Recent advances in wearable biosensors for non-invasive monitoring of specific metabolites and electrolytes associated with chronic kidney disease: Performance evaluation and future challenges

Silk fibroin-based wearable SERS biosensor for simultaneous sweat monitoring of creatinine and uric acid

Sweat biomarkers have the potential to offer valuable clinical insights into an individual's health and disease condition. Current sensors predominantly utilize enzymes and antibodies as biometric components to measure biomarkers present in sweat quantitatively. However, enzymes and antibodies are susceptible to interference by environmental factors, which may affect the performance of the sensor. Herein, we present a wearable microfluidic surface-enhanced Raman scattering (SERS) biosensor that enables the non-invasive and label-free detection of biomarkers in sweat. Concretely, we developed a bimetallic self-assembled anti-opal array structure with uniform hot spots, enhanced the Raman scattering effect, and integrated it into a silk fibroin-based sensing patch. Utilizing a silk fibroin substrate in the wearable SERS sensor imparts desirable properties such as softness, breathability, and biocompatibility, which enables the sensor to establish close contact with the skin without causing chemical or physical irritation. In addition, introducing microfluidic channels enables the controlled and high temporal resolution management of sweat, facilitating more efficient sweat collection. The proposed label-free SERS sensor can offer chemical 'fingerprint' information, enabling the identification of sweat analytes. As an illustration of the feasibility, we have effectively monitored the creatinine and uric acid levels in sweat. This study presents a versatile and highly sensitive approach for the simultaneous detection of biomarkers in human sweat, showcasing significant potential for application in point-of-care monitoring.

Calibration-free and ready-to-use wearable electroanalytical reporting system (r-WEAR) for long-term remote monitoring of electrolytes markers

A major bottleneck in the development of wearable ion-selective sensors is the inherent conditioning and calibration procedures at the user's end due to the signal's instability and non-uniformity. To address this challenge, we developed a strategy that integrates three interdependent materials and device engineering approaches to realize a Ready-to-use Wearable ElectroAnalytical Reporting system (r-WEAR) for reliable electrolytes monitoring. The strategy collectively utilized (1) finely-configured diffusion-limiting polymers to stabilize the electromotive force in the electrodes, (2) a uniform electrical induction in electrochemical cells to normalize the open-circuit potential (OCP), and (3) an electrical shunt to maintain the OCP across the entire sensor in the r-WEAR. The approaches jointly enable fabrication of homogeneously stable and uniform ion-selective sensors, eliminating common conditioning and calibration practices. As a result, the r-WEAR demonstrated a signal's variation down to ±1.99 mV with a signal drift of 0.5 % per hour (0.12 mV h-1) during a 12-h continuous measurement of 10 sensors and a signal drift as low as 13.3 μV h-1 during storage. On-body evaluations of the r-WEAR for four days without conditioning and re-/calibration further validated the sensor's performance in realistic settings, indicating its remarkable potential for practical usage in a user operation-free manner in wearable healthcare applications.

AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring

The steady progress in consumer electronics, together with improvement in microflow techniques, nanotechnology, and data processing, has led to implementation of cost-effective, user-friendly portable devices, which play the role of not only gadgets but also diagnostic tools. Moreover, numerous smart devices monitor patients' health, and some of them are applied in point-of-care (PoC) tests as a reliable source of evaluation of a patient's condition. Current diagnostic practices are still based on laboratory tests, preceded by the collection of biological samples, which are then tested in clinical conditions by trained personnel with specialistic equipment. In practice, collecting passive/active physiological and behavioral data from patients in real time and feeding them to artificial intelligence (AI) models can significantly improve the decision process regarding diagnosis and treatment procedures via the omission of conventional sampling and diagnostic procedures while also excluding the role of pathologists. A combination of conventional and novel methods of digital and traditional biomarker detection with portable, autonomous, and miniaturized devices can revolutionize medical diagnostics in the coming years. This article focuses on a comparison of traditional clinical practices with modern diagnostic techniques based on AI and machine learning (ML). The presented technologies will bypass laboratories and start being commercialized, which should lead to improvement or substitution of current diagnostic tools. Their application in PoC settings or as a consumer technology accessible to every patient appears to be a real possibility. Research in this field is expected to intensify in the coming years. Technological advancements in sensors and biosensors are anticipated to enable the continuous real-time analysis of various omics fields, fostering early disease detection and intervention strategies. The integration of AI with digital health platforms would enable predictive analysis and personalized healthcare, emphasizing the importance of interdisciplinary collaboration in related scientific fields.

