Microwave-based stroke detection system: an experimental investigation of brain tissue volume, composition, and motion artifacts

Abstract Microwave detection is a prospective method in promptly identifying strokes, thereby facilitating clinical intervention and improved prognosis. We aimed to explore the factors affecting microwave stroke detection results, including brain tissue volume, composition, and motion artifacts. Various brain tissue conductivities were simulated using different concentrations of sodium chloride solutions. Physical experiments were conducted utilizing a microwave detection system, with observations focused on changes in S -parameters. Eigenvalue changes are most notable for volume alterations and motion artifacts. The eigenvalues of motion artifacts and volumes exhibit distinctions at specific frequencies. At 1.85 GHz, differences in the imaginary part of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mn>11</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> depend solely on volume variation. The study reveals that volume changes and motion artifacts significantly impact microwave detection outcomes. Motion artifacts can be initially mitigated by targeting specific frequency points. The optimal eigenvalues for characterizing volume changes are differences in imaginary parts of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mn>11</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> , and real parts of differences in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mn>21</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mrow> </mml:math> serve as the optimal feature for characterizing composition changes.