Skin-Interfaced Wearable Sweat Sensors for Precision Medicine.

Wearable sensors hold great potential in empowering personalized health monitoring, predictive analytics, and timely intervention toward personalized healthcare. Advances in flexible electronics, materials science, and electrochemistry have spurred the development of wearable sweat sensors that enable the continuous and noninvasive screening of analytes indicative of health status. Existing major challenges in wearable sensors include: improving the sweat extraction and sweat sensing capabilities, improving the form factor of the wearable device for minimal discomfort and reliable measurements when worn, and understanding the clinical value of sweat analytes toward biomarker discovery. This review provides a comprehensive review of wearable sweat sensors and outlines state-of-the-art technologies and research that strive to bridge these gaps. The physiology of sweat, materials, biosensing mechanisms and advances, and approaches for sweat induction and sampling are introduced. Additionally, design considerations for the system-level development of wearable sweat sensing devices, spanning from strategies for prolonged sweat extraction to efficient powering of wearables, are discussed. Furthermore, the applications, data analytics, commercialization efforts, challenges, and prospects of wearable sweat sensors for precision medicine are discussed.

Unrevealing the connection between real sample analysis and analytical method. The case of cytokines.

Cytokines are compounds that belong to a special class of signaling biomolecules that are responsible for several functions in the human body, being involved in cell growth, inflammatory, and neoplastic processes. Thus, they represent valuable biomarkers for diagnosing and drug therapy monitoring certain medical conditions. Because cytokines are secreted in the human body, they can be detected in both conventional samples, such as blood or urine, but also in samples less used in medical practice such as sweat or saliva. As the importance of cytokines was identified, various analytical methods for their determination in biological fluids were reported. The gold standard in cytokine detection is considered the enzyme-linked immunosorbent assay method and the most recent ones have been considered and compared in this study. It is known that the conventional methods are accompanied by a few disadvantages that new methods of analysis, especially electrochemical sensors, are trying to overcome. Electrochemical sensors proved to be suited for the elaboration of integrated, portable, and wearable sensing devices, which could also facilitate cytokines determination in medical practice.

Triple Therapy for Cystic Fibrosis Phe508del-Gating and -Residual Function Genotypes.

BACKGROUND: Elexacaftor-tezacaftor-ivacaftor is a small-molecule cystic fibrosis transmembrane conductance regulator (CFTR) modulator regimen shown to be efficacious in patients with at least one Phe508del allele, which indicates that this combination can modulate a single Phe508del allele. In patients whose other CFTR allele contains a gating or residual function mutation that is already effectively treated with previous CFTR modulators (ivacaftor or tezacaftor-ivacaftor), the potential for additional benefit from restoring Phe508del CFTR protein function is unclear. METHODS: We conducted a phase 3, double-blind, randomized, active-controlled trial involving patients 12 years of age or older with cystic fibrosis and Phe508del-gating or Phe508del-residual function genotypes. After a 4-week run-in period with ivacaftor or tezacaftor-ivacaftor, patients were randomly assigned to receive elexacaftor-tezacaftor-ivacaftor or active control for 8 weeks. The primary end point was the absolute change in the percentage of predicted forced expiratory volume in 1 second (FEV1) from baseline through week 8 in the elexacaftor-tezacaftor-ivacaftor group. RESULTS: After the run-in period, 132 patients received elexacaftor-tezacaftor-ivacaftor and 126 received active control. Elexacaftor-tezacaftor-ivacaftor resulted in a percentage of predicted FEV1 that was higher by 3.7 percentage points (95% confidence interval [CI], 2.8 to 4.6) relative to baseline and higher by 3.5 percentage points (95% CI, 2.2 to 4.7) relative to active control and a sweat chloride concentration that was lower by 22.3 mmol per liter (95% CI, 20.2 to 24.5) relative to baseline and lower by 23.1 mmol per liter (95% CI, 20.1 to 26.1) relative to active control (P<0.001 for all comparisons). The change from baseline in the Cystic Fibrosis Questionnaire-Revised respiratory domain score (range, 0 to 100, with higher scores indicating better quality of life) with elexacaftor-tezacaftor-ivacaftor was 10.3 points (95% CI, 8.0 to 12.7) and with active control was 1.6 points (95% CI, -0.8 to 4.1). The incidence of adverse events was similar in the two groups; adverse events led to treatment discontinuation in one patient (elevated aminotransferase level) in the elexacaftor-tezacaftor-ivacaftor group and in two patients (anxiety or depression and pulmonary exacerbation) in the active control group. CONCLUSIONS: Elexacaftor-tezacaftor-ivacaftor was efficacious and safe in patients with Phe508del-gating or Phe508del-residual function genotypes and conferred additional benefit relative to previous CFTR modulators. (Funded by Vertex Pharmaceuticals; VX18-445-104 ClinicalTrials.gov number, NCT04058353.).