Recent advances in smart wearable sensors for continuous human health monitoring

In recent years, the biochemical and biological research areas have shown great interest in a smart wearable sensor because of its increasing prevalence and high potential to monitor human health in a non-invasive manner by continuous screening of biomarkers dispersed throughout the biological analytes, as well as real-time diagnostic tools and time-sensitive information compared to conventional hospital-centered system. These smart wearable sensors offer an innovative option for evaluating and investigating human health by incorporating a portion of recent advances in technology and engineering that can enhance real-time point-of-care-testing capabilities. Smart wearable sensors have emerged progressively with a mixture of multiplexed biosensing, microfluidic sampling, and data acquisition systems incorporated with flexible substrate and bodily attachments for enhanced wearability, portability, and reliability. There is a good chance that smart wearable sensors will be relevant to the early detection and diagnosis of disease management and control. Therefore, pioneering smart wearable sensors into reality seems extremely promising despite possible challenges in this cutting-edge technology for a better future in the healthcare domain. This review presents critical viewpoints on recent developments in wearable sensors in the upcoming smart digital health monitoring in real-time scenarios. In addition, there have been proactive discussions in recent years on materials selection, design optimization, efficient fabrication tools, and data processing units, as well as their continuous monitoring and tracking strategy with system-level integration such as internet-of-things, cyber-physical systems, and machine learning algorithms.

Nickel-cobalt metal-organic frameworks based flexible hydrogel as a wearable contact lens for electrochemical sensing of urea in tear samples

A flexible, wearable, non-invasive contact lens sensor utilizing nickel-cobalt metal-organic framework (Ni-Co-MOF) based hydrogel is introduced for urea monitoring in tear samples. The synthesized Ni-Co-MOF hydrogel exhibits a porous structure with interconnected voids, as visualized by Scanning Electron Microscopy (SEM). Detailed structural and vibrational properties of the material were characterized using X-ray Diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy, and Raman spectroscopy. The developed Ni-Co-MOF hydrogel sensor showcases a detection limit of 0.445 mM for urea within a linear range of 0.5-70 mM. Notably, it demonstrates exceptional selectivity, effectively distinguishing against interfering species like UA, AA, glucose, dopamine, Cl-, K+, Na+, Ca2+, and IgG. The enhanced electrocatalytic performance of the Ni-Co-MOF hydrogel electrode is attributed to the presence of Ni and Co, fostering Ni2+ oxidation on the surface and forming a Co2+ complex that acts as a catalyst for urea oxidation. The fabricated sensor exhibits successful detection and retrieval of urea in simulated tear samples, showcasing promising potential for bioanalytical applications. The binder-free, non-toxic nature of the Ni-Co-MOF hydrogel sensor presents exciting avenues for future utilization in non-enzymatic electrochemical sensing, including applications in wearable devices, point-of-care diagnostics, and personalized healthcare monitoring.

