Positive airway pressure using loop gain

Abstract

A system (50) for delivering a flow of gas to an airway of a respiratory system of a patient includes a flow generator (52), a sensor (74), and a loop gain controller (60). The loop gain controller selectively controls the flow of gas to the airway in accordance with a positive airway pressure (PAP) therapy mode. The loop gain controller includes (a) a stability metric module (80), (b) a condition monitoring module (82) that monitors ventilation characteristics of the flow of gas in the respiratory system of the patient and provides an output indicative of the monitored ventilation characteristics, (c) a loop gain decision module (84) that determines future ventilation characteristics targets and device gain targets, (d) a therapy prescription decision module (86) that determines a therapy command pressure or delivery characteristic, and (e) a pressure delivery module (88) that controls the flow generator (52) to deliver the flow of gas at the determined therapy command pressure or delivery characteristic for future breaths.

Description

Technical Field

[0001] This embodiment generally relates to a system and method for positive airway pressure therapy, and more specifically to a system and method for positive airway pressure therapy that utilizes loop gain for ventilation stability. Background Technology

[0002] Patients with congestive heart failure (CHF) often suffer from breathing disorders such as obstructive sleep apnea (OSA) or central sleep apnea. Another such respiratory condition that CHF patients frequently experience during sleep is called Cheyne-Stokes breathing. Figure 1 A typical Cheyne-Stokes breathing (CSR) pattern 30 is illustrated, characterized by rhythmic waxing phases 32 and waning phases 34, with periodically repeated high respiratory drive (hyperventilation) phases 36 and low respiratory drive (hypoventilation or apnea) phases 38. A typical Cheyne-Stokes cycle, generally represented as 40, lasts approximately one minute and is characterized by a gradual increase (arrow A) in peak respiratory flow over several cycles, followed by a gradual decrease (arrow B) in peak respiratory flow over several cycles. A typical Cheyne-Stokes cycle ends with a central apnea or hypoventilation following the waning phase. Apnea, hyperventilation, and abnormal changes in respiratory depth and rate often induce awakenings, thus reducing sleep quality. This sleep disruption caused by the CSR cycle, along with the periodic decline in arterial oxygen saturation, puts stress on the cardiovascular system, particularly the heart.

[0003] The earliest treatments for CSR involved stimulating respiratory drive by administering theophylline, caffeine, or 1-3% inhaled carbon dioxide to the patient. While these treatments, which sometimes effectively reduced CSR, had the drawback of increasing respiratory rate, as the increase in respiratory rate proportionally increased the workload on the heart and respiratory system.

[0004] Recent work in the treatment of sleep apnea and related breathing disorders includes bilevel positive airway therapy. In bilevel therapy, pressure is alternately applied within the patient's airway at relatively high and low prescribed pressure levels, resulting in alternating large and small amplitudes of therapeutic pressure. The larger and smaller amplitudes of the prescribed pressure levels are called inspiratory positive airway pressure (IPAP) and expiratory positive airway pressure (EPAP), respectively. The inspiratory and expiratory pressures are synchronized with the patient's inspiratory and expiratory cycles, respectively.

[0005] Some preliminary studies have shown that cardiac output improves when patients are supported by bilevel pressure therapy. It has also been recognized that CSR can be treated by increasing respiratory effort using positive pressure support when the CSR pattern is in the hypoventilation zone 38. To achieve this, it is known to use a ventilator or pressure support system to deliver machine-triggered breaths during the hypoventilation interval when the patient's own respiratory drive is weakened or absent. Alternatively, another approach to treating CSR is to selectively re-inhale CO2 during the hyperventilation phase of the CSR cycle. However, this approach requires additional equipment to be used with a typical ventilator system.

[0006] Besides the aforementioned cases, one of the earliest published works involving the modeling of the human respiratory system, including the use of digital computers, is "A mathematical model of the human respiratory control system": Milhorn, Benton, Ross, Guyton: 1965. In this study, Milhorn et al. created a system diagram of the respiratory system and derived a series of time-domain equations describing the interactions of each subsystem. Furthermore, Khoo et al.'s 1982 publication disclosed the creation of a mathematical model of Cheyne-Stokes respiration, or breathing (CSR). Khoo et al.'s publication initiated a sophisticated control system-based approach to this modeling problem of the human respiratory system.

[0007] In 2010, Wellman et al. described an experiment in which several participants collected data and a model was generated that was suitable for describing the loop gain response under several device conditions. In 2014, Terrill et al. continued their work on loop gain quantization of data collected without intervention.

[0008] Several references to the relevant background art include documents D1-D6 below. Document D1 (US 2003 / 121519A1 (ESTES MARK C[US] et al.)) relates to a system for treating medical disorders such as obstructive sleep apnea, which involves applying a gain to the flow rate of pressurized gas delivered to the patient during the inspiratory and / or expiratory phases of the respiratory cycle to deliver pressurized gas proportionally to the corresponding gain during inspiration and / or expiration. In addition to the pressure of the gain change, a baseline pressure may be applied, and an elevated pressure distribution may be employed to assist or control inspiration. The system can be fully automated in response to feedback provided by a flow sensor that determines an estimated patient flow rate. A leak computer may be included to instantaneously calculate gas leakage from the system. The system can be used in conjunction with conventional continuous positive airway pressure therapy, such as CPAP or dual-layer positive airway pressure devices, to achieve a variety of beneficial therapeutic applications.

[0009] Document D2 (WO 2016 / 065411 A1 (RESMED LTD[AU])) relates to a method and apparatus for providing automatic control of a respiratory pressure therapy device (such as a servo ventilator). The controller controls the application of pressure support ventilation therapy to a patient's airway. The controller also controls the respiratory pressure therapy device to automatically titrate the expiratory positive airway pressure (EPAP) for pressure support ventilation therapy to maintain airway patency in the patient. The EPAP may be limited by a floor pressure limit. The controller also controls the respiratory pressure therapy device to repeatedly adjust the floor pressure limit according to events of interest during the automatic titration of EPAP. Such a method can improve the treatment of patients, such as those with sleep-disordered breathing comorbid with hyperarousal disorder.

[0010] Document D3 (WO 2018 / 204985 A1 (RESMED LTD[AU])) relates to a device for treating respiratory disturbances in a patient. The device includes a pressure generator configured to generate an airflow to provide ventilatory support to the patient; a transducer configured to generate a flow signal representing the characteristics of the airflow; and a controller configured to analyze the flow signal to estimate the patient's inspiratory and expiratory volumes, and to servo-control the degree of ventilatory support to adjust the estimated tidal volume toward a target tidal volume. The gain of the servo control depends on the difference between the estimated inspiratory and expiratory volumes.

[0011] Reference D4 (WO 00 / 45882A1 (REMMERS JOHN E [CA]; HAJDUK ERIC ANDREW [CA]; PLATTRONALD SCOTT [CA]) relates to a system for reducing central sleep apnea (CSA) using certain methods to increase rebreathing during a sleep cycle. This reduces peroxidation typically caused by overbreathing cycles, thereby reducing compensatory underbreathing cycles and effectively reducing loop gain associated with CSA. One embodiment of the device includes a blower (60), a mask (64) with a gas outlet (66), and a tube (62) connecting the blower and the mask. Reference D5 (NEMATI SHAMIM et al.: “Model-based characterization of ventilatory stability using spontaneous breathing”, JOURNAL OF APPLIED PHYSIOLOGY, vol. 111, no. 1, July 1, 2011, pp. 55-67, XP 055793445, US) ISSN: 8750-7587, 001:10.1152 / japplphysioI.01358.2010) relates to model-based characterization of ventilatory stability using spontaneous breathing. D5 discloses a method based on trivariate autoregressive modeling using tidal volume, end-expiratory PCO2, and PO2, which provides estimates of the overall “loop gain,” chemoreflex gain, and device gain of the respiratory control system and its components. D5 discloses that “model-based spontaneous breathing analysis can 1) characterize the dynamics of the respiratory control system, and 2) provide simple tools for elucidating an individual’s ventilatory instability tendency, thereby allowing for potential treatments targeting underlying mechanisms.”