Explainable Deep Learning-Assisted Self-Calibrating Colorimetric Patches for In Situ Sweat Analysis.

Sweat has emerged as a compelling analyte for noninvasive biosensing technology because it contains a wealth of important biomarkers in hormones, organic biomacromolecules, and various ionic mixtures. These components offer valuable insights and can reflect an individual's physiological conditions. Here, we introduced an explainable deep learning (DL)-assisted wearable self-calibrating colorimetric biosensing analysis platform to efficiently and precisely detect the biomarker's concentration in sweat. Specifically, we have integrated the advantages of the colorimetric sensing method, adsorbing-swelling hydrogel, and explainable DL algorithms to develop an enzyme/indicator-immobilized colorimetric patch, which has reliable colorimetric sensing ability and excellent adsorbing-swelling function. A total of 5625 colorimetric images were collected as the analysis data set and assessed two DL algorithms and seven machine learning (ML) algorithms. Zn2+, glucose, and Ca2+ in human sweats could be facilely classified and quantified with 100% accuracy via the convolutional neural network (CNN) model, and the testing results of actual sweats via the DL-assisted colorimetric approach are 91.7-97.2% matching with the classical UV-vis spectrum. Class activation mapping (CAM) was utilized to visualize the inner working mechanism of CNN operation, which contributes to verify and explicate the design rationality of the noninvasive biosensing technology. An "end-to-end" model was established to ascertain the black box of the DL algorithm, promoted software design or principium optimization, and contributed facile indicators for health monitoring, disease prevention, and clinical diagnosis.

Integrated Electrochemical Aptasensor Array toward Monitoring Anticancer Drugs in Sweat.

In the realm of clinical practice, the concurrent utilization of anticancer medications can enhance their overall therapeutic efficacy. However, it is crucial to acknowledge that the interactions among these anticancer drugs can potentially yield detrimental consequences on their intended outcomes. Consequently, the assessment of both anticancer potency and potential toxic side effects is greatly refined when multiple anticancer drugs are simultaneously detected and evaluated. Here, we designed a wearable electrochemical aptasensor array for monitoring multiple anticancer drugs in sweat. The integrated sensor array consists of three working electrodes modified with three different aptamers (Apt1, Apt2, and Apt3), a Au counter electrode, and a Ag/AgCl reference electrode. Molecular docking simulations were performed to show the binding affinities between three anticancer drugs and their corresponding aptamers. Various eigenvalues were derived from the square-wave voltammetry electrochemical signals, and these data sets were subjected to rigorous analysis through multivariate data analysis techniques. This analytical approach demonstrated exceptional performance by achieving flawless 100% accuracy in the precise identification of nine anticancer drugs consistently at uniform concentrations. Furthermore, the integrated wearable sensor array exhibited impressive capabilities, correctly recognizing all nine anticancer drugs with 100% accuracy and successfully distinguishing between these drugs in artificial sweat samples. The proposed sensor array presents good stability for 15 days. Flexibility tests showed stable device performance after 500 twisting cycles. This innovative wearable sensing array represents a novel approach for achieving real-time monitoring and precise adjustment of drug dosages. It offers invaluable insights for tailoring the treatment of anticancer drugs to individual patients, predicting both drug efficacy and potential adverse reactions within the field of clinical medicine.

A Wearable Thin-Film Hydrogel Laser for Functional Sensing on Skin.

