Since the beginning of the COVID-19 pandemic, the use of face masks has become not only mandatory in several countries but also an acceptable approach for combating the pandemic. In the quest for designing an effective and useful face mask, triboelectric nanogenerators (TENGs) have been recently proposed. Novel functionalities are provided with the use of TENGs in face masks due to the induced triboelectrification generated by the exhaled and inhaled breath, allowing their use as an energy sensor. Nonetheless, within the face mask, the presence of nontextile plastics or other common triboelectric (TE) materials can be undesired. Herein, we propose the use of an all-fabric TENG (AF-TENG) with the use of high molecular weight polyethylene (UHMWPE) and cotton fabric as negative and positive triboelectric layers, respectively. With these materials, it is possible to detect the breathing of the patient, which in the case of not detecting a signal over a few minutes can trigger an alarm locally, providing valuable time. Also, in this article, we have sent breathing signals locally and remotely to distances up to 20 km via Wi-Fi and LoRa, the same as warning signals in the case of detecting anomalies. This work reveals the use of TENGs in smart face masks as an important tool to be used in difficult epidemiological periods to the general public, bringing much more comfort and relaxation to patients and elderly in today's society, and based on pristine eco-friendly materials.
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http://dx.doi.org/10.1021/acssensors.2c02825 | DOI Listing |
Sensors (Basel)
January 2025
School of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
This review offers a comprehensive and in-depth analysis of face mask detection and recognition technologies, emphasizing their critical role in both public health and technological advancements. Existing detection methods are systematically categorized into three primary classes: feaRture-extraction-and-classification-based approaches, object-detection-models-based methods and multi-sensor-fusion-based methods. Through a detailed comparison, their respective workflows, strengths, limitations, and applicability across different contexts are examined.
View Article and Find Full Text PDFMedicina (Kaunas)
January 2025
Department of Orthodontics, Faculty of Dentistry, Ataturk University, 25030 Erzurum, Turkey.
: The aim of this prospective study was to assess the effects of rapid maxillary expansion (RME) and/or face mask (FM) treatments on the pharyngeal airway in patients with skeletal Class III malocclusion caused by maxillary deficiency. This study utilized cone beam computed tomography (CIBT) for a three-dimensional (3D) analysis of airway changes, comparing the results with those of a control group consisting of untreated skeletal Class III patients. : The study included 60 participants (34 boys, 26 girls) aged 9 to 14 years, all diagnosed with skeletal Class III malocclusion due to maxillary underdevelopment.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Anesthesiology, The Second Affiliated Hospital, The Army Military Medical University, Chongqing, China.
Background: Rapid sequence induction intubation (RSII) is commonly used in emergency surgeries for patients at high risk of aspiration. However, these patients are more susceptible to hypoxemia during the RSII process. High-flow nasal cannula (HFNC) oxygen therapy has emerged as a potential alternative to traditional face mask (FM) ventilation pre- and apneic oxygenation.
View Article and Find Full Text PDFActa Paediatr
January 2025
Department of Neonatology, University Children's Hospital of Tuebingen, Tuebingen, Germany.
Aim: Face masks and binasal prongs are commonly used interfaces for applying continuous positive airway pressure (CPAP) in neonatology. We aimed to assess CPAP stability in a randomised controlled in vitro study.
Methods: In a simulated resuscitation scenario of a 1000-g preterm infant with respiratory distress, 20 operators (10 with/without neonatology experience) aimed to maintain a CPAP of 5 cmHO as precisely as possible using face masks or binasal prongs in random order.
J Imaging
January 2025
Department of Precision Instrument, Tsinghua University, Beijing 100084, China.
The increasing reliance on deep neural network-based object detection models in various applications has raised significant security concerns due to their vulnerability to adversarial attacks. In physical 3D environments, existing adversarial attacks that target object detection (3D-AE) face significant challenges. These attacks often require large and dispersed modifications to objects, making them easily noticeable and reducing their effectiveness in real-world scenarios.
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