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Basic structure and main functional components of a mechanical ventilator. ETT: endotracheal tube.
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This review addresses how the combination of physiology, medicine and engineering principles contributed to the development and advancement of mechanical ventilation, emphasising the most urgent needs for improvement and the most promising directions of future development.
Several aspects of mechanical ventilation are introduced, highlighting on on...
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Citations
... For example, many studies reporting on scoliosis classify outcomes based on surgery, however with changing treatment patterns [55] the utility of surgery as a proxy for clinically-significant scoliosis will decrease. Similarly, recommended strategies for ventilation vary among clinical centers [39,56,57], and practice is changing (in particular for how IV is used) [58], which will impact the comparability of estimates of the timing of respiratory decline across studies from different periods. Finally for cardiomyopathy, with advancements in screening tools [59,60] as well as evidence of benefits to early treatment [61], it is likely that initial signs will now be detected earlier, which would result in an apparent decrease in the mean age at cardiomyopathy over the coming years. ...
Background
Duchenne muscular dystrophy (DMD) is a severe rare progressive inherited neuromuscular disorder, leading to loss of ambulation (LOA) and premature mortality. The standard of care for patients with DMD has been treatment with corticosteroids for the past decade; however a synthesis of contemporary data describing the clinical course of DMD is lacking. The objective was to summarize age at key clinical milestones (loss of ambulation, scoliosis, ventilation, cardiomyopathy, and mortality) in the corticosteroid-treatment-era.
Methods
A systematic review was conducted using MEDLINE and EMBASE. The percentage experiencing key clinical milestones, and the mean or median age at those milestones, was synthesized from studies from North American populations, published between 2007 and 2018.
Results
From 5637 abstracts, 29 studies were included. Estimates of the percentage experiencing key clinical milestones, and age at those milestones, showed heterogeneity. Up to 30% of patients lost ambulation by age 10 years, and up to 90% by 15 years of age. The mean age at scoliosis onset was approximately 14 years. Ventilatory support began from 15 to 18 years, and up to half of patients required ventilation by 20 years of age. Registry-based estimates suggest that 70% had evidence of cardiomyopathy by 15 years and almost all by 20 years of age. Finally, mortality rates up to 16% by age 20 years were reported; among those surviving to adulthood mortality was up to 60% by age 30 years.
Conclusions
Contemporary natural history studies from North America report that LOA on average occurs in the early teens, need for ventilation and cardiomyopathy in the late teens, and death in the third or fourth decade of life. Variability in rates may be due to differences in study design, treatment with corticosteroids or other disease-modifying agents, variations in clinical practices, and dystrophin mutations. Despite challenges in synthesizing estimates, these findings help characterize disease progression among contemporary North American DMD patients.
... To encourage and support the patient's spontaneous breathing, many research works have been completed to indicate respiratory patterns that emulate or track a patient's own breathing pattern. For adaptive support ventilation (ASV), the control scheme plays an important role in automatically modifying deep breaths and the rate of respiration [7][8][9]. e purposes of control are to optimize the minimum rate of breathing and mimic the patient's breathing frequency in a natural way. In reverse, in neurally adjusted ventilatory assistance (NAVA), the trigger from the patient's own neural ventilatory signal drives the ventilating machine. ...
