Sweat Patch Research Articles

Importance of Electrolytes in Exercise Performance and Assessment Methodology After Heat Training: A Narrative Review

Performing exercise in hot environmental conditions presents athletes with potential negative physiological and perceptual implications. Key constituents, such as fluid and electrolytes, are lost during sweating through the process of cooling the human body. The loss of electrolytes impairs exercise performance. Heat training is one strategy to combat sweat electrolyte loss, with decreased sweat electrolyte concentration being a main sudomotor adaptation. To measure sweat electrolyte concentration, two common assessment methods are typically utilized: whole-body washdown and regional sweat patch measurements. The effects of physiological adaptations and sweat electrolyte assessment methodology have been investigated; however, the importance of methodological differences between sweat electrolyte measurements following heat training has yet to be explored. This review explores the differences between sweat electrolyte measurement techniques following adaptations incurred with heat training. Future research directions are also provided.

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to investigate a predictive model for sleep efficiency and its associated features in older adults living with dementia in their own homes. This was an exploratory, observational study. A total of 69 older adults diagnosed with dementia were included in this study. Data were collected via actigraphy for sleep and physical activity for 14 days, a sweat patch for cytokines for 2-3 days, and a survey of diseases, medications, psychological and behavioral symptoms, functional status, and demographics at baseline. Using 730 days of actigraphy, sweat patches, and baseline data, the best prediction model for sleep efficiency was selected and further investigated to explore its associated top 10 features using machine learning analysis. The CatBoost model was selected as the best predictive model for sleep efficiency. In order of importance, the most important features were sleep regularity, number of medications, dementia medication, daytime activity count, instrumental activities of daily living, neuropsychiatric inventory, hypnotics, occupation, tumor necrosis factor-alpha, and waking hour lux. This study established the best sleep efficiency predictive model among community-dwelling older adults with dementia and its associated features using machine learning and various sources, such as the Internet of Things. This study highlights the importance of individualized sleep interventions for community-dwelling older adults with dementia based on associated features.

Evolution of materials, geometries, and fabrication of sweat patches and their use in high-throughput point-of-care/onsite sensing

Sweat is a non-invasive fluid used to monitor various medically relevant analytes for disease diagnosis and healthcare monitoring. Sweat patches are used to collect contaminant-free sweat from individuals in any setting. In the past 50 years, sweat patches have evolved on various fronts, like fabrication methods, materials, and microfluidic channel designs. The primary goal of this study is to explore the evolution of sweat patches over the last 50 years in terms of materials such as polydimethylsiloxane (PDMS), adhesives, and other polymers, as well as microfluidic channel geometries and fabrication approaches. In addition, modern sweat patches are integrated with electrodes and electronic systems that enable sweat collection and in-situ analysis. The sweat patches are classified into two classes: early and modern sweat patches. Further, applications of these sweat patches in monitoring hydration, performance, metabolites, and disease diagnosis have been elaborately discussed. In the end, the conclusion and future outlook are discussed to give insight into further research.

Microfluidic sweat patch based on capillary force and evaporation pump for real-time continuous sweat analysis.

In addition to the common blood and urine, fresh sweat contains a diverse range of physiological indicators that can effectively reflect changes in the body's state. Wearable sweat sensors are crucial for understanding human physiological health; however, real-time in situ measurement of multiple biomarkers in sweat remains a significant challenge. Here, we propose a wearable microfluidic patch featuring an integrated microfluidic channel and evaporation pump for accelerated and continuous sweat collection, eliminating the need for additional sweat storage cavities that typically impede real-time detection. Capillary forces are harnessed to facilitate the rapid flow of sweat through the detection area, while an evaporation pump based on porous laser-induced graphene enhances sweat evaporation. The synergistic integration of these two components enables an uninterrupted flow of fresh sweat within the patch, ensuring real-time monitoring. The influence of channel size parameters on sweat flow velocity is analyzed, and the optimal width-to-height ratio for achieving the desired flow velocity is determined. By implementing a multi-channel parallel design with chamfering, liquid flow resistance is effectively reduced. Furthermore, the patch integrates sensor modules for sodium ion, chloride ion, glucose, and pH value measurements, ensuring excellent sealing and stability of the assembled system. This work presents a simplified approach to developing wearable sweat sensors that hold the potential for health monitoring and disease diagnosis.

