Design and Development of an Automated Compression Mechanism for a Bag-Valve-Mask-Based Emergency Ventilator

Calilung, Edwin J.; Española, Jason L.; Dadios, Elmer P.; Culaba, Alvin B.; Sybingco, Edwin; Vicerra, Ryan Rhay P.; Madrazo, Alma Bella; Lim, Laurence Gan; Billones, Robert Kerwin C.; Lopez, Siegfred; Ligutan, Dino Dominic; Palingcod, Julius; Castillo, Carl John Patrick

doi:10.1109/hnicem51456.2020.9400150

Cited by 9 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most of the published works have proposed either a form of conventional bag valve mask (BVM) [4] or a pressure regulatory valve system [5]. A BVM system integrates electronic bag squeezing mechanism at a set frequency [6][7][8][9] based on an idea first reported in a research paper by Husseini et al [10]. One of the main disadvantages of these type of systems is that the air volume cannot be adjusted based on the patient's 2 requirement which thus poses a potential risk of damage to the lungs [11,12].…”

Section: Introductionmentioning

confidence: 99%

Design and Performance Evaluation of a Low-Cost Non-Invasive Electromechanical Ventilator With Feedback Mechanism

Nuary Alam,

Faiz,

Akash

et al. 2024

IEEE Access

View full text Add to dashboard Cite

The use of non-invasive ventilator (NIV) is common in both acute and chronic respiratory failure. It delivers oxygenated air into the lungs via positive pressure but requires careful monitoring and titration to avoid complications. Some of the major challenges in NIV research are improving synchronicity between patient and NIV, monitoring capabilities, portability, cost, and simple operation with myriad modes to improve patient adherence. This current paper proposes a non-invasive electromechanical ventilator which operates automatically based on real-time bio feedback to provide respiratory care considering patient's breathing requirement. The system monitors two biofeedback signals: namely the oxygen saturation (SpO2) and respiratory rate (RR) to select appropriate mode of breathing aid and terminates operation when the patient's vital reaches safe value. To extract the feedback parameters, a simulation model has been developed in MATLAB where discrete wavelet transform is used to extract RR from the real time photoplethysmography (PPG) signal of the patient. The hardware-generated result exhibits a mean absolute percentage error (MAPE) of less than 10% when compared to the output of the simulation model. The analyses of Box whisker and Bland Altman also demonstrated significant agreement between the measured RR and simulated RR for the younger demographic. This ventilator system has mean accuracy of 81% since it can deliver correct breathing pattern based on the biofeedback from the patient. This portable ventilator can be used by patients at home and clinics to get relief from breathing discomforts with an accessible control interface which does not require much prior medical knowledge.

show abstract

Section: Introductionmentioning

confidence: 99%

Design and Performance Evaluation of a Low-Cost Non-Invasive Electromechanical Ventilator With Feedback Mechanism

Nuary Alam,

Faiz,

Akash

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The last part is devoted to examples of programming for different Boolean functions and simple control algorithms. All programs are written using the Ladder Diagram language [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Modification of Control Oil Feeding with PLC Using Simulation Visual Basic and Neural Network Analysis

Yuliza

Muwardi

Pratama

et al. 2022

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

View full text Add to dashboard Cite

The oil feeding system is an oil distribution system used in engine lubrication by flowing it directly to the engine parts to be lubricated through pipes. In addition, it is also a raw material for the production process by collecting the oil first in the storage tank, then weighing it on the oil scale before use in the production process. The current control is still using the conventional model. The operating system is still manual, and the absence of identity and damage information makes it difficult for the engineer to troubleshoot. The research method is to modify the oil feeding system control using PLC (Programmable Logic Controller) and Visual Basic to display process information. This process uses the Neural Network (NN) method. The simulation results show that the PLC program and visual basic software can be connected properly. The speed of the data transfer test connection that can be obtained is 32 ms. The prediction process of the oil feeding system using the backpropagation algorithm Neural Network and the activation function, which uses the binary sigmoid function (logsig) with the 17-10-1 architecture having very good performance getting the MSE value below the error value of 0.001 maximum epoch 961 and hidden layer 10 with an MSE value of 0.00099915.

show abstract

“…In [8], the work proposes an automated system of the manual BVM process using industrial sensors and PLC to improve the reliability of the ventilator. Finally, in [5], the authors propose a much more compact and portable design that consists of compression of a plastic air tank.…”

Section: Introductionmentioning

confidence: 99%

Pressure and Volume Control of a Non-invasive Mechanical Ventilator: a PI and LQR Approach

Morales

Palomino

Terreros

et al. 2021

2021 9th International Conference on Control, Mechatronics and Automation (ICCMA)

View full text Add to dashboard Cite

Many studies in recent years have been focused on treating diseases caused by the SARS-CoV-2 virus, such as the Covid-19 disease. In this regard, the development of mechanical ventilation systems became very important for the care of patients with moderate symptoms caused by the virus. Most of the works developed used the non invasive mechanical ventilation system, since this is rapidly assembled and replicated. This work is centered on automating the manual Bag-Valve-Mask (BVM) ventilation of the Emergency Mechanical Ventilator for ICU (UTEC-AE EMV-ICU). For this purpose, it is necessary to implement a satisfactory control system to reach the adequate volume or pressure for patients. The control system implemented for the UTEC-AE EMV-ICU is based on LQR method for the three non-invasive ventilation modes (volumen controlled ventilation, pressure controlled ventilation, and assisted ventilation). The LQR control system of the UTEC-AE EMV-ICU was tested in an artificial lung where the obtained results were compared and discussed with the obtained results from a PI control system.

show abstract

Design and Development of an Automated Compression Mechanism for a Bag-Valve-Mask-Based Emergency Ventilator

Cited by 9 publications

References 26 publications

Design and Performance Evaluation of a Low-Cost Non-Invasive Electromechanical Ventilator With Feedback Mechanism

Design and Performance Evaluation of a Low-Cost Non-Invasive Electromechanical Ventilator With Feedback Mechanism

Modification of Control Oil Feeding with PLC Using Simulation Visual Basic and Neural Network Analysis

Pressure and Volume Control of a Non-invasive Mechanical Ventilator: a PI and LQR Approach

Contact Info

Product

Resources

About