Differential Pressure Spirometry for Mechanical Ventilation Using Dichotomic Search

Abstract

In invasive mechanical ventilation (IMV), it is critical that the flow value is estimated correctly, as it is used as a trigger variable for ventilatory assistance. Furthermore, the numerical integration of the flow allows the calculation of the total volume per breath (tidal volume), which clinicians use to identify trauma or lung capacity in the patient. The current COVID-19 pandemic has demonstrated the need to develop safe and efficient techniques for measuring this spirometry variable because many mechanical ventilators delivered to hospitals were unable to measure it directly. A good device to estimate flow is a D-lite sensor, which works by the Venturi effect, is cheap, reusable, and proximal to the patient. However, the regressions applied to the flow estimation model are limited for use in real conditions. This article presents a flow estimation method that uses a D-Lite device, a fraction of inspired oxygen (FiO2) cell, and two pressure sensors as critical items. Our novel method adapts the dichotomous search algorithm instead of conventional regression algorithms to estimate flow using a D-lite sensor; this change in the standard procedure allowed us a fast calibration process, a good low-flow estimation, and low computational time for flow estimation. The method was validated experimentally to compute the tidal volume according to the measurement requirement error range of +/-10%. The consideration of FiO2 percentage in the gas mixture and the good low-flow estimation make this novel method useful for real ventilation conditions. The flow calculations have been performed at different ambient conditions and compared with gas analyzers show an average relative error of up to 4.86%. Finally, we present an analysis of the error flow estimation considering the variation in each variable. Technical recommendations for applying this novel method to achieve invasive mechanical ventilation safely are presented, based on the capabilities of the embedded system used by developers.

Evaluating Airflow Sensor Methods: Precision in Indirect Calorimetry

“…However, inertial effects described as “lag‐before‐start” and “spin‐after‐stop” [22, 48] may impact flow measurement precision. The fV, preferred in many applications for its inherent stability over time [49–52], and more recently applied to spirometry [53, 54] is inherently similar to the more common pitot‐static tube, due its computational underpinnings [55]. As such, these differential pressure‐based devices inherently produce a nonlinear signal, which makes them ideal for higher flows, yet compromised during low flows [31], which may impact flow measurement precision.…”

Short Review for Design and Implementation of a New Low-Cost Prototype Portable Smart Ventilator

“…The device also provided sensors to measure air pressure. This technology supported a dichotomous algorithm instead of the traditional technique to measure the amount of FiO2 flow well and in little time [30].…”

“…6. D-lite spirometer [30] Finally, Ticllacuri et al (2022) presented a respirator that works on a linear-quadratic model using an electrical circuit, which was dealt with mathematically through differential equations. Thus, through this model, it could control the work of the ventilator, and mechanical ventilation was provided to patients [29].…”