Test platform for simulating patient conditions

Abstract

A test platform for simulating patient conditions. In accordance with methods, systems, platforms and modules, the controller of a ventilator, may be tested. Where the ventilator manages automated mechanical ventilation controllers' maintenance of peripheral oxygen saturation (SpO2) for a simulated patient, an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FiO2) and the peak inspiratory pressure ventilator settings of the ventilator is tested by a test platform controller. Where the ventilator manages end-tidal carbon dioxide (EtCO2) of a simulated patient, operation of the test platform controlled by the platform controller of the test platform in providing carbon dioxide generation, lung compliance (CL) and airway resistance (RAW) states while providing an EtCO2 level that is responsive to changes in tidal volume and respiratory rate changes of the patient is tested.

Description

Atty. Docket No. ISR 24-52.WOTEST PLATFORM FOR SIMULATING PATIENT CONDITIONSSTATEMENT OF GOVERNMENT INTEREST

[0001] The invention described herein may be manufactured, used and licensed by or for the United States Government.PRIORITY CLAIM

[0002] This application claims the benefit of provisional application serial number 63 / 685,864 filed August 22, 2024 and titled “Mechanical Ventilation Test Platform for Simulating Patent Lung Conditions” and provisional application serial number 63 / 685,862 filed August 22, 2024 and titled “Oxygen Partial Pressure Responsive Test Platform for Simulating Patient Lung Conditions” the entire contents of which are hereby incorporated by reference.BACKGROUND

[0003] Automated controllers have been developed for various tasks in a variety of different industries. Automation has been used in agriculture, the automotive industry, as well as the medical field. Automation in medicine has the potential to streamline medical procedures, reduce the cognitive burden on medical providers, lower the skill threshold for challenging procedures, and improve patient outcomes, and has been implemented in extracorporeal circulatory support systems, resuscitation during hemorrhagic shock, and assisted ventilation in intensive care units.

[0004] Fully automated mechanical ventilation has been an increasingly researched topic due to the COVID-19 pandemic, resulting in studies on controllers being developed and further integrated with patient monitoring. Even with this increased research on mechanical ventilation, respiratory failure occurrences following trauma-induced shock occur, even as other parameters, such as hemodynamics, may have appeared satisfactory to medical providers. Failure to manage appropriate ventilation during respiratory failure can rapidly become fatal, serving as a significant contributor to potentially preventable mortality in trauma emergencies. To increase the survival of patients requiring ventilation, automated ventilator controllers need to be able to manage the delivery of oxygen (O2), normalize alveolar ventilation in the lungs, increase lung volume, reduce the work required for breathing, and aid in carbon dioxide (CO2) removal, ensuring appropriate oxygenation and the removal of waste from the system. Automated ventilation controllers, in addition toAtty. Docket No. ISR 24-52.WO managing various aspects of patient respiration, will also need to include safeguards for the prevention of ventilator-induced lung injuries, which can be caused by both the over- and under-inflation of the lungs. This highlights the need for automated controllers to include precise ventilator strategies that minimize extending the lungs into the ranges where injury can occur, unless absolutely necessary for patient survival.

[0005] Designing controllers to manipulate physiological parameters is difficult due to the complexity of biological systems. This difficulty greatly increases with traumatic injury where the body’s natural “control” systems are rapidly changing and interacting with each other to mitigate the effects of trauma and increase the likelihood of survival. The design of human physiological controllers often relies on data from animal studies, such as those performed on swine. While swine are a recognized model for certain human physiology due to their similarities, there remain differences compared to humans that must be fully addressed in clinical trials prior to regulatory approval. Large amounts of data from animal studies are usually required for designing and debugging physiological controllers, with additional large animal studies needed to field test the controllers post-designing and debugging. This iterative process is costly as large animals require housing at an accredited research facility that must provide a highly regulated regimen of care, following strict standards for appropriate nourishment, general well-being, and veterinary services. This cost is compounded by the often-large number of animals required to statistically power these studies and the substantial time and personnel commitments required to complete studies.

[0006] To mitigate the downsides of extensive animal testing, hardware-in-loop (HIL) benchtops have been used for more streamlined testing. HIL testing enables the more robust evaluation of how controllers will perform when real -world equipment is in use — a feature lacking with strictly in silico models. With the rapidly accelerating advancement of computational capabilities that enable the use of larger and more sophisticated machine learning models, in silico ventilation patient simulators have been growing ever more robust. They have been able to predict individual patient changes in response to ventilator settings as well as gas / aerosol substance transport. However, these models still require extensive, highly specialized datasets from clinical trials for training. Some models enable communication with external sensors and devices, but the outputs of the physical devices do not directly impact the sensor readings. The ventilator settings or measurements of the output are commonly used to estimate a change in the physiological variables, which are then simulated and streamed to the sensors. Previous benchtop models for simulating physiological data have been developed for testing patient care during a coma, the testing of cerebrospinal fluid shunt systems, andAtty. Docket No. ISR 24-52.WO the testing of fluid resuscitation strategies for patients experiencing hemorrhagic shock. There have been several HIL systems previously developed for mechanical ventilation. Simulated lungs that mimic specific respiratory dynamics have been used for controllers that manage positive end-expiratory pressure (PEEP), and in silico simulations have been designed for modeling the interactions between mechanical ventilators and human lungs. There have also been complex lung simulators developed, like the xPULM simulator developed by Pasteka et al. Their system combines in silico, ex vivo, and mechanical components into one physical platform to capture flow and pressure changes at differing respiratory rates (RRs) and tidal volumes (VT). Another group developed a physical lung model with adjustable mechanical properties that was able to mimic a normal lung, an obstructive lung, and restrictive lung diseases. However, these models primarily focus on physically reproducing the pressure and volume mechanics of ventilation and — except for Laubscher et al. — still use in silico simulations for CO2 generation and / or end-tidal CO2 (EtCCh) waveforms. Additionally, none of these models account for O2 delivery, one of the primary purposes of mechanical ventilation.

[0007] Overall, automated ventilation control has the potential to simplify critical care in civilian and military environments. However, control systems require extensive testing for proper tuning, which can be cost-ineffective when relying solely on animal studies for troubleshooting. Although in-silico models have become exceedingly advanced in recent years, they still require large and highly specialized data to be properly tuned and are not able to operate with physical devices, leaving an important gap in the ability to determine the performance of a controller. Systems that include hardware control still often lack a direct link between the real-world outputs of the ventilator and the feedback signals that serve as the inputs to the ventilator controller.BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The accompanying drawings provide visual representations which will be used to describe various representative embodiments more fully and can be used by those skilled in the art to better understand the representative embodiments disclosed and their inherent advantages. In these drawings, like reference numerals identify corresponding or analogous elements.

[0009] FIG. 1 is a functional block diagram of a mechanical ventilator simulator module, in accordance with embodiments of the disclosure.Atty. Docket No. ISR 24-52.WO

[0010] FIG. 2 is a the mechanical ventilation test platform or module, in accordance with embodiments of the disclosure.

[0011] FIG. 3 is a cross-section of a flow reduction connector, in accordance with embodiments of the disclosure.

[0012] FIGs. 4A, 4B illustrate diagrams of a testing system or platform with a MechVent module and lung compliance, in accordance with embodiments of the disclosure.

[0013] FIGs. 5A, 5B illustrates variable airway resistance using an actuator, in accordance with embodiments of the disclosure.

[0014] FIG. 6 illustrates an example ventilator / ventilator platform, in accordance with embodiments of the disclosure.

[0015] FIGs. 7A, 7B illustrate closed-loop ventilation controller logic for CO2 removal, in accordance with embodiments of the disclosure.

[0016] FIGs. 8A, 8B and 8C illustrate the use of a MechVent system to simulate lung function and support ongoing ventilation, in accordance with embodiments of the disclosure.

[0017] FIGs. 9A, 9B illustrate an example ventilator / ventilator platform, in accordance with embodiments of the disclosure.

[0018] FIGs. 7A, 7B illustrate closed-loop ventilation controller logic for CO2 removal, in accordance with embodiments of the disclosure.

[0019] FIGs. 8A, 8B and 8C illustrate the use of a MechVent system to simulate lung function and support ongoing ventilation

[0020] FIGs. 9A, 9B illustrate testing results with the MechVent module, in accordance with embodiments of the disclosure.

[0021] FIGs. 10A, 10B illustrate individual trial runs for MechVent closed loop controller runs, in accordance with embodiments of the disclosure.

[0022] FIGs. 11 A, 11B, 11C and 11D illustrate EtCCh and MV relationships, in accordance with embodiments of the disclosure.

[0023] FIG. 12 is a block diagram of an example Oxy Vent setup, in accordance with embodiments of the disclosure.

[0024] FIG. 13 is a block diagram of a diagram of an Oxy Vent module / platform, in accordance with embodiments of the disclosure.

[0025] FIG. 14 is an example gas diffuser used within the pressure chamber or canister, in accordance with embodiments of the disclosure.

[0026] FIG. 15 is example pressure chamber / canister that may be used in the Oxy Vent setup, in accordance with embodiments of the disclosure.Atty. Docket No. ISR 24-52.WO

[0027] FIGs. 16A, 16B illustrate closed-loop ventilation controller logic for O2 delivery in a Oxy Vent module, in accordance with embodiments of the disclosure.

[0028] FIGs. 17A, 17B illustrate characterization of the Oxy Vent module FiO? functionality, in accordance with embodiments of the disclosure.

[0029] FIGs. 18A, 18B illustrate characterization of the Oxy Vent module PEEP functionality, in accordance with embodiments of the disclosure.

[0030] FIGs. 19 A, 19B illustrate evaluation of closed-loop controller logic for the Oxy Vent module, in accordance with embodiments of the disclosure.

[0031] FIG. 20 illustrates combination testing module that may be used in a combined test platform, in accordance with embodiments of the disclosure.

[0032] FIG. 21 illustrates a system diagram having a combination ventilation module that may be used in a combined test platform, in accordance with embodiments of the disclosure.