In the early stage of the 21st century, humankind is facing high medical risks. To the best of our knowledge, there is currently no efficient way to stop chains of infections, and hence citizens suffer significantly increasing numbers of diseases. The most important factor in this scenario is the lack of necessary equipment to cure disease and maintain our living. Once breath cannot be guaranteed, humans find themselves in a dangerous state. This study aimed to design, control, model, and simulate mechanical ventilator that is open-source structure, lightweight, and portable, which is proper for patients to cure themselves at home. In the scope of this research, the hardware platform for the mechanical design, implementation of control rules, and some trials of both simulations and experiments are presented as our methodology. The proposed design of ventilator newly features the bioinspired mechanism, finger-like actuator, and flow rate-based control. Firstly, the approximate evaluation of the lung model is presented with some physiological characteristics. Owing to this investigation, the control scheme was established to adapt to the biological body. Moreover, it is essential for the model to be integrated to determine the appropriate performance of the closed-loop system. Derived from these theoretical computations, the innovative concept of mechanical design was demonstrated using the open-source approach, and the real-world model was constructed. In order to estimate the driving torque, the hardware modeling was conducted using mathematical expressions. To validate the proposed approach, the overall system was evaluated using Matlab/Simulink, and experiments with the proposed platform were conducted in two situations: 20 lpm as a reference flow rate for 4 seconds and 45 lpm for 2.5 seconds, corresponding to normal breath and urgent breath. From the results of this study, it can be clearly observed that the system’s performance ensures that accurate airflow is provided, although the desired airflow fluctuates. Based on the test scenario in hardware, the RMS (root-mean-square) values of tracking errors in airflow for both cases were 1.542 and 1.767. The proposed design could deal with changes in airflow, and this machine could play a role as a proper, feasible, and robust solution to support human living.
1. Introduction
Artificial ventilation support is a life-saving method that is utilized to provide enough air. Most patients that require this could not breathe adequately on their own. This technique is also used to deal with respiratory failures as well as during and after major surgical operations. One of the most popular respiratory supports is positive pressure mechanical ventilation [1], which is employed in various modalities [2]. Recently, several technologies for ventilators have been developed to individually adjust the system parameters to match patients’ requirements [3–6]. In those works, the key factor is to synchronize the human breathing rate with the frequency of breaths provided by the machinery system. It is absolutely true that any asynchrony between human and machine could cause severe distress and fatigue. Additionally, the excessive use of sedatives or prolongation of mechanical ventilation could occur during medical treatment. To encourage and support the patient’s spontaneous breathing, many research works have been completed to indicate respiratory patterns that emulate or track a patient’s own breathing pattern. For adaptive support ventilation (ASV), the control scheme plays an important role in automatically modifying deep breaths and the rate of respiration [7–9]. The purposes of control are to optimize the minimum rate of breathing and mimic the patient’s breathing frequency in a natural way. In reverse, in neurally adjusted ventilatory assistance (NAVA), the trigger from the patient’s own neural ventilatory signal drives the ventilating machine. The activated signal is identified by electrodes mounted on a nasogastric tube located at the lower esophagus [10, 11]. In the last category, proportional assisted ventilation (PAV) supplies proportional pressure to the patient’s own breathing effort during respiration. Basically, it is a weaning technique and cannot be utilized during the period of treatment [12–14].
In the last few months, there has been an increased demand for ventilators during the treatment process of COVID-19 (coronavirus disease 2019) patients [15]. In fact, the situation for humankind at this time has become very challenging. Even well-equipped hospitals have had to expend great efforts to meet the increase in the number of sick persons, such as sharing the same air supply between two patients [16], meaning that they could not satisfy all requirements at the same time. To deal with the worldwide trouble of ventilator shortage, developers have innovated to release low-cost, open-source ventilators [17, 18] for numerous patients. Basically, these developments are able to provide instantaneous responses in hospital or healthcare service. It is agreed that this approach might be potentially one of the best solutions for poor nations or emergency cases [19].
In fact, a mechanical ventilator is a device that supports humans to breathe in order to maintain their blood oxygenation. Breathing regularly starts with inspiratory activity when air enters the lung and ends with an exhalation of breath, when air is expired. The inspiration is prompted by differences in pressure naturally exerted by the diaphragm and the chest motion as well as by a machine-driven mechanism in the human airway that launches a flow of air. Expiring is passive and motivated by the elastic force of the tissues in the lung.