[0012] Reference D6 (DEACON-DIAZ NAOMI et al., “Inherent vs. induced loop gain abnormalities in obstructive sleep apnea”, FRONTIERS IN NEUROLOGY, vol. 9, 2 November 2018, XP 055793447, DOI: 10.3389 / fneur.2018.00896) addresses inherent and induced loop gains in obstructive sleep apnea. D6 discloses that quantifying unstable ventilatory chemoreflex control as loop gain is considered one of the four key pathophysiological features contributing to obstructive sleep apnea (OSA). Novel treatments aimed at reducing loop gain are being investigated, with the goal of tailoring future OSA treatments to the specific causes of apnea in individuals. However, few studies have evaluated loop gains in OSA controls and non-OSA controls, and those that do provide little evidence to support the existence of inherent abnormalities in overall chemical loop gain or its components (controller and device gain) in OSA patients versus non-OSA controls. However, intermittent hypoxia can induce high control gain through tumor-induced alterations to chemoreflex control, and can also reduce equipment gain through oxidative stress-induced inflammation and reduced lung function.

[0013] While each of the above efforts (i.e., as discussed in the background art) is useful in attempting to understand, quantify, and test one’s own understanding of the human respiratory system, there is still a need for improved positive airway pressure therapy methods and devices to overcome the problems in the prior art. Summary of the Invention

[0014] According to one aspect, a system for delivering airflow to the airway of a patient's respiratory system is disclosed. The system includes an airflow generator, at least one sensor, and a loop gain controller. The airflow generator generates airflow and delivers it to a patient circuit to deliver airflow to the airway of the patient's respiratory system. The at least one sensor generates an output signal associated with at least one characteristic related to the airflow. The loop gain controller, in response to the generated output signal, selectively controls the airflow to the airway of the patient's respiratory system according to a positive airway pressure (PAP) therapy mode. The airflow flowing into the airway of the patient's respiratory system from the airflow generator via the patient circuit is a positive flow, and the airflow flowing out of the airway of the patient's respiratory system is a negative flow. Furthermore, the PAP therapy mode is configured to utilize loop gain to achieve ventilatory stability in order to treat insufficient respiratory system loop gain corresponding to ventilatory instability.

[0015] The loop gain controller includes (a) a stability measurement module, (b) a condition monitoring module, (c) a loop gain decision module, (d) a therapy prescription decision module, and (e) a pressure delivery module. The stability measurement module is configured to determine at least one stability measurement. The condition monitoring module is configured to monitor ventilation characteristics of airflow in the patient's respiratory system and provide an output indicating the monitored ventilation characteristics. The monitored ventilation characteristics correspond at least to the occurrence of a sleep-disordered breathing (SDB) event in the patient's respiratory system. The loop gain decision module is configured to determine future ventilation characteristic targets and device gain targets based on the determined at least one stability measurement and the output from the condition monitoring module. The therapy prescription decision module is configured to determine a therapy command pressure or delivery characteristic based on the determined future ventilation characteristic targets and device gain targets, wherein the therapy command pressure or delivery characteristic includes a single command pressure or delivery characteristic or a combination of more than one command pressure or delivery characteristic. The pressure delivery module is configured to control an airflow generator to deliver airflow to the airways of the patient's respiratory system at the determined therapy command pressure or delivery characteristic for future breathing.

[0016] According to another aspect, at least one stability metric includes one or more of the following: (a) clinical loop gain, which is defined as: Wherein G describes the dynamic responsiveness of the patient ventilation system controller, PACO2-PICO2 is the PCO2 gradient of alveolar inhalation for gas exchange, lung volume represents the volume of gas in the patient's lungs available to buffer changes in alveolar CO2, T is a complex time factor that is primarily determined by the cycle delay and partly by the time constant for gas exchange in the lungs; (b) the statistical correlation of the clinical loop gain with (a), where the statistical correlation is generated based on respiratory characteristics; and (c) the composite metric, where the composite metric is generated based on respiratory characteristics.

[0017] According to another aspect, the respiratory characteristics used to generate at least one stability metric include one or more of the following: i) the rate of change of minute ventilation, ii) ventilation overshoot detection, iii) ventilation undershoot detection, iv) the period, phase, and amplitude of periodic breathing, v) a model that handles CO2 consumption, vi) a model that handles sleep stages and / or central nervous system arousal, vii) a simple open-window mean minute ventilation, and viii) any combination of the above.

[0018] According to another aspect, the future ventilation characteristic targets and device gain targets determined via the loop gain decision module include amplitude and / or phase information of airflow in the patient's respiratory system airway. The future ventilation characteristic targets and device gain targets also provide loop gain control in response to the delivery of therapeutic command pressure or delivery characteristics via the pressure delivery module. Furthermore, based on amplitude and / or phase information, the future ventilation characteristic targets and device gain targets modify the loop gain in the patient's respiratory system by increasing or decreasing it via backflow-based gain to achieve ventilation stability.

[0019] According to another aspect, future ventilation characteristic targets and device gain targets, determined via the loop gain decision module, modify the device gain of one or more device components of the patient's respiratory system. Specifically, the future ventilation characteristic targets and device gain targets modify the device gain via changes in one or more pressure delivery characteristics. One or more pressure delivery characteristics may include one or more of the following: (i) baseline pressure, (ii) inspiratory pressure, and (iii) expiratory pressure.

[0020] According to another aspect, the loop gain decision module also includes a flow-based gain scheduler. The flow-based gain scheduler is configured to (i) schedule a flow-based gain proportional to the magnitude and / or rate of change in the pattern of increase / decrease in the patient's respiratory effort. The flow-based gain scheduler is also configured to (ii) increase or decrease the patient's respiratory effort to counteract unstable increase / decrease in muscle effort within the patient's respiratory system. Furthermore, the therapy prescription decision module is configured to determine a therapy command pressure or delivery characteristic based at least on the loop gain input from the flow-based gain scheduler. The therapy command pressure or delivery characteristic, when delivered, is configured to generate a flow-based gain that provides pressure therapy in a manner sufficient to overcome obstructive SDB events; or in other words, the therapy command pressure or delivery characteristic, when delivered, is configured to adjust the flow-based gain and device gain configured to normalize the loop gain.

[0021] According to another aspect, the future ventilation characteristic target determined via the loop gain decision module includes continuously calculated flow-based pressure amplification throughout the respiratory period. The calculated flow-based pressure amplification is the product of (i) the instantaneous patient airway gas flow rate and (ii) the flow-based gain factor. Furthermore, the sign of the instantaneous patient airway gas flow rate is positive during inspiration and negative during expiration. Additionally, for positive values ​​of the determined flow-based gain factor, the loop gain controller drives ventilation via the pressure delivery module and the airflow generator to increase ventilation in the patient's respiratory system. For negative values ​​of the determined flow-based gain factor, the loop gain controller restricts ventilation via the pressure delivery module and the airflow generator to reduce ventilation in the patient's respiratory system.

[0022] According to another aspect, the loop gain decision module is further configured to determine a flow-based gain factor, wherein determining the flow-based gain factor includes adjusting the flow-based gain factor. The determined or adjusted flow-based gain factor is based on the patient's respiratory system status monitored at the current stage of instability in the patient's respiratory cycle, in response to an output signal generated by at least one sensor. Furthermore, the loop gain decision module adjusts the flow-based gain factor for a given condition, and the adjustment occurs only when the corresponding condition is occurring in the patient's respiratory system. In another embodiment, the condition monitoring module is further configured to collect and monitor the output signal of at least one sensor, which corresponds to the input for determining the respiratory system loop gain in positive airway pressure (PAP) therapy.