[0033] FIG. 22 is a flowchart that illustrates an example methodology of a combination ventilation platform / module, in accordance with embodiments of the disclosure.DETAILED DESCRIPTION

[0034] Automated ventilator controllers have the potential to simplify oxygen and carbon dioxide management for trauma. In the pre-hospital or military medicine environment, trauma care can be required for prolonged periods by personnel with limited ventilator management training. As such, there is a need for closed-loop control systems that can adapt ventilator management to a complex, ever-changing medical environment.

[0035] As described herein, a novel hardware-in-loop test platform for the independent troubleshooting and evaluation of oxygen and carbon dioxide automated ventilator management capabilities is presented. The oxygen management system provides an analogue blood oxygen signal that is responsive to the fraction of inspired oxygen and the peak inspiratory pressure ventilator settings. A tested oxygenation controller successfully reached the target oxygen saturation within 5 min. The carbon dioxide removal system integrates with commercial ventilator technology and mimics carbon dioxide generation, lung compliance, and airway resistance while providing an end-tidal carbon dioxide level that is responsive to changes in the tidal volume and respiratory rate settings. A test mechanical ventilator controller was able to regulate EtCCh regardless of the starting value within 10Atty. Docket No. ISR 24-52.WO min. This highlights the system’s functionality and demonstrates use of hardware-in-loop test platforms for evaluating closed-loop controller technologies.

[0036] Mortality rates due to lung trauma account for a significant portion of fatalities for civilian and military medicine. As shown by the COVID-19 pandemic, not only does resource availability have an impact on patient outcomes, but also medical providers. When combined with delayed casualty evacuation in possible future conflicts, this will further increase the complexity of casualty management. Thus, the development of closed-loop ventilation devices is necessary.

[0037] According to the DoD Trauma Registry, 25% of recent combat casualties required mechanical ventilation and managing a ventilated patient is cognitively demanding for medical providers. In Multi-Domain Operations, extended prolonged field care will require even longer management of patients, further increasing the cognitive load on medical personnel. Closed-loop automated approaches can simplify ventilator management and provide adequate respiratory needs to combat casualties.

[0038] The need for closed loop ventilator technology on the future battlefield and in other environments is understood. Hardware in loop (HIL) test platform can be used for testing closed loop ventilator devices to replicate the oxygen gas-liquid exchange physiology.

[0039] The hardware in loop test platform for mechanical venting testing may be comprised of two independently functioning models: (1) mechanical and (2) oxygen vent functions. Integration into hardware in loop (HIL) test platform for hemorrhage resuscitation using automated controllers is a beneficial usage.

[0040] The disclosure describes a system for the development of a simulator platform specifically built for testing of closed-loop ventilator controllers and devices. The disclosure describes a system for the development of a mechanical ventilator (MechVent herein) simulator platform specifically built for testing of closed-loop ventilator controllers. As described herein, the development of a test platform replicates the oxygen physiology and mechanics of a lung for use in testing closed-loop control ventilation algorithms.

[0041] As described here, novel oxygenation and CO2 ventilation HIL testing setups for the development and testing of automated ventilation controllers are presented. In summary, this work provided the following contributions:• the development and characterization of a HIL ventilation system for oxygenation• the development and characterization of a HIL system for CO2 ventilation using commercial ventilator technologyAtty. Docket No. ISR 24-52.WO• closed-loop ventilator controller evaluation using HIL systems and physiological scenarios to highlight the utility of the ventilator test platform

[0042] Materials and Methods

[0043] In establishing HIL platforms, two vital signs are targeted as corollaries to the primary purposes of mechanical ventilation mentioned above: (i) peripheral oxygen saturation (SpCh) for both O2 delivery and atelectasis prevention and (ii) EtCCh for the removal of carbon dioxide. An effective test platform must not only be able to simulate normal physiologically relevant behavior but must also allow some degree of independent manipulation of the signals to simulate “sick” patients to test the limits of a controller’s capabilities. To achieve this, the ventilation / CCh removal module or platform may be isolated from the O2 transport module, reducing the complex challenges that would be involved in producing a controllable O2-CO2 gas exchange medium. These two simulation modules are referenced as MechVent and OxyVent, respectively, herein. The following is a description of the design and system characterization testing for both the MechVent and OxyVent modules, ending with a description of the automated ventilator control logic and testing approaches. Alternately, a combination of the MechVent and Oxy Vent simulation modules is also contemplated and described herein. The terms ventilator module and ventilator platform may be used interchangeably herein.

[0044] Mechanical Vent (MechVent) Setup

[0045] To control EtCO2, mechanical ventilators modulate various settings including the PEEP, peak inspiratory pressure (PIP), and minute ventilation (MV) — which is itself the arithmetical product of VT and RR. Additional physiological characteristics that directly impact the dynamics of mechanical ventilation include airway resistance (RAW) and lung compliance (CL). The MechVent module may primarily generate EtCCh readings within a physiological range that responds to changes in the select ventilator settings mentioned above while also enabling the adjustment of simulated patient variables (namely RAW and CL). Development and testing were conducted using the MOVES® SLC™ ventilator platform (Thornhill Medical, Toronto, ON, Canada). This system was selected due to its ruggedized design for prehospital medicine and ongoing collaboration with the manufacturer, which allowed for the reading of FIG. 13 input data and the sending of ventilator commands in real time. This capability is important for tuning and characterizing the MechVent system, as well as testing the automated ventilator controller.Atty. Docket No. ISR 24-52.WO

[0046] Reference to FIG. 1 shows a functional block diagram of a mechanical ventilator simulator module 100. Beginning with CO2 generation block 110 and expansion tank block 120, carbon dioxide is sent into the system via a pressurized tank and the expansion tank 120 acts as an external volume to help stepdown the CO2 pressure. With regard to flow reduction and one-way valve block 130, to obtain a desired range of end-tidal CO2, a tubing connecter in which the output periodically decreases in size, effectively stepping down the flow rate of the incoming gas was designed (see FIG. 3 for example), was utilized. Additionally, a one way valve was implemented to prevent air from the ventilator 160 from flowing into the expansion tank 120.

[0047] With regard to variable airway resistance block 150, airway resistance is modulated into the system to simulate air way resistance. A particular example is shown in FIGs. 5A, 5B below.

[0048] This part of the simulator platform system 100 may be comprised of an expanding volume bellows 140 to mimic mechanical lung function. The bellows 140 is secured within a frame that is connected via two ports: Gas Out 144 to a mechanical ventilator 160, such as the MOVES® SLC™ ventilator platform, which contains an end-tidal CO2 sensors and Gas In inlet 142 to a 100% carbon dioxide supply 110, 120, 130. The tubing to the ventilator 160 contains an actuator "pinch" valve, for example, for modulating airway resistance in the system, represented by variable airway resistance 150. The bellows setup allows for modulating lung compliance by adjusting the force applied to the bellows, such as by flow reduction and one-way valve 130. For example, an electronic solenoid valve attached to the expansion tank 120 for regulating carbon dioxide into the system at a controlled rate may be provided. All of the components may be controlled under platform control by a platform controller like a microcontroller and computer programming (shown in FIG. 2) using MATLAB, for example.

[0049] Development of a ventilator (MechVent) simulator platform as disclosed herein is specially built for testing of ventilator closed-loop controllers. The MechVent platform tests a ventilation controller’s proficiency in managing a simulated patient’s EtCCh by adjusting RR and VT at different CL and RAW states. The platform incorporates elements to simulate physiological RAW, CL , and EtCCh. The system may use a bellows as a lung analogue with a one liter capacity, for example. The patient simulator is then connected to the MOVES® SLC™ platform to be ventilated with ambient air while EtCO2 values are produced by adding calculated amounts of compressed CO2 to each expiration. CL was simulated using a dynamic weight on the bellows, and RAW was modulated using an actuatorAtty. Docket No. ISR 24-52.WO that pinches tubing in series between the ventilator and bellows. Each can be modified in real-time over a range of values.

[0050] Features of the system in accordance with certain embodiments include:

[0051] 1. Compatibility with the MOVES® SLC™ or other ventilator platform.

[0052] 2. Ability to modulate EtCO? values as measured by the ventilator

[0053] 3. Demonstrate that EtCO? changes in response to RR and VT as would be expected in a normal patient.

[0054] 4. Functionality at different CL and RAW states.

[0055] Referring now to FIG. 2, a diagram of a mechanical ventilator (MechVent) hardware-in-loop HIL) test module 200 for evaluation of CO2 removal is shown. CO2 gas flows from the supply tank 205 to the expansion tank 210 and bellows 220. Lung compliance and airway resistance can be adjusted in the hardware-in-loop system 200 via airway resistance control 260. The ventilator 230 measures EtCCh and enables the tidal volume and respiratory rate settings to be set under platform control via computer control by computer 240 and microcontroller 250 (platform controller).

[0056] More particularly, the mechanical ventilation test platform or module (MechVent system), as shown in FIG. 2, includes a cylindrical bellows 210 (McMaster-Carr, Elmhurst, IL, USA) with cuff ends that could be sealed on one end using a cuff insert and secured to the manifold that is connected to the ventilator on the other. The size of the bellows is chosen to operate within a relevant VT range of 200-1200 mL without overly stressing the bellows’ material. Interface components — including the central three-way hub, hose fittings, a custom choke, and parts for the RAW and CL adjustments — may be modeled using computer-aided design (CAD) software and either 3D printed or assembled from lasercut acrylic parts. A 5 in (127 mm) diameter acrylic cylinder was used to house the bellows, and a laser-cut lid was fixed to the cuff insert on the upper end of the bellows. The combination of the cylinder housing and lid served to ensure the even and unidirectional expansion of the bellows during respiration and provided a support platform for the CL adjustment compartment 222. Lung compliance was manually set by placing standardized weights in the CL compartment. As CL changes are more associated with chronic conditions and are not expected to rapidly change during trauma, setting this simulated patient characteristic once at the beginning of a test was considered acceptable; this was in comparison to an automated real-time adjustment, which could also be done. The lower end of the bellows was attached to the central three-way hub, which was seated within the base ofAtty. Docket No. ISR 24-52.WO the housing. The central hub contained three ports: the main port that attached to the bellows, a supply port 224 that was connected to the CO2 supply, and the final port226 that connected to the ventilator.