Adaptively resettable microfluidic patch for sweat rate and electrolytes detection

Skin-interfaced microfluidic patch has become a reliable device for sweat collection and analysis. However, the intractable problems of emptying the microchannel for reuse, and the channel's volumetric capacity limited by the size of the patch, directly hinder the practical application of sweat sensors. Herein, we report an adaptively resettable microfluidic sweat patch (Art-Sweat patch) capable of continuously monitoring both sweat rate (0.2–4.0 μL min−1) and total ionic charge concentration (10–200 mmol L−1). We develop a platform with a vertical and horizontal microchannel combined strategy, enabling repeatedly filling sweat and emptying the microchannel for autonomously resetting and detecting. The variation in the emptied volume is designed to be adaptively identified by the sensor, resulting in enhanced stability and an enlarged volumetric capacity of over 300 μL. By integrating with self-designed wireless transmission modules, the proposed Art-Sweat patch shows product-level wearability and high performance in monitoring variations in regional sweat rate and concentration for hydration status assessment.

Fluorescence-Recovered Wearable Hydrogel Patch for In Vitro Detection of Glucose Based on Rare-Earth Nanoparticles.

The physiological state of the human body can be indicated by analyzing the composition of sweat. In this research, a fluorescence-recovered wearable hydrogel patch has been designed and realized which can noninvasively monitor the glucose concentration in human sweat. Rare-earth nanoparticles (RENPs) of NaGdF4 doped with different elements (Yb, Er, and Ce) are synthesized and optimized for better luminescence in the near-infrared second (NIR-II) and visible region. In addition, RENPs are coated with CoOOH of which the absorbance has an extensive peak in the visible and NIR regions. The concentration of H2O2 in the environment can be detected by the fluorescence recovery degree of CoOOH-modified RENPs based on the fluorescence resonance energy transfer effect. For in vivo detection, the physiological state of oxidative stress at tumor sites can be visualized through its fluorescence in NIR-II with low background noise and high penetration depth. For the in vitro detection, CoOOH-modified RENP and glucose oxidase (GOx) were doped into a polyacrylamide hydrogel, and a patch that can emit green upconversion fluorescence under a 980 nm laser was prepared. Compared with the conventional electrochemical detection method, the fluorescence we presented has higher sensitivity and linear detection region to detect the glucose. This improved anti-interference sweat patch that can work in the dark environment was obtained, and the physiological state of the human body is conveniently monitored, which provides a new facile and convenient method to monitor the sweat status.

Enrichment of sweat-derived extracellular vesicles of human and bacterial origin for biomarker identification.

Sweat contains biomarkers for real-time non-invasive health monitoring, but only a few relevant analytes are currently used in clinical practice. In the present study, we investigated whether sweat-derived extracellular vesicles (EVs) can be used as a source of potential protein biomarkers of human and bacterial origin. Methods: By using ExoView platform, electron microscopy, nanoparticle tracking analysis and Western blotting we characterized EVs in the sweat of eight volunteers performing rigorous exercise. We compared the presence of EV markers as well as general protein composition of total sweat, EV-enriched sweat and sweat samples collected in alginate skin patches. Results: We identified 1209 unique human proteins in EV-enriched sweat, of which approximately 20% were present in every individual sample investigated. Sweat derived EVs shared 846 human proteins (70%) with total sweat, while 368 proteins (30%) were captured by medical grade alginate skin patch and such EVs contained the typical exosome marker CD63. The majority of identified proteins are known to be carried by EVs found in other biofluids, mostly urine. Besides human proteins, EV-enriched sweat samples contained 1594 proteins of bacterial origin. Bacterial protein profiles in EV-enriched sweat were characterized by high interindividual variability, that reflected differences in total sweat composition. Alginate-based sweat patch accumulated only 5% proteins of bacterial origin. Conclusion: We showed that sweat-derived EVs provide a rich source of potential biomarkers of human and bacterial origin. Use of commercially available alginate skin patches selectively enrich for human derived material with very little microbial material collected.