[0023] According to another aspect, a method for delivering airflow to the airway of a patient's respiratory system includes: generating an airflow, generating an output signal, and selectively controlling the airflow to the airway of the patient's respiratory system via a loop gain controller. Generating and delivering the airflow to the patient loop is accomplished via an airflow generator for further delivering the airflow to the airway of the patient's respiratory system. Generating the output signal associated with at least one characteristic related to the airflow is accomplished via at least one sensor. Selectively controlling the airflow to the airway of the patient's respiratory system is further accomplished via the loop gain controller in response to the generated output signal according to a positive airway pressure (PAP) therapy mode. The airflow flowing into the airway of the patient's respiratory system from the airflow generator via the patient loop is a positive flow, and the airflow flowing out of the airway of the patient's respiratory system is a negative flow. The PAP therapy mode is configured to address insufficient respiratory system loop gain corresponding to ventilatory instability by utilizing loop gain to achieve ventilatory stability.

[0024] According to another aspect, the method includes selectively controlling via a loop gain controller: (a) determining at least one stability metric via a stability metric module, (b) monitoring ventilation characteristics of airflow in the patient's respiratory system via a condition monitoring module and providing an output indicating the monitored ventilation characteristics, wherein the monitored ventilation characteristics correspond at least to the occurrence of a sleep-disordered breathing (SDB) event in the patient's respiratory system, (c) determining future ventilation characteristic targets and device gain targets via a loop gain decision module based on the determined at least one stability metric and the output from the condition monitoring module, (d) determining a therapy command pressure or delivery characteristic via a therapy prescription decision module based on the determined future ventilation characteristic targets and device gain targets, wherein the therapy command pressure or delivery characteristic includes a single command pressure or delivery characteristic or a combination of more than one command pressure or delivery characteristic, and (e) controlling an airflow generator via a pressure delivery module to deliver airflow to the airways of the patient's respiratory system at the therapy command pressure or delivery characteristic for future breathing.

[0025] According to another aspect, at least one stability metric includes one or more of the following: (a) clinical loop gain, which is defined as: Wherein G describes the dynamic responsiveness of the patient ventilation system controller, PACO2-PICO2 is the PCO2 gradient of alveolar inhalation for gas exchange, lung volume represents the volume of gas in the patient's lungs available to buffer changes in alveolar CO2, T is a complex time factor that is primarily determined by the cycle delay and partly by the time constant for gas exchange in the lungs; (b) the statistical correlation of the clinical loop gain with (a), wherein the statistical correlation is generated based on respiratory characteristics; and (c) the composite metric, wherein the composite metric is generated based on respiratory characteristics.

[0026] According to another aspect, the method includes respiratory characteristics for generating at least one stability metric, such as the rate of change of minute ventilation, ii) ventilatory overshoot detection, iii) ventilatory undershoot detection, iv) the period, phase, and amplitude of periodic breathing, v) a model for handling CO2 consumption, vi) a model for handling sleep stages and / or central nervous system arousal, vii) a simple open-window mean minute ventilation, and viii) any combination of the above.

[0027] According to another aspect, the method includes future ventilation characteristic targets and device gain targets determined via a loop gain decision module: (i) including amplitude and / or phase information of airflow in the airways of the patient's respiratory system; (ii) providing loop gain control in response to the delivery of a therapy command pressure or delivery characteristic via a pressure delivery module; and (iii) modifying the loop gain in the patient's respiratory system for ventilation stability by increasing or decreasing, based on amplitude and / or phase information, via a backflow-based gain. Furthermore, the future ventilation characteristic targets and device gain targets determined via the loop gain decision module modify the device gain of one or more device components of the patient's respiratory system via changes in one or more pressure delivery characteristics. One or more pressure delivery characteristics include one or more of the following: (i) baseline pressure, (ii) inspiratory pressure, and (iii) expiratory pressure.

[0028] According to another aspect, the method includes selective control via a loop gain controller, further comprising: (c)(i) scheduling a flow-based gain via a flow-based gain scheduler of a loop gain decision module, the flow-based gain being proportional to the magnitude and / or rate of change in the pattern of increase or decrease in the patient's respiratory effort; and (c)(ii) increasing or decreasing the patient's respiratory effort via determined future ventilation characteristic targets and device gain targets, thereby counteracting unstable increase or decrease in muscle effort in the patient's respiratory system. In another embodiment, the method includes selective control via a loop gain controller, further comprising: (d)(i) determining a therapy command pressure or delivery characteristic via a therapy prescription decision module based at least on loop gain input from the flow-based gain scheduler, wherein the therapy command pressure or delivery characteristic, when delivered, is configured to generate a flow-based gain that provides pressure therapy in a manner sufficient to overcome obstructive SDB events, or in other words, the therapy command pressure or delivery characteristic, when delivered, is configured to regulate the flow-based gain and device gain configured to normalize the loop gain.

[0029] Embodiments of this disclosure advantageously treat respiratory instability (i.e., instability in the respiratory or ventilation system) in patients using positive pressure therapy and a negative feedback closed-loop control system that modulates the loop gain of the human respiratory system (i.e., the loop gain of the ventilation system) to counteract fluctuations in the patient's ventilatory response to a given PAP therapy or treatment. Other advantages provided by embodiments of this disclosure include one or more of the following: 1) using flow-based gain to counteract spontaneous effort, which does generate pressure, but this pressure is proportional to the spontaneous flow; 2) using device gain as an auxiliary method to provide loop gain stability (e.g., if the patient's response to a given PAP therapy or treatment is unstable, the first line of defense might be to increase the EPAP pressure to increase the device gain); 3) previously known ASV devices use long observation windows, where the target is determined by a proportion of a calculated average, while the algorithm according to this embodiment uses a stability metric that can be calculated within a shorter time window.

[0030] After reading and understanding the following detailed description, other advantages and benefits will become clear to those skilled in the art. Attached Figure Description

[0031] The embodiments disclosed herein may take the form of various components and component arrangements, as well as various steps and step arrangements. Therefore, the accompanying drawings are for illustrative purposes and should not be construed as limiting the embodiments. In the drawings, the same reference numerals refer to the same elements. Furthermore, it should be noted that the drawings may not be drawn to scale.

[0032] Figure 1This is a diagram of a typical Cheyne-Stokes breathing cycle, which is processed by a system and method of positive airway pressure therapy utilizing loop gain for ventilation stability according to embodiments of the present disclosure.

[0033] Figure 2 These are graphs showing the relationship between several responses of a control system and time. These responses are classified as underdamped, critically damped, and overdamped.

[0034] Figure 3 This is a functional block diagram of a system for positive airway pressure therapy that utilizes loop gain for ventilation stability according to an embodiment of the present disclosure.

[0035] Figure 4 This is a flowchart view of a method for positive airway pressure therapy utilizing loop gain for ventilation stability according to embodiments of the present disclosure; and

[0036] Figure 5 This is another flowchart view, which is part of a method for positive airway pressure therapy that utilizes loop gain for ventilation stability according to embodiments of the present disclosure. Detailed Implementation

[0037] Embodiments of this disclosure, along with their various features and advantageous details, are explained more fully with reference to the non-limiting examples described and / or illustrated in the accompanying drawings and detailed in the following description. It should be noted that the features shown in the drawings are not necessarily drawn to scale, and features of one embodiment may be used in conjunction with other embodiments that will be recognized by those skilled in the art, even if not explicitly stated herein. Descriptions of well-known components and processing techniques may be omitted to avoid unnecessarily obscuring the embodiments of this disclosure. The examples used herein are intended only to facilitate an understanding of how embodiments of this disclosure can be practiced and to further enable those skilled in the art to practice these methods. Therefore, the examples herein should not be construed as limiting the scope of embodiments of this disclosure, which are defined only by the appended claims and applicable law.