[0057] As an analogue for CO2 generation, a compressed gas cylinder 205 (Airgas, Radnor, PA, USA) supplies medical -grade CO2, and components are connected using 14 in (~6.4 mm) plastic tubing, as an example. A two-stage regulator reduces the pressure to around 10 psi (-517 mmHg) and was connected to a 15 gal (-57-L) expansion tank (McMaster-Carr, Elmhurst, IL, USA) to stabilize the supply pressure. The initial MechVent design employed continuous flow and a custom-designed choke, which was connected to an adapter fitting that then connected to the supply port 224 of the central hub. The custom choke was later replaced by an automated solenoid valve 270, as shown in the diagram, enabling variable CO2 generation based on how rapidly the valve opened and closed. The final port 226 of the hub was connected to the ventilator 230 using3 / 4 in (-19 mm) plastic tubing and a fitting that connected to the standardized vent hose. The RAW control was positioned along the3 / 4 in (-19 mm) tubing between the hub and the vent hose connection and comprised a 12 V linear actuator, a platform controller such as microcontroller 250 (Arduino®, Monza, Italy), and two relays configured as an H-bridge circuit to control polarity. This setup enabled the bi-directional control of the actuator’s extension, allowing the tubing to be pinched at various levels to simulate different airway resistances. The RAW system was constrained to three positions: Open, Partial (occluding the tubing by approximately half), and Full (denoting full extension of the actuator, while still allowing minimal airflow). Intermediate positions were explored and found to have minimal to no effect on system responsiveness beyond what was already obtained by these three positions.

[0058] Further characterization parameters may be used. For example, to collect characterization data for MechVent, functional simulations were run as follows:

[0059] 1. Each scenario was 4-6 minutes in duration.

[0060] 2. One simulation scenario began with a RR of 15 bpm, which was increased to 25 bpm after 2 min, then reduced to 6 bpm for the final 2 min.

[0061] 3 A second set of scenarios involved getting a baseline CL value, then periodically decreasing the CL every 2-3 min to see the effect on VT.

[0062] 4. Additional scenarios were constructed by varying multiple variables at once, such as CL, RAW, and RR to measure the effect on VT.Atty. Docket No. ISR 24-52.WO

[0063] 5. A final set of scenarios involved RAW states of fully open, half constricted, and fully constricted also with constant RR (15 bpm) and Control Pressure (23 crnFEO) values.

[0064] CO2 Generation 205 & Expansion Tank 210: Carbon Dioxide is sent into the system via a pressurized tank 205 and the expansion tank 210 acts as an external volume to help stepdown the CO2 pressure.

[0065] Flow Reduction & One Way Valve

[0066] Referring to FIG. 3, a cross-section of a flow reduction connector 300 is shown. It was found that to obtain the desired 35-45mmHg range of end-tidal CO2, the flow of gas must be reduced further. This was accomplished by designing a tubing connecter 300 where the output periodically decreases in size, effectively stepping down the flow rate of the incoming gas. Additionally, a one way valve was implemented to prevent air from the ventilator 230 from flowing into the expansion tank 210.

[0067] Referring to FIGs. 4A and 4B, diagrams of a main system with MechVent module and lung compliance is illustrated. The MechVent utilizes a flexible bellows to simulate the inspiratory cycle 420 and expiratory cycle 410 of the respiratory system 400. The bellows is sealed to make sure that it can inflate properly while maintaining a pressure / volume set by the ventilator. An "inlet" and "outlet" is also attached to the bottom of the system so that CO2 and the ambient air from the ventilator can mix into the bellow 430. The resulting mixture is then fed back into the ventilator.

[0068] On top of the bellow 430 lies an enclosure 440 that houses the dynamic weight 445 that can modulate the lung compliance on the system 400.

[0069] Referring now to FIGs. 5 A, 5B, variable airway resistance is further illustrated. To modulate airway resistance into the system, part of the tubing in the system is fed through a frame, designed to fit a linear actuator 500. The actuator extends to different lengths, and eventually pinches the tubing in order to simulate air way resistance, as shown in Figs. 5 A, 5B. An open position 510 of linear actuator 500 is illustrated in FIG. 5 A while a fully occluded (closed) position 520 of linear actuator 500 is shown in FIG. 5B.

[0070] FIG. 6 illustrates an example ventilator / ventilator platform 600. As an example, the ventilator in the drawing used in the system is the MOVES® SLC™ ventilator 610, due to its ability to be controlled via external software. Using TCP communication, variables on the ventilator are able to be adjusted remotely, and closed loop controllers can beAtty. Docket No. ISR 24-52.WO tested on the system. Interfaces 610 of a pad, tablet, computer, Personal computer (PC), server, or other communications interface, facilitates and supports such communications.

[0071] With additive manufacturing, various iterations of the MechVent were developed, leading to a design with a compartment for the bellows and an acrylic enclosure to limit the bellows’ expansion to one direction. The MechVent system was able to realistically simulate lung function and support ongoing ventilation from the MOVES® SLC™ platform with controllable breaths within ±3 mmHg EtCCh readings ranging from 30 to 48 mmHg. Mimicked CL and RAW levels were respectively controllable from 30-75 mL / cmH20 and 2-3 cmH2O / L / s.

[0072] The MechVent platform was successfully constructed and integrated with the MOVES® SLC™ ventilator as described above; however the test platform may be used with this or other types of ventilators. The system is responsive to VT and RR and can modulate EtCO2, RAW, and CL. The platform may be for developing ventilator controllers. Further, this MechVent platform may be integrated into a larger testbed with hemorrhage and anesthesia modules that will allow for simultaneous testing of multiple controller technologies.

[0073] MechVent Module Characterization / Results

[0074] A comprehensive series of tests was developed to characterize the system’s response; these focused on variations in MV, RAW, and CL. The calculated CL values and the corresponding expiratory tidal volume (VTE) were recorded using various loads in the CL compartment ranging from 200 to 1000 g. The calculated RAW values and corresponding VTE and inspiratory tidal volume (VTI) were also recorded at each RAW setting. A baseline CL load of 500 g and an ‘Open’ RAW level were used for all EtCO2 control testing. The system performance was evaluated across RRs ranging from 6 to 30 breaths per minute (BPM), and each test ran for 10 min, generating 600 data points per scenario. Pearson’s correlation values between the controller parameters and responses were calculated, as were the statistical significances for each correlation. Although the ventilator did not support Continuous Mandatory Ventilation (CMV), the system was tested using Intermittent Mandatory Ventilation (IMV) modes. This resulted in minor discrepancies between the VTI and VTE, but the testing protocol still facilitated the collection of critical data, enabling the simulation of real-world ventilatory conditions and contributing to system refinement.

[0075] In addition, a series of tests were conducted on the MechVent module to confirm its usability for evaluating automated ventilation controllers. A decision-table-based controller following a modified version of the Acute Respiratory Distress Syndrome NetworkAtty. Docket No. ISR 24-52.WO(ARDSNet) protocol (Figure 2A)

[0035] was used to bring the system within the target range of 30-40 mmHg. Test runs were conducted at 60 s sampling rates and included scenarios with either low (~20 mmHg) or high (~60 mmHg) starting EtCO? values. To achieve the different baseline EtCCh levels while holding the initial settings of the system constant (7 L / min, MV and 5 cm H2O, PEEP), a solenoid valve was used in place of the custom choke, with the duration of valve opening controlling the CO2 supply (Figure 2B). The simulated patient’s weight was defined as 70 kg in order to provide sufficient VT overhead for the upper MV range of the ARDSNet protocol. As mentioned above, MV is the product of RR and VT, either of which can be changed independently to produce the same net change in MV.

[0076] Referring to FIGs. 7A, 7B, closed-loop ventilation controller logic for CO2 removal is illustrated. In flowchart 700 of FIG. 7A, the functional controller logic flowchart is shown, followed by decision table steps 750 of the VT and RR. Arrows in the drawing denote the direction for increases and decreases by controller logic and grey shaded values represent the starting point for controller logic in this example embodiment. FIG. 7B provides a summary of test scenarios used for evaluating closed-loop ventilation controller logic in this example.

[0077] The MechVent system was able to realistically simulate lung function and support ongoing ventilation from the MOVES® SLC™ platform with controllable breaths within ±3 mmHg EtCO2 readings ranging from 30 to 48 mmHg. Mimicked CL and RAW levels were respectively controllable from 14-60 mL / cmH20 and 2-3 cmH2O / L / s, as shown in Figures 8a, 8B, and 8C. These drawings provide a summary of MechVent Characterization Results. Characterization of (FIG. 8A) EtCO2 & RR trends, (FIG. 8B) CL impact on VTE, (FIG. 8C) Airway resistance impact on VTE & VTI is shown.

[0078] Under normal conditions, the MechVent module was able to effectively reproduce EtCCh readings in the 35-45 mmHg range when RR and VT were held in normal ranges (10 BPM and 500 mL, respectively), and the EtCCh output of the system correlated with changes in either RR or VT, following normal physiology (FIG. 8A). For the patient variability features, both VTE and VTI were similarly decreased by higher RAW, with Open, Partial, and Full resulting in VTE|VTI values of 963.31983.0 mL, 621 ,4|607.4 mL, and 360.4|360.8 mL, respectively, and the range of calculated RAW levels was 2-3 cm H2O / L / S (FIG. 8B). The lung compliance loads had a near-linear relationship with the corresponding lung compliance values, as measured by the ventilator, with 200 g producing a reading of ~56 mL / cm H2O and 1000 g producing a reading of -14.5 mL / cm H2O (FIG. 8C). FIG. 8AAtty. Docket No. ISR 24-52.WO provides an evaluation of MechVent’s ability to successfully replicate an inverse relationship between the RR and EtCCh. FIG. 8B illustrates average expiratory (VTE) and inspiratory (VTI) tidal volumes at three example RAW settings. FIG. 8C demonstrates average VTE and CL setting in this embodiment.

