirmed by in vitro and in vivo studies. The hydrogel also offers transparency, passive-cooling, ultraviolet (UV)-shielding, and 3D printability, enhancing its practicality for everyday use. The engineered sensor demonstratesimproved efficiency, stability, and sensitivity in motion/haptic sensing, advancing real-time human healthcare monitoring.

MXene-Based Pressure Sensor with a Self-Healing Property for Joule Heating and Friction Sliding

As a kind of flexible electronic device, flexible pressure sensor has attracted wide attention in medical monitoring and human-machine interaction. With the continuous deepening of research, high-sensitivity sensor is developing from single function to multi-function. However, Current multifunctional sensors lack the ability to integrate joule heating, detect sliding friction, and self-healing. Herein, a MXene/polyurethane (PU) flexible pressure sensor with a self-healing property for joule heating and friction sliding is fabricated. The MXene/PU sensitive layer with special spinosum structure is prepared by a simple spraying method. After face-to-face assembly of the sensitive layers, the MXene/PU flexible pressure sensor is obtained and showed excellent sensitivity (150.65 kPa-1), fast response/recovery speed (75.5/63.9 ms), and good stability (10 000 cycles). Based on the self-healing property of PU, the sensor also has the ability to heal after mechanical damage. In addition, the sensor realizes the joule heating function under low voltage, and has the real-time monitoring ability of sliding objects. Combined with low cost and simple manufacturing method, the multi-functional MXene/PU flexible sensor shows a wide range of application potential in human activity monitoring, thermal management, and slip recognition.

Wearable smart contact lenses: A critical comparison of three physiological signals outputs for health monitoring

Smart contact lenses (SCLs) have been considered as novel wearable devices for out-of-hospital and self-monitoring applications. They are capable of non-invasively and continuously monitoring physiological signals in the eyes, including vital biophysical (e.g., intraocular of pressure, temperature, and electrophysiological signal) and biochemical signals (e.g., pH, glucose, protein, nitrite, lactic acid, and ions). Recent progress mainly focuses on the rational design of wearable SCLs for physiological signal monitoring, while also facilitating the treatment of various ocular diseases. It covers contact lens materials, fabrication technologies, and integration methods. We also highlight and discuss a critical comparison of SCLs with electrical, microfluidic, and optical signal outputs in health monitoring. Their advantages and disadvantages could help researchers to make decisions when developing SCLs with desired properties for physiological signal monitoring. These unique capabilities make SCLs promising diagnostic and therapeutic tools. Despite the extensive research in SCLs, new technologies are still in their early stages of development and there are a few challenges to be addressed before these SCLs technologies can be successfully commercialized particularly in the form of rigorous clinical trials.

Switchable Power Generation in Triboelectric Nanogenerator Toward Chip-Less Wearable Power Module Applications

A conceptual shift toward next-generation wearable electronics is driving research into self-powered electronics technologies that can be independently operated without plugging into the grid for external power feeding. Triboelectric nanogenerators (TENGs) are emerging as a key component of self-powered electronics, but a power type mismatch between supply and demand limits their direct implementation into wearable self-powered electronics. Here, a TENG with switchable power mode capability is reported where the charge flow direction is modulated over the course of slow and random mechanical stimuli, with exceptional rectification capabilities as high as ≈133, stable outputs over the cycles, and design flexibility in different platforms. Importantly, the remarkable switchable power generation with fabric counter materials illuminates a new path for the smooth integration of flexible TENGs into wearable self-powered electronics.

Nucleic acid-based wearable and implantable electrochemical sensors

The rapid advancements in nucleic acid-based electrochemical sensors for implantable and wearable applications have marked a significant leap forward in the domain of personal healthcare over the last decade. This technology promises to revolutionize personalized healthcare by facilitating the early diagnosis of diseases, monitoring of disease progression, and tailoring of individual treatment plans. This review navigates through the latest developments in this field, focusing on the strategies for nucleic acid sensing that enable real-time and continuous biomarker analysis directly in various biofluids, such as blood, interstitial fluid, sweat, and saliva. The review delves into various nucleic acid sensing strategies, emphasizing the innovative designs of biorecognition elements and signal transduction mechanisms that enable implantable and wearable applications. Special perspective is given to enhance nucleic acid-based sensor selectivity and sensitivity, which are crucial for the accurate detection of low-level biomarkers. The integration of such sensors into implantable and wearable platforms, including microneedle arrays and flexible electronic systems, actualizes their use in on-body devices for health monitoring. We also tackle the technical challenges encountered in the development of these sensors, such as ensuring long-term stability, managing the complexity of biofluid dynamics, and fulfilling the need for real-time, continuous, and reagentless detection. In conclusion, the review highlights the importance of these sensors in the future of medical engineering, offering insights into design considerations and future research directions to overcome existing limitations and fully realize the potential of nucleic acid-based electrochemical sensors for healthcare applications.

Natural Polymer-Based Hydrogel Dressings for Wound Healing

Significance: Acute wounds such as severe burns and chronic wounds like diabetic ulcers present a significant threat to human health. Wound dressings made from natural polymers offer inherent properties that effectively enhance wound healing outcomes and reduce healing time. Recent Advances: Numerous innovative hydrogels are being developed and translated to the clinic to successfully treat various wound types. This underscores the substantial potential of hydrogels in the future wound care market. Economically, annual sales of wound care products are projected to reach $15-22 billion by 2024. Critical Issues: While chitosan-, cellulose-, and collagen-based hydrogel dressings are currently commercially available, scaling-up and manufacturing hydrogels for commercial products remain a challenging process. In addition, ensuring the sterility and stability of the chemical or biological components comprising the hydrogel is a critical consideration. Future Directions: In light of the persistent increase in wound fatalities and the resulting economic and social impacts, as well as the importance of educating the public about dietary health and disease, there should be increased investment in new wound care dressings, particularly hydrogels derived from natural products. With numerous researchers dedicated to advancing preclinical hydrogels, the future holds promise for more innovative and more personalized hydrogel wound dressings.

Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review

BACKGROUND

Clinical decision-making in oncology is a complex process influenced by numerous disease-related factors, patient demographics, and logistical considerations. With the advent of artificial intelligence (AI), precision medicine is undergoing a shift toward more precise and personalized care. Wearable device technology complements this paradigm shift by offering continuous monitoring of patient vitals, facilitating early intervention, and improving treatment adherence. The integration of these technologies promises to enhance the quality of oncological care, making it more responsive and tailored to individual patient needs, thereby enabling wider implementation of such applications in the clinical setting.

SUMMARY

This review article addresses the integration of wearable devices and AI in oncology, exploring their role in patient monitoring, treatment optimization, and research advancement along with an overview of completed clinical trials and utility in different aspects. The vast applications have been exemplified using several studies, and all the clinical trials completed till date have been summarized in Table 2. Additionally, we discuss challenges in implementation, regulatory considerations, and future perspectives for leveraging these technologies to enhance cancer care and radically changing the global health sector.

KEY MESSAGES

AI is transforming cancer care by enhancing diagnostic, prognostic, and treatment planning tools, thus making precision medicine more effective. Wearable technology facilitates continuous, noninvasive monitoring, improving patient engagement and adherence to treatment protocols. The combined use of AI and wearables aids in monitoring patient activity, assessing frailty, predicting chemotherapy tolerance, detecting biomarkers, and managing treatment adherence. Despite these advancements, challenges such as data security, privacy, and the need for standardized devices persist. In the foreseeable future, wearable technology can hold significant potential to revolutionize personalized oncology care, empowering clinicians to deliver comprehensive and tailored treatments alongside standard therapy.

Wafer-Scale Fabrication of Wearable All-Carbon Nanotube Photodetector Arrays

With electronic devices evolving toward portable and high-performance wearables, the constraints of complex and wet processing technologies become apparent. This study presents a scalable photolithography/chemical-free method for crafting wearable all-carbon nanotube (CNT) photodetector device arrays. Laser-assisted patterning and dry deposition techniques directly assemble gas-phase CNTs into flexible devices without any lithography or lift-off processes. The resulting wafer-scale all-CNT photodetector arrays showcase excellent uniformity, wearability, environmental stability, and notable broadband photoresponse, boasting a high responsivity of 44 AW-1 and a simultaneous detectivity of 1.9 × 109 Jones. This research provides an efficient, versatile, and scalable strategy for manufacturing wearable all-CNT device arrays, allowing widespread adoption in wearable optoelectronics and multifunctional sensors.

Directionally Exfoliated Ni/Co Hydroxide-Organic Framework Nanosheets for Enhanced Wearable Glucose Sensing

We report two-dimensional (2D) Ni/Co-based metal hydroxide-organic framework nanosheets (Ni/Co-MHOF NSs) for the construction of an efficient electrochemical nonenzymatic glucose sensor. The nanosheet architecture maximizes the exposure of coordinatively unsaturated metal sites, which enables a largely improved electrocatalytic performance toward the glucose oxidation reaction. The as-designed nonenzymatic sensor exhibits a high sensitivity of 235.71 μA·mM-1·cm-2 and a wide linear range of 1-3000 μM. The sensor presents excellent selectivity against several potential interferences and a short response time of 3.0 s. Of interest, a high-performance flexible sensor is developed by depositing the Ni/Co-MHOF NSs on screen-printed electrodes, which reveal decent bending stability. The designed glucose sensor patch can attach to the human body and realize noninvasive glucose monitoring in human sweat. This work may shed light on the application of novel MHOFs in the field of wearable electrochemical sensing.

Conductive Polymer-Based Hydrogels for Wearable Electrochemical Biosensors

Hydrogels are gaining popularity for use in wearable electronics owing to their inherent biomimetic characteristics, flexible physicochemical properties, and excellent biocompatibility. Among various hydrogels, conductive polymer-based hydrogels (CP HGs) have emerged as excellent candidates for future wearable sensor designs. These hydrogels can attain desired properties through various tuning strategies extending from molecular design to microstructural configuration. However, significant challenges remain, such as the limited strain-sensing range, significant hysteresis of sensing signals, dehydration-induced functional failure, and surface/interfacial malfunction during manufacturing/processing. This review summarizes the recent developments in polymer-hydrogel-based wearable electrochemical biosensors over the past five years. Initially serving as carriers for biomolecules, polymer-hydrogel-based sensors have advanced to encompass a wider range of applications, including the development of non-enzymatic sensors facilitated by the integration of nanomaterials such as metals, metal oxides, and carbon-based materials. Beyond the numerous existing reports that primarily focus on biomolecule detection, we extend the scope to include the fabrication of nanocomposite conductive polymer hydrogels and explore their varied conductivity mechanisms in electrochemical sensing applications. This comprehensive evaluation is instrumental in determining the readiness of these polymer hydrogels for point-of-care translation and state-of-the-art applications in wearable electrochemical sensing technology.

Wireless and Battery-Free Sensor for Interstitial Fluid Pressure Monitoring

Congestive heart failure (CHF) is a fatal disease with progressive severity and no cure; the heart's inability to adequately pump blood leads to fluid accumulation and frequent hospital readmissions after initial treatments. Therefore, it is imperative to continuously monitor CHF patients during its early stages to slow its progression and enable timely medical interventions for optimal treatment. An increase in interstitial fluid pressure (IFP) is indicative of acute CHF exacerbation, making IFP a viable biomarker for predicting upcoming CHF if continuously monitored. In this paper, we present an inductor-capacitor (LC) sensor for subcutaneous wireless and continuous IFP monitoring. The sensor is composed of inexpensive planar copper coils defined by a simple craft cutter, which serves as both the inductor and capacitor. Because of its sensing mechanism, the sensor does not require batteries and can wirelessly transmit pressure information. The sensor has a low-profile form factor for subcutaneous implantation and can communicate with a readout device through 4 layers of skin (12.7 mm thick in total). With a soft silicone rubber as the dielectric material between the copper coils, the sensor demonstrates an average sensitivity as high as -8.03 MHz/mmHg during in vitro simulations.