[0038] It should be understood that the embodiments of this disclosure are not limited to the specific methods, protocols, devices, apparatuses, materials, applications, etc., described herein, as these can vary. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the claimed embodiments. It must be noted that, as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly specifies otherwise.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments of this disclosure pertain. Preferred methods, apparatuses, and materials are described, although any methods and materials similar to or equivalent to those described herein may be used in the practice or testing of the embodiments.

[0040] According to one embodiment, positive airway pressure (PAP) is used to treat various sleep-disordered breathing conditions of the human respiratory system (or ventilation system), including obstructive sleep apnea (OSA) and Cheyne-Stokes respiration (CSR). Furthermore, as discussed herein, loop gain (or “loop gain”) describes the magnitude of the ventilation system’s ventilatory response to disturbances in the system. Underdamped systems with a loop gain greater than 1 (i.e., loop gain > 1, also referred to herein as “high loop gain”) are unstable and lead to repetitive inadequate breathing in OSA and CSR. Currently known automated servo ventilation (ASV) devices provide ventilation to the patient when increased ventilation is needed; however, such currently known ASV devices cannot limit patient ventilation when the patient’s ventilatory response (e.g., muscle effort) exceeds baseline. In other words, currently known ASV devices attempt to stabilize ventilation by providing support when necessary to ensure a ventilation target determined as the proportion of spontaneous ventilation. This provides limited benefit because the method cannot identify changes in the timing of increases and decreases in respiratory drive. Conversely, embodiments of this disclosure advantageously monitor effort over time and provide reverse ventilation in phase with the central controller.

[0041] According to one aspect, embodiments of this disclosure advantageously address the inability of existing known ASV devices to treat the hyperventilation phase in patients with high loop gain. In particular, embodiments of this disclosure advantageously treat respiratory instability (i.e., instability in the respiratory or ventilation system) in patients using positive pressure therapy and a negative feedback closed-loop control system that adjusts the loop gain of the human respiratory system (i.e., the loop gain of the ventilation system) to counteract fluctuations in the patient's ventilation response.

[0042] While a comprehensive mathematical model of the human respiratory system (or ventilation system) is not required, this paper describes the main components of the human respiratory system and their contributions to ventilation stability. Lumped models allow for generalization, a widely accepted approach that allows for discussion of the subject matter in a broad sense. For example, it is acceptable to frame the problem without defining each component, especially when their contributions are small and less correlated, or when they are nonlinear and complex. For the purposes of this disclosure, the following description of respiratory system components will be used, relating to the central controller, devices, device gain and device gain modification, body compensation modulator, and clinician device component gain modification.

[0043] Central controller Central control of ventilation in the human respiratory system occurs in the medulla oblongata and pons of the brain, utilizing both central and peripheral chemoreceptors. The medulla oblongata, located in the brainstem, is responsible for automatic functions such as respiration, blood pressure, circulation, cardiac function, and digestion. The pons, horseshoe-shaped structures in the brainstem, are vital for life. Composed of nerve fibers connecting the cerebrum and cerebellum, the pons bridges sensory information between the left and right hemispheres of the brain. Central chemoreceptors monitor CO2 levels in the cerebrospinal fluid, while peripheral chemoreceptors, located in the aorta and carotid bodies, monitor CO2 and O2 in the blood. The aortic body is located along the aortic arch. The carotid body is located within the carotid artery. Due to their location, the time constant of central chemoreceptors is much slower (approximately 50 seconds) compared to the peripheral chemoreceptors, which have a time constant between 10 and 30 seconds.

[0044] equipment Human respiratory or gas exchange system equipment consists of equipment components. As discussed in this paper, a lumped equipment model includes at least the lungs, gas exchange units (i.e., alveoli), and gas transport units (i.e., hemoglobin). Furthermore, the equipment has a total equipment gain corresponding to the relationship between equipment inputs and equipment outputs.

[0045] Device gain and device gain modification Each device component has its own gain, that is, the relationship between input and output. These gains are non-linear, vary between individuals, and contribute to the overall device gain. Ventilation equipment is a complex interaction of dynamic device components. For example, the device gain of the lungs changes constantly due to air mixing, lung volume, heart rate, interstitial fluid, body position, and so on. To aid further understanding, several examples of contributions to the constantly changing device gain are given below, including the V / Q ratio and cycle delay.

[0046] The V / Q ratio is an expression of the operational efficiency of the alveoli in the lungs, representing the ratio of the number of ventilation units at the alveoli to the number of gas exchange units in the blood. The V / Q efficiency on the alveolar ventilation side varies depending on the partial pressures of oxygen (O2) and carbon dioxide (CO2). For each breath, respiratory depth and rate, as well as functional residual capacity (FRC) (i.e., the amount of air remaining in the lungs at the end of passive exhalation), all affect the partial pressures of gases present at the alveoli. Positive lung pressure affects V / Q by opening the small airways and increasing ventilation in the distal alveoli. Heart rate and cardiac output also affect perfusion efficiency and gas exchange processes, the latter depending on the movement of hemoglobin across the alveoli. Because the lungs are a complex pulmonary vascular network, respiratory depth and interstitial fluid levels also affect V / Q efficiency.

[0047] Another contribution to device gain is circulatory delay, whose central output can contribute to the cycle length of periodic respiration. The time delay in the arrival of newly perfused blood at chemopreceptors is a function of cardiac efficiency (e.g., related to ejection fraction, cardiac output, vascular resistance, and circulating volume). Circulatory delay is generally considered to increase the likelihood of Cheyne-Stokes respiration in patients with chronic heart failure and low left ventricular ejection fraction (LVEF) (e.g., 20%–50%). The cycle length of periodic respiration is generally considered to be correlated with LVEF, with longer cycle times associated with more impaired LVEF. In contrast, the cycle time observed in treating emergency periodic respiration is 30 seconds, while the cycle time in low LVEF (<20%) is close to 86 seconds. Besides the above, other device gains... regulator This may include heart rate, circulating blood volume, and hemoglobin levels, which will not be discussed further in this article.

[0048] Body compensatory regulators Some device components function in a compensatory manor to compensate for another damaged device (i.e., the damaged device). Several examples will now be discussed. One of the simplest examples is the heart rate response to hypoventilation. An increase in heart rate can be seen in obstructive sleep apnea (OSA) subjects to maintain adequate oxygen levels in the tissues during hypoventilation. In this example, hypoventilation is a decrease in device gain, while the increase in heart rate is an increase in device gain.

[0049] A second example of a device component functioning in a compensatory operating zone to compensate for another impaired device is chemosensitivity in central sleep apnea (CSA). In this example, central chemosensitivity is the response of the central controller to compensate for reduced cardiac output. Patients with chronic heart failure have impaired cardiac output, which results in a cyclic delay. The time delay between pulmonary gas exchange and blood reaching the chemosensors is longer than normal. This loop delay can be viewed as a reduction in device gain, and the central controller's compensatory response to this situation is an increase in CO2 chemosensitivity, which can be viewed as an increase in device gain.

[0050] Increased chemosensitivity was sufficient to maintain stable ventilation during the early stages of CO injury and deep sleep. As CO injury worsened, ventilation became unstable as the total loop gain approached -1 (1). This condition was described as an augmenting-decrease breathing pattern, periodic breathing, Cheyne-Stokes breathing (CSR), and Hunter Cheyne-Stokes breathing. The cycle time of periodic breathing was correlated with left ventricular ejection fraction (LVEF) and ranged from 60 to 90 seconds.