Despite the changes to noninvasive respiratory support, mechanical ventilation remains an essential tool for the medical care of critically ill patients. A variety of advanced techniques for medical devices with available modes and data fusion present potential solutions. Since various manufacturers utilize different nomenclature to depict relative modes of ventilation, communication among users of different machines has turned into a challenge. The working modes of mechanical ventilation are often categorized into the acts of breathing. Breaths could be started by a timing mechanism in spite of a person’s inspiratory efforts. Alternatively, breaths might be prompted by the patient’s inspiration, which is named as synchronization or patient-triggered ventilation.
2. Motivations
In general, there are clearly typical classifications of ventilation machines. Firstly, adaptive support ventilation [20, 21] or automatic compensation ventilation [9, 22] is one of the best examples in terms of patient–ventilator synchrony. The goal of this type of machine is to support the resistive work of breathing via the artificial airway. The control scheme is usually a form of pressure control, and the system modeled by the mathematical expression indicates the airway pressure from the inspiratory flow. This native breath is initiated with inspiration, which is triggered and cycled by the patient. A nurse or doctor should input the size and choose the proper airway. Then, the ventilation machine utilizes a look-up table to identify the airway resistance. In this case, the controller is intelligent enough to drive the whole system according to the installed mathematical model. This requires complex computations with a short response from the patient’s inspiration. In these articles, the reasonable mechanism to avoid the fail-safe mistake, the understandable control scheme to deal with the diversity of patients, and the ability to collect enough data are some achievable lessons.
In the second category, neurally adjusted ventilatory assistance [23, 24] is actually a servo targeting circuit that is similar to the first type of machine. However, it requires more complicated requirements for implementation. In the field of patient-ventilator synchrony [25], this machine assists both the resistive and elastic work of breathing in proportion to the patient’s respiratory efforts. Although the severe acute exacerbations are out of this scope, the specific controlled trials and the status of patients in advance are beneficial for our study. Normally, the design controller must evaluate the airway pressure to be proportional according to the signal obtained from diaphragmatic activity. The user inserts the ratio value between voltage and pressure so that the controller manipulates the airway pressure. Besides, the third classification, called proportional assisted ventilation [26, 27], is also a servo targeting circuit, although it uses a more complex model than the two previous types. In the same method, this ventilator [28] provides both the resistive and elastic work of the breath related to the patient’s respiratory effort. It receives different feedback signals in terms of patient–ventilator synchrony. Additionally, the working mechanism is to control pressure based on the equation of motion for the respiratory system. To start the operating mode, the user must put in the desired values for elastance and resistance to be supported. From these analyses, the correct setting of ventilating mode and patient-oriented design are rewarded.
In recent times, the concept of open-source hardware [29, 30] has gathered pace in our community, especially for mechanical ventilators [31, 32]. Aiming at the treatment and prevention of COVID-19, modern microprocessor-based electronic devices [33, 34] have been embedded such that a complex control scheme, advanced functions, and powerful resources can be implemented. In [35], the researchers studied a microcontroller-driven mechanical ventilator using Ambu Bag which is pressed by the arm mechanism. The trajectory of mechanical components is planned by camshaft (CAM) generation. The output results present the time-varying characteristic of tidal volume. In the same method, but with a different mechanism, the authors in [29] developed a low-cost, open-source ventilator that was catalyzed by the global shortage of mechanical ventilator for COVID-19 patients. The driving motor, which is controlled by a Raspberry Pi, provides a maximum pressure of up to 70 cm H2O. Additionally, although the design is simple but efficient, the experimental device for ventilation satisfies the desired volume and pressure in respect to clinical requirements [36]. For future steps, developers are discussing the reliability of the mechanisms and software, mass production with appropriate standards, and regulatory approval or exemption. With the aim of portability, the investigators in [37] introduced an easy-to-use and mobile version of the Ambu Bag-based compression machine. This system is manipulated by Arduino and offers various breathing modes with varying tidal volumes. The rate for breathing is 5 to 40 breaths/minute, and the maximum ratio between inhalation and exhalation is 1 : 4. The repeatability and ability to precisely exceed personal capabilities in this design were proved in experiments. Although the original design consisting of two paddles is actuated by an electric motor [38], there are still several efforts to develop pressure-controlled ventilation. It is noted that the usage of electromechanical actuators to press Ambu Bag is an excellent solution. Whether supplies of compressed air are available or not, the tidal volume could increase linearly [39].
