Sticker-Type Remote Monitoring System for Early Risk Detection of Catheter Associated Urinary Tract Infections.

A substantial number of critically ill patients in intensive care units (ICUs) rely on indwelling urinary catheters (IDCs), demanding regular monitoring of urine bags. This process increases the workload for healthcare providers and elevates the risk of exposure to contagious diseases. Moreover, IDCs are a primary cause of catheter-associated urinary tract infections (UTIs) in ICU patients whose delayed detection can have life-threatening complications. To address this, we have developed a Sticker Type Antenna for Remote Sensing (STARS) system capable of measuring urine flow rate and conductivity as early-risk markers for UTIs, alongside tracking patients' urine bag status to facilitate medical automation for healthcare providers. STARS comprises a simple, low-cost, disposable antenna module for contactless measurements of urine volume and conductivity, and a reusable wireless module for real-time data transmission. Systematic studies on STARS revealed its stable performance within physiologically relevant ranges of urine volume (0 to 2000 ml) and conductivity (5 to 40 mS/cm) in urine bags. As a proof-of-concept, STARS was tested in artificially created healthy and infected urine specimens to validate its non-contact sensing performance in detecting the onset of UTIs in catheterized patients within a hospital-like environment. STARS represents the first application of a real-time, contactless, wireless monitoring platform for simultaneous urine bag management and early risk detection of UTIs.

Smart Capsule For Targeted Detection Of Inflammation Levels Inside The Gi Tract.

Effective management of Inflammatory Bowel Disease (IBD) is contingent upon frequent monitoring of inflammation levels at targeted locations within the gastrointestinal (GI) tract. This is crucial for assessing disease progression and detecting potential relapses. To address this need, a novel single-use capsule technology has been devised that enables region-specific inflammation measurement, thereby facilitating repeatable monitoring within the GI tract. The capsule integrates a pH-responsive coating for location-specific activation, a chemiluminescent paper-based myeloperoxidase (MPO) sensor for inflammation detection, and a miniaturized photodetector, complemented by embedded electronics for real-time wireless data transmission. Demonstrating linear sensitivity within the physiological MPO concentration range, the sensor is capable of effectively identifying inflammation risk in the GI fluid. Luminescence emitted by the sensor, proportional to MPO concentration, is converted into an electrical signal by the photodetector, generating a quantifiable energy output with a sensitivity of 6.14 µJ/U.ml-1. The capsule was also tested with GI fluids collected from pig models simulating various inflammation states. Despite the physiological complexities, the capsule consistently activated in the intended region and accurately detected MPO levels with less than a 5% variation between readings in GI fluid and a PBS solution. This study heralds a significant step towards minimally invasive, in situ GI inflammation monitoring, potentially revolutionizing personalized IBD management and patient-specific therapeutic strategies.

Smart capsule for monitoring inflammation profile throughout the gastrointestinal tract.

Inflammatory bowel disease (IBD) has become alarmingly prevalent in the last two decades affecting 6.8 million people worldwide with a starkly high relapse rate of 40% within 1 year of remission. Existing visual endoscopy techniques rely on subjective assessment of images that are error-prone and insufficient indicators of early-stage IBD, rendering them unsuitable for frequent and quantitative monitoring of gastrointestinal health necessary for detecting regular relapses in IBD patients. To address these limitations, we have implemented a miniaturized smart capsule (2.2 cm × 11 mm) that allows monitoring reactive oxygen species (ROS) levels as a biomarker of inflammation for quantitative and frequent profiling of inflammatory lesions throughout the gastrointestinal tract. The capsule is composed of a pH and oxidation reduction potential (ORP) sensor to track the capsule's location and ROS levels throughout the gastrointestinal tract, respectively, and an optimized electronic interface for wireless sensing and data communication. The designed sensors provided a linear and stable performance within the physiologically relevant range of the GI tract (pH: 1-8 and ORP: -500 to +500 mV). Additionally, systematic design optimization of the wireless interface electronics offered an efficient sampling rate of 10 ms for long-running measurements up to 48 h for a complete evaluation of the entire gastrointestinal tract. As a proof-of-concept, the capsule the capsule's performance in detecting inflammation risks was validated by conducting tests on in vitro cell culture conditions, simulating healthy and inflamed gut-like environments. The capsule presented here achieves a new milestone in addressing the emerging need for smart ingestible electronics for better diagnosis and treatment of digestive diseases.

A new paradigm of reliable sensing with field-deployed electrochemical sensors integrating data redundancy and source credibility.

For a continuous healthcare or environmental monitoring system, it is essential to reliably sense the analyte concentration reported by electrochemical sensors. However, environmental perturbation, sensor drift, and power-constraint make reliable sensing with wearable and implantable sensors difficult. While most studies focus on improving sensor stability and precision by increasing the system's complexity and cost, we aim to address this challenge using low-cost sensors. To obtain the desired accuracy from low-cost sensors, we borrow two fundamental concepts from communication theory and computer science. First, inspired by reliable data transmission over a noisy communication channel by incorporating redundancy, we propose to measure the same quantity (i.e., analyte concentration) with multiple sensors. Second, we estimate the true signal by aggregating the output of the sensors based on their credibility, a technique originally developed for "truth discovery" in social sensing applications. We use the Maximum Likelihood Estimation to estimate the true signal and the credibility index of the sensors over time. Using the estimated signal, we develop an on-the-fly drift-correction method to make unreliable sensors reliable by correcting any systematic drifts during operation. Our approach can determine solution pH within 0.09 pH for more than three months by detecting and correcting the gradual drift of pH sensors as a function of gamma-ray irradiation. In the field study, we validate our method by measuring nitrate levels in an agricultural field onsite over 22 days within 0.06 mM of a high-precision laboratory-based sensor. We theoretically demonstrate and numerically validate that our approach can estimate the true signal even when the majority (~ 80%) of the sensors are unreliable. Moreover, by restricting wireless transmission to high-credible sensors, we achieve near-perfect information transfer at a fraction of the energy cost. The high-precision sensing with low-cost sensors at reduced transmission cost will pave the way for pervasive in-field sensing with electrochemical sensors. The approach is general and can improve the accuracy of any field-deployed sensors undergoing drift and degradation during operation.