Soft Epidermal Paperfluidics for Sweat Analysis by Ratiometric Raman Spectroscopy.

The expanding interest in digital biomarker analysis focused on non-invasive human bodily fluids, such as sweat, highlights the pressing need for easily manufactured and highly efficient soft lab-on-skin solutions. Here, we report, for the first time, the integration of microfluidic paper-based devices (μPAD) and non-enhanced Raman-scattering-enabled optical biochemical sensing (Raman biosensing). Their integration merges the enormous benefits of μPAD, with high potential for commercialization and use in resource-limited settings, with biorecognition-element-free (but highly selective) optical Raman biosensing. The introduced thin (0.36 mm), ultra-lightweight (0.19 g), and compact footprint (3 cm2) opto-paperfluidic sweat patch is flexible, stretchable, and conforms, irritation-free, to hairless or minimally haired body regions to enable swift sweat collection. As a great advantage, this new bio-chemical sensory system excels through its absence of onboard biorecognition elements (bioreceptor-free) and omission of plasmonic nanomaterials. The proposed easy fabrication process is adaptable to mass production by following a fully sustainable and cost-effective process utilizing only basic tools by avoiding typically employed printing or laser patterning. Furthermore, efficient collection and transportation of precise sweat volumes, driven exclusively by the wicking properties of porous materials, shows high efficiency in liquid transportation and reduces biosensing latency by a factor of 5 compared to state-of-the-art epidermal microfluidics. The proposed unit enables electronic chip-free and imaging-less visual sweat loss quantification as well as optical biochemical analysis when coupled with Raman spectroscopy. We investigated the multimodal quantification of sweat urea and lactate levels ex vivo (with syntactic sweat including +30 sweat analytes on porcine skin) and achieved a linear dynamic range from 0 to 100 mmol/L during fully dynamic continuous flow characterization.

The Gx Sweat Patch for personalized hydration management

The Gx Sweat Patch is a wearable microfluidic sweat sensor that can be worn by athletes to monitor their sweating rate and sweat chloride concentration. Here, we highlight the commercialization of the Gx Sweat Patch, from developing and optimizing prototypes of a wearable sweat-sensing platform, to validation in competitive individual and team-sport athletes, and the challenges of commercial launch.

Determination of licit and illicit drugs and metabolites in human sweat by liquid chromatography-tandem mass spectrometry.

A liquid chromatography-tandem mass spectrometry screening method in sweat was developed for the simultaneous determination of three licit drugs (nicotine, paracetamol, and caffeine); four illicit drugs (cocaine, ketamine, 25I-NBOMe and methamphetamine) and two metabolites (benzoylecgonine and cotinine). Target drugs were liberated from sweat patches with pH 5 sodium acetate buffer and further purified by solid phase extraction (SPE) utilising Strata-X-Drug B cartridges. Optimal solvent constituents for SPE organic wash and elution were 70% v/v methanol in deionised water and 5% v/v ammonium hydroxide in methanol respectively. Chromatographic separation was achieved using a superficially porous particle C18 column with gradient elution, using (A) 0.1% formic acid in water and (B) acetonitrile as mobile phase constituents. Target drugs were identified using a combination of retention time, and the ion ratios for two precursor-product ion transitions for each analyte monitored in multiple reaction monitoring (MRM) mode. The method was linear for all target drugs from 1.0-150.0 ng mL-1 with corresponding limits of quantitation of 1.0 ng mL-1. Limits of detection were found to range from 0.1-0.6 ng per patch. The method was subsequently applied to the analysis of sweat samples from five male and four female participants aged 20-25 years. Sweat was collected from two areas (right forearm and left thigh) using protected layers of gauze. All eighteen patches tested positive for at least one target analyte. The results of this study not only show a multi-substance screening method was achieved but also that sweat patches can be used to indicate an individual's drug use. Therefore, they can provide an alternative non-invasive technique for forensic applications.

Artificial Neural Network-Assisted Wearable Flexible Sweat Patch for Drug Management in Parkinson's Patients Based on Vacancy-Engineered Processing of g-C3N4.