Wireless Technologies in Flexible and Wearable Sensing: From Materials Design, System Integration to Applications

Wireless and wearable sensors attract considerable interest in personalized healthcare by providing a unique approach for remote, noncontact, and continuous monitoring of various health-related signals without interference with daily life. Recent advances in wireless technologies and wearable sensors have promoted practical applications due to their significantly improved characteristics, such as reduction in size and thickness, enhancement in flexibility and stretchability, and improved conformability to the human body. Currently, most researches focus on active materials and structural designs for wearable sensors, with just a few exceptions reflecting on the technologies for wireless data transmission. This review provides a comprehensive overview of the state-of-the-art wireless technologies and related studies on empowering wearable sensors. The emerging functional nanomaterials utilized for designing unique wireless modules are highlighted, which include metals, carbons, and MXenes. Additionally, the review outlines the system-level integration of wireless modules with flexible sensors, spanning from novel design strategies for enhanced conformability to efficient transmitting data wirelessly. Furthermore, the review introduces representative applications for remote and noninvasive monitoring of physiological signals through on-skin and implantable wireless flexible sensing systems. Finally, the challenges, perspectives, and unprecedented opportunities for wireless and wearable sensors are discussed.

Transdermal Sensing of Enzyme Biomarker Enabled by Chemo-Responsive Probe-Modified Epidermal Microneedle Patch in Human Skin Tissue

Wearable bioelectronics represents a significant breakthrough in healthcare settings, particularly in (bio)sensing which offers an alternative way to track individual health for diagnostics and therapy. However, there has been no notable improvement in the field of cancer, particularly for skin cancer. Here, a wearable bioelectronic patch is established for transdermal sensing of the melanoma biomarker, tyrosinase (Tyr), using a microneedle array integrated with a surface-bound chemo-responsive smart probe to enable target-specific electrochemical detection of Tyr directly from human skin tissue. The results presented herein demonstrate the feasibility of a transdermal microneedle sensor for direct quantification of enzyme biomarkers in an ex vivo skin model. Initial performance analysis of the transdermal microneedle sensor proves that the designed methodology can be an alternative for fast and reliable diagnosis of melanoma and the evaluation of skin moles. The innovative approach presented here may revolutionize the landscape of skin monitoring by offering a nondisruptive means for continuous surveillance and timely intervention of skin anomalies, such as inflammatory skin diseases or allergies and can be extended to the screening of multiple responses of complementary biomarkers with simple modification in device design.

Microneedle Patches-Integrated Transdermal Bioelectronics for Minimally Invasive Disease Theranostics

Wearable epidermal electronics with non- or minimally-invasive characteristics can collect, transduce, communicate, and interact with accessible physicochemical health indicators on the skin. However, due to the stratum corneum layer, rich information about body health is buried under the skin stratum corneum layer, for example, in the skin interstitial fluid. Microneedle patches are typically designed with arrays of special microsized needles of length within 1000 µm. Such characteristics potentially enable the access and sample of biomolecules under the skin or give therapeutical treatment painlessly and transdermally. Integrating microneedle patches with various electronics allows highly efficient transdermal bioelectronics, showing their great promise for biomedical and healthcare applications. This comprehensive review summarizes and highlights the recent progress on integrated transdermal bioelectronics based on microneedle patches. The design criteria and state-of-the-art fabrication techniques for such devices are initially discussed. Next, devices with different functions, including but not limited to health monitoring, drug delivery, and therapeutical treatment, are highlighted in detail. Finally, key issues associated with current technologies and future opportunities are elaborated to sort out the state of recent research, point out potential bottlenecks, and provide future research directions.

Advances in pH Sensing: From Traditional Approaches to Next-Generation Sensors in Biological Contexts

pH has been considered one of the paramount factors in bodily functions because most cellular tasks exclusively rely on precise pH values. In this context, the current techniques for pH sensing provide us with the futuristic insight to further design therapeutic and diagnostic tools. Thus, pH-sensing (electrochemically and optically) is rapidly evolving toward exciting new applications and expanding researchers' interests in many chemical contexts, especially in biomedical applications. The adaptation of cutting-edge technology is subsequently producing the modest form of these biosensors as wearable devices, which are providing us the opportunity to target the real-time collection of vital parameters, including pH for improved healthcare systems. The motif of this review is to provide insight into trending tech-based systems employed in real-time or in-vivo pH-responsive monitoring. Herein, we briefly go through the pH regulation in the human body to help the beginners and scientific community with quick background knowledge, recent advances in the field, and pH detection in real-time biological applications. In the end, we summarize our review by providing an outlook; challenges that need to be addressed, and prospective integration of various pH in vivo platforms with modern electronics that can open new avenues of cutting-edge techniques for disease diagnostics and prevention.

A Novel Machine-Learning-Based Noise Detection Method for Photoplethysmography Signals

Wearable devices are widespread for continuous health monitoring; capturing various physiological parameters for remote health monitoring and early detection of health issues. These devices are susceptible to interference such as Motion Artifacts (MA) and Baseline Wanders (BW). Mitigating potential false alarms due to those artifacts is an important challenge in wearable healthcare. To tackle this challenge, it is crucial to first identify noise in the signals recorded by wearable systems. Most of the conventional methods rely on reference data like accelerometer data to detect noise in Photoplethysmogram (PPG) signals. This study proposes a Machine Learning (ML)-based approach to distinguish between clean and corrupted segments in PPG signals without relying on other sensors' data. Binary and three-class classification on clean, MA-, and BW-corrupted signals produce promising F1-scores from 89.3% to 99.4%.