The field of open-source mechanical ventilators has experienced a steep rise of contributions during the global pandemic. Although some countries have suffered a third or fourth wave of COVID-19, many predictions have been released that the number of ventilated patients is dramatically increasing, meaning that they will exceed the total supply of current ventilators in hospital or healthcare centers. Industrial developers, researchers, governments, and startups are motivated to enter the worldwide race to establish cheap, easy-to-manufacture mechanical ventilators. There is a diversity of these research works as clear design patterns are lacking, and the machines do not satisfy the minimum functional specifications or present hardly any innovation.
In this paper, a biomimetic study of a noninvasive mechanical ventilator has been proposed in the emergent situation. The purpose of our work is to design, control, model, and simulate mechanical ventilator with an open-source hardware, high mobility, and less heaviness for home-based treatment. The technical features of proposed ventilator consist of the bioinspired mechanism, finger-like actuator, and flow rate-based control. In this methodology, the physiological model of the lung is estimated to mimic the particular characteristics of the human body. Additionally, this implementation of theoretical modeling could create the closed-loop control scheme. Later, the conceptual mechanism of an overall ventilator is represented in detail together with a 3D model. In order to identify the driving torque from actuators, the dynamic performance of the mechanical prototype is analyzed. From these achievements, it is seen clearly that our approach is a feasible, effective, and capable solution in the emergent scenario. In particular, it achieves the requirements of being of low-cost, available, and easy to maintain in poor nations. The rest of this paper is constructed as follows. Section 3 demonstrates the mathematical expressions of the lung model according to the physical evaluations. From the academic estimation, the illustration of the control loop is presented in the first part of Section 4. Furthermore, the internal structure of the conceptual scheme and mechanical computations are depicted in detail in the second part of Section 4, while many achievements in both numerical simulation and practical implementation are made in Section 5. Finally, several conclusions and future works are presented in Section 6.
3. Fundamental Model of Breathing
In the initial stage, it is necessary to present the model of breathing mechanics to offer a basic picture of how the ventilation system works. This model is simplified and illustrates the relations among system variables. It is particularly focused on the pressure needed to drive gas into the airway and inflate the lung. Therefore, the physical model of breathing mechanics [22, 26] that is mostly used is a rigid flow conducting tube connected to an elastic compartment, as shown in Figure 1. This is a simplification of the above model from the viewpoint of pressure, volume, and flow. It is noted that the interface is not taken into account in this model because it is often insignificant. The lung and flow from the mouth are considered as the volume and airway, respectively. In this case, there are some notations due to the motion of the respiratory system. The transrespiratory pressure is characterized from the input air to volume while the transairway pressure and transthoracic pressure are symbolized as its components. When entering our body, the air meets the reaction from muscles, named as resistance. In addition, the ratio between the change of volume and the variation of pressure in the lung is referred to as compliance.
... During the past decades, improvements in our understanding of respiratory physiology and pathology, as well as various technological advancements, have allowed the development of ventilators that are more sophisticated and versatile [1]. These have more ventilation modes, expanded applications, and can provide patients with more accurate and desired ventilation. ...
Background: In mechanical ventilation, there are still some challenges to turn a modern ventilator into a fully reactive device, such as lack of a comprehensive target variable and the unbridged gap between input parameters and output results. This paper aims to present a state ventilation which can provide a measure of two primary, but heterogenous, ventilation support goals. The paper also tries to develop a method to compute, rather than estimate, respiratory parameters to obtain the underlying causal information.
Methods: This paper presents a state ventilation, which is calculated based on minute ventilation and blood gas partial pressures, to evaluate the efficacy of ventilation support and indicate disease progression. Through mathematical analysis, formulae are derived to compute dead space volume/ventilation, alveolar ventilation, and CO2 production.