[0051] During initial exposure to positive airway pressure, approximately 5% to 15% of other healthy, non-cardiac patients develop therapeutic emergency periodic breathing. In these patients, exposure to positive airway pressure increases airway, gas exchange, and loop gain, resulting in unstable periodic breathing similar to CSR, but with a cycle duration of 30 seconds. This condition typically decreases over time; however, a small percentage of patients require similar therapeutic interventions as those with CSR.

[0052] A third example of a device component that functions in compensatory work zones to compensate for another impaired device is chemosensitivity in obstructive sleep apnea (OSA). Chemosensitivity and high loop gain have also been used to describe sleep-disordered breathing in OSA. Furthermore, high loop gain has been used to describe intermittent hypoxic mixed events in OSA subjects. In these centrally mediated hypoventilations, patients exhibit hyperventilation, leading to repetitive cycles of hyperventilation, reduced upper airway muscle expansion, and partial to complete closure of the upper airway. The ventilatory response to hypoxia is typically suppressed, resulting in hyperventilation and hypocapnia. While continuous positive airway pressure (CPAP) is the primary therapeutic intervention for airway collapse, CPAP increases device gain and can further promote loop gain. This can sometimes lead to over-titering of CPAP pressures until the loop gain is suppressed by excessively high expiratory positive airway pressure (EPAP) pressures.

[0053] Clinical physician device component gain modification Clinicians have sought interventions to improve ventilatory stability in patients with impaired loop gain by altering the gain of device components. In chronic heart failure, when patients experience ventilatory instability due to hyperchemisensitivity, treatment strategies involve increasing the gain of device components through modification. This affects the reduction of the operational burden on the central controller of the respiratory system, thereby decreasing its responsiveness to CO2 and O2 signals. Some strategies use positive inotropic drugs that increase cardiac contractility, targeting damaged myocardium.

[0054] In addition, positive pressure CPAP (continuous positive airway pressure) therapy in acute care has been used to improve cardiac output. Positive pressure increases device gain by increasing cardiac output through increased ventilation space, reduced venous return, and decreased ventricular volume as described by the Frank-Starling mechanism. Diuretics similarly alter device gain by controlling blood volume. Inhaled oxygen increases lung component gain by increasing perfusion efficiency. Inhaled CO2 increases carbon dioxide pressure (PCO2), and acetazolamide decreases alveolar carbon dioxide pressure (PACO2), both reducing the inhaled carbon dioxide pressure (PICO2) gradient. Changing body position to lateral or upright positions increases lung volume and its contribution to overall system loop gain.

[0055] System loop gain: The overall system loop gain is the system's response to disturbances. In a negative feedback system, the loop gain is the product of the controller and device gains and the observed error signals from central and peripheral chemopreceptors. In particular, according to the relationship given in Equation 1, the loop gain of a ventilation control system (i.e., the human respiratory system) can be quantified by four measurable factors.

[0056]

[0057] Where G describes the dynamic responsiveness of the controllers of the human respiratory system (peripheral and central chemoreceptor sensitivity). The remaining factors constitute the gain due to the device: PACO2-PICO2 is the PCO2 gradient of alveolar excitation for gas exchange (note that if the alveolar and excitation levels are equal, the device gain will be zero); lung volume represents the volume of gas in the lungs available to buffer changes in alveolar CO2; T is a complex time factor that depends primarily on the cycle delay and partly on the time constant of gas exchange in the lungs (formally, T = [(2π / [cycle period])]). 2 +1 / τlung2] -0.5 The same equation can be written to describe the additional contribution of feedback control via O2 to the loop gain. Since the controller gain G describes the ventilatory changes in response to changes in PCO2 (or PO2), G can be modified by other factors. In a CSA cycle, as ventilatory drive increases, typically accompanied by a progression from sleep to wakefulness, this further enhances ventilatory drive and consequently increases ventilatory oscillations and increases G. Furthermore, changes in upper airway patency occurring concurrently with PCO2 in patients with an upper airway response also increase G.

[0058] Clinical significance of loop gain: Loop gain becomes clinically significant in patients when ventilation control is affected by instability due to low or high loop gain. It has been determined that a system loop gain exceeds one (1) only under specific conditions (i.e., the system becomes unstable). Loop gain can be further understood according to general control theory, as follows. The response of a control system can be classified into three categories: underdamped, critically damped, and overdamped. Now refer to Figure 2 The diagram illustrates the responses of four control systems, labeled A(42), B(44), C(46), and D(48). System responses A, B, and D have loop gains less than 1, while system response C indicates a loop gain greater than 1. Figure 2 In the diagram, response curve A represents the underdamped response. Response curve B represents the overdamped response. Response curve C represents the unsteady underdamped condition where the loop gain is greater than 1. Finally, response curve D represents the critical damping condition.

[0059] Measuring Loop Gain: Several methods exist for measuring loop gain in both awake and sleeping patients. The wakefulness test has been used to measure loop gain through a single or series of breath-holds. Sleeping patients have undergone a CPAP descent test, where a decrease in CPAP pressure drives differences in device gain, corresponding differences in ventilation and effort are collected, and these differences are used to estimate loop gain. The model generated by this test has been further used to estimate loop gain from polysomnography (PSG) data without intervention.

[0060] Unfortunately, the loop gain values ​​produced by these methods are subject to the conditions under which the corresponding loop gain values ​​are determined, and the loop gain values ​​must be constructed at a specific frequency, which may differ from the fundamental frequency of a particular patient. Furthermore, for a given patient, the loop gain is not constant but varies based on sleep stage, body posture, and therapeutic stress level.

[0061] Clinical Applications of Loop Gain: In practice, the clinical use of loop gain can help clinicians provide personalized care. Loop gain can help validate a clinician's intuition about the type of treatment intervention. Protocols and guidelines are far from established, but possible baseline conditions may be collected, including measures from the field of respiratory science. These measures include the Apnea-Insufficiency Index (AHI), Arousal Index, Sleep Continuity Measures, Blood Gas, Desaturation Index, etc. Loop gain and / or some ventilatory stability measures associated with loop gain can be applied more generally to the population. This baseline data will be interpreted, and then the intervention will be introduced based on the interpretation.

[0062] Ideally, the intervention would be self-titered against a set of objectives. These objectives might be multifactorial, aimed at stabilizing breathing and / or treating underlying conditions such as obstructive sleep apnea. For example, CPAP increases loop gain by increasing device gain, thereby reducing the load on the central controller of the human respiratory system. In multifactor titration, the intervention examines the benefit to obstructive sleep apnea events as well as the benefit to loop gain. CPAP pressure can be increased until (i) no further benefit is observed in either outcome, or (ii) a negative effect is observed in either outcome. Without this approach, and focusing solely on event elimination, it is possible to increase device gain, leading to loop gain instability.

[0063] Post-treatment assessments can evaluate stability and common treatment goals. Regular follow-up, especially in some automated manner, will allow clinicians to adjust as needed.

[0064] With the development of positive airway pressure (PAP) therapy, a trend towards precision medicine or disease-specific medicine has emerged. A brief review of existing PAP therapy algorithms is included in Table 1 below. As will be described, each existing PAP therapy algorithm is designed to target a specific need. In many cases, pressure delivery is personalized to the individual throughout the therapy process.

[0065] Table 1

[0066]

[0067] Regarding the design of CPAP therapy and its common design elements, a basic positive airway pressure device includes a pneumatic source such as a rotary fan, a pressure sensor for closed-loop fan control, and a respiratory velocimeter for measuring airflow. The patient (or the person receiving treatment) is connected via a flexible tubing and a mask with a specially designed orifice to expel CO2. Using the pressure sensor as feedback, the fan speed is adjusted to the desired mask pressure, which includes the pressure drop across the tubing and mask determined by current flow conditions. Because mask pressure varies dynamically with pressure control, small residual flow-based control errors can affect the patient loop gain.

[0068] In addition to the above discussion, a brief review of several treatments indicated in Table 1 is provided below.