Evolution of Musculoskeletal Electronics

The musculoskeletal system, constituting the largest human physiological system, plays a critical role in providing structural support to the body, facilitating intricate movements, and safeguarding internal organs. By virtue of advancements in revolutionized materials and devices, particularly in the realms of motion capture, health monitoring, and postoperative rehabilitation, "musculoskeletal electronics" has actually emerged as an infancy area, but has not yet been explicitly proposed. In this review, the concept of musculoskeletal electronics is elucidated, and the evolution history, representative progress, and key strategies of the involved materials and state-of-the-art devices are summarized. Therefore, the fundamentals of musculoskeletal electronics and key functionality categories are introduced. Subsequently, recent advances in musculoskeletal electronics are presented from the perspectives of "in vitro" to "in vivo" signal detection, interactive modulation, and therapeutic interventions for healing and recovery. Additionally, nine strategy avenues for the development of advanced musculoskeletal electronic materials and devices are proposed. Finally, concise summaries and perspectives are proposed to highlight the directions that deserve focused attention in this booming field.

Paper-Based Electrochemical (Bio)Sensors for the Detection of Target Analytes in Liquid, Aerosol, and Solid Samples

The last decade has been incredibly fruitful in proving the multifunctionality of paper for delivering innovative electrochemical (bio)sensors. The paper material exhibits unprecedented versatility to deal with complex liquid matrices and facilitate analytical detection in aerosol and solid phases. Such remarkable capabilities are feasible by exploiting the intrinsic features of paper, including porosity, capillary forces, and its easy modification, which allow for the fine designing of a paper device. In this review, we shed light on the most relevant paper-based electrochemical (bio)sensors published in the literature so far to identify the smart functional roles that paper can play to bridge the gap between academic research and real-world applications in the biomedical, environmental, agrifood, and security fields. Our analysis aims to highlight how paper's multifarious properties can be artfully harnessed for breaking the boundaries of the most classical applications of electrochemical (bio)sensors.

Wearable Sensors for Physiological Condition and Activity Monitoring

Rapid technological advancements have transformed the healthcare sector from traditional diagnosis and treatment to personalized health management. Biofluids such as teardrops, sweat, interstitial fluids, and exhaled breath condensate offer a rich source of metabolites that can be linked to the physiological status of an individual. More importantly, these biofluids contain biomarkers similar to those in the blood. Therefore, developing sensors for the noninvasive determination of biofluid-based metabolites can overcome traditionally invasive and laborious blood-test-based diagnostics. In this context, wearable devices offer real-time and continuous physiological conditions and activity monitoring. The first-generation wearables included wristwatches capable of tracking heart rate variations, breathing rate, body temperature, stress responses, and sleeping patterns. However, wearable sensors that can accurately measure the metabolites are needed to achieve real-time analysis of biomarkers. In this review, recent progresses in wearable sensors utilized to monitor metabolites in teardrops, breath condensate, sweat, and interstitial fluids are thoroughly analyzed. More importantly, how metabolites can be selectively detected, quantified, and monitored in real-time is discussed. Furthermore, the review includes a discussion on the utility of, multifunctional sensors that combine metabolite sensing, human activity monitoring, and on-demand drug delivery system for theranostic applications.

3D-Printed Flexible Microfluidic Health Monitor for In Situ Sweat Analysis and Biomarker Detection

Wearable sweat biosensors have shown great progress in noninvasive, in situ, and continuous health monitoring to demonstrate individuals' physiological states. Advances in novel nanomaterials and fabrication methods promise to usher in a new era of wearable biosensors. Here, we introduce a three-dimensional (3D)-printed flexible wearable health monitor fabricated through a unique one-step continuous manufacturing process with self-supporting microfluidic channels and novel single-atom catalyst-based bioassays for measuring the sweat rate and concentration of three biomarkers. Direct ink writing is adapted to print the microfluidic device with self-supporting structures to harvest human sweat, which eliminates the need for removing sacrificial supporting materials and addresses the contamination and sweat evaporation issues associated with traditional sampling methods. Additionally, the pick-and-place strategy is employed during the printing process to accurately integrate the bioassays, improving manufacturing efficiency. A single-atom catalyst is developed and utilized in colorimetric bioassays to improve sensitivity and accuracy. A feasibility study on human skin successfully demonstrates the functionality and reliability of our health monitor, generating reliable and quantitative in situ results of sweat rate, glucose, lactate, and uric acid concentrations during physical exercise.

Unconventional acoustic wave propagation transitions induced by resonant scatterers in the high-density limit

Experiments on ultrasound propagation through a gel doped with resonant encapsulated microbubbles provided evidence for a discontinuous transition between wave propagation regimes at a critical excitation frequency. Such behavior is unlike that observed for soft materials doped with non-resonant air or through liquid foams, and disagrees with a simple mixture model for the effective sound speed. Here, we study the discontinuous transition by measuring the transition as a function of encapsulated microbubble volume fraction. The results show the transition always occurs in the strong-scattering limit (l/λ < 1, l and λ are the mean free path and wavelength, respectively), that at the critical frequency the effective phase velocity changes discontinuously to a constant value with increasing microbubble volume fraction, and the measured critical frequency shows a power law dependence on microbubble volume fraction. The results cannot be explained by multiple scattering theory, viscous effects, mode decoupling, or a critical density of states. It is hypothesized the transition depends upon the microbubble on-resonance effective properties, and we discuss the results within the context of percolation theory. The results shed light on the discontinuous transition's physics, and suggest soft materials can be engineered in this manner to achieve a broad range of physical properties with potential application in ultrasonic actuators and switches.