Disease diagnosis and application analysis of molecularly imprinted polymers (MIPs) in saliva detection

Saliva has significantly evolved as a diagnostic fluid in recent years, giving a non-invasive alternative to blood analysis. A high protein concentration in saliva is delivered directly from the bloodstream, making it a "human mirror" that reflects the body's physiological state. It plays an essential role in detecting diseases in biomedical and fitness monitoring. Molecularly imprinted polymers (MIPs) are biomimetic materials with custom-designed synthetic recognition sites that imitate biological counterparts renowned for sensitive analyte detection. This paper reviews the progress made in research about MIP biosensors for detecting saliva biomarkers. Specifically, we investigate the link between saliva biomarkers and various diseases, providing detailed insights into the corresponding biosensors. Furthermore, we discuss the principles of molecular imprinting for disease diagnostics and application analysis, including recent advances in integrated MIP-sensor technologies for high-affinity analyte detection in saliva. Notably, these biosensors exhibit high discrimination, allowing for the detection of saliva biomarkers linked explicitly to chronic stress disorders, diabetes, cancer, bacterial or viral-induced illnesses, and exposure to illicit toxic substances or tobacco smoke. Our findings indicate that MIP-based biosensors match and perhaps surpass their counterparts featuring integrated natural antibodies in terms of stability, signal-to-noise ratios, and detection limits. Additionally, we highlight the design of MIP coatings, strategies for synthesizing polymers, and the integration of advanced biodevices. These tailored biodevices, designed to assess various salivary biomarkers, are emerging as promising screening or diagnostic tools for real-time monitoring and self-health management, improving quality of life.

Preparation of β-Cyclodextrin Functionalized Platform for Monitoring Changes in Potassium Content in Perspiration

The monitoring of potassium ion (K+) levels in human sweat can provide valuable insights into electrolyte balance and muscle fatigue non-invasively. However, existing laboratory techniques for sweat testing are complex, while wearable sensors face limitations like drift, fouling and interference from ions such as Na+. This work develops printed electrodes using β-cyclodextrin functionalized reduced graphene oxide (β-CD-RGO) for selective K+ quantification in sweat. The β-CD prevents the aggregation of RGO sheets while also providing selective binding sites for K+ capture. Electrodes were fabricated by screen printing the β-CD-RGO ink onto conductive carbon substrates. Material characterization confirmed the successful functionalization of RGO with β-CD. Cyclic voltammetry (CV) showed enhanced electrochemical behavior for β-CD-RGO-printed electrodes compared with bare carbon and RGO. Sensor optimization resulted in a formulation with 30% β-CD-RGO loading. The printed electrodes were drop-casted with an ion-selective polyvinyl chloride (PVC) membrane. A linear range from 10 μM to 100 mM was obtained along with a sensitivity of 54.7 mV/decade. The sensor showed good reproducibility over 10 cycles in 10 mM KCl. Minimal interference from 100 mM Na+ and other common sweat constituents validated the sensor's selectivity. On-body trials were performed by mounting the printed electrodes on human subjects during exercise. The K+ levels measured in sweat were found to correlate well with serum analysis, demonstrating the sensor's ability for non-invasive electrolyte monitoring. Overall, the facile synthesis of stable β-CD-RGO inks enables the scalable fabrication of wearable sensors for sweat potassium detection.

Epidermal Wearable Biosensors for the Continuous Monitoring of Biomarkers of Chronic Disease in Interstitial Fluid

Healthcare technology has allowed individuals to monitor and track various physiological and biological parameters. With the growing trend of the use of the internet of things and big data, wearable biosensors have shown great potential in gaining access to the human body, and providing additional functionality to analyze physiological and biochemical information, which has led to a better personalized and more efficient healthcare. In this review, we summarize the biomarkers in interstitial fluid, introduce and explain the extraction methods for interstitial fluid, and discuss the application of epidermal wearable biosensors for the continuous monitoring of markers in clinical biology. In addition, the current needs, development prospects and challenges are briefly discussed.

The convergence of traditional and digital biomarkers through AI-assisted biosensing: A new era in translational diagnostics?