[0069] Continuous positive airway pressure (CPAP) therapy is primarily used for obstructive sleep apnea, but it can also be used to treat acute cardiogenic pulmonary edema.

[0070] Bilevel pressure (BiPAP) therapy provides alternating high and low pressure to drive ventilation during inspiration. This therapy modality is primarily used for patients with resistant, restrictive lung disease, and obese patients with hypoventilation. BiPAP provides consistent pressure support regardless of the patient's effort. The resulting tidal volume will vary and, depending on the configured pressure support level, the patient may be unable to control the inhaled tidal volume, which can destabilize patients with high loop gain and may lead to hypocapnia. BiPAP can be configured to provide machine-initiated or timed breathing when the patient lacks or reduces effort due to hypocapnia.

[0071] Average Volume Guaranteed Pressure Support (AVAPS) is a therapeutic modality that utilizes the benefits of BiPAP, featuring closed-loop control around a tidal volume setpoint. This modality benefits BiPAP patients and has the added benefit of adjusting pressure support based on the patient's muscle effort. AVAPS can also support mechanical ventilation.

[0072] Proportional assisted ventilation (PAV) is a therapy modality that monitors transient patient flow rate. And volume (V) to achieve and according to the equation of motion Calculate the applied pressure (P), where f1 and f2 are functions of the appropriate choice of the relationship between pressure and volume (elastic aid) and the relationship between pressure and flow rate (resistive aid).

[0073] Automated servo ventilation (ASV) is a therapy mode designed to treat patients with high-loop-gain ventilation control deficits. An ASV device monitors certain aspects of ventilation and provides pressure support only when needed to maintain a certain percentage (typically 90% of the monitored value). Because of this percentage, ASV devices are designed to allow patient-guided therapy. Similar to BiPAP, machine breathing can be configured in this mode.

[0074] Various problems and / or disadvantages are overcome by the positive airway pressure therapy system utilizing loop gain for ventilation stability according to embodiments of the present disclosure, further as can be understood from the discussion herein.

[0075] Referring again to Table 1 above, automated servo ventilation is described as a therapy designed to treat conditions with high loop gain. Existing automated servo devices monitor certain aspects of ventilation over several minutes, calculate a certain percentage of that value, and provide pressure support as needed to ensure that future ventilation volumes reach at least that magnitude. These ventilation targets are some measure of the magnitude of ventilation, such as tidal volume, minute ventilation, or peak flow. However, this existing technology has several drawbacks that require improvement. Current ASV devices only provide pressure support for a period of time during which respiratory reduction (hypoventilation) occurs. The pressure support provided by current ASV devices only drives more ventilation for the patient. During hyperventilation (i.e., increased ventilation), current ASV devices revert to a pressure mode equivalent to CPAP, which is essentially non-therapeutic in terms of reducing the increase or decrease in respiratory modes.

[0076] The shortcomings discussed in the previous paragraph are addressed in U.S. Patent 9,463,293, entitled "SERVO VENTILATION USING NEGATIVE PRESSURE SUPPORT," and U.S. Patent 9,044,560, entitled "SERVO VENTILATION USING PRESSURE DROP FROMBASELINE." Both patents describe a method that includes reducing ventilation when muscle effort exceeds a baseline. These methods continue to target ventilation at a certain amplitude, increasing pressure support whenever muscle effort falls below the baseline, and increasing pressure support whenever muscle effort exceeds the baseline. While these methods provide the ability to control hyperventilation aspects of servo device therapeutic therapy, they do not provide targeted therapy specific to insufficient loop gain.

[0077] Therefore, embodiments of this disclosure advantageously provide a positive airway pressure (PAP) therapy algorithm that addresses loop gain deficiencies by targeting the root cause of the deficiency.

[0078] In addition to the definitions provided above, the following additional definitions shall apply to embodiments of this disclosure:

[0079] Loop gain (or “loop gain”): The formal diagnostic assessment of respiratory loop gain is well established in the clinical community. Some of these assessment methods involve laboratory testing, while others, less invasive, have been described using information from polysomnography (PSG). In central sleep apnea (CSA) and the periodic breathing that occurs during treatment, patients with loop gain exhibit cyclic breathing patterns that are well mathematically described in frequency domain mathematics. In obstructive sleep apnea (OSA), the hyperventilatory response to obstructive events requires different analytical approaches. For the description of this work, it is recognized that there will not be a single form of representation, and the term loop gain will be used as a general term, not specific to any particular algorithm or method for determining loop gain. For the purposes of this discussion, loop gain can be any form of descriptive representation of ventilatory stability, including but not limited to existing known published forms of loop gain, response time constants, rate of change measures, slew rate, overshoot measurements, sleep stages, wakefulness, etc. Furthermore, artificial intelligence can be used to construct models that represent loop gain as a composite metric.

[0080] Flow-based gain therapy (FBGT) is a general term that can combine one or more specific means to alter the interaction between device-assisted ventilation (PAP) therapy and the patient. As discussed above with reference to U.S. Patent 9,463,293 entitled “SERVO VENTILATION USING NEGATIVE PRESSURE SUPPORT” and U.S. Patent 9,044,560 entitled “SERVO VENTILATION USING PRESSURE DROP FROM BASELINE”, it is possible to counteract muscle exertion during movement and reduce effective ventilation in the patient using negative pressure support. For embodiments of this disclosure, compared to the mentioned patent literature, the system and method utilize a flow-based gain (or flow-based gain factor) capability, by which a portion of the supported mask pressure is calculated as a gain factor multiplied by the instantaneous patient flow rate. The gain factor (i) promotes ventilation when positive and (ii) restricts ventilation when negative. While the application of patient flow-based gain may appear similar to proportional assisted ventilation (PAV) equations (as further discussed herein), there are significant differences in intent. PAV incorporates a flow-based gain factor to overcome respiratory impedance. In the therapy according to embodiments of the systems and methods of this disclosure, altering the flow-based gain (or flow-based gain factor) to manage ventilatory stability includes applying a negative gain to counteract muscle effort. Flow-based ventilatory gain therapy acts as a control stabilizer for the central controller of the human respiratory system.

[0081] The system and method embodiments of positive airway pressure therapy (PAP) utilizing loop gain for ventilatory stability disclosed herein advantageously address the role of chemosensitivity in patients with chronic respiratory distress syndrome (CSA). For CSA and the treatment of emergency periodic breathing, during the adjustment of breathing modes, the system includes a gain scheduler configured to schedule a flow-based gain proportional to the magnitude and / or rate of change in the adjustment mode, increasing or decreasing the patient's effort to counteract unstable muscle effort. In doing so, PAP therapy utilizing loop gain to achieve ventilatory stability provides more standardized ventilation and introduces a central controller of the human respiratory system into a stable breathing pattern.

[0082] The system and method embodiments of positive airway pressure therapy (PAP) utilizing loop gain for ventilatory stability disclosed herein also advantageously address the role of chemosensitivity in OSA patients. Patients with obstructive sleep apnea who are chemosensitized will also benefit from PAP therapy that utilizes loop gain to maintain ventilatory stability. During obstructive events, ventilation fluctuates significantly due to arousal responses to hypoxemia. This therapy (i.e., utilizing loop gain to maintain ventilatory stability) provides similar benefits to patients via flow-based gain scheduling. In this patient's case, most obstructive events are prevented by not allowing muscle effort to cause fluctuations in minute ventilation sufficient to initiate this adverse pattern.

[0083] According to embodiments of this disclosure, a positive airway pressure therapy system utilizing loop gain for ventilation stability includes system components for performing at least one sub-therapy (e.g., flow-based gain therapy (FBGT)). As discussed, FBGT involves several sub-processes, including condition monitoring, response determination, therapy delivery, and information reporting. A brief discussion of each sub-process is provided below.