A flexible, stretchable and wearable strain sensor based on physical eutectogels for deep learning-assisted motion identification

Physical eutectogels as a newly emerging type of conductive gel have gained extensive interest for the next generation multifunctional electronic devices. Nevertheless, some obstacles, including weak mechanical performance, low self-adhesive strength, lack of self-healing capacity, and low conductivity, hinder their practical use in wearable strain sensors. Herein, lignin as a green filler and a multifunctional hydrogen bond donor was directly dissolved in a deep eutectic solvent (DES) composed of acrylic acid (AA) and choline chloride, and lignin-reinforced physical eutectogels (DESL) were obtained by the polymerization of AA. Due to the unique features of lignin and DES, the prepared DESL eutectogels exhibit good transparency, UV shielding capacity, excellent mechanical performance, outstanding self-adhesiveness, superior self-healing properties, and high conductivity. Based on the aforementioned integrated functions, a wearable strain sensor displaying a wide working range (0-1500%), high sensitivity (GF = 18.15), rapid responsiveness, and excellent stability and durability (1000 cycles) and capable of detecting diverse human motions was fabricated. Additionally, by combining DESL sensors with a deep learning technique, a gesture recognition system with accuracy as high as 98.8% was achieved. Overall, this work provides an innovative idea for constructing multifunction-integrated physical eutectogels for application in wearable electronics.

An Inertial-Based Wearable System for Monitoring Vital Signs during Sleep

This study explores the feasibility of a wearable system to monitor vital signs during sleep. The system incorporates five inertial measurement units (IMUs) located on the waist, the arms, and the legs. To evaluate the performance of a novel framework, twenty-three participants underwent a sleep study, and vital signs, including respiratory rate (RR) and heart rate (HR), were monitored via polysomnography (PSG). The dataset comprises individuals with varying severity of sleep-disordered breathing (SDB). Using a single IMU sensor positioned at the waist, strong correlations of more than 0.95 with the PSG-derived vital signs were obtained. Low inter-participant mean absolute errors of about 0.66 breaths/min and 1.32 beats/min were achieved, for RR and HR, respectively. The percentage of data available for analysis, representing the time coverage, was 98.3% for RR estimation and 78.3% for HR estimation. Nevertheless, the fusion of data from IMUs positioned at the arms and legs enhanced the inter-participant time coverage of HR estimation by over 15%. These findings imply that the proposed methodology can be used for vital sign monitoring during sleep, paving the way for a comprehensive understanding of sleep quality in individuals with SDB.

[Development of flexible multi-phase barium titanate piezoelectric sensor for physiological health and action behavior monitoring]

Self-powered wearable piezoelectric sensing devices demand flexibility and high voltage electrical properties to meet personalized health and safety management needs. Aiming at the characteristics of piezoceramics with high piezoelectricity and low flexibility, this study designs a high-performance piezoelectric sensor based on multi-phase barium titanate (BTO) flexible piezoceramic film, namely multi-phase BTO sensor. The substrate-less self-supported multi-phase BTO films had excellent flexibility and could be bent 180° at a thickness of 33 μm, and exhibited good bending fatigue resistance in 1 × 10 4 bending cycles at a thickness of 5 μm. The prepared multi-phase BTO sensor could maintain good piezoelectric stability after 1.2 × 10 4 piezoelectric cycle tests. Based on the flexibility, high piezoelectricity, wearability, portability and battery-free self-powered characteristics of this sensor, the developed smart mask could monitor the respiratory signals of different frequencies and amplitudes in real time. In addition, by mounting the sensor on the hand or shoulder, different gestures and arm movements could also be detected. In summary, the multi-phase BTO sensor developed in this paper is expected to develop convenient and efficient wearable sensing devices for physiological health and behavioral activity monitoring applications.

MnO2 Nanoparticles Decorated PEDOT:PSS for High Performance Stretchable and Transparent Supercapacitors

With the swift advancement of wearable electronics and artificial intelligence, the integration of electronic devices with the human body has advanced significantly, leading to enhanced real-time health monitoring and remote disease diagnosis. Despite progress in developing stretchable materials with skin-like mechanical properties, there remains a need for materials that also exhibit high optical transparency. Supercapacitors, as promising energy storage devices, offer advantages such as portability, long cycle life, and rapid charge/discharge rates, but achieving high capacity, stretchability, and transparency simultaneously remains challenging. This study combines the stretchable, transparent polymer PEDOT:PSS with MnO2 nanoparticles to develop high-performance, stretchable, and transparent supercapacitors. PEDOT:PSS films were deposited on a PDMS substrate using a spin-coating method, followed by electrochemical deposition of MnO2 nanoparticles. This method ensured that the nanosized MnO2 particles were uniformly distributed, maintaining the transparency and stretchability of PEDOT:PSS. The resulting PEDOT:PSS/MnO2 nanoparticle electrodes were gathered into a symmetric device using a LiCl/PVA gel electrolyte, achieving an areal capacitance of 1.14 mF cm-2 at 71.2% transparency and maintaining 89.92% capacitance after 5000 cycles of 20% strain. This work presents a scalable and economical technique to manufacturing supercapacitors that combine high capacity, transparency, and mechanical stretchability, suggesting potential applications in wearable electronics.

Advancements in MXene Composite Materials for Wearable Sensors: A Review

In recent years, advancements in the Internet of Things (IoT), manufacturing processes, and material synthesis technologies have positioned flexible sensors as critical components in wearable devices. These developments are propelling wearable technologies based on flexible sensors towards higher intelligence, convenience, superior performance, and biocompatibility. Recently, two-dimensional nanomaterials known as MXenes have garnered extensive attention due to their excellent mechanical properties, outstanding electrical conductivity, large specific surface area, and abundant surface functional groups. These notable attributes confer significant potential on MXenes for applications in strain sensing, pressure measurement, gas detection, etc. Furthermore, polymer substrates such as polydimethylsiloxane (PDMS), polyurethane (PU), and thermoplastic polyurethane (TPU) are extensively utilized as support materials for MXene and its composites due to their light weight, flexibility, and ease of processing, thereby enhancing the overall performance and wearability of the sensors. This paper reviews the latest advancements in MXene and its composites within the domains of strain sensors, pressure sensors, and gas sensors. We present numerous recent case studies of MXene composite material-based wearable sensors and discuss the optimization of materials and structures for MXene composite material-based wearable sensors, offering strategies and methods to enhance the development of MXene composite material-based wearable sensors. Finally, we summarize the current progress of MXene wearable sensors and project future trends and analyses.