Herein, we developed a flexible, low-cost non-enzymatic sweat sensing chip for in situ acquisition of bioinformation in sweat of individuals under exercise conditions to advance personal health monitoring and medication management for patients with Parkinson's disease. This low-cost, flexible, wearable sweat sensor consists of a printed screen electrode modified with g-C3N4 material and an external MSME element. The doping strategy and surface activation strategy of the g-C3N4-based exhibited efficient glucose oxidase-like activity and electrochemical activity when testing l-dopa and glucose in sweat. The optimized signal was transmitted to a smartphone for processing 12 individuals with simulated dosing, enabling continuous monitoring of l-dopa metabolism in sweat and management of dosing. The generalization ability and robustness of models constructed by methods such as multiple linear regression, artificial neural networks, and convolutional neural networks were compared cross-sectionally. Deep learning models based on artificial neural networks help develop a user-personalized medication administration reminder system, which provides a promising paradigm for reliable medication supervision for Parkinson's patients in the Internet of Things era.

A "Two-Part" Resonance Circuit Based Detachable Sweat Patch for Noninvasive Biochemical and Biophysical Sensing.

Wearable electronics play important roles in noninvasive, continuous, and personalized monitoring of multiple biosignals generated by the body. To unleash their full potential for next-generation human centered bio-integrated electronics, the wireless sensing capability is a desirable feature. However, state-of-the-art wireless sensing technologies exploit rigid and bulky electronic modules for power supply, signal generation, and data transmission. This study reports a battery-free device technology based on a "two-part" resonance circuit model with modularized, physically separated, and detachable functional units for magnetic coupling and biosensing. The resulting platform combines advantages of electronics and microfluidics with low cost, minimized form factors, and improved performance stability. Demonstration of a detachable sweat patch capable of simultaneous recording of cortisol concentration, pH value, and temperature highlights the potential of the "two-part" circuit for advanced, transformative biosensing. The resulting wireless sensors provide a new engineering solution to monitoring biosignals through intimate and seamless integration with skin surfaces.

The Impact of the Gx Sweat Patch on the Hydration Status of Division III College Athletes

The Impact of the Gx Sweat Patch on the Hydration Status of Division III College Athletes

A low-cost and simple-fabricated epidermal sweat patch based on “cut-and-paste” manufacture

Continuous, non-invasive, and multi-parametric sensing of sweat is noted to be appealing to many applications such as personalized medicine, athletic performance, and military readiness. Microfluidic sensing patches are widely reported to perform sweat collection, transportation, and multi-parameters analysis; however, time-consuming and multi-step manufacturing process actually prevents the large-scale application. In this study, a “cut-and-paste (CAP)” method is devised to pattern and transfer polydimethylsiloxane (PDMS) and polyethylene terephthalate (PET) film to fabricate the microfluidic patch. The “bear like” patch, composed of four polymer-based layer, are completely carved automatically within 2 min by the desktop cutting machine. The sweat glucose and lactate are monitored in real time with newly proposed wearable sweat patches. The concentration ratio between blood glucose and iontophoresis-induced sweat glucose was over 512.37 as calculated. And the latter lagged behind the former over 70 min about peak of concentration. Also, using the fabricated sensors, we have analyzed the levels of glucose and lactate and compared them in both exercise- and iontophoresis-induced sweat. These results indicate the CAP method has great potential for the microfluidic integrated wearable platforms with low-cost, versatility, and mechanically flexibility, which would promote the development of wearable sweat microfluidic devices and application in individualized health monitoring.

Assessment of Withdrawal, Mood, and Sleep Inventories After Monitored 3-Week Abstinence in Cannabis-Using Adolescents and Young Adults.

