Self-Balanced Near-Field Microwave Radiometer for Passive Tissue Thermometry

Issac, Jeslin P; Sugumar, Sathya Priya; Arunachalam, Kavitha

doi:10.1109/jsen.2022.3150871

Cited by 11 publications

(2 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the total radiation power received by the antenna is determined by the combined radiation power of the environment, clothing, and skin tissues. The variation parameters are numerous, which greatly limits the accuracy of inverting the internal temperature of the human body [36,37]. In summary, the accuracy of temperature measurement using the microwave radiation method is closely linked to the near-field radiation characteristics of the antenna, the uncertainty of calibration link brightness temperature, and the temperature contribution weight of the inversion algorithm [38][39][40].…”

Section: Near-field Temperature Contribution Weight Function Measurem...mentioning

confidence: 99%

Review of Accurate Detection of Human Skin Tissue Temperature Based on Microwave Radiation Method

Wu,

Liu

2024

Preprint

View full text Add to dashboard Cite

Microwave radiation diagnosis technology can detect thermal changes in skin tissue earlier than anatomical changes, but its detection accuracy is limited by non-target radiation interference in the measurement environment, additional measurement errors of system units, and energy scattering and transmission between skin tissues. This paper aims to address the scientific challenges of analyzing the forward and inversion modelling detection mechanism of layered accurate temperature measurement of human skin tissue based on multi-band. The study focuses on the construction of a pencil beam antenna optimization system, the optimization strategy of high-sensitivity correlated radiometer architecture, and the high-precision multi-band forward and inversion modelling detection algorithm. The key technologies include: (1) A new method of integrated modeling and multi-index optimization of antenna with high directivity and small aperture is proposed, and a priori knowledge-guided neural network of pencil beam distribution is constructed to realize the inversion model of antenna structural parameters; (2) The influence mechanism of high sensitivity correlated radiometer architecture error is analyzed, and a periodic phase shift error correction algorithm based on uniform polar circle is designed; (3) Combining deep learning theory and hyper-parameter optimization framework, an iterative model is established, and the objective function modified by the penalty factor is defined to realize a new detection method combining forward and inversion. This paper presents a theoretical foundation for the industrialization of microwave radiation diagnostic technology.

show abstract

Section: Near-field Temperature Contribution Weight Function Measurem...mentioning

confidence: 99%

Review of Accurate Detection of Human Skin Tissue Temperature Based on Microwave Radiation Method

Wu,

Liu

2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Near-field Temperature Contribution Weight Function Measurem...mentioning

confidence: 99%

Review of Accurate Detection of Human Skin Tissue Temperature Based on Microwave Radiation Method

Wu,

Liu

2024

Preprint

View full text Add to dashboard Cite

Microwave radiation diagnosis technology can detect thermal changes in skin tissue earlier than anatomical changes, but its detection accuracy is limited by non-target radiation interference in the measurement environment, additional measurement errors of system units, and energy scattering and transmission between skin tissues. This paper aims to address the scientific challenges of analyzing the forward and inversion modelling detection mechanism of layered accurate temperature measurement of human skin tissue based on multi-band. The study focuses on the construction of a pencil beam antenna optimization system, the optimization strategy of high-sensitivity correlated radiometer architecture, and the high-precision multi-band forward and inversion modelling detection algorithm. The key technologies include: (1) A new method of integrated modeling and multi-index optimization of antenna with high directivity and small aperture is proposed, and a priori knowledge-guided neural network of pencil beam distribution is constructed to realize the inversion model of antenna structural parameters; (2) The influence mechanism of high sensitivity correlated radiometer architecture error is analyzed, and a periodic phase shift error correction algorithm based on uniform polar circle is designed; (3) Combining deep learning theory and hyperparameter optimization framework, an iterative model is established, and the objective function modified by the penalty factor is defined to realize a new detection method combining forward and inversion. This paper presents a theoretical foundation for the industrialization of microwave radiation diagnostic technology.

show abstract