Rapid and Online Microvolume Flow-Through Dialysis Probe for Sample Preparation in Veterinary Drug Residue Analysis

A rapid and online microvolume flow-through dialysis probe designed for sample preparation in the analysis of veterinary drug residues is introduced. This study addresses the need for efficient and green sample preparation methods that reduce chemical waste and reagent use. The dialysis probe integrates with liquid chromatography and mass spectrometry (LC-MS) systems, facilitating automated, high-throughput analysis. The dialysis method utilizes minimal reagent volumes per sample, significantly reducing the generation of solvent waste compared to traditional sample preparation techniques. Several veterinary drugs were spiked into tissue homogenates and analyzed to validate the probe's efficacy. A diagnostic sensitivity of >97% and specificity of >95% were obtained for this performance evaluation. The results demonstrated the effective removal of cellular debris and particulates, ensuring sample integrity and preventing instrument clogging. The automated dialysis probe yielded recovery rates between 27 and 77% for multiple analytes, confirming its potential to streamline veterinary drug residue analysis, while adhering to green chemistry principles. The approach highlights substantial improvements in both environmental impact and operational efficiency, presenting a viable alternative to conventional sample preparation methods in regulatory and research applications.

AuNi bimetallic aerogel with ultra-high stability applied in smart and portable biosensing

Glucose detection is of significant importance in providing information to the human health management. However, conventional enzymatic glucose sensors suffer from a limited long-term stability due to the losing activity of the enzymes. In this work, the AuNi bimetallic aerogel with a well-defined nanowire network is synthesized and applied as the sensing nanomaterial in the non-enzymatic glucose detection. The three-dimensional (3D) hierarchical porous structure of the AuNi bimetallic aerogel ensures the high sensitivity of the sensor (40.34 μA mM-1 cm-2). Theoretical investigation unveiled the mechanism of the boosting electrocatalytic activity of the AuNi bimetallic aerogel toward glucose. A better adhesion between the sensing nanomaterial and the screen-printing electrodes (SPEs) is obtained after the introduction of Ni. On the basis of a wide linearity in the range of 0.1-5 mM, an excellent selectivity, an outstanding long-term stability (90 days) as well as the help of the signal processing circuit and an M5stack development board, the as-prepared glucose sensor successfully realizes remote monitoring of the glucose concentration. We speculate that this work is favorable to motivating the technological innovations of the non-enzymatic glucose sensors and intelligent sensing devices.

Emerging Trends of Nanofibrous Piezoelectric and Triboelectric Applications: Mechanisms, Electroactive Materials, and Designed Architectures

Over the past few decades, significant progress in piezo-/triboelectric nanogenerators (PTEGs) has led to the development of cutting-edge wearable technologies. Nanofibers with good designability, controllable morphologies, large specific areas, and unique physicochemical properties provide a promising platform for PTEGs for various advanced applications. However, the further development of nanofiber-based PTEGs is limited by technical difficulties, ranging from materials design to device integration. Herein, the current developments in PTEGs based on electrospun nanofibers are systematically reviewed. This review begins with the mechanisms of PTEGs and the advantages of nanofibers and nanodevices, including high breathability, waterproofness, scalability, and thermal-moisture comfort. In terms of materials and structural design, novel electroactive nanofibers and structure assemblies based on 1D micro/nanostructures, 2D bionic structures, and 3D multilayered structures are discussed. Subsequently, nanofibrous PTEGs in applications such as energy harvesters, personalized medicine, personal protective equipment, and human-machine interactions are summarized. Nanofiber-based PTEGs still face many challenges such as energy efficiency, material durability, device stability, and device integration. Finally, the research gap between research and practical applications of PTEGs is discussed, and emerging trends are proposed, providing some ideas for the development of intelligent wearables.

A Gradient Stiffness-Programmed Circuit Board by Spatially Controlled Phase-Transition of Supercooled Hydrogel for Stretchable Electronics Integration

Due to emerging demands in soft electronics, there is an increasing need for material architectures that support robust interfacing between soft substrates, stretchable electrical interconnects, and embedded rigid microelectronics chips. Though researchers have adopted rigid-island structures to solve the issue, this approach merely shifts stress concentrations from chip-conductor interfaces to rigid-island-soft region interfaces in the substrate. Here, a gradient stiffness-programmed circuit board (GS-PCB) that possesses high stretchability and stability with surface mounted chips is introduced. The board comprises a stiffness-programmed hydrogel substrate and a laser-patterned liquid metal conductor. The hydrogel simultaneously obtains a large stiffness disparity and robust interfaces between rigid-islands and soft regions. These seemingly contradictory conditions are accomplished by adopting a gradient stiffness structure at the interfaces, enabled by combining polymers with different interaction energies and a supercooled sodium acetate solution. By integrating the gel with laser-patterned liquid metal with exceptional properties, GS-PCB exhibits higher electromechanical stability than other rigid-island research. To highlight the practicality of this approach, a finger-sensor device that successfully distinguishes objects by direct physical contact is fabricated, demonstrating its stability under various mechanical disturbances.