Advances in consumer electronics, alongside the fields of microfluidics and nanotechnology have brought to the fore low-cost wearable/portable smart devices. Although numerous smart devices that track digital biomarkers have been successfully translated from bench-to-bedside, only a few follow the same fate when it comes to track traditional biomarkers. Current practices still involve laboratory-based tests, followed by blood collection, conducted in a clinical setting as they require trained personnel and specialized equipment. In fact, real-time, passive/active and robust sensing of physiological and behavioural data from patients that can feed artificial intelligence (AI)-based models can significantly improve decision-making, diagnosis and treatment at the point-of-procedure, by circumventing conventional methods of sampling, and in person investigation by expert pathologists, who are scarce in developing countries. This review brings together conventional and digital biomarker sensing through portable and autonomous miniaturized devices. We first summarise the technological advances in each field vs the current clinical practices and we conclude by merging the two worlds of traditional and digital biomarkers through AI/ML technologies to improve patient diagnosis and treatment. The fundamental role, limitations and prospects of AI in realizing this potential and enhancing the existing technologies to facilitate the development and clinical translation of "point-of-care" (POC) diagnostics is finally showcased.

Universal Fully Integrated Wearable Sensor Arrays for the Multiple Electrolyte and Metabolite Monitoring in Raw Sweat, Saliva, or Urine

Fully integrated wearable sensors are capable of dynamically, directly, and independently tracking biomarkers in raw noninvasive biofluids without any other equipment or accessories by integrating the unique on-body monitoring feature with the special complete functional implementation attribute. Sweat, saliva, and urine are three important noninvasive biofluids, and changes in their biomarkers hold great potential for revealing physiological conditions. However, it is still a challenge to design single fully integrated wearable sensor arrays (FIWSAs) that are universally able to concurrently measure electrolytes and metabolites in three of the most common noninvasive biofluids including sweat, saliva, and urine. Here, we propose the first single universal FIWSAs for wirelessly, noninvasively, and simultaneously measuring various metabolites (i.e., uric acid) and electrolytes (i.e., Na⁺ and H⁺) in raw sweat, saliva, or urine under subjects' exercise by integrating the specifically designed microfluidic, sensing, and electronic modules in a seamless manner. We evaluate its utility for noninvasive gout management in healthy subjects and in gout patients through a purine-rich meal challenge and with a medicine-treatment control, respectively. Noninvasive monitoring of multiple electrolytes and metabolites in a variety of raw noninvasive biofluids via such single universal FIWSAs may enrich the understanding of the biomarkers' levels in the body and would also facilitate self-health management.

A Short Review on Miniaturized Biosensors for the Detection of Nucleic Acid Biomarkers

Even today, most biomarker testing is executed in centralized, dedicated laboratories using bulky instruments, automated analyzers, and increased analysis time and expenses. The development of miniaturized, faster, low-cost microdevices is immensely anticipated for substituting for these conventional laboratory-oriented assays and transferring diagnostic results directly onto the patient's smartphone using a cloud server. Pioneering biosensor-based approaches might make it possible to test biomarkers with reliability in a decentralized setting, but there are still a number of issues and restrictions that must be resolved before the development and use of several biosensors for the proper understanding of the measured biomarkers of numerous bioanalytes such as DNA, RNA, urine, and blood. One of the most promising processes to address some of the issues relating to the growing demand for susceptible, quick, and affordable analysis techniques in medical diagnostics is the creation of biosensors. This article critically discusses a short review of biosensors used for detecting nucleic acid biomarkers, and their use in biomedical prognostics will be addressed while considering several essential characteristics.

Microneedle-Coupled Epidermal Sensors for In-Situ-Multiplexed Ion Detection in Interstitial Fluids

Maintaining the concentrations of various ions in body fluids is critical to all living organisms. In this contribution, we designed a flexible microneedle patch coupled electrode array (MNP-EA) for the in situ multiplexed detection of ion species (Na⁺, K⁺, Ca²⁺, and H⁺) in tissue interstitial fluid (ISF). The microneedles (MNs) are mechanically robust for skin or cuticle penetration (0.21 N/needle) and highly swellable to quickly extract sufficient ISF onto the ion-selective electrochemical electrodes (∼6.87 μL/needle in 5 min). The potentiometric sensor can simultaneously detect these ion species with nearly Nernstian response in the ranges wider enough for diagnosis purposes (Na⁺: 0.75-200 mM, K⁺: 1-128 mM, Ca²⁺: 0.25-4.25 mM, pH: 5.5-8.5). The in vivo experiments on mice, humans, and plants demonstrate the feasibility of MNP-EA for timely and convenient diagnosis of ion imbalances with minimal invasiveness. This transdermal sensing platform shall be instrumental to home-based diagnosis and health monitoring of chronic diseases and is also promising for smart agriculture and the study of plant biology.

