1. Small fiber neuropathy diagnosis by a non-invasive electrochemical method: mimicking the in-vivo responses by optimization of electrolytic cell parameters
- Author
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Kamel Khalfallah, Virginie Lair, Amandine Calmet, Hanna Ayoub, Philippe Brunswick, Sophie Griveau, Fethi Bedioui, and Michel Cassir
- Subjects
Materials science ,integumentary system ,Electrolytic cell ,General Chemical Engineering ,Analytical chemistry ,Context (language use) ,Electrolyte ,Electrochemical cell ,Sudomotor ,In vivo ,Electrode ,Electrochemistry ,Current density ,Biomedical engineering - Abstract
Prevalence of type II diabetes and cardiometabolic diseases is increasing worldwide and early identification of their complications could reduce healthcare costs. An early complication of diabetes is small fiber neuropathy that can be diagnosed through assessment of sweat dysfunction. In this context, the Sudoscan™ technology developed by Impeto Medical provides early diagnosis, rapid and non-invasive analysis of sudomotor functions. This technology is based on measurements of skin current density via the imposition of low amplitude voltages (4 to 1.5V) between electrodes applied to the skin and measuring the low current generated. These electrodes are sensitive to the composition of the sweat produced by the eccrine glands when stimulated. To optimize the electrode materials and the diagnosis, a better insight into the origin of the electrochemical signals is needed by mimicking the in vivo results through the use of a model electrochemical cell reproducing physiological sweat conditions. In this paper, the electrode surface was modified with polymeric membranes to mimic the role of the filter of the skin and to get similar results to those obtained by Sudoscan™. Then, the composition of the electrolyte was changed by optimizing its viscosity to reduce the flow of Cl − ions to the electrode surface. The electrochemical behavior of the electrodes, measured in terms of current-voltage studied in artificial sweat, were compared to those of the Sudoscan™ technology.
- Published
- 2014
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