One-step of ionic liquid-assisted stabilization and dispersion: Exfoliated graphene and its applications in stimuli-responsive conductive hydrogels based on chitosan

Conductive hydrogels, as novel flexible biosensors, have demonstrated significant potential in areas such as soft robotics, electronic devices, and wearable technology. Graphene is a promising conductive material, but its dispersibility in aqueous solutions exists difficulties. Here, we discover that untreated graphene, after exfoliation by different ionic liquids, can disperse well in aqueous solutions. We investigate the impact of four ionic liquids with varying alkyl chain lengths ([Bmim]Cl, [Omim]Cl, [Dmim]Cl, [Hmim]Cl) on the dispersibility of grapheme, and a dual physically cross-linked network hydrogel structure is designed using acrylamide (AM), acrylic acid (AA), methyl methacrylate octadecyl ester (SMA), ionic liquid@graphene (ILs@GN), and chitosan (CS). Notably, SMA, CS, AA and AM act as dynamic cross-linking points through hydrophobic interactions and hydrogen bonding, playing a crucial role in energy dissipation. The resulting hydrogel exhibits outstanding stretchability (2250 %), remarkable toughness (1.53 MJ/m3) in tensile deformation performance, high compressive strength (1.13 MPa), rapid electrical responsiveness (response time ∼ 50 ms), high electrical conductivity (12.11 mS/cm), and excellent strain sensing capability (GF = 12.31, strain = 1000 %). These advantages make our composite hydrogel demonstrate high stability in extensive deformations, offering repeatability in pressure and strain and making it a promising candidate for multifunctional sensors and flexible electrodes.

Tailored Polypyrrole Nanofibers as Ion-to-Electron Transduction Membranes for Wearable K+ Sensors

Conductive polymers are recognized as ideal candidates for the development of noninvasive and wearable sensors for real-time monitoring of potassium ions (K+) in sweat to ensure the health of life. However, the low ion-to-electron transduction efficiency and limited active surface area hamper the development of high-performance sensors for low-concentration K+ detection in the sweat. Herein, a wearable K+ sensor is developed by tailoring the nanostructure of polypyrrole (PPy), serving as an ion-to-electron transduction layer, for accurately and stably tracing the K+ fluctuation in human sweat. The PPy nanostructures can be tailored from nanospheres to nanofibers by controlling the supramolecular assembly process during PPy polymerization. Resultantly, the ion-to-electron transduction efficiency (17-fold increase in conductivity) and active surface area (1.3-fold enhancement) are significantly enhanced, accompanied by minimized water layer formation. The optimal PPy nanofibers-based K+ sensor achieved a high sensitivity of 62 mV decade-1, good selectivity, and solid stability. After being integrated with a temperature sensor, the manufactured wearable sensor realized accurate monitoring of K+ fluctuation in the human sweat.

A universal nucleic acid detection platform combing CRISPR/Cas12a and strand displacement amplification with multiple signal readout

Rapid and sensitive detection of nucleic acids has become crucial in various fields. However, most current nucleic acid detection methods can only be used in specific scenarios, such as RT-qPCR, which relies on fluorometer for signal readout, limiting its application at home or in the field due to its high price. In this paper, a universal nucleic acid detection platform combing CRISPR/Cas12a and strand displacement amplification (CRISPR-SDA) with multiple signal readout was established to adapt to different application scenarios. Nucleocapsid protein gene of SARS-CoV-2 (N gene) and hepatitis B virus (HBV) DNA were selected as model targets. The proposed strategy achieved the sensitivity of 53.1 fM, 0.15 pM, and 1 pM for N gene in fluorescence mode, personal glucose meter (PGM) mode and lateral flow assay (LFA) mode, respectively. It possessed the ability to differentiate single-base mismatch and the presence of salmon sperm DNA with a mass up to 105-fold of the targets did not significantly interfere with the assay signal. The general and modular design idea made CRISPR-SDA as simple as building blocks to construct nucleic acid sensing methods to meet different requirements by simply changing the SDA template and selecting suitable signal report probes, which was expected to find a breadth of applications in nucleic acids detection.

Imperceptible augmentation of living systems with organic bioelectronic fibres

The functional and sensory augmentation of living structures, such as human skin and plant epidermis, with electronics can be used to create platforms for health management and environmental monitoring. Ideally, such bioelectronic interfaces should not obstruct the inherent sensations and physiological changes of their hosts. The full life cycle of the interfaces should also be designed to minimize their environmental footprint. Here we report imperceptible augmentation of living systems through in situ tethering of organic bioelectronic fibres. Using an orbital spinning technique, substrate-free and open fibre networks-which are based on poly (3,4-ethylenedioxythiophene):polystyrene sulfonate-can be tethered to biological surfaces, including fingertips, chick embryos and plants. We use customizable fibre networks to create on-skin electrodes that can record electrocardiogram and electromyography signals, skin-gated organic electrochemical transistors and augmented touch and plant interfaces. We also show that the fibres can be used to couple prefabricated microelectronics and electronic textiles, and that the fibres can be repaired, upgraded and recycled.

Exploiting the Specificity of CRISPR/Cas System for Nucleic Acids Amplification-Free Disease Diagnostics in the Point-of-Care

Rapid and reliable molecular diagnostics employing target nucleic acids and small biomarkers are crucial strategies required for the precise detection of numerous diseases. Although diagnoses based on nucleic acid recognition are some of the most efficient and precise procedures, these tests often require expensive equipment and skilled professionals. Recent advancements in diagnostic innovations, particularly those based on clustered regularly interspaced short palindromic repeats (CRISPR), aim to provide thorough screening at homes, in clinics, and in the field. In comparison to traditional molecular techniques like PCR, CRISPR/Cas-based detection, using the single-stranded nucleic acid trans-cleavage abilities of Cas12 or Cas13, shows significant potential as a molecular diagnostic tool. It offers benefits such as attomolar-level sensitivity, single-base precision, and rapid turnover rates. Both Cas enzymes demonstrate exceptional specificity and sensitivity, holding substantial promise in disease diagnostics and beyond. Consequently, various amplification-free CRISPR/Cas-based detection methods have emerged, aiming to maintain sensitivity despite the absence of pre-amplification. This allows for the detection of non-nucleic acid targets and facilitates integration into point-of-care settings. This Review highlights current advances in amplification-free CRISPR/Cas detection systems in disease diagnostics and investigates their utility in point-of-care settings. Furthermore, the mechanisms of alternative CRISPR-based amplification-free detection of other small molecules, aside from nucleic acids, for disease diagnosis will also be briefly discussed.