Introduction: Among adolescents and young adults, cannabis use is prevalent. Prior studies characterizing withdrawal effects in this age range have primarily included treatment seeking or comorbid psychiatric samples; these studies have identified several affected domains, especially sleep, mood, and anxiety. The present study compared a community (i.e., nontreatment seeking) sample of cannabis-using and control participants on mood, anxiety, sleep, and withdrawal inventories during the course of a monitored 3-week cannabis abstinence period. Materials and Methods: Seventy-nine adolescent and young adult participants (cannabis-using group=37 and control group=42) were recruited from the community to undergo 3 weeks of confirmed abstinence (i.e., urine and sweat patch toxicology) and completion of Cannabis Withdrawal Symptom Criteria, State-Trait Anxiety Inventory, Beck's Depression Inventory, and Pittsburgh Sleep Quality Index across the study period. Repeated measures and cross-sectional regressions were used to examine main effects of group and interactions with time (where appropriate), while accounting for recent alcohol use and cotinine levels. Results: Cannabis-using participants reported higher mood (p=0.006), overall withdrawal (p=0.009), and sleep-related withdrawal (p<0.001) symptoms across abstinence compared to controls. Overall withdrawal severity (p=0.04) and sleep-related withdrawal symptoms (p=0.02) demonstrated a quadratic trajectory across the monitored abstinence periods, with an increase from baseline and subsequent decreases in symptom severity. No differences of anxiety scores (p=0.07) or trajectories (p=0.18) were observed. By study completion, groups did not differ among sleep quality components (all p's>.05). Conclusions: These findings revealed that nontreatment-seeking cannabis-using adolescents and young adults reported heightened total withdrawal symptoms during a 3-week sustained abstinence period relative to controls. Cannabis-using participants demonstrated an increase in withdrawal symptom trajectory during the first week followed by decreased symptoms from weeks 2 to 3, which contrasts with prior linear decreases observed in cannabis-using adolescent and young adults. More mood symptoms were observed in the cannabis-using group even while excluding for comorbid psychopathologies-along with significantly more sleep problems during the abstinence period. Implications include the necessity to provide psychoeducation for recreational, nontreatment-seeking cannabis-using individuals about cannabis withdrawal, mood symptoms, and sleep quality difficulties when cannabis cessation is attempted, to improve likelihood of long-term sustained abstinence.

Dehydration measurement using sweat sensor patch and pulse sensor

Technology has increased visibly large. People find ways to easily detect their conditions. Heartbeat and dehydration level is one of the most common among people especially athletes. Athletes are drifted towards wearable technologies to track their training and recovery. Usually a dehydrated person sweats more. The sweat contains various physiological substance and health data. Based on studies sweat consists of salts and ions like [Na+], [K+], [Cl] lactate, glucose and ammonia. We are developing a wearable sweat analyser that can detect the raise in concentration of sodium and potassium. The sweat patch consist of a counter electrode created by screen printing Silver Chloride (AgCl) nanoparticles on Polydimithylsiloxane (PDMS) material and reference electrode (RE) created on the patch material by adding a platinum nanoparticle. This sweat sensor patch is connected to a microcontroller along with a temperature sensor and a Bluetooth module. The data which is collected by the sweat patch and the temperature sensor is sent via Bluetooth to mobile application were the data is displayed.

High Social Coping Self-Efficacy Associated With Lower Sweat Interleukin-6 in Older Adults With Chronic Illness.

Inflammation, particularly interleukin-6 (IL-6), is associated with chronic disease in older adults, but not all older adults have the same progression of poor health outcomes. Self-efficacy may play a role in buffering the inflammatory burden in chronic disease. To evaluate associations between self-efficacy and IL-6, 159 community-dwelling older adults (N = 159, Mage = 82 years, SD = 6.3 years) with one or more chronic illnesses were recruited for this cross-sectional study. Sweat IL-6 was collected using a noninvasive sweat patch worn for 72 hrs. Multiple linear regression with bootstrapping showed a significant association between social coping self-efficacy and IL-6 (β = -0.534, p = .010) after adjustment for age, sex, race, body mass index, financial strain, chronic conditions, and social support. Although preliminary, this study creates a rationale to explore the self-efficacy inflammatory biomarker association further. Enhancing self-efficacy might be a viable nonpharmacological treatment to lower or slow the inflammatory burden in older adults.