3D Printed Hydrogel Microneedle Arrays for Interstitial Fluid Biomarker Extraction and Colorimetric Detection

To treat and manage chronic diseases, it is necessary to continuously monitor relevant biomarkers and modify treatment as the disease state changes. Compared to other bodily fluids, interstitial skin fluid (ISF) is a good choice for identifying biomarkers because it has a molecular composition most similar to blood plasma. Herein, a microneedle array (MNA) is presented to extract ISF painlessly and bloodlessly. The MNA is made of crosslinked poly(ethylene glycol) diacrylate (PEGDA), and an optimal balance of mechanical properties and absorption capability is suggested. Besides, the effect of needles’ cross-section shape on skin penetration is studied. The MNA is integrated with a multiplexed sensor that provides a color change in a biomarker concentration-dependent manner based on the relevant reactions for colorimetric detection of pH and glucose biomarkers. The developed device enables diagnosis by visual inspection or quantitative red, green, and blue (RGB) analysis. The outcomes of this study show that MNA can successfully identify biomarkers in interstitial skin fluid in a matter of minutes. The home-based long-term monitoring and management of metabolic diseases will benefit from such practical and self-administrable biomarker detection.

Recent Advances in Microfluidics-Based Electrochemical Sensors for Foodborne Pathogen Detection

Using pathogen-infected food that can be unhygienic can result in severe diseases and an increase in mortality rate among humans. This may arise as a serious emergency problem if not appropriately restricted at this point of time. Thus, food science researchers are concerned with precaution, prevention, perception, and immunity to pathogenic bacteria. Expensive, elongated assessment time and the need for skilled personnel are some of the shortcomings of the existing conventional methods. Developing and investigating a rapid, low-cost, handy, miniature, and effective detection technology for pathogens is indispensable. In recent times, there has been a significant scope of interest for microfluidics-based three-electrode potentiostat sensing platforms, which have been extensively used for sustainable food safety exploration because of their progressively high selectivity and sensitivity. Meticulously, scholars have made noteworthy revolutions in signal enrichment tactics, measurable devices, and portable tools, which can be used as an allusion to food safety investigation. Additionally, a device for this purpose must incorporate simplistic working conditions, automation, and miniaturization. In order to meet the critical needs of food safety for on-site detection of pathogens, point-of-care testing (POCT) has to be introduced and integrated with microfluidic technology and electrochemical biosensors. This review critically discusses the recent literature, classification, difficulties, applications, and future directions of microfluidics-based electrochemical sensors for screening and detecting foodborne pathogens.

Electrochemical-based remote biomarker monitoring: Toward Internet of Wearable Things in telemedicine

Internet of Wearable Things (IoWT) will be a major breakthrough for remote medical monitoring. In this scenario, wearable biomarker sensors have been developing not only to diagnose point-of-care (POC) of diseases, but also to continuously manage them. On-body tracking of biomarkers in biofluids is regarded as a proper substitution of conventional biomarker sensors for dynamic sampling and analyzing due to their high sensitivity, conformability, and affordability, creating ever-rising the market demand for them. In a wireless body area network (WBAN), data is captured from all sensors on the body to a smartphone/laptop, and sent the sensed data to a cloud for storing, processing, and retrieving, and ultimately displayed the data on custom applications (Apps). Wearable IoT biomarker sensors are used for early diseases diagnosis and continuous monitoring in developing countries in which people hardly access to healthcare systems. In this review, we aim to highlight a wide range of wearable electrochemical biomarker sensors, accompanied by microfluidics for continuous sampling, which will pave the way toward developing wearable IoT biomarker sensors to track health status. The current challenges and future perspective in skin-conformal biomarker sensors will be discussing their potential applicability for IoWT in cloud-based telemedicine.