[0079] Meeh Vent Testing

[0080] To evaluate the closed-loop controller functionality of the MechVent module, tests at different starting EtCCh settings by using the decision table logic shown in FIGs. 7A, 7B for the controller were conducted. A duty cycle of 3.3% for the solenoid valve supplying CO2 was found to result in generally stable EtCCh readings of ~20 mmHg and a setting of 6% produced baseline readings of ~40 mmHg. A duty cycle of 7.3% produced high EtCCh readings, stabilizing at ~60 mmHg. The controller was initialized at the middle of the ARDSNet table with a VT of 550 mL (8 mL / kg for 70 kg patient) and RR of 12 BPM, but was free to make adjustments immediately at the beginning of the test and then once every 60 s afterwards. Data were averaged across the three test runs, as shown in FIGs. 9A, 9B, which provide a summary of closed-loop testing results with the MechVent module. FIG. 9A illustrates MV and EtCCh for a high starting EtCCh at 60 mmHg while FIG. 9B illustrates minute ventilation and EtCCh for a low starting EtCCh at 20 mmHg.

[0081] Further, FIGs. 10A and 10B illustrate individual trial runs for each MechVent closed loop controller runs. FIG. 10A shows MV and EtCCh for each replicate, as partitioned by a red and green dotted line. Green shaded region indicates the target EtCCh range. FIG. 10B shows VT set and measured for each individual run. Accordingly, plots of EtCCh and MV against time across all trials for the low and high starting EtCCh scenarios are shown in FIG. 10A. Adjustments to RR and VT were shown to reliably control the system’s EtCCh, raising it from ~20 to > 35 mmHg within 5 min, and lowering it from ~55 to < 45 mmHg in ~4 min. It should be noted that there are two potential values for VT that are relevant and could be used to calculate MV. One is the ventilator’s setting for VT (VTset), while the other is the real-time, physical measurement of VT during operation (VrMeasured). Large discrepancies between these values can indicate an issue with the system, helping to identify an early leak in the system, which was repaired, and Vrset vs. VrMeasured plots were regularly generated as a quality measure for all tests (FIG. 10B). All MV values were calculated using VrMeasured-Atty. Docket No. ISR 24-52.WO

[0082] FIGs. 11 A-l ID illustrate EtCCh and MV relationships in low and high tests. FIG. 11 A illustrates a scatter plot with an inverse trend between MV and EtCCh in low EtCCh tests. FIG. 1 IB shows the effects of VT on EtCCh in low EtCCh tests. FIG. 11C illustrates the relationship between MV and EtCCh in high EtCCh tests. FIG. 1 ID shows the effects of RR changes on EtCCh in high EtCCh tests. Pearson’s correlation (R) values are shown for each, along with the statistical significance for each data trend. More particularly, the scatter plots of tests starting at an EtCCh level of 20 mmHg are shown in FIG. 11 A, which highlights the inverse relationship (inverse trend) between MV and EtCCh when changing VT and RR. Runs starting from this low position showed little to no correlation between EtCCh and RR, as the controller was primarily updating VT values to the system (FIG. 1 IB). The high EtCCh tests revealed the same inverse relationship with MV, as shown with the low EtCCh tests, showcasing the ability of the system to modulate EtCCh down to a healthy range (FIG. 11C). The main factor in the modulation of MV for the high tests was RR, which is shown by FIG. 1 ID.

[0083] In view of the foregoing, the importance of closed loop ventilator technology in multi-domain operations on the future battlefield or other environment can be readily understood, as can the use of hardware in loop (HIL) test platforms for testing mechanical closed loop ventilator. Key design criteria and engineering approaches have been taken to accurately mimic mechanical ventilator functions in a hardware in loop test platform.

[0084] Oxygen Ventilation (Oxy Vent) Module

[0085] The second independently functional model for hardware in loop (HIL) test platform for mechanical venting testing may be an oxygen ventilator function.

[0086] This part of the simulator platform system may use a closed canister partially filled with water whose dissolved oxygen is measured by a dissolved oxygen (DO) probe (Atlas Scientific) and may reside on the same platform as the MechVent setup. The container contains an inlet and outlet port. The inlet port is supplied by fractional air and nitrogen whose rates are controlled by electronic solenoid valves. The outlet port is monitored by air pressure sensor and regulated by an additional electronic solenoid valve. In doing so, the system can modulate its DO levels, analogous to SpO2, which can be altered by adjusting the fractional oxygen supplied or canister pressure, analogous to ventilator control parameters. All of the components are controlled by a platform controller, such as a microcontroller and computer programming using MATLAB, for example.

[0087] When a patient is being mechanically ventilated, there are several settings that may be adjusted to maintain healthy SpCh levels. Two such settings are the fraction ofAtty. Docket No. ISR 24-52.WO inspired oxygen (FiO?), based on the alveolar gas equation, and PEEP. Thus, the Oxy Vent module needed to provide an analogue for SpO? within a physiologically relevant range, as well as the ability to manipulate said SpO? reading via changes in the provided analogues for FiO? and PEEP.

[0088] A test platform for testing automated mechanical ventilation controllers’ maintenance of SpO? by adjusting the FiO? and PEEP settings is provided. The platform simulates SpO? analogously through DO level in water measurement in a closed container. DO is controlled by bubbling air and nitrogen (N?) gas through the water as an analogue for FiO?. The pressure in the container is an analogue for PEEP to modify gas solubility. The range of DO is then scaled to a relevant SpO? range. The controller outputs for FiO? and PEEP can then be transformed to the gas ratio and container (canister) pressure domains, respectively.

[0089] As described herein, this Oxy Vent part of the system may use a closed canister partially filled with water whose dissolved oxygen is measured by DO sensor (Atlas Scientific). The container contains an inlet and outlet port. The inlet port is supplied by fractional air and nitrogen whose rates are controlled by electronic solenoid valves. The outlet port is monitored by air pressure sensor and regulated by an additional electronic solenoid valve. In doing so, the system can modulate its DO levels, analogous to SpO?, which can be altered by adjusting the fractional oxygen supplied or canister pressure, analogous to ventilator control parameters. All of the components are controlled by a platform controller such as a microcontroller and computer programming using MATLAB, for example.

[0090] The construction of the Oxy Vent platform 1200 consists mainly of a closed, pressurized canister with solenoid valves to allow control of intake and outtake of gas as shown in FIG. 12. FIG. 12 is a block diagram 1200 of an example Oxy Vent setup with DO probe and gas flow into the chamber shown for the device. The device is programmable under a platform controller via a microcontroller (such as an Arduino), for example. To ensure a consistent supply 1210 of pressurized gas, expansion tanks 1220, 1222 are placed in line between the gas tanks 1212 (O2), 1214 (N2) and the pressurized canister 1240. Controll is provided by a microcontroller 1250 such as Arduinos, for example, that controls the opening and closing of solenoid valves 1230 to ensure a consistent target pressure. Relief valve 1270 may be used in that regard as needed. A DO probe 1260 is coupled to canister 1240 as shown.

[0091] Referring now to FIG. 13, a diagram of an Oxy Vent module / platform 1300 is illustrated. Compressed nitrogen (N2) and air flow from the supply tanks 1312, 1314 toAtty. Docket No. ISR 24-52.WO expansion tanks 1322, 1324 and then to the pressurize canister 1340 through solenoid valves 1332, 1334 is controlled by a platform controller such as a microcontroller 1350, coupled to control computer 1370. DO level in the pressure canister 1340 is measured, as is the canister pressure used to regulate the outflow through an additional solenoid valve 1360 coupled to pressure sensor 1362.

[0092] In accordance with an example embodiment, to simulate SpO2, the Oxy Vent module incorporates the usage of a DO probe (Atlas Scientific, Long Island City, NY, USA) to measure the DO content in approximately 1200 mL of plain tap water contained in a closed, rigid cylindrical canister 1340, as shown in FIG. 13. The DO level within the water was controlled by bubbling a mixture of Breathing Grade Air and Ultra-High-Purity Grade Nitrogen (N2) into the water, and the ratio of this mixture could then be treated as an analogue for FiO2. Compressed gas cylinders (Airgas, Radnor, PA, USA) 1311, 1314 are used to supply the gases to the system using % in (~6.4 mm) plastic tubing and barbed fittings to connect each major component. Similarly to the MechVent module, two-stage regulators may be used to step down the supply pressure from each cylinder to 15 psi (-776 mmHg), and 15 gal (-57-L) expansion tanks (McMaster-Carr, Elmhurst, IL, USA) were used to improve the stability of the supplied pressure. The outlets of each of the two expansion tanks 1322, 1324 were connected to solenoid valves (US Solid, Cleveland, OH, USA) 1332, 1334, which enabled independent control over the flow of each gas. Following the solenoid valves, the two supply lines 1333, 1334, respectively, were merged using a T-fitting into a single line 1336 that was then connected to the inlet 1342 of the rigid canister 1340, as shown in FIG. 13. Since the solenoid valves 1332, 1334 function in a binary fashion, i.e., being either fully open or fully closed, further control over the composition of the supplied gas mixture is enabled by utilizing open-closed pulsations at various duty cycles. A three duty cycles defined as Full, open 100% of the time; Partial, open 50% of the time; and Off, closed may be used.

[0093] Because the Oxy Vent module performance relies on the absorption of O2 into the water, multiple steps were taken to improve consistency and reliability in the rapidity and homogeneity of said absorption. First, a gas diffuser such as a diffusion ring is connected to the gas inlet and positioned at the bottom of the canister. This diffusion ring distributes the gas from the supply line out around the perimeter of the canister through a series of holes, rather than a single centralized point. The canister may also be placed on a magnetic stir plate (Thermo Scientific, Waltham, MA, USA) paired with a crosshead stir bar, which was set in the center of this diffusion ring and spun at 200 rpm. Finally, a secondary diffusion plate mayAtty. Docket No. ISR 24-52.WO be integrated overtop the diffusion ring and stir bar. This plate spanned the entire cross section above the stir bar and included an array of 11 holes with spacings of approximately 23 mm. This prevents or greatly reduces the formation of a vortex in the canister from the stir bar and helped to compensate for any higher concentration of gas coming from the diffusion ring holes closer to the supply line connection. FIG. 14 shows a gas diffuser is used within the pressure chamber or canister 1240 to ensure adequate gas mixing. FIG. 15 shows an example pressure chamber / canister 1240 of the type that may be used in the Oxy Vent setup.