Results: Measurements from a reported clinical study are used to verify the analysis and demonstrate the application of derived formulae. The state ventilation gives the expected trend to show patient status, and the calculated mean values of dead space volume, alveolar ventilation, and CO2 production are 158mL, 8.8L/m, and 0.45L/m respectively for a group of patients.
Discussions and Conclusions: State ventilation can be used as a target variable since it reflects patient respiratory effort and gas exchange. The derived formulas provide a means to accurately and continuously compute respiratory parameters using routinely available measurements to characterize the impact of different contributing factors.
... 10 In general, this section of the mechanical ventilator connects the patient with the main system with two limbs: the inspiratory one that leaves the equipment and reaches the patient, and an expiratory one that goes from the patient to the expiratory valve. 11,12 Therefore, the choice of effective cleaning and disinfection protocols, as well as postdisinfection microbiological analysis, is relevant for the control of VAP in COVID-19 patients. Under this antecedent, the aim of this work was to show the impact on reducing the incidence of cases of contamination after disinfection of mechanical ventilators after changing the disinfection method. ...
Introduction:
Mechanical ventilators are essential biomedical devices for the respiratory support of patients with SARS-CoV-2 infection. These devices can be transmitters of bacterial pathogens. Therefore, it is necessary to implement effective disinfection procedures. The aim of this work was to show the impact of the modification of a cleaning and disinfection method of mechanical ventilators of patients with SARS-CoV-2 and ventilator-associated pneumonia.
Material and methods:
338 mechanical ventilators of patients infected with SARS-CoV-2 and ESKAPE bacteria were divided in two groups. Group A and B were subjected to cleaning and disinfection with superoxidation solution-Cl/enzymatic detergent and isopropyl alcohol, respectively. Both groups were cultured for the detection of ESKAPE bacteria. The isolates were subjected to tests for identification, resistance, adherence, and genomic typing.
Results:
Contamination rates of 21.6% (n=36) were identified in group A. The inspiratory limb was the circuit involved in most cases of post-disinfection contamination. Acinetobacter baumanni, Pseudomonas aeruginosa, and multi-resistant Klebsiella pneumoniae were the pathogens involved in the contamination cases. The pathogens were highly adherent and in the case of A. baumanni, clonal dispersion was detected in 14 ventilators. Disinfection with enzymatic detergents allows a 100% reduction in contamination rates.
Conclusion:
The implementation of cleaning and disinfection with enzymatic detergents/ isopropyl alcohol of mechanical ventilators of patients with SARS-CoV-2 and ESKAPE bacteria had a positive impact on post-disinfection microbial contamination rates.
... Acquiring competence in treatments using complex medical devices, such as mechanical ventilators, requires a good theoretical and practical background [2]. The practitioner should understand the mechanical concepts and equations relating the different variables involved in ventilation in order to succeed in setting an effective and safe combination of parameters for each patient condition. ...
Description and presentation of an open access spreadsheet application for learning spontaneous breathing mechanics and mechanical ventilation https://bit.ly/2TyXo1C.
... According to one estimate at the beginning of the pandemic, 30 % of all hospitalized COVID-19 patients needed ventilation. 43 Since their invention in the first half of the twentieth century, ventilators have become increasingly complex and technology-intensive medical devices (Dellaca et al. 2017). Nowadays, a ventilator is made up of about 700 components, including mechanical and electronical devices as well as computer code (Netland 2020). ...
... Source: Dellaca et al. 2017 Major steps in the development included the use of electronic components in the 1970s and microprocessors in the 1980s. Both enabled the ever more accurate monitoring of the ventilation process and of the health condition of the patient by using sensors. ...
... Both enabled the ever more accurate monitoring of the ventilation process and of the health condition of the patient by using sensors. The process of ventilation is intricate due to the danger of ventilation-induced lung injury (VILI), i.e. ventilation must be carefully planned and executed considering the individual situation of the patients (Dellaca et al. 2017). ...
