Details

Autor(en) / Beteiligte

• Baker, Lindsay B.
• Seib, Melissa S.
• Barnes, Kelly A.
• Brown, Shyretha D.
• King, Michelle A.
• De Chavez, Peter John D.
• Qu, Shankang
• Archer, Julian
• Wolfe, Anthony S.
• Stofan, John R.
• Carter, James M.
• Wright, Donald E.
• Wallace, Jessica
• Yang, Da Som
• Liu, Shanliangzi
• Anderson, John
• Fort, Tucker
• Li, Weihua
• Wright, John A.
• Lee, Stephen P.
• Model, Jeffrey B.
• Rogers, John A.
• Aranyosi, Alexander J.
• Ghaffari, Roozbeh

Titel

Skin‐Interfaced Microfluidic System with Machine Learning‐Enabled Image Processing of Sweat Biomarkers in Remote Settings

Ist Teil von

• Advanced materials technologies, 2022-11, Vol.7 (11), p.n/a

Erscheinungsjahr

2022

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• Dehydration has many deleterious effects on cognitive and physical performance as well as physiological function, in the context of sports, industrial work, clinical rehabilitation, and military applications. Because sweat loss and electrolyte loss vary across individuals, conventional sweat testing strategies using absorbent patch techniques are employed in laboratory settings to characterize sweat biomarkers; however, these techniques are not suitable for remote environments. Here, an updated wearable microfluidic sweat testing system targeted for recreational athletes is presented that includes a microfluidic patch accommodating a broad range of sweating rates, and a smartphone app incorporating digital image processing algorithms to enable real‐time analysis under different lighting conditions and patch orientations. Expansive field trials (n = 148 subjects) show significant correlations between the microfluidic patch and standard absorbent patch in measuring sweating rate and sweat chloride concentration during recreational exercise. This validation study demonstrates the applicability of the microfluidic patch and software platform for field testing in recreational athletes. This study demonstrates the validity of a wearable microfluidic device, machine learning‐based image detection, and colorimetric image processing on a smartphone that collectively enables real‐time sweat loss and chloride analysis under uncontrolled ambient conditions. This microfluidic patch and custom‐designed software application system have utility for personalized hydration in remote settings, with implications for sports, industrial work, and military applications.