[0094] Even with this design, however, there remained a variable which impacted O2 absorption — system pressure. An outlet port alone would eliminate any pressure build up, but by connecting this outlet port to a pressure inducer followed by a third solenoid valve, this variable could be controlled. By taking advantage of the differences in O2 solubility in water at differing pressures, an analogue for PEEP could then be introduced by regulating the pressure within the canister. The regulation of this pressure was controlled via a platform controller such as a microcontroller (Arduino®, Monza, Italy), whose behavior could be modified according to the needs of the experiment. With this implementation, the internal pressure of the system could be permitted to increase / decrease at any point, thus raising / lowering the O2 solubility in real time. Although temperature also affects O2 solubility, the ease and speed of pressure control combined with the naturally static nature of the system’s temperature made pressure the preferred variable to use. These two controls provided ample capacity to adjust the DO levels in response to the ventilator settings, allowing robust testing capabilities for automated ventilator controllers.

[0095] Oxy Vent Module Characterization / Results

[0096] The system’s behavior was characterized by using a series of baseline and oxygenation procedures. Of particular interest was how the DO saturation ceiling and DO absorption rate were affected by the supplied gas mixture and canister pressure. Each experimental run started by deoxygenating the water via a nitrogen flush, followed by bubbling various air-nitrogen ratios whilst simultaneously regulating the pressure within the canister. The change in DO with time was recorded and analyzed to develop characteristic functions of the system’s response. Each test ran for a period of 5 min to allow sufficient time for the system DO to reach a reasonably steady state. Bubbled gas mixtures were tested in triplicate at a gage canister pressure of approximately 5 psi (-250 mmHg). To observe changes in the DO saturation and responsiveness with a dynamic pressure range, variable pressure tests were conducted with a selection of air-nitrogen ratios that began at an initialAtty. Docket No. ISR 24-52.WO gage canister pressure of 0 psi, increasing to 5 psi, and then finally to 10 psi. The canister pressure was held at each step for 5 min, with tests run in triplicate.

[0097] To further test the Oxy Vent module, a preliminary decision-table-based closed-loop control logic was conceived for managing the O2 ventilator settings. FIGs. 16A, 16B illustrate closed-loop ventilation controller logic for O2 delivery in a Oxy Vent module. FIG. 16A provides a flowchart 1600 of decision table functionality with an ARDSnet controller logic, for example, for PEEP and FiO2. Arrows denote direction for increases and decreases by controller logic and grey shaded values represent the starting point for controller logic. FIG. 16B provides a summary of test scenarios used for evaluating closed-loop ventilation controller logic.

[0098]

[0099] More specifically, automated logic was based on the ARDSNet protocol developed by the NIH NHLBI ARDS Clinical Network, which has been used for automating ventilator function in other studies, FIG. 16 A. The lower PEEP and higher FiCh logic was used but additional rules were added to further prioritize FiCE adjustments when SpCh fell below a certain threshold. Logic started on the first step in the ARDSNet table, and, if SpCh ever drifted below 90%, immediate setting adjustments would be performed to increase FiCE to 100% and then continue following PEEP adjustments based on the ARDSNet decision table. Once SpO2 was above 96%, FiO2 would decrease according to the ARDSnet decision table. Two sampling rates for the oxygen management logic were evaluated at 5 s and 60 s (FIG. 16B). The thresholds of a maximum value such as 100% for FiO2 and less than 90%, 90 to 96% or other ranges, and greater than 96% for SpO2 can be other values or changed without departing from the scope of the disclosure. The Oxy Vent module was characterized regarding its DO responsiveness to FiO2 and PEEP levels. There was minimal variance in the DO during the initialization of each run between the six air-nitrogen ratios.

[0100] FIGs. 17A, 17B illustrate characterization of the Oxy Vent module FiO2 functionality in accordance with an example implementation. Average trends for six airnitrogen ratios (n = 3 each) and their dissolved oxygen (DO, ppm) values over the course of five minutes. In FIG. 17 A, DO versus time relations for each air-nitrogen ratio not normalized to the starting value is shown; shaded regions denote standard deviation. In FIG. 17B each air-nitrogen ratio is normalized to their minimum value to better illustrate the differences in DO values over the five-minute period.Atty. Docket No. ISR 24-52.WO

[0101] The system had a range of DO between 2.63 (air-nitrogen ratio of Partial air and N2 Off) and 8.95 (air-nitrogen ratio of Full air and N2 Off) ppm, with a standard deviation of 0.181 and 1.04, respectively. The ability of the system to achieve both differing O2 absorption rates and O2 saturation levels using varying ratios of air-nitrogen is demonstrated in FIGs. 17A, 17B. In addition, FIGs. 17A, 17B demonstrate how the DO trends compare to each air-nitrogen ratio when normalized by the minimum value of each respective ratio. DO values for each air-nitrogen ratio, with specific minimum, maximum, and mean values of DO and standard deviations for each respective ratio, are shown in Table 1, which provides a summary of the minimum, maximum and mean values of DO (ppm) and the respective minimum and maximum standard deviation values.

[0102] Table 1Partial Air / Full N2 Partial Air / Partial N2 Full Air / Full N2DO Std Dev. DO Std Dev. DO Std Dev.Min 2.63 0.181 2.69 0.148 2.73 0.0153Max 5.30 0.414 5.90 0.392 6.69 0.702Full Air / Partial N2 Partial Air / N2 Off Full Air / N2 OffDO Std Dev. DO Std Dev. DO Std Dev.Min 2.70 0.125 2.80 0.139 2.63 0.643Max 6.95 0.589 8.17 0.990 8.95 1.04

[0103] FIGs. 18 A, 18B illustrates characterization of the Oxy Vent module PEEP functionality. Average results for three air-nitrogen ratios (n = 3 each) and their dissolved oxygen (DO, ppm) values across three different pressure steps (Pcan) held for five minutes. FIG. 18A illustrates DO values over time without normalization and FIG. 18B illustrates DO values over time with normalization to their minimum values; shaded regions denote the standard deviation for each air-nitrogen ratio and the three pressure steps labeled above the horizontal axis on each plot.

[0104] The Oxy Vent test platform was successfully fabricated to withstand pressure up to 775 mmHg. The range of DO achieved was -2-14 mgO2 / L within a pressure range of 0- 520 mmHg. Performance is compared to anticipated physiological responsiveness from estimated gas-liquid interface coefficients.Atty. Docket No. ISR 24-52.WO

[0105] A variety of Oxygen to Nitrogen ratios were tested, achieving different results in peak saturation levels. Creating a consistent waveform can be accomplished by bubbling alternating ratios of Oxygen to Nitrogen.

[0106] More particularly with regard to an example embodiment, adding a modification to PEEP, there was minimal variation in the DO values between the three airnitrogen ratios during the initialization of the runs. Throughout the three varying canister pressures of 0, 5, and 10 psi, the system had a range of DO values between 2.39 ± 0.0873 and 9.72 ± 0.604 ppm, as shown in FIGs. 18A, 18B. The pressures were each held for five minutes until the system reached steady-state DO values. At a canister pressure of 0 psi, the steady-state DO was 5.61, 6.72, and 7.24 ppm for air-nitrogen ratios of Partial / Partial, Partial / Off, and Full / Full, respectively. When the canister pressure was increased to 5 psi, the steady-state DO reached values of 6.42, 7.98, and 7.98 ppm for the air-nitrogen ratios previously mentioned. Finally, for the same previously listed air-nitrogen ratios, the steadystate DO values reached 7.26, 9.72, and 9.34 ppm at a canister pressure of 10 psi. In addition to the steady-state (maximum) DO values, the minimum DO values and standard deviation values at each respective pressure step are displayed in Table 2, which provides a summary of minimum and maximum values of DO and the respective minimum and maximum standard deviation values at the varying pressure steps of 0, 5, and 10 psi.

[0107] Table 2Partial Air / Partial N2 Partial Air / Ni Off Full Air / Full N20 psi 5 psi 10 psi 0 psi 5 psi 10 psi 0 psi 5 psi 10 psiMin 2.43 5.57 6.38 2.55 6.72 7.98 2.39 7.22 7.97DO Max 5.61 6.42 7.26 6.72 7.98 9.72 7.24 7.98 9.34Min 0.271 0.205 0.302 0.246 0.282 0.372 0.0873 0.0451 0.0404Std Dev. Max 0.650 0.360 1.03 0.493 0.426 0.604 0.193 0.154 0.344

[0108] This range of DO values was fit against a range of SpO2values (80 to 100%) the system needed to mimic, resulting in the following calibration Equation (1) for DO to SpO2:SpO2= 100 - 4 x (7 - DO) (1)

[0109] Oxy Vent TestingAtty. Docket No. ISR 24-52.WO

[0110] After the conversion of DO to SpO2values was implemented, the Oxy Vent module was tested with a closed-loop controller using the oxygen management logic described earlier (FIGs. 16A, 16B). Three replicate runs at two sampling rates — 5 s and 60 s — were averaged across each run and the resulting data are shown in FIG. 19 A, 19B, which illustrate evaluation of closed-loop controller logic with the Oxy Vent module. The average controller performance for maintaining SpO2across five-minute testing scenarios using 5 s (FIG. 19 A) and 60 s (FIG. 19B) sampling rate controller configurations (n = 3 each). Controllers adjusted FiO2and PEEP / Pcanto reach the target SpO2in each respective run. SpO2and FiO2are plotted on the left axis while Pcanand PEEP are shown on the right axis. The shaded region for each variable denotes the standard deviation.

[0111] More particularly with regard to an example embodiment, the controller configuration in FIG. 19A updated every 5 s and reached the target SpO2range by keeping FiO2constant at 100% while adjusting PEEP to increase SpO2. The controller in FIG. 19B updated every 60 s and reached the target SpO2range by keeping PEEP constant at 5 cm H2O while adjusting FiO2from 100% to a final target of 90% due to overshooting the target SpO2. Overall, both controller configurations successfully adjusted either FiO2or PEEP to reach the target SpO2programmed in the controller logic.