Evidence for the transfer of methadone and EDDP by sweat to children\u2019s hair

In cases where there is a question as to whether children have come into contact with drugs, examinations of their scalp hair are frequently carried out. Positive test results are often discussed in the forensic community due to the various possible modes via which drugs and their metabolites can be incorporated into the hair. These include drug uptake by the child (e.g. oral ingestion or inhalation), but also contamination of hair via contact with the sweat from drug users. In this study, the possibility of methadone and its metabolite EDDP being incorporated into children’s hair by contact with sweat from persons undergoing opiate maintenance therapy (methadone) was examined. The transfer of methadone and EDDP via sweat from methadone patients (n = 15) to children’s hair was simulated by close skin contact of drug-free children’s hair, encased in mesh-pouches, for 5 days. Sweat-collecting patches (hereafter referred to as ‘sweat patches’) were applied to the test persons’ skin. One strand of hair and one sweat patch were collected daily from each patient. Analyses were performed using GC–MS/MS (hair) and LC–MS/MS (serum, sweat patches). After 4 days of skin contact, methadone was detectable in the formerly drug-free hair strands in all 15 study participants. EDDP was detectable in 34 of 75 hair strands, with the maximum number of positive results (11 EDDP-positive hair strands) being detected after 5 days. These results show that transfer of methadone and EDDP to drug-free hair is possible through close skin contact with individuals taking part in methadone substitution programmes. A correlation between serum concentration, sweat concentration and substance concentration in hair strands could not be demonstrated, but a tendency towards higher concentrations due to longer contact time is clearly evident.

The effect of short and continuous absorbent patch application on local skin temperature underneath

Objective. By attaching absorbent patches to the skin to collect sweat, an increase in local skin temperature (T sk) underneath the patches seems unavoidable. Yet this effect has not been quantified. The present study investigates the effect of absorbent patch application on local T sk underneath. Approach. Ten healthy participants cycled for 60 min at an exercise intensity relative to their body surface area (40 W.m−2) in three environmental conditions (temperate: 25 °C 45% RH, hot-humid: 33 °C 65% RH and hot-dry: 40 °C 30% RH). The effect of short sweat sampling (i.e. from min 25–30 to min 55–60) on T sk was examined on the right scapula. T sk of the left scapula served as control. The effect of continuous sweat sampling (i.e. four consecutive 15 min periods) on T sk was examined on the right upper arm. T sk of the left upper arm served as control. Main results. Neither short nor continuous application of absorbent sweat patches affected T sk underneath the patches in the hot-humid and hot-dry condition (P > 0.05). In the temperate condition, continuous application led to a significant increase in T sk underneath the patches during the first and second minute. This increase remained throughout the experiment (1.8 ± 0.6 °C; P < 0.001). Short application of sweat patches did not affect the local T sk underneath (P > 0.05) in the temperate condition. Significance. To avoid a significant increase in local T sk underneath sweat patches, continuous application should be prevented in, especially, a temperate condition. Timely removal of sweat patches should be taken into account during longer periods of collecting sweat in field or laboratories settings.

Printed Iontophoretic‐Integrated Wearable Microfluidic Sweat‐Sensing Patch for On‐Demand Point‐Of‐Care Sweat Analysis

AbstractIn recent years, wearable epidermal sweat sensors have received extensive attention owing to their great potential to provide personalized information on the health status of individuals at the molecular level. For on‐demand medical analysis of sweat in sedentary conditions, a cost‐effective wearable integrated platform combining sweat stimulation, sampling, transport, and analysis is highly desirable. In this work, a printed iontophoretic system integrated into a microfluidic sensing platform, which combines sweat induction, collection, and real‐time analysis of sweat‐ions into a single patch for on‐demand sweat monitoring on human subjects in stationary conditions is reported. The incorporation of microfluidics features facilitates sweat sampling, collection, and guiding through capillary effect. The multisensing sensor array exhibits sensitivity close to Nernstian behavior for sodium, potassium, and pH. The correlation between the concentrations of ions measured with the sweat patch and with ion chromatography analysis demonstrates the applicability of the system for real‐time point‐of‐care monitoring of the health status of individuals. Furthermore, the sweat patch electronic interface with wireless transmission enables real‐time data monitoring and storage over a cloud platform. This printed iontophoretic‐integrated fluidic sweat patch provides a cost‐effective solution for the on‐demand analysis of sweat components for healthcare applications.