Spectral Methods for Response Enhancement of Microwave Resonant Sensors in Continuous Non-Invasive Blood Glucose Monitoring

• Published in: Bioengineering (Basel) Vol. 9; no. 4; p. 156
• Main Authors: Buonanno, Giovanni, Brancaccio, Adriana, Costanzo, Sandra, Solimene, Raffaele
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 04.04.2022; MDPI
• Subjects: Accuracy; Algorithms; Bioengineering; Blood; Fourier analysis; Fourier transforms; Frequency dependence; Frequency response; Glucose; Glucose monitoring; Microwave sensors; microwaves resonant biosensors; Monitoring; noninvasive continuous blood glucose monitoring; Sensors; Signal processing; Spectral methods; noninvasive continuous blood glucose monitoring; signal processing; microwaves resonant biosensors
• ISSN: 2306-5354; 2306-5354
• DOI: 10.3390/bioengineering9040156

In this paper, the performance of three recent algorithms for the frequency-response enhancement of microwave resonant sensors are compared. The first one, a single-step algorithm, is based on a couple of direct-inverse Fourier transforms, giving a densely sampled response as a result. The second algorithm exploits an iterative procedure to progressively restricts the frequency response. The final one is based on the super-resolution MUSIC algorithm. The comparison is carried out through a Monte Carlo analysis. In particular, synthetic signals are firstly exploited to mimic the frequency response of a resonant microwave sensor. Then, experimental data collected from water-glucose solutions are adopted as validation test for potential applications in noninvasive blood-glucose monitoring.