[0112] Overall, the Oxy Vent test platform for evaluating ventilators was successfully constructed and resulted in a PEEP and FiO2responsive system. The platform may be integrated with a larger platform for simulating ventilation and hemorrhage control and resuscitation. This system will enable testing various closed-loop controllers and their interactions during combat casualty care and other types of care.

[0113] Combination Meeh Vent / Oxy Vent ventilator module / platform

[0114] The MechVent system was able to generate EtCO2values that are considered normal for healthy patients while being provided ventilation from the MOVES® SLC™ or other ventilation platform. The RAW and CL features of the system were effective and capable of reproducing the RAW and CL values calculated by the ventilator and that fall within physiologically normal ranges. In addition, the effects of different RAW and CL values on the dynamics of ventilation also matched what is considered normal. Specifically, increased RAW correlated to a decrease in VT, while a decrease in CL (lungs are stiffer) also correlated with a reduced VT. Important target variable, EtCO2, could be successfully raised or lowered within the MechVent module via adjustments to MV, to adjust EtCO2readings. Finally, the MechVent system’s ability to generate values outside the optimal “healthy” range isAtty. Docket No. ISR 24-52.WO demonstrated. A representative, decision-table-driven controller modeled after recognized ventilator protocols was used to successfully bring the system back within the optimal range.

[0115] The characterization of the Oxy Vent module showed that the system could produce a range of DO values that could easily be scaled to fit a relevant range of SpO? values. It was demonstrated how the DO value could be changed by adjusting the Air:N2 ratio of the supplied gas mixture or by changing Pcan. A few notable effects from these two settings were observed. First, the O2 absorption rate was impacted little by differences in the canister pressure and only seemed to be noticeably reduced when Air flow was partial and N2 was being supplied as well. These conditions were only met in two configurations, i.e., Partial Air / Partial N2 and Partial Air / Full N2, since interestingly, Partial Air with N2 Off had one of the fastest absorption rates. The more significant effects of the system settings were seen in the plateaus of the DO plots. These plateaus represent the short-term, steady-state DO level under the corresponding system conditions. It is not the saturation point of the mixture, since the solution is not technically O2 saturated; however, it can be loosely thought of as a dynamic saturation or equilibrium point, since it is the peak DO level that can be reasonably expected under those conditions.

[0116] Although the MechVent and Oxy Vent modules / platforms may operate independently, a singular or combination ventilator module has logic that mirrors relevant pressure values across both systems and maps both the oxygen consumption and CO2 output to a unifying “metabolic” function. These modules may be integrated into a larger, polytrauma HIL automated testbed for resuscitation controllers that incorporate systems for testing fluid resuscitation controllers for hemorrhagic shock, automated extremity / junctional tourniquet control, and anesthesia management. The final combination ventilation testing module or platform will enable the evaluation of a wide range of automated technologies for managing trauma patients, including algorithms that identify contraindications that may not be accounted for by standalone devices or controllers.

[0117] Referring now to FIG. 20, a schematic diagram 2000 of an example combination testing module that may be used in a combined test platform is illustrated. A closed canister 2000 with an array of ports (inlets and outlets) 2015, 2035, 2040, 2045, 2055; an electrochemical DO probe 2025; and an attached bellows 2010. As an example, the canister 2000 may be assembled from a 6-inch section of 4-inch inner diameter aluminum pipe along with base and top end caps.Atty. Docket No. ISR 24-52.WO

[0118] Construction

[0119] Beginning from the bottom, a 3D printed diffusion ring 2060 is seated inside the base end cap and forms a sealed connection through the vent inlet (inspiration) port 2040 with a fitting connected to the inspiration line of the mechanical ventilator (such as, for example, the MOVES® SLC™). The canister 2000 holds approximately 1200 mL of plain tap water, and the central section of the canister includes three ports 2035, 2032 for the DO probe 2030, 2055 that are submerged below the water line when filled. One port 2032 seats the DO probe 2030 while the other two serve as inlet and outlet connections (inlet port 2035 and high DO H2O outlet port 2055), enabling the water inside the cannister to be exchanged as needed. The water inlet port 2035 is fed by a peristaltic pump which supplies water from a separate reservoir (not shown) of deoxygenated water. Bubbled nitrogen gas is used to keep the DO level of the water in the separate reservoir near zero. The water outlet port also uses a peristaltic pump to remove oxygenated water from within the canister and can either drain it as waste or return it to the separate reservoir to be deoxygenated and reused.

[0120] The top end cap contains three ports 2015, 2045, 2050 that are positioned above the water line when filled. The vent outlet (expiration) port 2045 may be identical to the vent inlet port 2040 and connects to the expiration line and the gas sampling line of the mechanical ventilator. One of the remaining two ports 2015 serves as a CO2 gas inlet which is supplied by a compressed gas tank and regulated via a proportional solenoid valve (not shown). The other port, regulated exhaust port 2050, connects to a regulated exhaust line which permits the release of additional gas as needed. Finally, the top end cap includes a hole 2070 that forms a sealed connection with the bellows 2010 above. The bellows 2010 is sealed on the upper end with a solid plastic cap which also serves as a platform for the CL compartment (not shown) and may all be contained within a clear, rigid tube (not shown) for support.

[0121] Referring now to FIG. 21, a system diagram 2100 having a combination ventilation module that may be used in a combined test platform is illustrated. As shown in the drawing, CO2 canister 2105 provides CO2 gas to expansion tank 2110. CO2 inlet solenoid valve 2112 is coupled to the CO2 inlet port 2113 (analogous to CO2 inlet 2015 of FIG. 20). Pressure relief solenoid valve 2116 and pressure sensor 2118 are coupled to pressure- regulated exhaust port 2120 (analogous to pressure regulated exhaust 2050 of FIG. 20). Canister 2130 has a lung compliance compartment 2132 housing weights 2134 that can be added or removed, bellows 2136, DO probe 2138, and diffusion ring 2142 inside end capAtty. Docket No. ISR 24-52.WO2140, together with the ports described above in connection with FIG. 20. Expiration line 2146, and also EtCO2sample line 2142, are coupled to expiration / outlet port 2145 (analogous to expiration / outlet port 2045 of FIG. 20); inspiration line 2150 is coupled to inspiration / inlet port 2151 (analogous to inspiration / inlet port 2040 of FIG. 20); and low DO FEO line 2148 is coupled to low DO H2O inlet 2147 (analogous to DO H2O inlet 2035 of FIG. 20), integrates with the deoxygenated water inlet pump 2162 and connects to deoxygenated water reservoir 2164, as shown. Deoxygenated water reservoir 2164 is coupled to N2 tank 2166.

[0122] Inlet solenoid valve 2112, pressure relief solenoid valve 2116, pressure sensor 2118, DO probe 2138, airway resistance control 2152, computer control 2190, and ventilator 2170 are controlled by a platform controller such as microcontroller 2180.

[0123] As described in more detail below, ventilator 2170 supplies 02-rich air to canister 2130 at inspiration / inlet port 2151. Air is bubbled into H2O volume 2135, increasing the DO reading as an analogue for SpO2. The “inhaled” air fills the bellows 2136 which is mixed with a controlled amount of CO2, resulting in an EtCO2 reading. Pressure in canister 2130 can be maintained by the automated pressure-relief exhaust provided by pressure-relief solenoid valve 2116 and pressure sensor 2118 at pressure-regulated exhaust port 2120. The ventilator 2170 completes the breath by pulling CO2-mixed expired air from the outlet expiration / outlet port 2145. Control of low DO H2O inlet 2147 is used to simulate additional patient challenges by exchanging equal volumes of high DO water with de-oxygenated water to slow or inhibit patient oxygenation.

[0124] Operation

[0125] More specifically, a mechanical ventilator 2170 will push a volume of oxygenrich air through the inspiration line 2150 connection to inspiration port 2151 during the inspiration phase of a breath. This line 2150 will supply the air to the inlet port 2151 of the module which will then be directed throughout the diffusion ring 2142 and bubbled into the volume of water 2135. A portion of the oxygen will get dissolved in the water changing the DO level which will be constantly monitored by the DO probe 2138, simulating a patient’s SpO2. During inspiration, the air will accumulate in the bellows 2136 and a small amount of CO2 will be injected via the CO2 inlet valve 2112 to mix with the inspired air, simulating CO2 generation / offload by the patient. During the expiration phase of the breath, the mechanical ventilator 2170 will draw the air out of the module via the expiration / outlet port 2145. During this phase a sample line 2142 will pull small samples of the exhaled breath to measureAtty. Docket No. ISR 24-52.WOEtC O2. This inspiration / expiration cycle will continue for the duration of the simulated treatment, during which several parameters of the module can be adjusted in real-time to simulate a patient responding, or not responding to treatment, to evaluate closed-loop controllers designed to automate the mechanical ventilator’s functions and / or settings.

[0126] Adjustable parameters

[0127] The RAW component is unchanged from the MechVent Module design. Airway resistance control 2152 on the inspiration line 2150 prior to coupling with inlet port 2151 controls airway resistance. This may be an actuator that functions as a pinch valve on the inspiration line prior to the connection with the inlet port of the new module as shown.

[0128] Similarly, CL component is unchanged and consists of a compartment 2132 that holds standardized weights 2134 that can be added or removed. This process of weight control may be manual or it may be automated (automatic).

[0129] The water inlet / outlet capability enables high DO, oxygenated water to be removed and replaced with low DO, deoxygenated water. This can be controlled in a way that lowers the DO level, simulating a patient not receiving enough oxygen, as seen in numerous conditions including ARDS or certain cardiovascular diseases. An alternate case would be to exchange the water at rates that can either stall or simply reduce the rate of increase of the DO level at the current FiO? setting, demanding a higher concentration to be administered to improve the patient’s condition. This is also needed in a variety of cases requiring mechanical ventilation including COVID-19 infection, blast lung injury, and burn- related inhalation injuries.

[0130] The amount of CO2 supplied can be reduced or increased to simulate cases of abnormally low EtCO? as seen in patients with pulmonary embolisms, pneumothorax, and hypovolemic shock, or high EtCO? which can be caused by infections such as sepsis or breathing issues like a late-stage asthma attack. The pressure-regulated exhaust can simulate issues such as leaks in the vent line or allow pressure to be properly regulated if high volumes of CO2 are being injected into the system.

