Sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome

NewsGuard 100/100 Score

A recent study published in the Communications Engineering Journal discussed the opportunities and challenges of sweat-based wearables for monitoring metabolic syndrome.

Study: Opportunities and challenges for sweat-based monitoring of metabolic syndrome via wearable technologies. Image Credit: ViktorGladkov/Shutterstock.comStudy: Opportunities and challenges for sweat-based monitoring of metabolic syndrome via wearable technologies. Image Credit: ViktorGladkov/Shutterstock.com

Background

Metabolic syndrome predisposes individuals to a higher risk of cancer, type 2 diabetes, cardiovascular disease, and lung function impairment. The global prevalence of the syndrome has steadily increased over the past decades, especially among older adults. Typically, patients present with hypertension, high fasting glucose levels, and obesity.

Patients with metabolic syndrome have a 20% higher risk of myocardial infarction and are more likely to exhibit sodium sensitivity. Lifestyle modifications, such as dietary changes, can reduce diabetes risk in metabolic syndrome patients.

Further, individuals with metabolic syndrome commonly show a pro-inflammatory state, indicated by high C-reactive protein (CRP) levels.

Mobile health technology can assess metabolic syndrome, related risk factors, and relevant parameters through wearable smart clothing, wristbands, smartwatches, and rings that collect data.

Sweat-based technology is a novel approach for monitoring clinical parameters and signs associated with the syndrome because sweat contains numerous biomarkers.

Most developments regarding real-time biomarker detection by wearables rely on electrochemical techniques, which are robust with low detection limits and can be miniaturized.

Integrating several sensing technologies in a single device can immensely impact public health. In the present study, the authors discussed the advances in sweat-based wearable devices and the challenges in achieving an integrated device.

Targets to assess metabolic syndrome

CRP, glucose, cortisol, sodium, and uric acid have been identified as relevant for diagnosing and managing metabolic syndrome.

Studies have reported measuring glucose in sweat via wearables with sweat patches or absorbent wristbands. However, many studies still need to validate sweat sensor-based measurements with standard methods.

Accumulation of sweat contaminants on sensors, such as lipids and proteins, termed biofouling, can interfere with accuracy. Alternatives, such as anti-fouling layers, enzyme stabilizers, and selective membranes, are being explored to prevent biofouling and improve the reliability and accuracy of sensors. Numerous studies have measured sodium in sweat, showing stability during exercise.

A few studies have indirectly validated them by examining changes in sweat under different physiological conditions. Further, emerging research suggests that wearable patches may measure inflammatory markers, including CRP, in sweat.

A proof-of-concept study revealed accurate detection of CRP in sweat using patches on inflammatory bowel disease patients. Moreover, comparison with standard assays indicated a high correlation.

Some studies have reported measuring uric acid in sweat. One study used a carbon sweat patch capable of measuring sodium, glucose, and uric acid and demonstrated the patch's stability in monitoring uric acid in real time. A future wearable to monitor metabolic syndrome should also collect data on cortisol.

Research suggests that metabolic syndrome patients show increased levels of an enzyme converting inactive cortisone to cortisol.

Besides, it is speculated that regulating cortisol levels could decrease metabolic syndrome-related signs such as high blood pressure, insulin resistance, and adiposity. One study measured cortisol and glucose in sweat, demonstrating a high correlation with standard methods for cortisol measurement.

Sensor materials and stability

The optimal sensing material, anatomical site, and sensor stability and robustness must be considered for developing sensors. Sensors that power themselves from electrochemical reactions are promising to eliminate batteries, although several challenges persist in translating this into practical solutions. Further, the biocompatibility of novel materials/components with the skin should also be explicitly evaluated. 

Several studies have indicated the stability of sweat sensors under varying physiological conditions. An ideal sensor must be stable and durable under changing environmental conditions. Aging and degradation of biological products in sensors can reduce sensitivity and reliability.

Additionally, polymeric and inorganic compounds can degrade with time. Thus, more research is required to address the aging of sensor components.

Integrated sensor

Evidence suggests that multi-sensor systems can enhance the predictive ability to detect relevant health events. Although electronic crosstalk can be resolved due to multiple sensing modalities, chemical crosstalk remains a potential concern, especially with biosensors generating hydrogen peroxide upon analyte interactions.

Nevertheless, microfluidic systems have been proposed as a solution, wherein sweat flow can be split and channeled into individual sensors.

Further, a future wearable for metabolic syndrome should measure abdominal obesity and physical activity. Practicality and patient comfort should be considered when selecting an appropriate anatomical site for continuous and non-invasive sweat collection.

Besides, properly placing the wearable in hot and cold environments is critical for accuracy and efficacy.

Concluding remarks

In sum, sweat-based wearables can potentially obtain vital data on biomarkers of metabolic syndrome and related conditions and can prove invaluable for individuals at risk of cardiovascular disease and diabetes.

While developing an integrated wearable is feasible, more research is required to determine the optimal anatomical site, accounting for sweat gland density and sweat rate, and validate the efficacy and reliability of wearables.

Journal reference:
Tarun Sai Lomte

Written by

Tarun Sai Lomte

Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Sai Lomte, Tarun. (2023, July 20). Sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome. News-Medical. Retrieved on April 28, 2024 from https://www.news-medical.net/news/20230720/Sweat-based-wearable-technologies-as-a-potential-monitoring-tool-for-patients-with-metabolic-syndrome.aspx.

  • MLA

    Sai Lomte, Tarun. "Sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome". News-Medical. 28 April 2024. <https://www.news-medical.net/news/20230720/Sweat-based-wearable-technologies-as-a-potential-monitoring-tool-for-patients-with-metabolic-syndrome.aspx>.

  • Chicago

    Sai Lomte, Tarun. "Sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome". News-Medical. https://www.news-medical.net/news/20230720/Sweat-based-wearable-technologies-as-a-potential-monitoring-tool-for-patients-with-metabolic-syndrome.aspx. (accessed April 28, 2024).

  • Harvard

    Sai Lomte, Tarun. 2023. Sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome. News-Medical, viewed 28 April 2024, https://www.news-medical.net/news/20230720/Sweat-based-wearable-technologies-as-a-potential-monitoring-tool-for-patients-with-metabolic-syndrome.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Ancient DNA reveals first prehistoric cases of Turner and Jacob's syndromes