Temperature-Corrected Fluidic Glucose Sensor Based on Microwave Resonator.

In this paper, a fluidic glucose sensor that is based on a complementary split-ring resonator (CSRR) is proposed for the microwave frequency region. The detection of glucose with different concentrations from 0 mg/dL to 400 mg/dL in a non-invasive manner is possible by introducing a fluidic system. The glucose concentration can be continuously monitored by tracking the transmission coefficient S 21 as a sensing parameter. The variation tendency in S 21 by the glucose concentration is analyzed with equivalent circuit model. In addition, to eradicate the systematic error due to temperature variation, the sensor is tested in two temperature conditions: the constant temperature condition and the time-dependent varying temperature condition. For the varying temperature condition, the temperature correction function was derived between the temperature and the variation in S 21 for DI water. By applying the fitting function to glucose solution, the subsidiary results due to temperature can be completely eliminated. As a result, the S 21 varies by 0.03 dB as the glucose concentration increases from 0 mg/dL to 400 mg/dL.

Sensitivity-Enhanced Fluidic Glucose Sensor Based on a Microwave Resonator Coupled With an Interferometric System for Noninvasive and Continuous Detection.

In this paper, a microwave fluidic glucose sensor based on a microwave resonator coupled with an interferometric system is proposed for sensitivity enhancement. The proposed glucose sensor consists of two parts: a sensing part and a sensitivity enhancement part. The former is composed of a rectangular complementary split ring resonator (CSRR), and the latter is composed of a variable attenuator, a variable phase shifter, two hybrid couplers, and an RF power detector. Because the variation in the electrical properties, which is utilized in the microwave detection scheme, with glucose concentration over the possible concentration range in the human body is very small, improvement of the sensitivity is critical for practical use. Thus, the effective sensing area of the rectangular CSRR is determined by considering the electric field distribution. In addition, magnitude and phase conditions for the effective sensitivity enhancement are derived from a mathematical analysis of the proposed interferometric system. In the present experiment, aimed at demonstrating the detection performance as a function of the glucose concentration in the range of 0 mg/dL to 400 mg/dL, the sensitivity is significantly improved by 48 times by applying the derived conditions for effective sensitivity enhancement. Furthermore, the accuracy of the proposed glucose sensor for glucose concentrations at a step of 100 mg/dL is verified by the Clarke error grid. Based on the measurement results, the proposed glucose sensor is demonstrated to be applicable to noninvasive and continuous monitoring in practical environments.

Radio-Frequency/Microwave Gas Sensors Using Conducting Polymer.

In this review, the advances in radio-frequency (RF) /microwave chemical gas sensors using conducting polymers are discussed. First, the introduction of various conducting polymers is described. Only polyaniline (PANi), polypyrrole (PPy) and poly(3,4-ethylenedioxythiophene) (PEDOT), which are mainly used for gas sensors in RF/microwave region, are focused in this review. Sensing mechanism of the three conducting polymers are presented. And the RF/microwave characteristics and RF/microwave applications of the three conducting polymers are discussed. Moreover, the gas sensors using conducting polymers in RF/microwave frequencies are described. Finally, the the challenges and the prospects of the next generation of the RF/microwave based chemical sensors for wireless applications are proposed.

Parallel Signal Processing of a Wireless Pressure-Sensing Platform Combined with Machine-Learning-Based Cognition, Inspired by the Human Somatosensory System.

Inspired by the human somatosensory system, pressure applied to multiple pressure sensors is received in parallel and combined into a representative signal pattern, which is subsequently processed using machine learning. The pressure signals are combined using a wireless system, where each sensor is assigned a specific resonant frequency on the reflection coefficient (S11 ) spectrum, and the applied pressure changes the magnitude of the S11 pole with minimal frequency shift. This allows the differentiation and identification of the pressure applied to each sensor. The pressure sensor consists of polypyrrole-coated microstructured poly(dimethylsiloxane) placed on top of electrodes, operating as a capacitive sensor. The high dielectric constant of polypyrrole enables relatively high pressure-sensing performance. The coils are vertically stacked to enable the reader to receive the signals from all of the sensors simultaneously at a single location, analogous to the junction between neighboring primary neurons to a secondary neuron. Here, the stacking order is important to minimize the interference between the coils. Furthermore, convolutional neural network (CNN)-based machine learning is utilized to predict the applied pressure of each sensor from unforeseen S11 spectra. With increasing training, the prediction accuracy improves (with mean squared error of 0.12), analogous to humans' cognitive learning ability.