[0131] Referring now to FIG. 22, flowchart 2200 illustrates an example methodology of a combination ventilation platform / module, in accordance with certain embodiments of the disclosure. At block 2210, a ventilator supplies inspired breath during an inspiration phase of a patient’s breathing. The inspired air is bubbled into water at block 2220.Atty. Docket No. ISR 24-52.WO

[0132] At block 2230, oxygen is dissolved into the water, simulating SpCh. At decision block 2240, the query is what is the SpCh? If SpCh is less than 90%, for example, the flow continues to decision block 2245. At decision block 2245, the query is whether the FiC>2 is 100%, if yes, then FiO2 is maintained and PEEP is increased by a step. If FiCE is not 100%, then FiCh is increased to 100% and the PEEP is maintained at block 2255. If SpCh is between 9o% to 96%, for example, flow continues to block 2260 to hold settings. If SpCh is greater than 96%, for example, flow continues to block 2265 to decrease PEEP, FiCh by one step.

[0133] Following the simulation of SpCh at blocks 2230-2265, the flow continues to block 2270. The ventilator pulls expired breath and measures EtCCh in blocks 2280-2295. At decision block 2280, the query is what is EtCCh? If less than 35 mmHg, for example, at block 2285, VT and RR are decreased by a step. If EtCCh is 35 to 45 mmHg, for example, the operation is to hold VT, RR settings as is at block 2290. If EtCCh is greater than 45 mmHg, for example, at block 2295 VT and RR are increased by a step.

[0134] Automated ventilation control has the potential to simplify critical care in civilian and military environments. However, control systems require extensive testing for proper tuning, which can be cost-ineffective when relying solely on animal studies for troubleshooting. Although in-silico models have become exceedingly advanced in recent years, they still require large and highly specialized data to be properly tuned and are not able to operate with physical devices, leaving an important gap in the ability to determine the performance of a controller. Systems that include hardware control still often lack a direct link between the real-world outputs of the ventilator and the feedback signals that serve as the inputs to the ventilator controller. Instead, the HIL testbed presented in this work allows for physical hardware debugging in a high-throughput manner for oxygen and mechanical ventilation controller logics. Both Oxy Vent and MechVent modules, alone or in combination, are able to reproduce the physiological feedback signals of interest within ranges that have been observed in in-vivo studies. Both modules are also directly responsive to the outputs of a commercial ventilator when controlled by a control scheme. Using this platform, more extensive testing can be performed prior to animal experiments, allowing for more refined controllers to be evaluated and drastically streamlining the translation process for these lifesaving medical devices. As a result, closed-loop ventilator development can be accelerated, thus lowering the skill threshold and improving ventilator management in future critical care and combat casualty care situations.Atty. Docket No. ISR 24-52.WO

[0135] As described herein, various sensors, solenoid valves, tubing, fittings, fabrication supplies, and microcontrollers may be used in the test platform to achieve the functionality and results described herein.

[0136] Embodiments of the invention have been described in the disclosure to explain the nature of the invention. Those skilled in the art may make changes in the details, materials, steps and arrangement of the described embodiments within the principle and scope of the invention, as expressed in the appended claims.

[0137] While implementations of the disclosure are susceptible to embodiment in many different forms, there is shown in the drawings and will herein be described in detail specific embodiments, with the understanding that the present disclosure is to be considered as an example of the principles of the disclosure and not intended to limit the disclosure to the specific embodiments shown and described. In the description above, like reference numerals may be used to describe the same, similar or corresponding parts in the several views of the drawings.

[0138] In this document, relational terms such as first and second, top and bottom, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” “includes,” “including,” “has,” “having,” or any other variations thereof, are intended to cover a nonexclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element preceded by “comprises . . .a” does not, without more constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0139] Reference throughout this document to “one embodiment,” “certain embodiments,” “an embodiment,” “implementation(s),” “aspect(s),” or similar terms means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of such phrases or in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments without limitation.Atty. Docket No. ISR 24-52.WO

[0140] The term “or” as used herein is to be interpreted as an inclusive or meaning any one or any combination. Therefore, “A, B or C” means “any of the following: A; B; C; A and B; A and C; B and C; A, B and C ” An exception to this definition will occur only when a combination of elements, functions, steps or acts are in some way inherently mutually exclusive. Also, grammatical conjunctions are intended to express any and all disjunctive and conjunctive combinations of conjoined clauses, sentences, words, and the like, unless otherwise stated or clear from the context. Thus, the term “or” should generally be understood to mean “and / or” and so forth. References to items in the singular should be understood to include items in the plural, and vice versa, unless explicitly stated otherwise or clear from the text.

[0141] Recitation of ranges of values herein are not intended to be limiting, referring instead individually to any and all values falling within the range, unless otherwise indicated, and each separate value within such a range is incorporated into the specification as if it were individually recited herein. The words “about,” “approximately,” or the like, when accompanying a numerical value, are to be construed as indicating a deviation as would be appreciated by one of ordinary skill in the art to operate satisfactorily for an intended purpose. Ranges of values and / or numeric values are provided herein as examples only, and do not constitute a limitation on the scope of the described embodiments. The use of any and all examples, or exemplary language (“e.g.,” “such as,” “for example,” or the like) provided herein, is intended merely to better illuminate the embodiments and does not pose a limitation on the scope of the embodiments. No language in the specification should be construed as indicating any unclaimed element as essential to the practice of the embodiments.

[0142] For simplicity and clarity of illustration, reference numerals may be repeated among the figures to indicate corresponding or analogous elements. Numerous details are set forth to provide an understanding of the embodiments described herein. The embodiments may be practiced without these details. In other instances, well-known methods, procedures, and components have not been described in detail to avoid obscuring the embodiments described. The description is not to be considered as limited to the scope of the embodiments described herein.

[0143] In the following description, it is understood that terms such as “first,” “second,” “top,” “bottom,” “up,” “down,” “above,” “below,” and the like, are words of convenience and are not to be construed as limiting terms. Also, the terms apparatus, device, system, etc. may be used interchangeably in this text.Atty. Docket No. ISR 24-52.WO

[0144] The many features and advantages of the disclosure are apparent from the detailed specification, and, thus, it is intended by the appended claims to cover all such features and advantages of the disclosure which fall within the scope of the disclosure.Further, since numerous modifications and variations will readily occur to those skilled in the art, it is not desired to limit the disclosure to the exact construction and operation illustrated and described, and, accordingly, all suitable modifications and equivalents may be resorted to that fall within the scope of the disclosure.

Claims

Atty. Docket No. ISR 24-52.WOWHAT IS CLAIMED IS:

1. A combination ventilation test platform, comprising: a combination module coupled to a gas in path and a gas out path of the test platform, including: a canister operable to receive gas in the gas in path having one or more intake valves coupled to and controlled by the platform controller; a dissolved oxygen (DO) probe coupled to the canister and controlled by the platform controller and operable to measure dissolved oxygen in the canister; a pressure sensor in the gas out path having one or more outtake valves, said sensor and said one or more outtake valves coupled to and controlled by the platform controller; a bellows controlled by the platform controller to simulate inspiratory and expiratory cycles of the respiratory system, coupled to the canister and the gas in path and the gas out path; a flow reduction path coupled to the bellows in the gas in path; a carbon dioxide generation and expansion tank coupled to the flow reduction path; and a variable airway resistance in the gas in path.

2. The platform of claim 1, the canister including a gas diffuser used within a pressure chamber of the canister to ensure adequate gas mixing.

3. The platform of claim 2, where the gas diffuser is a diffusion ring.Atty. Docket No. ISR 24-52.WO4. The platform of claim 1, where the platform controller controls adjustment of the fraction of inspired oxygen (FiCh) and positive end-expiratory pressure (PEEP) settings of a ventilator.

5. The platform of claim 1, where the platform controller controls simulation of peripheral oxygen saturation (SpCh) through a dissolved oxygen (DO) level in water measurement in a closed container.

6. The platform of claim 5, where the platform controller controls DO by bubbling air and nitrogen (N2) gas through the water as an analogue for FiO?.

7. The platform of claim 5, where pressure in the closed container is an analogue for PEEP to modify gas solubility.

8. The platform of claim 7, where the platform controller controls scaling of a range of DO to a relevant SpO2range.

9. The platform of claim 2, where the platform controls transformation of the outputs of the platform for FiO? and PEEP to the gas ratio and controller pressure domains under control of the platform controller.

10. The platform of claim 1, where the flow reduction path includes a one-way valve.

11. The platform of claim 1, the platform further comprising the mechanical ventilator coupled to the variable airway resistance in the gas out path, the mechanical ventilator operable to measure EtCCh.

12. The platform of claim 1, the platform further comprising a canister that houses the bellows and a lung compliance (CL) compartment.

13. The platform of claim 12, where the bellows is a flexible bellows.Atty. Docket No. ISR 24-52.WO14. The platform of claim 12, the flow reduction path including a flow reduction connector coupled to the canister.

15. The platform of claim 1, the variable airway resistance including a linear actuator configured to restrict tubing in the gas out path.

16. A method for testing a controller of a ventilator, comprising: a test platform testing the controller of the ventilator including one or more of: testing the controller of the ventilator in managing automated mechanical ventilation controllers’ maintenance of peripheral oxygen saturation (SpCh) for a simulated patient and generating an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FiCh) and the peak inspiratory pressure ventilator settings of the ventilator, said testing and generating under control of a platform controller of the oxygen ventilator test platform; and testing the controller of the ventilator in managing end-tidal carbon dioxide (EtCCh) of a simulated patient, operation of the test platform controlled by the platform controller of the test platform in providing carbon dioxide generation, lung compliance (CL) and airway resistance (RAW) states while providing a EtCCh level that is responsive to changes in tidal volume and respiratory rate changes of the patient.

17. The method of claim 16, further comprising: responsive a measured EtCCh level, the platform controller performing one or more of maintaining VT and RR settings of the ventilator, decreasing VT and RR settings of the ventilator, and increasing VT and RR settings of the ventilator.Atty. Docket No. ISR 24-52.WO18. The method of claim 17, further comprising maintaining functionality for different CL and RAW states.