Flexible photonics offers the possibility of realizing wearable sensors by bridging the advantages of flexible materials and photonic sensing elements. Recently, optical resonators have emerged as a tool to improve their oversensitivity by integrating with flexible photonic sensors. However, direct monitoring of multiple psychological information on human skin remains challenging due to the subtle biological signals and complex tissue interface. To tackle the current challenges, here, we developed a functional thin film laser formed by encapsulating liquid crystal droplet lasers in a flexible hydrogel for monitoring metabolites in human sweat (lactate, glucose, and urea). The three-dimensional cross-linked hydrophilic polymer serves as the adhesive layer to allow small molecules to penetrate from human tissue to generate strong light--matter interactions on the interface of whispering gallery modes resonators. Both the hydrogel and cholesteric liquid crystal microdroplets were modified specifically to achieve high sensitivity and selectivity. As a proof of concept, wavelength-multiplexed sensing and a prototype were demonstrated on human skin to detect human metabolites from perspiration. These results present a significant advance in the fabrication and potential guidance for wearable and functional microlasers in healthcare.

A Wearable Electrochemical Biosensor Utilizing Functionalized Ti3C2Tx MXene for the Real-Time Monitoring of Uric Acid Metabolite.

Wearable, noninvasive sensors enable the continuous monitoring of metabolites in sweat and provide clinical information related to an individual's health and disease states. Uric acid (UA) is a key indicator highly associated with gout, hyperuricaemia, hypertension, kidney disease, and Lesch-Nyhan syndrome. However, the detection of UA levels typically relies on invasive blood tests. Therefore, developing a wearable device for noninvasive monitoring of UA concentrations in sweat could facilitate real-time personalized disease prevention. Here, we introduce 1,3,6,8-pyrene tetrasulfonic acid sodium salt (PyTS) as a bifunctional molecule functionalized with Ti3C2Tx via π-π conjugation to design nonenzymatic wearable sensors for sensitive and selective detection of UA concentration in human sweat. PyTS@Ti3C2Tx provides many oxidation-reduction active groups to enhance the electrocatalytic ability of the UA oxidation reaction. The PyTS@Ti3C2Tx-based electrochemical sensor demonstrates highly sensitive detection of UA in the concentration range of 5 µM-100 µM, exhibiting a lower detection limit of 0.48 µM compared to the uricase-based sensor (0.84 µM). In volunteers, the PyTS@Ti3C2Tx-based wearable sensor is integrated with flexible microfluidic sweat sampling and wireless electronics to enable real-time monitoring of UA levels during aerobic exercise. Simultaneously, it allows for comparison of blood UA levels via a commercial UA analyzer. Herein, this study provides a promising electrocatalyst strategy for nonenzymatic electrochemical UA sensor, enabling noninvasive real-time monitoring of UA levels in human sweat and personalized disease prevention.

A Fully Elastic Wearable Electrochemical Sweat Detection System of Tree-Bionic Microfluidic Structure for Real-Time Monitoring.

Fresh sweat contains a diverse range of physiological indicators that can effectively reflect changes in the body. However, existing wearable sweat detection systems face challenges in efficiently collecting and detecting fresh sweat in real-time. Additionally, they often lack the necessary deformation capabilities, resulting in discomfort for the wearer. Here, a fully elastic wearable electrochemical sweat detection system is developed that integrates a sweat-collecting microfluidic chip, a multi-parameter electrochemical sensor, a micro-heater, and a sweat detection elastic circuit board system. The unique tree-bionic structure of the microfluidic chip significantly enhances the efficiency of fresh sweat collection and discharge, enabling real-time detection by the electrochemical sensors. The sweat multi-parameter electrochemical sensor offers high-precision and high-sensitivity measurements of sodium ions, potassium ions, lactate, and glucose. The electronic system is built on an elastic circuit board that matches perfectly to wrinkled skin, ensuring improved wearing comfort and enabling multi-channel data sampling, processing, and wireless transmission. This state-of-the-art system represents a significant advancement in the field of elastic wearable sweat detection and holds promising potential for extending its capabilities to the detection of other sweat markers or various wearable applications.

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.

Capillary electrophoresis with capacitively coupled contactless conductivity detection (C4 D) for rapid and simple determination of lactate in sweat.

