This paper presents a planar microwave sensor for the sensitive and accurate characterization of complex permittivity of solid materials. To realize the proposed sensor, the combination of a parallel interdigital capacitor and a dual wide gap resonator was etched on the ground plane and coupled with a transmission line in the top plane of a printed circuit board. The main advantage of the proposed sensor configuration lies in the generation of a high-intensity coupled resonating electric field suitable for the sensitive measurement of complex permittivity of solid materials. The high-intensity electric field enhances the coupling and field interaction, and thereby produces a high-accuracy permittivity characterization of a solid material exposed to the maximum field of the proposed sensor. Our developed microwave permittivity sensor, which characterized the complex permittivity of several materials by exploiting the measured shifts in resonance frequencies, exhibited a high sensitivity (up to 37% shift in resonance frequency for 20% change in permittivity) at least 1.5 times higher than previously reported microwave permittivity sensors. In addition, the proposed sensor exhibited 99.9% and 99.7% sensing accuracies for real and imaginary parts of permittivity, respectively, and the measurement results revealed an excellent (0.06758) and high sensitivity (67.58 MHz per unit change in real permittivity).

The integrated “perception‐memory” system is receiving increasing attention due to its crucial applications in humanoid robots, as well as in the simulation of the human retina and brain. Here, a Field Programmable Gate Array (FPGA) platform‐boosted system that enables the sensing, recognition, and memory for human‐computer interaction is reported by the combination of ultra‐thin Ag/Al/Paster‐based electronic tattoos (AAP) and Tantalum Oxide/Indium Gallium Zinc Oxide (Ta₂O₅/IGZO)‐based memristors. Notably, the AAP demonstrates exceptional capabilities in accommodating the strain caused by skin deformation, thanks to its unique structural design, which ensures a secure fit to the skin and enables the prolonged monitoring of physiological signals. By utilizing Ta₂O₅/IGZO as the functional layer, a high switching ratio is conferred to the memristor, and an integrated system for sensing, distinguishing, storing, and controlling the machine hand of multiple human physiological signals is constructed together with the AAP. Further, the proposed system implements emergency calls and smart homes using facial electromyogram signals and utilizing logical entailment to realize the control of the music interface. This innovative “perception‐memory” integrated system not only serves the disabled, enhancing human‐computer interaction but also provides an alternative avenue to enhance the quality of life and autonomy of individuals with disabilities.

This article presents a high-sensitivity, quantified, linear, and mediator-free resonator-based microwave biosensor for glucose sensing application. The proposed biosensor comprises an air-bridge-type asymmetrical differential inductor (L) and a center-loaded circular finger-based inter-digital capacitor (C) fabricated on Gallium Arsenide (GaAs) substrate using advanced micro-fabrication technology. The intertwined asymmetrical differential inductor is used to achieve a high inductance value with a suitable Q-factor, and the centralized inter-digital capacitor is introduced to generate an intensified electric field. The designed microwave sensor is optimized to operate at a low resonating frequency that increases the electric field penetration depth and interaction area in the glucose sample. The microwave biosensor is tested with different glucose concentrations (0.3–5 mg/ml), under different ambient temperatures (10–50 °C). The involvement of advanced micro-fabrication technology effectively miniaturized the microwave biosensor (0.006λ₀ × 0.005λ₀) and enhanced its filling factor. The proposed microwave biosensor demonstrates a high sensitivity of 117.5 MHz/mgmL^-1 with a linear response (r² = 0.9987), good amplitude variation of 0.49 dB/mgmL^-1 with a linear response (r² = 0.9954), and maximum reproducibility of 0.78% at 2 mg/mL. Additionally, mathematical modelling was performed to estimate the dielectric value of the frequency-dependent glucose sample. The measured and analyzed results indicate that the proposed biosensor is suitable for real-time blood glucose detection measurements.

In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0–6.3%, the respiration detection was 0–9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.