19. The method of claim 18, setting VT and RR of the ventilator under control by the platform controller.

20. The method of claim 16, further comprising: responsive to a measured SpCh level, the platform controller performing one or more of maintaining positive end-expiratory pressure (PEEP) and FiCh settings of the ventilator, increasing the FiCh setting and maintaining the PEEP setting of the ventilator, maintaining the FiCh setting and increasing the PEEP setting of the ventilator, and decreasing the PEEP and FiCh settings of the ventilator.

21. The method of claim 20, where if the measured SpCh level is at a maximum value, the platform controller maintaining the FiCh setting and increasing the PEEP setting of the ventilator.

22. The method of claim 20, further comprising the platform controller controlling adjusting the FiCh and PEEP settings by the platform controller of the oxygen ventilator test platform.

23. The method of claim 22, further comprising the platform controller controlling simulating SpCh through a dissolved oxygen (DO) level in water measurement in a closed container by one or more of the mechanical ventilator test platform and the oxygen ventilator test platform.

24. The method of claim 23, further comprising the platform controller controlling DO by bubbling air and nitrogen (N2) gas through the water as an analogue for FiO?.Atty. Docket No. ISR 24-52.WO25. The method of claim 23, where pressure in the closed contained is an analogue for PEEP to modify gas solubility.

26. The method of claim 25, further comprising the platform controller controlling scaling the range of DO to a relevant SpO? range.

27. The method of claim 20, further comprising the platform controller controlling transformation of the outputs of the platform for FiCh and PEEP to the gas ratio and controller pressure domains under control of the platform controller.

28. An oxygen ventilator test platform that tests a controller of a ventilator in managing oxygen levels of a simulated patient, where the oxygen ventilator platform under operation controlled by a platform controller tests automated mechanical ventilation controller maintenance of peripheral oxygen saturation (SpCh) and generates an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FiO2) and the peak inspiratory pressure ventilator settings of the ventilator.

29. The platform of claim 28, the platform comprises: a canister operable to receive gas in a gas in path having one or more intake valves coupled to and controlled by the platform controller; a dissolved oxygen (DO) probe coupled to the canister and controlled by the platform controller and operable to measure dissolved oxygen in the canister; and a pressure sensor in a gas out path having one or more outtake valves, said sensor and said one or more outtake valves coupled to and controlled by the platform controller.

30. The platform of claim 29, the canister including a gas diffuser used within a pressure chamber of the canister to ensure adequate gas mixing.Atty. Docket No. ISR 24-52.WO31. The platform of claim 30, where the gas diffuser is a diffusion ring.

32. The platform of claim 28, where the platform controller controls adjustment of the FiO2and positive end-expiratory pressure (PEEP) settings.

33. The platform of claim 28, where the platform controller controls simulation of SpO2through a dissolved oxygen (DO)level in water measurement in a closed container.

34. The platform of claim 33, where the platform controller controls DO by bubbling air and nitrogen (N2) gas through the water as an analogue for FiO2.

35. The platform of claim 33, where pressure in the closed container is an analogue for PEEP to modify gas solubility.

36. The platform of claim 35, where the platform controller controls scaling of a range of DO to a relevant SpO2range.

37. The platform of claim 28, where the platform controls transformation of the outputs of the platform for FiO2and PEEP to the gas ratio and controller pressure domains under control of the platform controller.

38. The platform of claim 28, where the platform further tests one or more of the controller of the ventilator in managing end-tidal carbon dioxide (EtCCh) of the simulated patient and a second controller of a second ventilator in managing EtCCh of the simulated patient.

39. A method for testing a controller of a ventilator that manages oxygen levels of a simulated patient, comprising: an oxygen ventilator test platform testing the controller of the ventilator in managing automated mechanical ventilation controllers’ maintenance of peripheral oxygen saturationAtty. Docket No. ISR 24-52.WO(SpO2) for a simulated patient and generating an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FiO2) and the peak inspiratory pressure ventilator settings of the ventilator, said testing and generating under control of a platform controller of the oxygen ventilator test platform.

40. The method of claim 39, further comprising: responsive to a measured SpO2level, the platform controller performing one or more of maintaining PEEP and FiO2settings of the ventilator, increasing the FiO2setting and maintaining the PEEP setting of the ventilator, maintaining the FiO2setting and increasing the PEEP setting of the ventilator, and decreasing the PEEP and FiO2settings of the ventilator.

41. The method of claim 40, where if the measured SpO2level is at a maximum value, the platform controller maintaining the FiO2setting and increasing the PEEP setting of the ventilator.

42. The method of claim 39, further comprising the platform controller controlling adjusting the FiO2and positive end-expiratory pressure (PEEP) settings by the platform controller of the oxygen ventilator test platform.

43. The method of claim 42, further comprising the platform controller controlling simulating SpO2through dissolved oxygen (DO) in water measurement in a closed container by one or more of the mechanical ventilator test platform and the oxygen ventilator test platform.

44. The method of claim 43, further comprising the platform controller controlling DO by bubbling air and nitrogen (N2) gas through the water as an analogue for FiO2.

45. The method of claim 43, where pressure in the closed contained is an analogue for PEEP to modify gas solubility.Atty. Docket No. ISR 24-52.WO46. The method of claim 45, further comprising the platform controller controlling scaling the range of DO to a relevant SpO? range.

47. The method of claim 39, further comprising: one or more of testing the controller of the ventilator in managing oxygen levels of the simulated patient and an oxygen ventilator test platform testing a second controller of a second ventilator in managing oxygen levels of the simulated patient.

48. The method of claim 47, further comprising one or more of the controller and the second controller transforming FIO2 and PEEP outputs to the gas ratio and controller pressure domains.

49. The method of claim 39, further comprising: testing the controller of the ventilator in managing end-tidal carbon dioxide (EtCCh) of a simulated patient.

50. A mechanical ventilator test platform that tests a controller of a ventilator in managing end-tidal carbon dioxide (EtCCh) of a simulated patient, where the test platform under operation controlled by a platform controller provides carbon dioxide generation, lung compliance (CL) and airway resistance (RAW) states while providing a EtCO2 level responsive to changes in one or more of tidal volume (Vt) and respiratory rate (RR) of the patient.

51. The platform of claim 50, where the EtCCh of the patient has an inverse relationship to the RR of the patient.

52. The platform of claim 50, where the EtCCh of the patient has an inverse relationship to minute ventilation (MV) of the patient that is responsive to change in one or more of VT and RR of the patient.Atty. Docket No. ISR 24-52.WO53. The platform of claim 51, where the platform further tests one or more of the controller of the ventilator in managing oxygen levels of the simulated patient and a second controller of a second ventilator in managing oxygen levels of the simulated patient.

54. The platform of claim 50, where the platform maintains functionality for different CL and RAW states.

55. The platform of claim 50, the platform comprises: a bellows controlled by the platform controller to simulate inspiratory and expiratory cycles of the respiratory system and has a gas in path and a gas out path; a flow reduction path coupled to the bellows in the gas in path; a carbon dioxide generation and expansion tank coupled to the flow reduction path; and a variable airway resistance in the gas out path.

56. The platform of claim 55, where the flow reduction path includes a one-way valve.

57. The platform of claim 55, the platform further comprising the mechanical ventilator coupled to the variable airway resistance in the gas out path, the mechanical ventilator operable to measure EtCCh.

58. The platform of claim 55, the platform further comprising a canister that houses the bellows and a lung compliance (CL) compartment.

59. The platform of claim 58, where the bellows is a flexible bellows.

60. The platform of claim 58, the flow reduction path including a flow reduction connector coupled to the canister.

61. The platform of claim 55, the variable airway resistance including a linear actuator configured to restrict tubing in the gas out path.Atty. Docket No. ISR 24-52.WO62. The platform of claim 50, where the platform further tests one or more of the controller of the ventilator in managing oxygen levels of the simulated patient and a second controller of a second ventilator in managing oxygen levels of the simulated patient.

63. A method for testing a controller of a ventilator that simulates patient lung conditions, comprising: a mechanical ventilator test platform testing a controller of a ventilator in managing end-tidal carbon dioxide (EtCCh) of a simulated patient, operation of the test platform controlled by a platform controller of the test platform in providing carbon dioxide generation, lung compliance (CL) and airway resistance (RAW) states while providing a EtCCh level that is responsive to changes in tidal volume and respiratory rate changes of the patient.

64. The method of claim 63, further comprising maintaining functionality for different CL and RAW states.

65. The method of claim 63, setting tidal volume (VT) and respiratory rate (RR) of the ventilator under control by the platform controller.

66. The method of claim 65, the method further comprising: responsive a measured EtCCh level, the platform controller performing one or more of maintaining VT and RR settings of the ventilator, decreasing VT and RR settings of the ventilator, and increasing VT and RR settings of the ventilator.

67. The method of claim 63, further comprising: one or more of testing the controller of the ventilator in managing oxygen levels of the simulated patient and an oxygen ventilator test platform testing a second controller of a second ventilator in managing oxygen levels of the simulated patient.

68. The method of claim 67, further comprising: testing by the platform controller the controller of the ventilator in managing automated mechanical ventilation controllers maintenance of peripheral oxygen saturationAtty. Docket No. ISR 24-52.WO(SpO2) for the simulated patient and generating under control of the platform controller an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FIO2) and the peak inspiratory pressure ventilator settings of the ventilator.

69. The method of claim 68, further comprising adjusting the fraction of inspired oxygen (FIO2) and positive end-expiratory pressure (PEEP) settings.

70. The method of claim 68, further comprising simulating SpCh through a dissolved oxygen (DO) level in water measurement in a closed container of one or more of the mechanical ventilator test platform and the oxygen ventilator test platform.

71. The method of claim 70, further comprising controlling DO by bubbling air and nitrogen (N2) gas through the water as an analogue for FIO2 under control of the platform controller.

72. The method of claim 70, where pressure in the closed contained is an analogue for PEEP to modify gas solubility.

73. The method of claim 72, further comprising the platform controller scaling the range of DO to a relevant SpO2 range.

74. The method of claim 68, further comprising the platform controller transforming FIO2 and PEEP outputs to the gas ratio and controller pressure domains.

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