Cerebral edema (CE) is a non-specific pathological swelling of the brain secondary to any type of neurological injury. The real-time monitoring of focal CE mostly found in early stage is of great significance to reduce mortality and disability. Magnetic Induction Phase Shift (MIPS) is expected to achieve non-invasive continuous monitoring of CE. However, most existing MIPS sensors are made of hard materials which makes it difficult to accurately retrieve CE information. In this article, we designed a conformal two-coil structure and a single-coil structure, and studied their sensitivity map using finite element method (FEM). After that, the conformal MIPS sensor that is preferable for local CE monitoring was fabricated by flexible printed circuit (FPC). Next, physical experiments were conducted to investigate its performance on different levels of simulated CE solution volume, measurement distance, and bending. Subsequently, 14 rabbits were chosen to establish CE model and another three rabbits were selected as controls. The 24-hour MIPS real-time monitoring experiments was carried out to verify that the feasibility. Results showed a gentler attenuation trend of the conformal two-coil structure, compared with the single-coil structure. In addition, the novel flexible conformal MIPS sensor has a characteristic of being robust to bending according to the physical experiments. The results of animal experiments showed that the sensor can be used for CE monitoring. It can be concluded that this flexible conformal MIPS sensor is desirable for local focusing measurement of CE and subsequent multidimensional information extraction for predicting model. Also, it enables a much more comfortable environment for long-time bedside monitoring.

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Background Cerebral edema is a common condition secondary to any type of neurological injury. The early diagnosis and monitoring of cerebral edema is of great importance to improve the prognosis. In this article, a flexible conformal electromagnetic two-coil sensor was employed as the electromagnetic induction sensor, associated with a vector network analyzer (VNA) for signal generation and receiving. Measurement of amplitude data over the frequency range of 1–100 MHz is conducted to evaluate the changes in cerebral edema. We proposed an Amplitude-based Characteristic Parameter Extraction (Ab-CPE) algorithm for multi-frequency characteristic analysis over the frequency range of 1–100 MHz and investigated its performance in electromagnetic induction-based cerebral edema detection and distinction of its acute/chronic phase. Fourteen rabbits were enrolled to establish cerebral edema model and the 24 h real-time monitoring experiments were carried out for algorithm verification. Results The proposed Ab-CPE algorithm was able to detect cerebral edema with a sensitivity of 94.1% and specificity of 95.4%. Also, in the early stage, it can detect cerebral edema with a sensitivity of 85.0% and specificity of 87.5%. Moreover, the Ab-CPE algorithm was able to distinguish between acute and chronic phase of cerebral edema with a sensitivity of 85.0% and specificity of 91.0%. Conclusion The proposed Ab-CPE algorithm is suitable for multi-frequency characteristic analysis. Combined with this algorithm, the electromagnetic induction method has an excellent performance on the detection and monitoring of cerebral edema.

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