Q/A
What studies have been done so far?
- Several studies have been performed, both as previous basic work, but also more recent, which shows the potential of EIS in skin barrier assessment. For more information see “Skin Barrier assessment” under Barrier and “Publications” under EIS Technology.
How does EIS compare to TEWL?
- EIS measures a different physiological parameter compared to Trans Epidermal Water Loss (TEWL) Whereas TEWL measures the amount of water evaporating from the skin, and provides one single value, EIS measures 2 parameters at 10 permutations over a frequency range, i.e., a large dataset in each measurement. Furthermore, it was shown in a clinical study (Electrical impedance spectroscopy for the characterization of skin barrier in atopic dermatitis) that EIS had better correlation to barrier related disease and biomarkers compared to TEWL.
What other areas except for AD could this be interesting to do research on?
- All other barrier related conditions, such as psoriasis but also other allergic disorders related to a defective skin barrier.
How does the AI work? How can I use it?
- Barrier related parameters are calculated after each measurement. However, to exploit the full potential of research or studies of the skin barrier, complete measurements over the frequency range are stored in the device and can be exported for further analysis, either in your own platforms or by importing the data into the Nevisense Dashboard, where all results can be presented and compared.
- For further analysis or AI development, SciBase can provide support and access to an AI development platform from the company Peltarion , in order to develop AI based classifiers for new areas or indications.
Is this a medical device? Can anyone buy it?
- Nevisense Go is today not classified as a medical device, but is to be used for research or studies. It conforms to IEC 60601-1-2 Electromagnetic compatibility, IEC 62133-2
How can a barrier score be developed and is it specific for one clinical indication?
- A barrier score is developed through studies that investigate differences in skin properties in different population groups. You can investigate e.g., dry skin vs normal, psoriasis vs normals etc. The AI could then evaluate what kind of separation can be made between group. In cases where a separation between groups can be identified , an AI model with a relevant significance can be developed based on a sufficiently large sample size.