Deep-Learning-Based Deconvolution of Mechanical Stimuli with Ti3C2Tx MXene Electromagnetic Shield Architecture via Dual-Mode Wireless Signal Variation Mechanism.

Passive component-based soft resonators have been spotlighted in the field of wearable and implantable devices due to their remote operation capability and tunable properties. As the output signal of the resonator-based wireless communication device is given in the form of a vector (i.e., a spectrum of reflection coefficient), multiple information can, in principle, be stored and interpreted. Herein, we introduce a device that can deconvolute mechanical stimuli from a single wireless signal using dual-mode operation, specifically enabled by the use of Ti3C2Tx MXene. MXene's strong electromagnetic shielding effect enables the resonator to simultaneously measure pressure and strain without overlapping its output signal, unlike other conductive counterparts that are deficient in shielding ability. Furthermore, convolutional neural-network-based deep learning was implemented to predict the pressure and strain values from unforeseen output wireless signals. Our MXene-integrated wireless device can also be utilized as an on-skin mechanical stimuli sensor for rehabilitation monitoring after orthopedic surgery. The dual-mode signal variation mechanism enabled by integration of MXene allows wireless communication systems to efficiently handle various information simultaneously, through which multistimuli sensing capability can be imparted into passive component-based wearable and implantable electrical devices.

Noncontact RF Vital Sign Sensor for Continuous Monitoring of Driver Status.

In this paper, a radio frequency vital sign sensor based on double voltage-controlled oscillators (VCOs) combined with a switchable phase-locked loop (PLL) is proposed for a noncontact remote vital sign sensing system. Our sensing system primarily detects the periodic movements of the human lungs and the hearts via the impedance variation of the resonator. With a change in impedance, both the VCO oscillation frequency and the PLL feedback voltage also change. Thus, by tracking the feedback voltage of the PLL, breath and heart rate signals can be acquired simultaneously. However, as the distance between the body and the sensor varies, there are certain points with minimal sensitivity, making it is quite difficult to detect vital signs. These points, called impedance null points, periodically occur at distances proportional to the wavelength. To overcome the impedance null point problem, two resonators operating at different frequencies, 2.40 and 2.76 GHz, are employed as receiving components. In an experiment to investigate the sensing performance as a function of distance, the measurement distance was accurately controlled by a linear actuator. Furthermore, to evaluate the sensing performance in a real environment, experiments were carried out with a male and a female subject in a static vehicle. To demonstrate the real-time vital sign monitoring capability, spectrograms were utilized, and the accuracy was assessed relative to reference sensors. Based on the results, it is demonstrated that the proposed remote sensor can reliably detect vital signs in a real vehicle environment.

Real-time Humidity Sensor Based on Microwave Resonator Coupled with PEDOT:PSS Conducting Polymer Film.

A real-time humidity sensor based on a microwave resonator coupled with a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) conducting polymer (CP) film is proposed in this paper. The resonator is patterned on a printed circuit board and is excited by electromagnetic field coupling. To enhance the sensitivity of the sensor, the CP film is located in the area with the strongest electric field in the resonator. To investigate the performance, the proposed sensor is placed alongside a reference sensor in a humidity chamber, and humidity is injected at room temperature. The experimental results indicate that the electrical properties of the resonator with the CP film, such as the transmission coefficient (S 21) and resonance frequency, change with the relative humidity (RH). Specifically, as the RH changes from 5% to 80%, S 21 and the resonance frequency change simultaneously. Moreover, the proposed sensor exhibits great repeatability in the middle of the sensing range, which is from 40% to 60% RH. Consequently, our resonator coupled with the CP film can be used as a real-time humidity-sensing device in the microwave range, where various radio-frequency devices are in use.