Current development of stretchable self-powered technology based on nanomaterials toward wearable biosensors in biomedical applications

In combination with the growing fields of artificial intelligence and Internet-of-things (IoT), the innovation direction of next-generation biosensing systems is toward intellectualization, miniaturization, and wireless portability. Enormous research efforts have been made in self-powered technology due to the gradual decline of traditional rigid and cumbersome power sources in comparison to wearable biosensing systems. Research progress on various stretchable self-powered strategies for wearable biosensors and integrated sensing systems has demonstrated their promising potential in practical biomedical applications. In this review, up-to-date research advances in energy harvesting strategies are discussed, together with a future outlook and remaining challenges, shedding light on the follow-up research priorities.

Fabrication of FeVO4/RGO Nanocomposite: An Amperometric Probe for Sensitive Detection of Methyl Parathion in Green Beans and Solar Light-Induced Degradation

Pesticide usage is one of the significant issues in modern agricultural practices; hence, monitoring pesticide content and its degradation is of utmost importance. A novel and simple one-pot deep eutectic solvent-based solvothermal method has been developed for the synthesis of FeVO₄/reduced graphene oxide (FeV/RGO) nanocomposite. The band gap of FeV decreased upon anchoring with RGO. Enhanced activity in the detection and photocatalytic degradation has been achieved in the FeV/RGO nanocomposite compared to pure FeV and RGO. FeV/RGO was used to modify glassy carbon electrode (GCE), and the fabricated electrode was evaluated for its electrochemical detection of methyl parathion (MP). The amperometric technique was found to be more sensitive with a 0.001-260 μM (two linear ranges; 0.001-20 and 25-260 μM) wide linear range and low limit of detection value (0.70 nM). The practical applicability of modified GCE is more selective and sensitive to real samples like river water and green beans. Photocatalytic degradation of MP has been examined using FeV, RGO, and FeV/RGO nanocomposite. FeV/RGO managed to degrade 95% of MP under solar light in 80 min. Degradation parameters were optimized carefully to attain maximum efficiency. Degradation intermediates were identified using liquid chromatography-mass spectrometry analysis. The degradation mechanism has been studied in detail. FeV/RGO could serve as a material of choice in the field of electrochemical sensors as well as heterogeneous catalysis toward environmental remediation.

Tear Biomarkers in Alzheimer's and Parkinson's Diseases, and Multiple Sclerosis: Implications for Diagnosis (Systematic Review)

Biological material is one of the most important aspects that allow for the correct diagnosis of the disease, and tears are an interesting subject of research because of the simplicity of collection, as the well as the relation to the components similar to other body fluids. In this review, biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS) in tears are investigated and analyzed. Records were obtained from the PubMed and Google Scholar databases in a timeline of 2015-2022. The keywords were: tear film/tear biochemistry/tear biomarkers + diseases (AD, PD, or MS). The recent original studies were analyzed, discussed, and biomarkers present in tears that can be used for the diagnosis and management of AD, PD, and MS diseases were shown. α-synTotal and α-synOligo, lactoferrin, norepinephrine, adrenaline, epinephrine, dopamine, α-2-macroglobulin, proteins involved in immune response, lipid metabolism and oxidative stress, apolipoprotein superfamily, and others were shown to be biomarkers in PD. For AD as potential biomarkers, there are: lipocalin-1, lysozyme-C, and lacritin, amyloid proteins, t-Tau, p-Tau; for MS there are: oligoclonal bands, lipids containing choline, free carnitine, acylcarnitines, and some amino acids. Information systematized in this review provides interesting data and new insight to help improve clinical outcomes for patients with neurodegenerative disorders.