... In such scenarios, mechanical ventilators can be deployed to decrease the work of breathing and to deliver a high concentration of oxygen into the lungs. A mechanical ventilator is essentially a medical device combining actuators, sensors, digital electronic and software to fulfill a predefined ventilation strategy [8][9][10]. The basic structure and main functional building blocks of a typical mechanical ventilator are depicted in Figure 1. ...
... Furthermore, there is no strict taxonomy in the naming of ventilation modes and manufacturers often introduce different names for similar modes, which can lead to confusion. Further advances in the complex field of mechanical ventilation could benefit from a truly interdisciplinary approach combining the knowledge of medical professionals and biomedical engineers [8,35]. ...
... Basic structure and main functional building blocks of a mechanical ventilator (taken and adapted from[8]). ...
During mechanical ventilation, a disparity between flow, pressure and volume demands of the patient and the assistance delivered by the mechanical ventilator often occurs. This paper introduces an alternative approach of simulating and evaluating patient–ventilator interactions with high fidelity using the electromechanical lung simulator xPULM™. The xPULM™ approximates respiratory activities of a patient during alternating phases of spontaneous breathing and apnea intervals while connected to a mechanical ventilator. Focusing on different triggering events, volume assist-control (V/A-C) and pressure support ventilation (PSV) modes were chosen to test patient–ventilator interactions. In V/A-C mode, a double-triggering was detected every third breathing cycle, leading to an asynchrony index of 16.67%, which is classified as severe. This asynchrony causes a significant increase of peak inspiratory pressure (7.96 ± 6.38 vs. 11.09 ± 0.49 cmH2O, p < 0.01)) and peak expiratory flow (−25.57 ± 8.93 vs. 32.90 ± 0.54 L/min, p < 0.01) when compared to synchronous phases of the breathing simulation. Additionally, events of premature cycling were observed during PSV mode. In this mode, the peak delivered volume during simulated spontaneous breathing phases increased significantly (917.09 ± 45.74 vs. 468.40 ± 31.79 mL, p < 0.01) compared to apnea phases. Various dynamic clinical situations can be approximated using this approach and thereby could help to identify undesired patient–ventilation interactions in the future. Rapidly manufactured ventilator systems could also be tested using this approach.
... In 32 such scenarios, mechanical ventilators can be deployed to decrease the work of breathing 33 and to deliver a high concentration of oxygen into the lungs. A mechanical ventilator 34 is essentially a medical device combining actuators, sensors, digital electronic and 35 software to fulfil a predefined ventilation strategy [8][9][10]. The basic structure and main 36 functional building blocks of a typical mechanical ventilator are depicted in Figure 1. ...
... Furthermore, there is no strict taxonomy in the naming of ventilation modes and manufacturers often introduce different names for similar modes which can lead to confusion. Further advances in the complex field of mechanical ventilation could benefit from a truly interdisciplinary approach combining the knowledge of medical professionals and biomedical engineers.[8,35] 88 1.3. ...
During mechanical ventilation, a disparity between flow, pressure or volume demands of the patient and the assistance delivered by the mechanical ventilator often occurs. Asynchrony effect and ventilator performance are frequently studied from ICU datasets or using commercially available lung simulators and test lungs. This paper introduces an alternative approach of simulating and evaluating patient-ventilator interactions with high fidelity using the electro-mechanical lung simulator xPULM™ under selected conditions. The xPULM™ approximates respiratory activities of a patient during alternating phases of spontaneous breathing and apnoea intervals while connected to a mechanical ventilator. Focusing on different triggering events, volume assist-controlled (V/A-C) and pressure support ventilation (PSV) modes were chosen to test patient-ventilator interactions. In V/A-C mode a double-triggering was detected every third breathing cycle leading to an asynchrony index of 16.67%, being classified as severe. This asynchrony causes a major increase of Peak Inspiratory Pressure PIP = 12.80 ± 1.39 cmH2O and Peak Expiratory Flow PEF = -18.33 ± 1.13 L/min when compared to synchronous phases of the breathing simulation. Additionally, events of premature cycling were observed during PSV mode. In this mode, the peak delivered volume during simulated spontaneous breathing phases almost doubles compared to apnoea phases. The presented approach demonstrates the possibility of simulating and evaluating disparities in fundamental ventilation characteristics caused by double-triggering and premature cycling under V/A-C and PSV ventilation modes. Various dynamic clinical situations can be approximated and could help to identify undesired patient-ventilation interactions in the future. Rapidly manufactured ventilator systems could also be tested using this approach.
