Abstract
Patient monitoring is an established method in healthcare, guarding the health status of patients by recording vital signs. The inclusion of sweat sensing in patient monitoring provides prominent opportunities since sweat contains physiologically and metabolically rich information about the patient. Sweat can be non-obtrusively obtained and could therefore enable continuous biomarker measurement. However, for several biomarkers, the concentration not only depends on a disorder but also on the sweat rate per gland and this is a major challenge for the clinical use of sweat sensing. In this work, we developed a sensing device framework, based on an innovative statistical analysis, capable of determining the average sweat rate per gland without a-priori knowledge of the number of glands. The statistical analysis can be adapted for various sweat rates and sweat gland densities. For a gland density of 0.1 glands.-2, a first prototype based on an open microfluidic structure has been fabricated. The prototype sweat collection device is fabricated by femtosecond laser machining of fused silica substrates, followed by a wet etching step. The prototype is tested by different flow rates of DI water that are supplied to it. The experiment shows that the design is capable of collecting and transporting low volumes of sweat as excreted by persons in a sedentary state.
Original language | English |
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Title of host publication | 2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 |
Publisher | Institute of Electrical and Electronics Engineers |
Number of pages | 6 |
ISBN (Electronic) | 978-1-6654-9384-0 |
DOIs | |
Publication status | Published - 10 Jul 2023 |
Event | 2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 - Jeju, Korea, Republic of Duration: 14 Jun 2023 → 16 Jun 2023 |
Conference
Conference | 2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 |
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Country/Territory | Korea, Republic of |
City | Jeju |
Period | 14/06/23 → 16/06/23 |
Funding
The understanding of the underlying probability theory and statistical analysis of this work was possible thanks to advice from prof. dr. ir. I.J.B.F. Adan from Eindhoven University of Technology.
Keywords
- Patient monitoring
- Sweat collection
- Sweat rate per gland
- Sweat sensing