An analytical method based on capillary electrophoresis (CE) using capacitively coupled contactless conductivity detection (C4 D) was developed and validated for fast, straightforward, and reliable determination of lactate in artificial and human sweat samples. The background electrolyte was composed of equimolar concentrations (10 mmol/L) of 2-(N-morpholino)ethanesulfonic acid and histidine, with 0.2 mmol/L of cetyltrimethylammonium bromide as electroosmotic flow inverter. The limit of detection and quantification were 3.1 and 10.3 µmol/L, respectively. Recoveries in the 97 to 118% range were obtained using sweat samples spiked with lactate at three concentration levels, indicating an acceptable accuracy. The intraday and interday precisions were 1.49 and 7.08%, respectively. The proposed CE-C4 D method can be a starting point for monitoring lactate concentrations in sweat samples for diagnostics, physiological studies, and sports performance assessment applications.

Blood, sweat, and fears: Athletes' perceptions of blood donation and engagement in physical activity.

BACKGROUND: Athletes are a key group from which likely eligible donors could be sourced. While blood donation has been popularized as detrimental to athletic performance, little is known about how athletes perceive blood donation. The aim of this study was to investigate athletes' perceptions of the impacts of donating blood on their athletic performance and whether these influence their engagement with blood donation. STUDY DESIGN AND METHODS: A total of 175 athletes (78 donors; 97 non-donors) prescreened as eligible to donate blood in Australia completed an online survey assessing the perceived impact of (i) donating blood on engagement and performance in physical activity (type of impact, direction, and duration) and (ii) engaging in physical activity on blood donation (magnitude of impact and modification of behavior). RESULTS: We found that 37%-39% of our sample indicated that they had considered the impact of donating blood on their engagement or performance in physical activity, with the impact seen as negative but short term. Fatigue was the most commonly identified impact of donation on performance in physical activity. While the impact of donating did not account for athletes' non-donor status, many donors noted changing their engagement in physical activity pre- and post-donation to allow recovery, and aligning blood donation with their training schedule. DISCUSSION: Athletes are a key community from which likely eligible donors could be sourced, however a significant proportion of athletes perceive that donating will negatively impact their athletic performance. Strategies to engage athletes with donation should acknowledge and facilitate athletes need to align their training with donating.

The protease corin regulates electrolyte homeostasis in eccrine sweat glands.

Sweating is a basic skin function in body temperature control. In sweat glands, salt excretion and reabsorption are regulated to avoid electrolyte imbalance. To date, the mechanism underlying such regulation is not fully understood. Corin is a transmembrane protease that activates atrial natriuretic peptide (ANP), a cardiac hormone essential for normal blood volume and pressure. Here, we report an unexpected role of corin in sweat glands to promote sweat and salt excretion in regulating electrolyte homeostasis. In human and mouse eccrine sweat glands, corin and ANP are expressed in the luminal epithelial cells. In corin-deficient mice on normal- and high-salt diets, sweat and salt excretion is reduced. This phenotype is associated with enhanced epithelial sodium channel (ENaC) activity that mediates Na+ and water reabsorption. Treatment of amiloride, an ENaC inhibitor, normalizes sweat and salt excretion in corin-deficient mice. Moreover, treatment of aldosterone decreases sweat and salt excretion in wild-type (WT), but not corin-deficient, mice. These results reveal an important regulatory function of corin in eccrine sweat glands to promote sweat and salt excretion.

Metabolite monitoring concept for the biometric identification of individuals from the skin surface.

This study aims at proof of concept that constant monitoring of the concentrations of metabolites in three individuals' sweat over time can differentiate one from another at any given time, providing investigators and analysts with increased ability and means to individualize this bountiful biological sample. A technique was developed to collect and extract authentic sweat samples from three female volunteers for the analysis of lactate, urea, and L-alanine levels. These samples were collected 21 times over a 40-day period and quantified using a series of bioaffinity-based enzymatic assays with UV-vis spectrophotometric detection. Sweat samples were simultaneously dried, derivatized, and analyzed by a GC-MS technique for comparison. Both UV-vis and GC-MS analysis methods provided a statistically significant MANOVA result, demonstrating that the sum of the three metabolites could differentiate each individual at any given day of the time interval. Expanding upon previous studies, this experiment aims to establish a method of metabolite monitoring as opposed to single-point analyses for application to biometric identification from the skin surface.

High performance nonenzymatic electrochemical sensors via thermally grown Cu native oxides (CuNOx) towards sweat glucose monitoring.

