Investigating the effect of materials and structures for negative pressure ventilators suitable for pandemic situation

Abughanam, Nada; Gaben, Shahd Sameer Mohammed; Chowdhury, Muhammad E. H.; Khandakar, Amith

doi:10.1007/s42247-021-00181-x

Cited by 8 publications

(14 citation statements)

References 37 publications

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“…Additionally, remote-sensing technology has continued to mature in recent decades with solutions to overcome power constraints. Nowadays, the development of bioinert and biocompatible materials that can be fabricated for artificial implants and bone replacements is becoming increasingly important [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Surface Acoustic Wave (SAW) Sensors for Hip Implant: A Numerical and Computational Feasibility Investigation Using Finite Element Methods

et al. 2023

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In this paper, a surface acoustic wave (SAW) sensor for hip implant geometry was proposed for the application of total hip replacement. A two-port SAW device was numerically investigated for implementation with an operating frequency of 872 MHz that can be used in more common radio frequency interrogator units. A finite element analysis of the device was developed for a lithium niobate (LiNBO3) substrate with a Rayleigh velocity of 3488 m/s on COMSOL Multiphysics. The Multiphysics loading and frequency results highlighted a good uniformity with numerical results. Afterwards, a hip implant geometry was developed. The SAW sensor was mounted at two locations on the implant corresponding to two regions along the shaft of the femur bone. Three discrete conditions were studied for the feasibility of the implant with upper- and lower-body loading. The loading simulations highlighted that the stresses experienced do not exceed the yield strengths. The voltage output results indicated that the SAW sensor can be implanted in the hip implant for hip implant-loosening detection applications.

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Section: Introductionmentioning

confidence: 99%

Surface Acoustic Wave (SAW) Sensors for Hip Implant: A Numerical and Computational Feasibility Investigation Using Finite Element Methods

et al. 2023

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“…Reminiscent of the polio pandemic, the COVID-19 pandemic and predicted urgency to ventilate patients caused a ventilator supply deficit, pushing the ingenuity and involvement of various companies (i.e. GM, Dyson, and Tesla) in ventilator design and manufacturing [ 2 , 11 , 16 , 18 ]. Optimal settings for modern mechanical ventilators are vital [ 76 ], but the most reoccurring concern is whether to artificially ventilate with positive- or negative-pressure [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

“…GM, Dyson, and Tesla) in ventilator design and manufacturing [ 2 , 11 , 16 , 18 ]. Optimal settings for modern mechanical ventilators are vital [ 76 ], but the most reoccurring concern is whether to artificially ventilate with positive- or negative-pressure [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Study of Ex-Vivo Murine Pulmonary Mechanics Under Positive- and Negative-Pressure Ventilation

Quiros,

Nelson,

Ulu

et al. 2023

Ann Biomed Eng

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Increased ventilator use during the COVID-19 pandemic resurrected persistent questions regarding mechanical ventilation including the difference between physiological and artificial breathing induced by ventilators (i.e., positive- versus negative-pressure ventilation, PPV vs NPV). To address this controversy, we compare murine specimens subjected to PPV and NPV in ex vivo quasi-static loading and quantify pulmonary mechanics via measures of quasi-static and dynamic compliances, transpulmonary pressure, and energetics when varying inflation frequency and volume. Each investigated mechanical parameter yields instance(s) of significant variability between ventilation modes. Most notably, inflation compliance, percent relaxation, and peak pressure are found to be consistently dependent on the ventilation mode. Maximum inflation volume and frequency note varied dependencies contingent on the ventilation mode. Contradictory to limited previous clinical investigations of oxygenation and end-inspiratory measures, the mechanics-focused comprehensive findings presented here indicate lung properties are dependent on loading mode, and importantly, these dependencies differ between smaller versus larger mammalian species despite identical custom-designed PPV/NPV ventilator usage. Results indicate that past contradictory findings regarding ventilation mode comparisons in the field may be linked to the chosen animal model. Understanding the differing fundamental mechanics between PPV and NPV may provide insights for improving ventilation strategies and design to prevent associated lung injuries.

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“…The COVID-19 pandemic struck the world, and it has severely overrun healthcare systems worldwide. It had an impact on social, economic, and all facets of human life [1,2]. As of August 2022, there were more than 6 million fatalities and more than 579 million active cases worldwide [3].…”

Section: Introductionmentioning

confidence: 99%

Signal, Image Processing and Embedded Systems Trends

2022

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The novel coronavirus disease ) is a highly contagious infectious disease. Even though there is a large pool of articles that showed the potential of using chest X-ray images in COVID-19 detection, a detailed study using a wide range of pre-trained convolutional neural network (CNN) encoders-based deep learning framework in screening viral, bacterial, and COVID-19 pneumonia are still missing. Deep learning network training is challenging without a properly annotated huge database. Transfer learning is a crucial technique for transferring knowledge from real-world object classification tasks to domain-specific tasks, and it may offer a viable answer. Although COVID-19 infection on the lungs and bacterial and viral pneumonia shares many similarities, they are treated differently. Therefore, it is crucial to appropriately diagnose them. The authors have compiled a large X-ray dataset (QU-MLG-COV) consisting of 16,712 CXR images with 8851 normal, 3616 COVID-19, 1485 viral, and 2740 bacterial pneumonia CXR images. We employed image pre-processing methods and 21 deep pre-trained CNN encoders to extract features, which were then dimensionality reduced using principal component analysis (PCA) and classified into 4-classes. We trained and evaluated every cutting-edge pre-trained network to extract features to improve performance. CheXNet surpasses other networks for identifying COVID

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Investigating the effect of materials and structures for negative pressure ventilators suitable for pandemic situation

Cited by 8 publications

References 37 publications

Surface Acoustic Wave (SAW) Sensors for Hip Implant: A Numerical and Computational Feasibility Investigation Using Finite Element Methods

Surface Acoustic Wave (SAW) Sensors for Hip Implant: A Numerical and Computational Feasibility Investigation Using Finite Element Methods

A Comparative Study of Ex-Vivo Murine Pulmonary Mechanics Under Positive- and Negative-Pressure Ventilation

Signal, Image Processing and Embedded Systems Trends

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