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. 2024 Mar 8;14:5760. doi: 10.1038/s41598-024-55360-7

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Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Flowchart of stroke localization with EVSLA algorithm. The algorithm takes S parameters of the raw measurement and calibration data in the frequency domain and locations of sensors as inputs. In the preprocessing step, the algorithm performs inverse Fourier transform (IFFT) of collected S parameters and generates visibility graphs. Generated graphs are used to construct statistical fields and compute the similarity levels between the calibration and raw data. Regions with higher dissimilarity are kept active and used for fusion. The obtained fusion matrix represents the likelihood of each pixel being affected by a stroke. Visualization of the fusion matrix shows the stroke location.