Diabetes, which is the seventh leading cause of death globally, necessitates real-time blood glucose monitoring, a process that is often invasive. A promising alternative is sweat glucose monitoring, which typically uses transition metals and their oxide nanomaterials as sensors. Despite their excellent surface-to-volume ratio, these materials have some drawbacks, including poor conductivity, structural collapse, and aggregation. As a result, selecting highly electroconductive materials and optimizing their nanostructures is critical. In this work, we developed a high-performance, low-cost, nonenzymatic sensor for sweat glucose detection, using the thermally grown native oxide of copper (CuNOx). By heating Cu foil at 160, 250, and 280 °C, we grew a native oxide layer of approximately 140 nm cupric oxide (CuO), which is excellent for glucose electrocatalysis. Using cyclic voltammetry, we found that our CuNOx sensors prepared at 280 °C exhibited a sensitivity of 1795 µA mM-1 cm-2, a linear range up to the desired limit of 1.00 mM for sweat glucose with excellent linearity (R2 = 0.9844), and a lower limit of detection of 135.39 µM. For glucose sensing, the redox couple Cu(II)/Cu(III) oxidizes glucose to gluconolactone and subsequently to gluconic acid, producing an oxidation current in an alkaline environment. Our sensors showed excellent repeatability and stability (remaining stable for over a year) with a relative standard deviation (RSD) of 2.48% and 4.17%, respectively, for 1 mM glucose. The selectivity, when tested with common interferants found in human sweat and blood, showed an RSD of 4.32%. We hope that the electrocatalytic efficacy of the thermally grown CuNOx sensors for glucose sensing can introduce new avenues in the fabrication of sweat glucose sensors.

An integrated wearable sticker based on extended-gate AlGaN/GaN high electron mobility transistors for real-time cortisol detection in human sweat.

Cortisol hormone imbalances can be detected through non-invasive sweat monitoring using field-effect transistor (FET) biosensors, which provide rapid and sensitive detection. However, challenges like skin compatibility and integration with sweat collection have hindered FET biosensors as wearable sensing platforms. In this study, we present an integrated wearable sticker for real-time cortisol detection based on an extended-gate AlGaN/GaN high electron mobility transistor (HEMT) combined with a soft bottom substrate and flexible channel for sweat collection. The developed devices exhibit excellent linearity (R2 = 0.990) and a high sensitivity of 1.245 µA dec-1 for cortisol sensing from 1 nM to 100 µM in high-ionic-strength solution, with successful cortisol detection demonstrated using authentic human sweat samples. Additionally, the chip's microminiature design effectively reduces bending impact during the wearable process of traditional soft binding sweat sensors. The extendedgate structure design of the HEMT chip enhances both width-to-length ratio and active sensing area, resulting in an exceptionally low detection limit of 100 fM. Futhermore, due to GaN material's inherent stability, this device exhibits long-term stability with sustained performance within a certain attenuation range even after 60 days. These stickers possess small, lightweight, and portable features that enable real-time cortisol detection within 5 minutes through direct sweat collection. The application of this technology holds great potential in the field of personal health management, facilitating users to conveniently monitor their mental and physical conditions.

Heat Transfer by Sweat Droplet Evaporation.

Sweating regulates the body temperature in extreme environments or during exercise. Here, we investigate the evaporative heat transfer of a sweat droplet at the microscale to unveil how the evaporation complexity of a sweat droplet would affect the body's ability to cool under specific environmental conditions. Our findings reveal that, depending on the relative humidity and temperature levels, sweat droplets experience imperfect evaporation dynamics, whereas water droplets evaporate perfectly at equivalent ambient conditions. At low humidity, the sweat droplet fully evaporates and leaves a solid deposit, while at high humidity, the droplet never reaches a solid deposit and maintains a liquid phase residue for both low and high temperatures. This unprecedented evaporation mechanism of a sweat droplet is attributed to the intricate physicochemical properties of sweat as a biofluid. We suppose that the sweat residue deposited on the surface by evaporation is continuously absorbing the surrounding moisture. This route leads to reduced evaporative heat transfer, increased heat index, and potential impairment of the body's thermoregulation capacity. The insights into the evaporative heat transfer dynamics at the microscale would help us to improve the knowledge of the body's natural cooling mechanism with practical applications in healthcare, materials science, and sports science.

