Linear regression model and least square method for experimental identification of AMBU bag in simple ventilator

Abstract

Purpose

In the COVID-19 outbreak periods, people's life has been deranged, leading to disrupt the world. Firstly, the number of deaths is growing and has the potential to surpass the highest level at any time. Secondly, the pandemic broke many countries' fortified lines of epidemic prevention and gave people a more honest view of its seriousness. Finally, the pandemic has an impact on life, and the economy led to a shortage in medical, including a lack of clinicians, facilities and medical equipment. One of those, a simple ventilator is a necessary piece of medical equipment since it might be useful for a COVID-19 patient's treatment. In some cases, the COVID-19 patients require to be treated by modern ventilators to reduce lung damage. Therefore, the addition of simple ventilators is a necessity to relieve high work pressure on medical bureaucracies. Some low-income countries aim to build a simple ventilator for primary care and palliative care using locally accessible and low-cost components. One of the simple principles for producing airflow is to squeeze an artificial manual breathing unit (AMBU) iterative with grippers, which imitates the motion of human fingers. Unfortunately, the squeezing angle of grippers is not proportional to the exhaust air volume from the AMBU bag. This paper aims to model the AMBU bag by a mathematical equation that enables to implement on a simple controller to operate a bag-valve-mask (BVM) ventilator with high accuracy performance.

Design/methodology/approach

This paper provides a curvature function to estimate the air volume exhausting from the AMBU bag. Since the determination of the curvature function is sophisticated, the coefficients of the curvature function are approximated by a quadratic function through the experimental identification method. To obtain the high accuracy performance, a linear regression model and a least square method are employed to investigate the characteristic of the BVM ventilator's grippers angle with respect to the airflow volume produced by the AMBU bag.

Findings

This paper investigates the correlation between the exhausting airflow of the AMBU bag and the grippers angle of the BVM ventilator.

Originality/value

The experimental results validated that the regression model of the characteristic of the exhausting airflow of the AMBU bag with respect to the grippers' angle has been fitted with a coefficient over 98% within the range of 350–750 ml.

Citation

Truong, C.T., Huynh, K.H., Duong, V.T., Nguyen, H.H., Pham, L.A. and Nguyen, T.T. (2023), "Linear regression model and least square method for experimental identification of AMBU bag in simple ventilator", International Journal of Intelligent Unmanned Systems, Vol. 11 No. 3, pp. 378-395. https://doi.org/10.1108/IJIUS-07-2021-0072