Mechanical Ventilator VENT19

A novel PID controller for pressure control of artificial ventilator using optimal rule based fuzzy inference system with RCTO algorithm

In order to improve the pressure tracking response of an artificial ventilator system, a novel proportional integral derivative (PID) controller is designed in the present work by utilizing an optimal rule-based fuzzy inference system (FIS) with a reshaped class-topper optimization algorithm (RCTO), which is named as (Fuzzy-PID). Firstly, a patient-hose blower-driven artificial ventilator model is considered, and the transfer function model is established. The ventilator is assumed to operate in pressure control mode. Then, a fuzzy-PID control structure is formulated such that the error and change in error between the desired airway pressure and actual airway pressure of the ventilator are set as inputs to the FIS. The gains of the PID controller (proportional gain, derivative gain, and integral gain) are set as outputs of the FIS. A reshaped class topper optimization algorithm (RCTO) is developed to optimize rules of the FIS to establish optimal coordination among the input and output variables of the FIS. Finally, the optimized Fuzzy-PID controller is examined for the ventilator under different scenarios such as parametric uncertainties, external disturbances, sensor noise, and a time-varying breathing pattern. In addition, the stability analysis of the system is carried out using the Nyquist stability method, and the sensitivity of the optimal Fuzzy-PID is examined for different blower parameters. The simulation results showed satisfactory results in terms of peak time, overshoot, and settling time for all cases, which were also compared with existing results. It is observed in the simulation results that the overshoot in the pressure profile is improved by 16% with the proposed optimal rule based fuzzy-PID as compared with randomly selected rules for the system. Settling time and peak time are also improved 60-80% compared to the existing method. The control signal generated by the proposed controller is also improved in magnitude by 80-90% compared to the existing method. With a lower magnitude, the control signal can also avoid actuator saturation problems.

An optimal internal model proportional integral controller to improve pressure tracking profile of artificial ventilator

Mechanical ventilator (MV) is a breathing support medical equipment used during medical surgery or in an intensive care unit (ICU) for critical patients to reduce the breathing work of the patient under ventilation. In this work, a piston-driven mechanical ventilator is studied. Such types of ventilators are generally used as anaesthesia ventilators with volume-controlled modes. A modern ventilator can operate in different modes, such as volume control, pressure control, or both. Pressure-controlled mode may be better suited for some cases, such as patients undergoing laparoscopic surgery, as compared to volume-controlled mode because it may increase compliance during pneumoperitoneum, enhance oxygenation, and lower the stress response postoperatively. The pressure profile of a PCV must exactly track the pressure profile of a patient under ventilation to avoid ventilator-induced diaphragmatic dysfunction. Therefore, an optimal internal model control base proportional integral (IMC-PI) controller is proposed. The optimum parameter of the filter component of the IMC-PI controller is found by an enhanced class topper optimization (ECTO) algorithm. The performance of the proposed controller is analyzed in different scenarios and compared with existing results. Graphical Abstract Optimal internal model proportional integral controller for human respiratory ventilator.

NISHASH: A reasonable cost-effective mechanical ventilator for COVID affected patients in Bangladesh

COVID-19 has elapsed all over the world with massive losses which indicate the lack of availability of medical equipment during the pandemic such as a ventilator. This is exemplified by the densely populated country Bangladesh who unable to maintain COVID-affected people because of the ventilator. Due to the higher price, unavailability, and manufacturing defection, most medical are unable to purchase this ventilator which causes terrible death for a respiratory problem. Of these cases, this paper represents a way to escape this problem and proposed a mechanical ventilator named “NISHASH” which will help to anticipate COVID affected people and higher price of the ventilator. Through the electromechanical instruments, a prototype lightweight easily moveable where preciously it automatically controls with digital feedback system ventilator which fulfills oxygen flow based on patient requirement are developed with different selection mode. The aim was to design and develop inexpensively automated easy to build to minimize the extreme shortage of the ventilator in Bangladesh. In this model of a mechanical ventilator, the cost is less than $90 where components are available all over the world.

PVP1-The People's Ventilator Project: A fully open, low-cost, pressure-controlled ventilator research platform compatible with adult and pediatric uses

Mechanical ventilators are safety-critical devices that help patients breathe, commonly found in hospital intensive care units (ICUs)-yet, the high costs and proprietary nature of commercial ventilators inhibit their use as an educational and research platform. We present a fully open ventilator device-The People's Ventilator: PVP1-with complete hardware and software documentation including detailed build instructions and a DIY cost of $1,700 USD. We validate PVP1 against both key performance criteria specified in the U.S. Food and Drug Administration's Emergency Use Authorization for Ventilators, and in a pediatric context against a state-of-the-art commercial ventilator. Notably, PVP1 performs well over a wide range of test conditions and performance stability is demonstrated for a minimum of 75,000 breath cycles over three days with an adult mechanical test lung. As an open project, PVP1 can enable future educational, academic, and clinical developments in the ventilator space.

Safety Control Architecture for Ventricular Assist Devices

In patients with severe heart disease, the implantation of a ventricular assist device (VAD) may be necessary, especially in patients with an indication for heart transplantation. For this, the Institute Dante Pazzanese of Cardiology (IDPC) has developed an implantable centrifugal blood pump that will be able to help a diseased human heart to maintain physiological blood flow and pressure. This device will be used as a totally or partially implantable VAD. Therefore, performance assurance and correct specification of the VAD are important factors in achieving a safe interaction between the device and the patient’s behavior or condition. Even with reliable devices, some failures may occur if the pumping control does not keep up with changes in the patient’s behavior or condition. If the VAD control system has no fault tolerance and no system dynamic adaptation that occurs according to changes in the patient’s cardiovascular system, a number of limitations can be observed in the results and effectiveness of these devices, especially in patients with acute comorbidities. This work proposes the application of a mechatronic approach to this class of devices based on advanced control, instrumentation, and automation techniques to define a method to develop a hierarchical supervisory control system capable of dynamically, automatically, and safely VAD control. For this methodology, concepts based on Bayesian networks (BN) were used to diagnose the patient’s cardiovascular system conditions, Petri nets (PN) to generate the VAD control algorithm, and safety instrumented systems to ensure the safety of the VAD system.