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![Metamaterial sensors (a) Modulated FSS [36] (b) Spiral resonator [37] (c) Surface plasmons resonator [38] (d) Liquid metal FSS [39] (e) Metamaterial textiles [40].](publication/373052137/figure/fig3/AS:11431281180932495@1691756204848/Metamaterial-sensors-a-Modulated-FSS-36-b-Spiral-resonator-37-c-Surface.png)
Metamaterial sensors (a) Modulated FSS [36] (b) Spiral resonator [37] (c) Surface plasmons resonator [38] (d) Liquid metal FSS [39] (e) Metamaterial textiles [40].
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![Figure 3. Metamaterial sensors (a) Modulated FSS [36] (b) Spiral...](publication/373052137/figure/fig3/AS:11431281180932495@1691756204848/Metamaterial-sensors-a-Modulated-FSS-36-b-Spiral-resonator-37-c-Surface_Q320.jpg)
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This paper provides an overview of flexible and wearable respiration sensors with emphasis on their significance in healthcare applications. The paper classifies these sensors based on their operating frequency distinguishing between high-frequency sensors which operate above 10 MHz and low-frequency sensors. The operating principles of breathing s...
Contexts in source publication
Context 1
... are widely utilized in the microwave frequency filters, radar absorbing materials (RAMs), and antenna reflectors [35]. For respiration sensing, a wireless apnea detector is proposed in [36] that utilizes a passive respiration sensor to measure the changes in airflow temperature during breathing, as shown in Figure 3a. A transponder based on a modulated FSS is employed that use a backscattered field technique for sensing and is composed of an array of dipoles loaded with varactor diodes. ...
Context 2
... frequency selective surfaces used for sensing present certain limitations in 226 terms of flexibility, as the materials and structures used are rigid. Therefore, liquid metal based technologies [39] and textile based substrates [40] are feasible options that can be explored for designing flexible metamaterials for wearable applications, as depicted in Figure 3d and Figure 3e. ...
Context 3
... frequency selective surfaces used for sensing present certain limitations in 226 terms of flexibility, as the materials and structures used are rigid. Therefore, liquid metal based technologies [39] and textile based substrates [40] are feasible options that can be explored for designing flexible metamaterials for wearable applications, as depicted in Figure 3d and Figure 3e. ...
Context 4
... inductance of a spiral is determined by its geometry (such as square, circular, or polygonal), number of turns, turn width, and spacing between turns. A breath rate sensor based on an SR tag is illustrated in Figure 3b that is printed on a thin, flexible textile substrate suitable for wearable applications [37]. The sensor detects respiratory movement of the abdomen during inspiration and expiration. ...
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Citations
Respiratory measurement is a crucial indicator for assessing health status; however, current methods for measuring respiratory rate and frequency are passive and not intuitive. This study investigates peak detection algorithms using a resistive strain sensor integrated into a garment for respiratory rate monitoring. The sensor, constructed with CNT material and a flexible rubber substrate, exhibits high conformity to the body’s contours. Designed for respiration measurement, the sensor maintains a low 6% strain for optimal sensitivity, demonstrating a 4% decrease after 800 repetitions of 10% elongation. Garment design emphasizes cohesion between the sensor and fabric, achieved through a piping technique. Respiratory measurement relies on a resistive sensor principle, where abdominal volume changes induce tension, altering resistance. Three peak detection algorithms are evaluated: the window size algorithm, low-pass filter, and FIR filter. The window size algorithm shows a 93% matching rate for normal breathing but requires manual adjustments based on breathing speed. The low-pass filter reduces noise but introduces lag, challenging peak matching. The FIR filter effectively detects peaks at increased speeds, achieving a matching rate exceeding 98%. The study concludes that the choice of algorithm depends on respiratory scenarios, with the window size algorithm suitable for regular cycles, the low-pass filter for real-time monitoring, and the FIR filter for accelerated respiratory rates. The study primarily explores static situations, indicating the need for future research on dynamic respiratory movements to enhance algorithm versatility.
