Precise data acquisition, characterization, and finding the relationship between permittivity variations of human skin with degree of burns is critically important because It further helps in the development of excellent sensor devices for diagnostics and treatment of patients suffering from burns and scalds. This work is also a part of the European "Senseburn" project that focuses to develop a non-invasive diagnostic tool for the assessment of human burns based on its degree and depth in the clinical setup. In this work, several Ex-vivo burnt samples were collected from the Uppsala University Hospital (Akademiska sjukhuset, Sweden), and out of that, eight samples with different burn degrees and of various human body parts were selected for the analysis. The dielectric characterization of the categorized samples was done by using an open-end co-axial probe kit. The measurement was made systematically and clinician feedback forms were maintained throughout the process. The measurement data followed the FASTCLUS procedure which was analyzed initially using density plot, Convergence, and cubic clustering criteria respectively. The dielectric characterization was made from 500 MHz to 10 GHz with 1001 points and from the previous sensor designs, the results were found to be excellent between 500 MHz to 5 GHz. For the statistical analysis, 11 frequency points were considered for 8 samples. The results of the basic statistical analysis using the FASTCLUS procedure resulted in 88 data sets. Later, data sets were analyzed based on the cluster-wise of all samples and sample-wise clusters. Every sample was made with two clusters i.e, cluster 1 which consisted of healthy sectors, and cluster 2 which consisted of burnt sectors. Furthermore, we found that the permittivity differences of clusters are proportional to the degree of the burns. This is pivotal information and It helps to improve the functioning of the diagnostic microwave sensors by designing them according to the permittivity variations. For this purpose, an extensive campaign of around 1000 measurements across a band of 1-30 GHz was done and it leads to the conclusion that each skin region of interest (ROI) provides unique dielectric properties.

Precise data acquisition, characterization, and finding the relationship between permittivity variations of human skin with degree of burns is critically important because It further helps in the development of excellent sensor devices for diagnostics and treatment of patients suffering from burns and scalds. This work is also a part of the European “Senseburn” project that focuses to develop a non-invasive diagnostic tool for the assessment of human burns based on its degree and depth in the clinical setup. In this work, several Ex-vivo burnt samples were collected from the Uppsala University Hospital (Akademiska sjukhuset, Sweden), and out of that, eight samples with different burn degrees and of various human body parts were selected for the analysis. The dielectric characterization of the categorized samples was done by using an open-end co-axial probe kit. The measurement was made systematically and clinician feedback forms were maintained throughout the process. The measurement data followed the FASTCLUS procedure which was analyzed initially using density plot, Convergence, and cubic clustering criteria respectively. The dielectric characterization was made from 500 MHz to 10 GHz with 1001 points and from the previous sensor designs, the results were found to be excellent between 500 MHz to 5 GHz. For the statistical analysis, 11 frequency points were considered for 8 samples. The results of the basic statistical analysis using the FASTCLUS procedure resulted in 88 data sets. Later, data sets were analyzed based on the cluster-wise of all samples and sample-wise clusters. Every sample was made with two clusters i.e, cluster 1 which consisted of healthy sectors, and cluster 2 which consisted of burnt sectors. Furthermore, we found that the permittivity differences of clusters are proportional to the degree of the burns. This is pivotal information and It helps to improve the functioning of the diagnostic microwave sensors by designing them according to the permittivity variations. For this purpose, an extensive campaign of around 1000 measurements across a band of 1–30 GHz was done and it leads to the conclusion that each skin region of interest (ROI) provides unique dielectric properties.