[0084] Regarding condition monitoring and the generation of flow-based gain factors (or flow-based gain values), the system and methods are based on and / or combined with the following. Loop gain control is based on a flow-based gain factor that counteracts the action of the central controller in the human respiratory system. In patients with high loop gain and chemosensitivity, the central controller over-responds to chemical stimuli from chemisenters. The goal of FBGT is to prevent and / or assist ventilation under unstable conditions by using pressure support acting on and / or through the action of the diaphragm, thereby preventing over- and / or under-compensation by the central controller. Throughout respiration, the flow-based pressure amplification is calculated as the product of patient flow rate and the flow-based (FB) gain factor, according to the following expression:

[0085] FB pressure amplification = (patient flow) × (FB gain value).

[0086] It is important to understand that this calculation of FB pressure amplification occurs continuously throughout the respiratory process. The sign of the patient flow rate is positive during inspiration and negative during expiration. If the FB gain factor is positive, the result will be an increase in ventilation. Conversely, if the FB gain factor is negative, the result will be a decrease in ventilation. The following sections will now discuss how to determine this FB gain factor, and then how to apply it.

[0087] FBGT design can accommodate various forms of instability. In the first example, consider a CSA patient exhibiting periodic breathing (i.e., increase and decrease). The FB gain factor can be updated based on the current phase of this cycle, moving in the opposite direction to cyclic ventilation. In this workspace, the gain factor is configured as a central controller directly opposing the human respiratory system. Next, consider a patient exhibiting acute sleep apnea (SDB) events with overshoot and undershoot. In this case, the FB gain (or FB gain factor) can be adjusted so that it becomes active only during acute SDB events. In this example, the gain would be adjusted to become negative during ventilatory overshoot and positive during ventilatory undershoot. Other examples of conditions include obesity-related hypoventilation syndrome and respiratory event-related arousal, where gain adjustment is condition-specific and occurs only when the corresponding condition's conditions occur.

[0088] Artificial intelligence (AI) can be employed to generate comprehensive models of loop gain using a multivariate approach with ventilation metrics. Ventilation metrics can include one or more common respiratory parameters, such as tidal volume, minute ventilation, and sleep apnea events. Ventilation metrics may also include time windowing and / or statistical treatments for minimum, maximum, and standard deviation. Given one or more independent variables, machine learning (ml) can be used to generate models or functions useful for predicting or determining loop gain; these independent variables can include ventilation metrics and / or features. One advantage of this approach is that machine learning models may be computationally less expensive than the target computation. Multivariate results may also be more generalizable to a wide range of populations and situations or limited to specific populations and situations. Machine learning techniques include multivariate linear regression and neural networks.

[0089] In a positive airway pressure therapy system utilizing loop gain for ventilation stability according to embodiments of this disclosure, FBGT is based on the calculation of at least one model comprising at least one metric describing ventilation stability; however, it is understood that this may be a large number of models comprising a large number of metrics (i.e., stability metrics). For example, at least one or more models may be generated by one or more of AI, ml, or a combination of AI and ml. Several embodiments of stability metrics may include one or more of the following:

[0090] a) Clinical loop gain as defined in the current literature (e.g., Formula 1 disclosed herein may be used);

[0091] b) The statistical correlation with the clinical loop gain in (A), wherein the statistical correlation is generated using the features discussed further below; and

[0092] c) Composite metrics generated using the features discussed below.

[0093] It is easy to understand that various features can be used to define respiratory stability. In particular, many respiratory features are helpful in constructing stability measures, including but not limited to:

[0094] i) Rate of change of minute ventilation.

[0095] ii) Ventilation overshoot detection,

[0096] iii) Ventilation under-adjustment detection,

[0097] iv) The period, phase, and amplitude of periodic breathing.

[0098] v) Models that handle CO2 consumption

[0099] vi) Models for handling sleep stages and / or central nervous system arousal.

[0100] vii) Simple average minute ventilation when opening windows, and

[0101] viii) Any combination of the above items.

[0102] In a positive airway pressure therapy system utilizing loop gain for ventilation stability according to embodiments of the present disclosure, the output of FBGT is a gain factor that is appropriately scaled to provide pressure support in a form opposite to that driven by the patient's muscle effort. According to embodiments of the present disclosure, once the FB gain factor is determined, it becomes part of the FBGT therapy subsystem.

[0103] In one embodiment, the system and method generate a 4-minute moving window of minute ventilation. The gain factor is determined by subtracting the 4-minute average from the average minute ventilation over three breaths. This difference is then multiplied by a scaling factor, typically a value between 0.01 and 0.09, and more preferably a value of 0.07 as a recommended value. In other words, the gain factor is determined according to the following expression:

[0104] FB gain factor = (4-minute mean minimum ventilation - 3-breath mean minimum ventilation) ×

[0105] (Proportion factor).

[0106] Turn now Figure 3This diagram illustrates a functional block diagram of a system 50 for positive airway pressure therapy that utilizes loop gain for ventilation stability according to an embodiment of the present disclosure. The positive airway pressure therapy system 50 includes a ventilator source 52, a database 54, a user interface 56, optional ventilation components 58, and a controller 60 operatively coupled to the ventilator source 52, the database 54, the user interface 56, and the optional ventilation components 58. The ventilator source or airflow generator 52 includes any suitable ventilator or airflow generator having an output port 62 configured to output ventilating gas. The output port 62 is configured to connect to a first plurality of ventilation components in a ventilation loop 64 between the ventilator source 52 and the patient 70.

[0107] In other words, the system 50 for delivering airflow to the airways of a patient's respiratory system includes a ventilator source or airflow generator 52, at least one sensor 74, and a loop gain controller 60. The airflow generator 52 generates airflow and delivers it to the patient circuit 64 to deliver airflow to the airways of the patient's respiratory system. The at least one sensor 74 generates an output signal associated with at least one characteristic related to the airflow. The loop gain controller 60, in response to the output signal generated by the at least one sensor 74, selectively controls the airflow to the airways of the patient's respiratory system according to a positive airway pressure (PAP) therapy mode. The airflow flowing into the airways of the patient's respiratory system from the airflow generator 52 via the patient or ventilation circuit 64 is a positive flow, and the airflow flowing out of the airways of the patient's respiratory system is a negative flow. Furthermore, the PAP therapy mode of the system 50 is configured to address insufficient respiratory system loop gain corresponding to ventilatory instability by utilizing loop gain to achieve ventilatory stability.

[0108] The PAP therapy system 50 is adapted for use with a patient or ventilation circuit 64, which may include multiple different ventilation circuit assemblies. The various ventilation circuit assemblies include at least one or more of a ventilation hose or tube 66 and a patient interface 68. The patient interface 68 may include any of a variety of patient interfaces attached to a patient 70 during ventilation therapy. The patient interface 68 may be invasively attached to the patient, such as with an endotracheal tube or tracheostomy tube, or non-invasively connected, such as with a nasal mask, full face mask, or nasal cannula. A caregiver or operator 72 may be present during the initial setup of the ventilator system device 50 and / or, if needed, provide assistance during ventilation therapy to the patient 70. The ventilation circuit assembly may also include one or more optional ventilation components 58 (e.g., a humidifier, heater, nebulizer, etc.), one or more sensors 74 (e.g., a temperature sensor, a flow sensor, etc.), and one or more valves 76. In one embodiment, the ventilation hose 66 includes a hose clamp (not shown) at its end configured to couple to an output port 62 of the ventilator source 52.

