Advanced Sensor Research最新文献

Ultrasound (US), as a non-invasive mechanical wave, has served as a visual tool for medical diagnosis and therapy for echolocation effect, cavitation effect, thermal effect, and generation of reactive oxygen species (ROS) with the aid of sonosensitizers. This review summarizes the history, effects, and biomedical applications of US, and US-assisted cancer therapy is highlighted. The rational combination of US with near-infrared afterglow nanoparticles, anti-tumor prodrugs, and stimuli-responsive nanocarriers, demonstrates the great promise for bioimaging, cancer therapy, and drug delivery, promoting US-related technology in biomedical diagnosis and therapeutics.

Human tactile perception involves the activation of mechanoreceptors located within the skin in response to external stimuli, along with the organization and processing within the brain. However, human sensations may be subject to the issues related to some physiological factors (such as skin injury or neurasthenia), resulting in inability to quantify tactile information. To address this challenge, a novel bio-inspired artificial tactile (BAT) sensing system enabled by the integration of optical microfiber (OM) with full-connected neural network (FCNN) in this paper is demonstrated, inspired by human physiological characteristics and tactile mechanisms. In this system, the BAT sensor mimics human skin, where the OM serves as the mechanoreceptor for sensing tactile stimuli, while the FCNN functions as a simulated human brain to train and extract the signal characteristics for intelligent object recognition. The experimental results indicate that the proposed BAT sensor can sensitively respond to both the contact force (static tactile stimuli), as well as the vibrotactile events (dynamic tactile stimuli) for the recognition of regular textures. Furthermore, by integrating the trained FCNN, the BAT sensing system accurately identifies various intricate surface textures with an exceptional accuracy of 95.7%, highlighting its potential in next-generation human-machine interaction and advanced robotics.

Sensors stand as pivotal cornerstones of technology, driving progress across a spectrum of industries through their ability to precisely capture and interpret an extensive array of physical phenomena. Among these advancements, microwave photonic (MWP) sensing has emerged as a new sensing technique, elevating sensing speed and resolution for practical applications. Integrated MWP sensors exhibit unparalleled capabilities in ultra-sensitive, label-free nanoscale detection, offering the potential to synergize with advanced integration techniques for a compact footprint and versatile designs. This paper reviews and summarizes the development and recent advances in integrated MWP sensing, focusing on the schemes based on microresonators. The diverse array of existing schemes is systematically categorized, elucidating their operational principles and performance demonstration. Furthermore, the assistance of machine learning and deep learning in integrated MWP sensors is explored, highlighting the potential of intelligent sensing paradigms. Finally, current challenges and opportunities aimed at further advancing MWP sensors are discussed.

SARS-CoV-2 Sensing and Detection

In article 2300135, Youssef Tawk and co-workers introduce an advanced portable device that leverages electromagnetic waves and data analytics to instantaneously detect and differentiate between the SARS-CoV-2 virus and different respiratory viruses. It employs a radio frequency (RF) circuit to electromagnetically identify virus signatures in diluted nasopharyngeal swabs with a detection accuracy of 94%, a sensitivity of 95%, and a specificity of 97.5%.

Triboelectric Nanogenerator

In article 2300129, Peihong Wang, Chunchang Wang, and co-workers show that the addition of citric and glycerol enhances water resistance, improves the softness of the chitosan-based film, results in low electronegativity and higher triboelectricity of chitosan-based film. Self-powered tactile sensor based on the TENG exhibits sensitive response to pressure and bending as well as humidity resistance, giving the sensor tremendous promise for a wide range of human motion monitoring and energy harvesting.

Electrochemical Biosensing

Electrochemical biosensing is a rapidly growing field within global healthcare research. In article 2300100, Matiar M. R. Howlader and co-workers provide a comprehensive review of the underlying principles and technological advancements in electrochemical sensing for health monitoring applications.

In human life, respiration serves as a crucial physiological signal. Continuous real-time respiration monitoring can provide valuable insights for the early detection and management of several respiratory diseases. High-sensitivity, noninvasive, comfortable, and long-term stable respiration devices are highly desirable. In spite of this, existing respiration sensors cannot provide continuous long-term monitoring due to the erosion from moisture, fluctuations in body temperature, and many other environmental factors. This research developed a wearable thermal-based respiration sensor made of cubic silicon carbide (3C-SiC) using a microfabrication process. The results showed that as a result of the Joule heating effect in the robustness 3C-SiC material, the sensor offered high sensitivity with the negative temperature coefficient of resistance of approximately 5,200ppmK^-1, an excellent response to respiration and long-term stability monitoring. Furthermore, by incorporating a deep learning model, this fabricated sensor can develop advanced capabilities to distinguish between the four distinct breath patterns: slow, normal, fast, and deep breathing, and provide an impressive classification accuracy rate of ≈ 99.7%. The results of this research represent a significant step in developing wearable respiration sensors for personal healthcare systems.

Flexible and stretchable tactile sensors are attracted in the fields of soft robotics, wearable electronics, and healthcare monitoring. The sensing performance of tactile sensors is commonly affected by external deformations like stretching, bending, and twisting, thus they may fail to function on deformable object surfaces. This paper presents a stretchable tactile sensor array using kirigami-patterned structural design and soft hinges to reduce the influences of deformation. The kirigami pattern of sensor array is parametrically studied to achieve the required expansion patterns. Laser engraving is employed to modify the micropillars on the force-sensitive rubber surface to increase the sensitivity. Characterization tests show that the sensor array has high sensitivity (≈1.49 × 10⁻¹ kPa⁻¹) for force sensing, and the stretching and bending deformation have almost negligible effects on sensing performance. Under 40% stretching or 180° bending conditions, the measured resistance changes (ΔR/R₀) is ≈0.03 and 0.06, respectively. To demonstrate the capability of developed sensor array, it is mounted on an expandable balloon surface for force detection. The recorded signals changed less than 1.5% during expanding process while rapidly rose under applied force, which indicated that the sensor array has the potential to effectively function on complex and deforming surfaces.

Circulating tumor cells (CTCs) have garnered special attention as promising cancer biomarkers. Phenotypic changes of CTCs reveal invaluable information for oncologists in disease prognosis and adjusting their treatment options. Microfluidic technology has emerged as a promising tool for CTC isolation; however, two major hurdles remain to be solved in employing them in CTC analysis. First, a rapid CTC isolation scheme is needed to allow immediate use of patient samples for point-of-care treatment monitoring. Second, multiplexed and streamlined CTC imaging is needed to facilitate CTC detection. Here, a microfluidic CTC sequential trapping array (STA) is proposed which addresses these hurdles enabling pipette-based CTC isolation and simultaneous profiling of multiple CTC protein expressions. The STA device isolates CTCs based on their size difference from blood cells and increases sample processing throughput through its parallel design configuration. It successfully isolates CTC from a depleted peripheral blood mononuclear cells sample of breast cancer patients with a high recovery rate of 80% and discriminates the number and types of CTCs in breast cancer based on their disease stage. These findings will open a new avenue in clinical translation of CTC profiling technologies. It will be an example for future translational developments in CTC-based cancer management.