Low-Cost Nonreversible Electronic-Free Wireless pH Sensor for Spoilage Detection in Packaged Meat Products.

Contamination of meat with pathogenic microorganisms can cause severe illnesses and food waste, which has significant negative impacts on both general health and the economy. In many cases, the expiration date is not a good indicator of meat freshness as there is a high risk of contamination during handling throughout the supply chain. Many biomarkers, including color, odor, pH, temperature, and volatile compounds, are used to determine spoilage. Among these, pH presents a simple and effective biomarker directly linked to the overgrowth of bacteria and degradation of the meat tissue. Low-cost methods for wireless pH monitoring are crucial in detecting spoilage on a large commercial scale. Existing technologies are often limited to short-range detection, with the use of batteries and different electronic components that increases both the manufacturing complexity and cost of the final device. To address these shortcomings, we have developed a cost-effective wireless pH sensor, which uses passive resonant frequency (RF) sensing, combined with a pH-responsive polymer that can be placed within packaged meat products and provide a remote assessment of the risk of microbial spoilage throughout the supply chain. The sensor tag consists of a sensing resonator coated with a pH-sensitive material and a passivated reference resonator operating in a differential frequency configuration. Upon exposure to elevated pH levels >6.8, the coating on the sensing resonator dissolves, which in turn results in a distinct change in the resonant frequency with respect to the reference resonator. Systematic theoretical and experimental results at different pH levels demonstrated that a 20% shift in resonant frequency demarcates the point for spoilage detection. As a proof of concept, the performance of the sensor in remotely detecting the risk of food spoilage was validated in packaged poultry over 10 days. The sensor fabrication process takes advantage of recent developments in the scalable manufacturing of flexible, low-cost devices, including selective laser etching of metalized plastic films and doctor-blade coating of stimuli-responsive polymer films. Furthermore, the biocompatibility of all the materials used in the sensor was confirmed with human intestinal cells (HCT-8 cells).

Temperature Self-Calibration of Always-On, Field-Deployed Ion-Selective Electrodes Based on Differential Voltage Measurement.

Originally developed for use in controlled laboratory settings, potentiometric ion-selective electrode (ISE) sensors have recently been deployed for continuous, in situ measurement of analyte concentration in agricultural (e.g., nitrate), environmental (e.g., ocean acidification), industrial (e.g., wastewater), and health-care sectors (e.g., sweat sensors). However, due to uncontrolled temperature and lack of frequent calibration in these field applications, it has been difficult to achieve accuracy comparable to the laboratory setting. In this paper, we propose a novel temperature self-calibration method where the ISE sensors can serve as their own thermometer and therefore precisely measure the analyte concentration in the field condition by compensating for the temperature variations. We validate the method with controlled experiments using pH and nitrate ISEs, which use the Nernst principle for electrochemical sensing. We show that, using temperature self-calibration, pH and nitrate can be measured within 0.3% and 5% of the true concentration, respectively, under varying concentrations and temperature conditions. Moreover, we perform a field study to continuously monitor the nitrate concentration of an agricultural field over a period of 6 days. Our temperature self-calibration approach determines the nitrate concentration within 4% of the ground truth measured by laboratory-based high-precision nitrate sensors. Our approach is general and would allow battery-free temperature-corrected analyte measurement for all Nernst principle-based sensors being deployed as wearable or implantable sensors.

A biodegradable chipless sensor for wireless subsoil health monitoring.

Precision Agriculture (PA) is an integral component of the contemporary agricultural revolution that focuses on enhancing food productivity in proportion to the increasing global population while minimizing resource waste. While the recent advancements in PA, such as the integration of IoT (Internet of Things) sensors, have significantly improved the surveillance of field conditions to achieve high yields, the presence of batteries and electronic chips makes them expensive and non-biodegradable. To address these limitations, for the first time, we have developed a fully Degradable Intelligent Radio Transmitting Sensor (DIRTS) that allows remote sensing of subsoil volumetric water using drone-assisted wireless monitoring. The device consists of a simple miniaturized resonating antenna encapsulated in a biodegradable polymer material such that the resonant frequency of the device is dependent on the dielectric properties of the soil surrounding the encapsulated structure. The simple structure of DIRTS enables scalable additive manufacturing processes using cost-effective, biodegradable materials to fabricate them in a miniaturized size, thereby facilitating their automated distribution in the soil. As a proof-of-concept, we present the use of DIRTS in lab and field conditions where the sensors demonstrate the capability to detect volumetric water content within the range of 3.7-23.5% with a minimum sensitivity of 9.07 MHz/%. Remote sensing of DIRTS can be achieved from an elevation of 40 cm using drones to provide comparable performance to lab measurements. A systematic biodegradation study reveals that DIRTS can provide stable readings within the expected duration of 1 year with less than 4% change in sensitivity before signs of degradation. DIRTS provides a new steppingstone toward advancing precision agriculture while minimizing the environmental footprint.