... Dynamic respiratory mechanics, pressure support ventilation, pulmonary compliance, resistance, tidal volume, airway compliance, airway resistance Date received: 9 April 2020; accepted: 6 January 2021 Background Mechanical ventilation is a lifesaving intervention that has been widely used in the management of critically ill patients for more than 50 years. 1 Analysis of individual respiratory mechanics is beneficial to guide the ventilator setting under the conditions of pulmonary protective mechanical ventilation. 2 Recently, in the analysis of respiratory mechanics, the focus has changed from static to dynamic conditions. ...
Objective
To evaluate the accuracy of respiratory mechanics using dynamic signal analysis during noninvasive pressure support ventilation (PSV).
Methods
A Respironics V60 ventilator was connected to an active lung simulator to model normal, restrictive, obstructive, and mixed obstructive and restrictive profiles. The PSV was adjusted to maintain tidal volumes (V T ) that achieved 5.0, 7.0, and 10.0 mL/kg body weight, and the positive end-expiration pressure (PEEP) was set to 5 cmH 2 O. Ventilator performance was evaluated by measuring the flow, airway pressure, and volume. The system compliance (C rs ) and airway resistance (inspiratory and expiratory resistance, R insp and R exp , respectively) were calculated.
Results
Under active breathing conditions, the C rs was overestimated in the normal and restrictive models, and it decreased with an increasing pressure support (PS) level. The R insp calculated error was approximately 10% at 10.0 mL/kg of V T , and similar results were obtained for the calculated R exp at 7.0 mL/kg of V T .
Conclusion
Using dynamic signal analysis, appropriate tidal volume was beneficial for R rs , especially for estimating R exp during assisted ventilation. The C rs measurement was also relatively accurate in obstructive conditions.
... A typical mechanical ventilator consists of a control unit, blender, valves/turbine, and sensors. The construction of the ventilation mode should involve three elements, including, ventilator breath control variable (volume and pressure control), breath sequence, and targeting scheme (Dellaca' et al., 2017). In mass casualty cases, low-cost portable mechanical ventilators have proved to be essential. ...
Purpose: It is now clear that the COVID-19 viruses can be transferred via airborne transmission. The objective of this study was to attempt the design and fabrication of an AMBU ventilator with a negative pressure headbox linked to a negative pressure transporting capsule, which could provide a low-cost construction, flexible usage unit, and also airborne prevention that could be manufactured without a high level of technology.
Method: The machine consists of an automated AMBU bag ventilator, a negative pressure headbox, and a transporting capsule. The function and working duration of each component were tested.
Results: The two main settings of the ventilator include an active mode that can be set at the time range of 0 s–9 h 59 min 59 s and a resting mode, which could work continuously for 24 h. The blower motor and battery system, which were used to power the ventilator, create negative air pressure within the headbox, and the transporting capsule, could run for at least 2 h without being recharged. The transporting capsule was able to create an air change rate of 21.76 ACH with-10 Pa internal pressure.
Conclusion: This automated AMBU ventilator allowed flow rate, rhythm, and volume of oxygen to be set. The hazardous expired air was treated by a HEPA filter. The patient’s transporting capsule is of a compact size and incorporates the air treatment systems. Further development of this machine should focus on how to link seamlessly with imaging technology, to verify standardization, to test using human subjects, and then to be the commercialized.
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