An Electronically Controlled Resonant Microwave Sensor Array for Skin Tumor Detection
The application of microwave sensors in skin tumor detection has attracted a great deal of interest from researchers due to its safety, sensitivity, non-invasiveness, and low cost. In this research, an electrically controlled two-dimensional microwave sensor array based on a complementary spiral resonator (CSR) for skin tumor detection is proposed. The detection is based on the resonant frequency shift of CSR caused by the skin tumor under test. The 10 × 10 CSRs excited by spoof surface plasmon polaritons (SSPPs) are etched on the ground as the sensing elements for sensing skin tissue under test. Each sensing element represents a pixel, and all the sensing elements together form a dielectric image of the tissue. They are independently controlled by the corresponding PIN diodes, which are conveniently controlled by an external controller. The introduction of electrical scanning allows the quick detection of skin tumors without mechanical scanning, greatly improving the detection efficiency. In addition, each sensing element senses the corresponding skin area highly independently under the control of the PIN diode, weakening mutual interference between the elements during the measurement. Compared to the frequency multiplexed sensor array, the sensing elements’ number of the designed sensor array is greatly improved while maintaining the sensing elements’ size consistent. The operating principle of the sensor array is analyzed in detail and numerically simulated in electromagnetic simulation software. Several experiments were performed on tissue phantoms to validate the effectiveness of the designed sensor array.
Authors
- Junkai Bai
- Hongfu Guo
- Xinquan Lai (ORCID: https://orcid.org/0000-0002-8319-9128)
Institutions
- Xidian University (CN)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3578636
- Citations
- 2
- Primary Topic
- Microwave Imaging and Scattering Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- National Key Research and Development Program of China