Advanced Sensor Research最新文献

Smart Monitoring Hydrogel Sensors

In article 2400003, Hong Zhang, Yang Luo, and co-workers report advancements in smart hydrogel sensors for health monitoring and early warning. Leveraging the biocompatible properties of hydrogels, these sensors facilitate continuous, precise monitoring of various physiological parameters. The review highlights the mechanisms of these sensors, their benefits for medical diagnostics, and directions for future research. It also explores their potential in various medical scenarios, such as disease monitoring and management, underscoring the need for further clinical validation.

In medical diagnosis, detecting disease biomarkers at ultra-low concentrations is vital. Point-of-care (POC) diagnostics require rapid detection, live monitoring, high sensitivity, low detection threshold, and cost-effectiveness. Carbon-based nanomaterials (CBNs) are promising due to their large surface-to-volume ratio, conductivity, biocompatibility, and stability, making them ideal for biosensors. Recent advancements in CBN applications, including biosensing, drug delivery, and cancer therapy, highlight their potential in enhancing detection sensitivity and specificity. Electrochemical sensors and biosensor platforms using carbon nanocomposites are pivotal in diagnostics. This review explores the current state and future challenges of CBN integration in POC settings, envisioning a transformative impact on healthcare diagnostics and therapeutics.

Integrated Microwave Photonic Sensors

Sensors stand as pivotal cornerstones of technologies. In article 2300145, Xiaoke Yi and co-workers demonstrate integrated microwave photonic sensors using microresonators for ultra-sensitive, high-resolution, and rapid detection. These compact sensors, enhanced through integration techniques and artificial intelligence, offer great potential across various applications, representing a significant advancement in modern sensing technologies.

Deformation-Insensitivity

Flexible sensor array using kirigami structural and soft-hinge design enables deformation-insensitive pressure detection. The sensitivity of sensor is enhanced by the modification with micropillars on conductive rubber. Characterization tests verify the almost negligible effects to sensor caused by 40% stretching and 180° bending interferences. The proposed sensor array is capable of functioning on the deformable surfaces with stable detection signals. More details can be found in article 2400012 by Yancheng Wang and co-workers.

The heart produces bioelectrical signals, which can be measured as an electrocardiogram (ECG) for the detection of rhythm disturbances. Rapid and precise detection of these arrhythmias is crucial for their termination by closed-looped therapeutic interventions to counteract detrimental effects. However, there is a current lack of such systems tailored for experimental cardiovascular applications. This hampers not only in-depth mechanistic studies but also translational testing of new therapeutic strategies, especially in an untethered manner in awake animal models. To break new ground, recent advances to develop a non-invasive AI-supported heart rhythm monitoring system for untethered automated arrhythmia detection in a continuous manner is combined. This system is housed in a lightweight jacket for mobile use and includes an on-skin ECG sensor, a low-power microprocessor unit, a massive data storage unit, and a power-management system. By implementing a novel hybrid algorithm based on so-called heart rate (R-R) variability and a case-specific AI model, 100% sensitivity and 95% specificity is achieved in detecting atrial arrhythmias within 2 s upon initiation in adult rats. Thereby, the novel system sets the stage for advanced mechanistic studies and therapeutic testing, including closed-loop applications aiming for the termination of a broad range of atrial arrhythmias.

Mechanical energy harvesters have recently emerged as promising options for self-powering sensors and small electronic devices. In this work, aluminum ferrite (AlFeO₃)/PVDF hybrid perovskite electrospun nanofiber-based tribo-enhanced piezoelectric nanogenerators (TPENGs) are developed for energy harvesting. The as-fabricated TPENG achieves an average voltage output of 52.3 V and an average current output of 1.23 µA. Additionally, the power density of the TPENG is calculated to be 0.085 W.m⁻² at an 80 MΩ external resistance load. A 3D-printed device is fabricated, containing nylon fabric (tribo-positive) as a rotor attached to printed fins, while six (AlFeO₃)/PVDF hybrid perovskite electrospun nanofiber piezoelectric nanogenerators (PENGs) wrapped with Kapton tape (tribo-negative) serve as the stator. The three printed fins of the device are moved by a string-based pulley, generating an open circuit voltage of 200 V and a short circuit current of 4.5 µA. The as-fabricated 3D-printed device with TPENGs is used to power small electronics (e.g., LEDs and watch) and an exercise setup, allowing patients to generate power by pulling the attached string, thereby estimating the level of impairment. Integrating energy harvesting into rehabilitation motivates patients to move impaired body parts, enhancing TPENG's application in healthcare as a practical and engaging tool for patient rehabilitation.

Glucose plays critical roles in many human body functions, above all as a source of energy. Abnormal levels of glucose are correlated to different diseases, importantly including diabetes. As such, quantification of glucose levels in body fluids is essential for health monitoring. Blood tests and, more recently, portable interstitial fluid tests, currently represent the benchmarks for glucose detection. Inconvenient invasive methods such as blood tests pose burdens on both patients and the healthcare system. In this review, noninvasive approaches to measure glucose levels in the human body are discussed, utilizing saliva as an alternative to conventional blood samples. Techniques explored and with the potential to enhance accuracy and their associated challenges are discussed.

Ion consumption plays key roles in maintaining bodily homeostasis and health. Here passive wireless, multimineral comonitoring arrays are studied that may potentially be utilized for emerging applications in precision nutrition. RF biosensors targeting select minerals (calcium or magnesium demonstrated herein) are built from integrating ion-selective membranes within a broadside-coupled split ring resonator architecture. RF sensors are typically monitored one at a time and such platforms often are incapable of comeasuring multiple confounding components. To address this challenge, this sensor arrays are further directly integrated alongside a conformal, custom readout coil that optimizes multi-RF sensor readout. Such optimized networks exhibit enhanced signal clarity, further facilitating coextraction of multiple ion components. A simple method of extracting multimineral concentrations from food even despite the imperfect selectivity of divalent ion-selective membranes is introduced. This passive wireless, zero-electronic ion-monitoring platform integrates seamlessly on foodware or packaging, possessing many applications in food measurement.