Smart wearable sensors are increasingly integrated into everyday life, interfacing with the human body to enable real-time monitoring of biological signals. This study focuses on creating high-sensitivity capacitive-type sensors by impregnating polyester-based 3D spacer fabric with a Carbon Nanotube (CNT) dispersion. The unique properties of conductive particles lead to nonlinear variations in the dielectric constant when pressure is applied, consequently affecting the gauge factor. The results reveal that while the fabric without CNT particles had a gauge factor of 1.967, the inclusion of 0.04 wt% CNT increased it significantly to 5.210. As sensor sensitivity requirements vary according to the application, identifying the necessary CNT wt% is crucial. Artificial intelligence, particularly the Multilayer Perception (MLP) model, enables nonlinear regression analysis for this purpose. The MLP model created and validated in this research showed a high correlation coefficient of 0.99564 between the model predictions and actual target values, indicating its effectiveness and reliability.
Wearable sensors are rapidly gaining influence in the diagnostics, monitoring, and treatment of disease, thereby improving patient outcomes. In this review, we aim to explore how these advances can be applied to magnetic resonance imaging (MRI). We begin by (i) introducing limitations in current flexible/stretchable RF coils and then move to the broader field of flexible sensor technology to identify translatable technologies. To this goal, we discuss (ii) emerging materials currently used for sensor substrates, (iii) stretchable conductive materials, (iv) pairing and matching of conductors with substrates, and (v) implementation of lumped elements such as capacitors. Applicable (vi) fabrication methods are presented, and the review concludes with a brief commentary on (vii) the implementation of the discussed sensor technologies in MRI coil applications. The main takeaway of our research is that a large body of work has led to exciting new sensor innovations allowing for stretchable wearables, but further exploration of materials and manufacturing techniques remains necessary, especially when applied to MRI diagnostics.
In recent years, the proliferation of wearable healthcare devices has marked a revolutionary shift in the personal health monitoring and management paradigm. These devices, ranging from fitness trackers to advanced biosensors, have not only made healthcare more accessible, but have also transformed the way individuals engage with their health data. By continuously monitoring health signs, from physical-based to biochemical-based such as heart rate and blood glucose levels, wearable technology offers insights into human health, enabling a proactive rather than a reactive approach to healthcare. This shift towards personalized health monitoring empowers individuals with the knowledge and tools to make informed decisions about their lifestyle and medical care, potentially leading to the earlier detection of health issues and more tailored treatment plans. This review presents the fabrication methods of flexible wearable healthcare devices and their applications in medical care. The potential challenges and future prospectives are also discussed.
This article explores the importance of wearable and remote technologies in healthcare. The focus highlights its potential in continuous monitoring, examines the specificity of the issue, and offers a view of proactive healthcare. Our research describes a wide range of device types and scientific methodologies, starting from traditional chest belts to their modern alternatives and cutting-edge bioamplifiers that distinguish breathing from chest impedance variations. We also investigated innovative technologies such as the monitoring of thorax micromovements based on the principles of seismocardiography, ballistocardiography, remote camera recordings, deployment of integrated optical fibers, or extraction of respiration from cardiovascular variables. Our review is extended to include acoustic methods and breath and blood gas analysis, providing a comprehensive overview of different approaches to respiratory monitoring. The topic of monitoring respiration with wearable and remote electronics is currently the center of attention of researchers, which is also reflected by the growing number of publications. In our manuscript, we offer an overview of the most interesting ones.
This work involves exploring non-invasive sensor technologies for data collection and preprocessing, specifically focusing on novel thermal calibration methods and assessing low-cost infrared radiation sensors for facial temperature analysis. Additionally, it investigates innovative approaches to analyzing acoustic signals for quantifying coughing episodes. The research integrates diverse data capture technologies to analyze them collectively, considering their temporal evolution and physical attributes, aiming to extract statistically significant relationships among various variables for valuable insights. The study delineates two distinct aspects: cough detection employing a microphone and a neural network, and thermal sensors employing a calibration curve to refine their output values, reducing errors within a specified temperature range. Regarding control units, the initial implementation with an ESP32 transitioned to a Raspberry Pi model 3B+ due to neural network integration issues. A comprehensive testing is conducted for both fever and cough detection, ensuring robustness and accuracy in each scenario. The subsequent work involves practical experimentation and interoperability tests, validating the proof of concept for each system component. Furthermore, this work assesses the technical specifications of the prototype developed in the preceding tasks. Real-time testing is performed for each symptom to evaluate the system's effectiveness. This research contributes to the advancement of non-invasive sensor technologies, with implications for healthcare applications such as remote health monitoring and early disease detection.