Preparation and Performance of a Fiber Optic Temperature Sensor with Multiple Fluorescence Mechanisms

The tip of a piece of plastic fiber was dyed with thymol blue to form a temperature probe. The fiber optic sensor was calibrated on a heatboard by comparison with a K-type thermal couple. Fluorescence characteristics including fluorescence intensity, emission bandwidth, peak & barycenter wavelengths, and self-referenced intensity ratio were used to carry the information of environment temperature. Accordingly, more than five temperature sensing functions were retrieved from the fluorescent sensor. Among such functions, the emission band barycenter showed premium precision. Temperature-driven shift of the emission band barycenter has a sensitivity of 0.095 nm/K, with a nonlinearity of 2.2%FS, resolution of 4 K and repeatability of 1.8%FS. The sensor can find its applications in wearable devices and radiofrequency ablation. Finally in a verification experiment, the sensor was used to monitor the temperature of a microwave oven chamber in real time.

Design of a Humidity Sensor for a PPE Kit Using a Flexible Paper Substrate

The present work reports the rapid sweat detection inside a PPE kit using a flexible humidity sensor based on hydrothermally synthesized ZnO (zinc oxide) nanoflowers (ZNFs). Physical characterization of ZNFs was done using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transmission infrared spectroscopy (FTIR), UV-visible, particle size analysis, Raman analysis, and X-ray photoelectron spectroscopy (XPS) analysis, and the hydrophilicity was investigated by using contact angle measurement. Fabrication of a flexible sensor was done by deposition on the paper substrate using the spin coating technique. It exhibited high sensitivity and low response and recovery times in the humidity range 10-95%RH. The sensor demonstrated the highest sensitivity of 296.70 nF/%RH within the humidity range 55-95%RH, and the rapid response and recovery times were also calculated and found as 5.10/1.70 s, respectively. The selectivity of the proposed sensor was also analyzed, and it is highly sensitive to humidity. The humidity sensing characteristics were theoretically witnessed in terms of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) and electronic properties of sensing materials in ambient and humid conditions. These theoretical results are evidence of the interaction of ZnO with humidity. Overall, the present study provides a scope of architecture-enabled paper-based humidity sensors for the detection of sweat levels inside PPE kits for health workers.

Advanced Multiparallel-Connected Piezoresistive Physical Sensors: Elevating Performance Reliability of Flexible Strain and Pressure Sensors

A physical sensor with a sensing medium comprising multiparallel-connected (MPC) piezoresistive pathways in both the vertical and horizontal directions was developed to achieve improved sensing performance. The MPC sensing medium reduces the total resistance and offsets noise, offering enhanced signal stability and device reliability and providing a high-performance sensing platform. The signal change and gauge factor (GF) of the 3PW-5L strain sensor (comprising three lines and five layers of piezoresistive pathways horizontally and vertically, respectively) were, respectively, 5.9 and 4.7 times higher than those of the 1PW-1L sensor composed of a monosensing pathway; the hysteresis of the detected signal was also significantly reduced. The linearity of the detected signal increased from 0.912 for 1PW-1L to 0.995 for 3PW-5L, indicating a greater sensing reliability. The direction of the applied tensile strain was successfully detected using the MPC sensing medium with an orthogonal configuration. The MPC piezoresistive sensor composing vertically stacked piezoresistive pathways demonstrated excellent performance as a pressure sensor; the 3PW-5L pressure sensor afforded a GF of 0.121 ± 0.002 kPa-1 with a linearity of 0.998 under an applied pressure ≥16.4 kPa. The MPC piezoresistive physical sensor offers a superior sensing performance and should contribute to the future development of wearable sensors and electronic devices.

Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures

Machine learning holds significant research potential in the field of nanotechnology, enabling nanomaterial structure and property predictions, facilitating materials design and discovery, and reducing the need for time-consuming and labor-intensive experiments and simulations. In contrast to their achiral counterparts, the application of machine learning for chiral nanomaterials is still in its infancy, with a limited number of publications to date. This is despite the great potential of machine learning to advance the development of new sustainable chiral materials with high values of optical activity, circularly polarized luminescence, and enantioselectivity, as well as for the analysis of structural chirality by electron microscopy. In this review, an analysis of machine learning methods used for studying achiral nanomaterials is provided, subsequently offering guidance on adapting and extending this work to chiral nanomaterials. An overview of chiral nanomaterials within the framework of synthesis-structure-property-application relationships is presented and insights on how to leverage machine learning for the study of these highly complex relationships are provided. Some key recent publications are reviewed and discussed on the application of machine learning for chiral nanomaterials. Finally, the review captures the key achievements, ongoing challenges, and the prospective outlook for this very important research field.

Wireless and battery-free wearable biosensing of riboflavin in sweat for precision nutrition

Nutrition assessment is crucial for dietary guidance and prevention of malnutrition. Recent endeavors in wearable biochemical sensors have enabled real-time, in situ analysis of nutrients in sweat. However, the monitoring of riboflavin, an indispensable vitamin B involved in energy metabolism, remains challenging due to its trace level and variations in the sweat matrix. Herein, we report a wireless, battery-free, and flexible wearable biosensing system for the in situ monitoring of sweat riboflavin. Highly sensitive and selective electrochemical voltammetric detection is realized based on the synergistic effect of electrodeposited reduced graphene oxide (rGO) and platinum nanoparticles (PtNPs) with a low detection limit of 1.2 nM. The fully integrated system is capable of sweat sampling with the microfluidic patch, real-time riboflavin analysis and pH calibration with the flexible electrode array, as well as wirelessly simultaneous near field communication (NFC) energy harvesting and data transmission with the flexible circuit and a smartphone. On-body human sweat analysis demonstrates high accuracy cross-validated with gold-standard measurements, and reveals a strong correlation between sweat and urine riboflavin levels. The proposed wearable platform opens up attractive possibilities for noninvasive nutrient tracking, providing strong potential for personalized dietary guidance towards precision nutrition.