The correlation of urea and creatinine concentrations in sweat and saliva with plasma during hemodialysis: an observational cohort study.

OBJECTIVES: Urea and creatinine concentrations in plasma are used to guide hemodialysis (HD) in patients with end-stage renal disease (ESRD). To support individualized HD treatment in a home situation, there is a clinical need for a non-invasive and continuous alternative to plasma for biomarker monitoring during and between cycles of HD. In this observational study, we therefore established the correlation of urea and creatinine concentrations between sweat, saliva and plasma in a cohort of ESRD patients on HD. METHODS: Forty HD patients were recruited at the Dialysis Department of the Catharina Hospital Eindhoven. Sweat and salivary urea and creatinine concentrations were analyzed at the start and at the end of one HD cycle and compared to the corresponding plasma concentrations. RESULTS: A decrease of urea concentrations during HD was observed in sweat, from 27.86 mmol/L to 12.60 mmol/L, and saliva, from 24.70 mmol/L to 5.64 mmol/L. Urea concentrations in sweat and saliva strongly correlated with the concentrations in plasma (ρ 0.92 [p<0.001] and 0.94 [p<0.001], respectively). Creatinine concentrations also decreased in sweat from 43.39 µmol/L to 19.69 µmol/L, and saliva, from 59.00 µmol/L to 13.70 µmol/L. However, for creatinine, correlation coefficients were lower than for urea for both sweat and saliva compared to plasma (ρ: 0.58 [p<0.001] and 0.77 [p<0.001], respectively). CONCLUSIONS: The results illustrate a proof of principle of urea measurements in sweat and saliva to monitor HD adequacy in a non-invasive and continuous manner. Biosensors enabling urea monitoring in sweat or saliva could fill in a clinical need to enable at-home HD for more patients and thereby decrease patient burden.

Wearable biosensors for human sweat glucose detection based on carbon black nanoparticles.

Wearable glucose biosensors enable noninvasive glucose monitoring, thereby enhancing blood glucose management. In this work, we present a wearable biosensor based on carbon black nanoparticles (CBNPs) for glucose detection in human sweat. The biosensor consists of CBNPs, Prussian blue (PB), glucose oxidase, chitosan, and Nafion. The fabricated biosensor has a linear range of 5 µM to 1250 µM, sensitivity of 14.64 µA mM-1 cm-2, and a low detection potential (-0.05 V, vs. Ag/AgCl). The detection limit for glucose was calculated as 4.83 µM. This reusable biosensor has good selectivity and stability and exhibits a good response to glucose in real sweat. These results demonstrate the potential of our CBNP-based biosensor for monitoring blood glucose in human sweat.

Enhanced Sweat Biosensing with Thread-Embedded Microfluidic Devices.

BACKGROUND This study explored the integration of conductive threads into a microfluidic compact disc (CD), developed using the xurographic method, for a potential sweat biosensing platform. MATERIAL AND METHODS The microfluidic CD platform, fabricated using the xurographic method with PVC films, included venting channels and conductive threads linked to copper electrodes. With distinct microfluidic sets for load and metering, flow control, and measurement, the CD's operation involved spinning for sequential liquid movement. Impedance analysis using HIOKI IM3590 was conducted for saline and artificial sweat solutions on 4 identical CDs, ensuring reliable conductivity and measurements over a 1 kHz to 200 kHz frequency range. RESULTS Significant differences in |Z| values were observed between saline and artificial sweat treatments. 27.5 µL of saline differed significantly from 27.5 µL of artificial sweat, 72.5 µL of saline from 72.5 µL of artificial sweat, and 192.5 µL of saline from 192.5 µL of sweat. Significant disparities in |Z| values were observed between dry fibers and Groups 2, 3, and 4 (varying saline amounts). No significant differences emerged between dry fibers and Groups 6, 7, and 8 (distinct artificial sweat amounts). These findings underscore variations in fiber characteristics between equivalent exposures, emphasizing the nuanced response of the microfluidic CD platform to different liquid compositions. CONCLUSIONS This study shows the potential of integrating conductive threads in a microfluidic CD platform for sweat sensing. Challenges in volume control and thread coating degradation must be addressed for transformative biosensing devices in personalized healthcare.