[0109] Still referencing Figure 3 The database or storage 54 includes an electronic storage medium that stores information electronically. The electronic storage medium of the database storage 54 may include one or both of system storage provided integrally with the system 50 (i.e., substantially non-removable) and removable storage removably connected to the system 50 via, for example, a port (e.g., USB port, FireWire port, etc.) or a drive (e.g., a disk drive, etc.). The database or storage 54 may include one or more of the following: optically readable storage media (e.g., optical disc, etc.), magnetically readable storage media (e.g., magnetic tape, magnetic hard disk drive, floppy disk drive, etc.), charge-based storage media (e.g., EPROM, EEPROM, RAM, etc.), solid-state storage media (e.g., flash memory drive, etc.), and / or other electronically readable storage media. The database or storage 54 may store software algorithms, information determined by the controller 60, information received via the user interface 56, and / or other information that enables the system 50 to function properly. The database or storage 54 may be a separate component within the system 50, or the database storage 54 may be provided integrally with one or more other components of the system 50 (e.g., the controller 60). Furthermore, the database or storage 54 can ideally be contained and maintained (i.e., updated) on a web server, a shared computer, based on the Internet, or contained in a third-party data center, and the system 50 can access the data via telecommunications protocols (e.g., via a wired or wireless communication connection to the third-party data center).

[0110] User interface 56 is configured to provide an interface between system 50 and a user (e.g., operator 72, patient or subject 70, caregiver, therapy decision-maker, etc.) through which the user can provide and receive information from system 50. User interface 56 enables the transmission of one or more of data, results and / or instructions, and any other communicable items (collectively, “information”) between the user and system 50. Examples of information that can be transmitted to patient 70 or user 72 are reports detailing trends in the patient’s breathing patterns, such as respiratory rate, tidal volume, and applied pressure during (breathing) therapy. Another example of information that can be conveyed by patient 70 and / or user 72 is an alarm or unsafe condition detected by system 50. Examples of interface devices suitable for inclusion in user interface 56 include keypads, buttons, switches, keyboards, knobs, levers, displays, touchscreens, speakers, microphones, indicator lights, audible alarms, and printers. Information can be provided to patient 70 via user interface 56 in the form of auditory, visual, tactile, and / or other sensory signals. In one embodiment, user interface 56 may be integrated with a removable storage interface provided by a database or storage 54. In such an example, information is loaded from removable storage (e.g., a smart card, flash drive, removable disk, etc.) that allows the user to customize the implementation of system 50. Other technologies for communicating with system 50 are envisioned as user interface 56.

[0111] As described above, controller 60 is operatively coupled to ventilator source or airflow generator 52, database 54, user interface 56, and optional ventilation assembly 58. Controller 60 includes one or more modules, including at least a stability measurement module 80, a condition monitoring module 82, a loop gain decision module 84, a therapy prescription decision module 86, and a pressure delivery module 88, as will be discussed further herein. Furthermore, controller 60 can be configured for wired or wireless communication with remote devices or networks, for example, as indicated by reference numeral 78.

[0112] In one embodiment, controller 60 includes one or more of the following: a microprocessor, a microcontroller, a field-programmable gate array (FPGA), an integrated circuit, discrete analog or digital circuit components, hardware, software, firmware, or any combination thereof, for further performing the various functions discussed herein according to the requirements of a given ventilator system device implementation and / or application. Controller 60 may also include one or more of the various modules discussed herein. Additional details regarding controller 60 are provided below with reference to the accompanying drawings. Furthermore, modules 80-88 may include one or more of the following: integrated circuits, discrete analog or digital circuit components, hardware, software, firmware, or any combination thereof, for further performing the various functions discussed herein according to the requirements of a given ventilator system device implementation and / or application. Furthermore, one or more of modules 80-88 may also include various combinations of one or more of the various modules. It should also be understood that the described modules may be computer program modules rendered in a non-transitory computer-readable medium.

[0113] The stability measurement module 80 of the controller 60 is configured to determine at least one stability metric. The at least one stability metric includes one or more of the following: (a) clinical loop gain, (b) statistical correlation with the clinical loop gain in (a), and (c) a composite metric. Clinical loop gain is defined as: Wherein G describes the dynamic response of the patient ventilation system controller, PACO2-PICO2 is the PCO2 gradient generated by alveolar excitation for gas exchange, lung volume represents the volume of gas available in the patient's lungs to buffer changes in alveolar CO2, and T is a complex time factor determined primarily by the cycle delay and partly by the time constant for gas exchange in the lungs. Furthermore, the statistical correlation with the clinical loop gain in (a) is generated based on respiratory characteristics, as described below. Additionally, the composite metric is generated based on respiratory characteristics. The respiratory characteristics used to generate the statistical correlation or composite metric for at least one stability metric, determined via the stability metric module and / or condition monitoring module, include one or more of the following: i) the rate of change of minute ventilation, ii) ventilation overshoot detection, iii) ventilation undershoot detection, iv) the period, phase, and amplitude of periodic breathing, v) a model handling CO2 consumption, vi) a model handling sleep stages and / or central nervous system arousal, vii) a simple open-window mean minute ventilation, and viiii) any combination of the above.

[0114] The condition monitoring module 82 of the controller 60 is configured to monitor the ventilation characteristics of airflow in the patient's respiratory system and provide an output indicating the monitored ventilation characteristics. The monitored ventilation characteristics correspond at least to the occurrence of a sleep-disordered breathing (SDB) event in the patient's respiratory system.

[0115] The loop gain decision module 84 of the controller 60 is configured to determine future ventilation characteristic targets and device gain targets based on at least one determined stability metric and output from the condition monitoring module. In one embodiment, the future ventilation characteristic targets and device gain targets determined via the loop gain decision module 84 include amplitude and / or phase information of airflow in the airway of the patient's respiratory system. The future ventilation characteristic targets and device gain targets also provide loop gain control in response to the delivery of therapeutic command pressure or delivery characteristics via the pressure delivery module 88. Furthermore, based on amplitude and / or phase information, the future ventilation characteristic targets and device gain targets modify the loop gain in the patient's respiratory system by increasing or decreasing it to achieve ventilation stability via backflow-based gain.

[0116] The therapy prescription decision module 86 of the controller 60 is configured to determine the therapy command pressure or delivery characteristics based on the determined future ventilation characteristic targets and equipment gain targets, wherein the therapy command pressure or delivery characteristics include a single command pressure or delivery characteristic or a combination of more than one command pressure or delivery characteristic.

[0117] The pressure delivery module 88 of the controller 60 is configured to control the ventilation source or airflow generator 52 to deliver airflow to the patient's airway for future breathing at a determined therapeutic command pressure or delivery characteristics. In other words, the pressure delivery module 88 is configured to control the operation of the ventilator source 52, wherein the operating parameters are determined at least based on the output of the therapy prescription decision module 86. Furthermore, the outputs of various modules can be advantageously used to estimate the compliance of the ventilation circuit, thereby improving the accuracy of circuit compensation. Improved accuracy of circuit compliance leads to improved estimation of patient parameters such as flow rate, tidal volume, and respiratory parameters such as work of breathing (WOB), muscle pressure (Pmus), pressure-time product (PTP), and intrinsic positive end-expiratory pressure (PEEPi). These parameters are commonly used to assess patient condition or as inputs to closed-loop ventilator control. Each component can have categorized compliance, or compliance can be estimated based on the compressibility of the gas and an estimate of the component's amplitude via the gas volume (i.e., space) within a given component. Circuit compliance is used to correct distal measurements to corresponding proximal values ​​for a reference patient. Distal measurements are more accurate when circuit-induced losses (including compliance losses) are corrected for. Regarding circuit compliance, the phrase "circuit compensation," used herein, refers to corrective measures applied to circuit compliance. In other words, ventilator source 52 is configured to deliver a ventilating gas with one or more ventilation characteristics in response to one or more operating parameters provided via pressure delivery module 88, thereby providing improved patient parameter monitoring and feedback control in an improved closed-loop ventilator.

[0118] In one embodiment, future ventilation characteristic targets and device gain targets determined via loop gain decision module 84 modify the device gain of one or more device components of the patient's respiratory system. Specifically, the future ventilation characteristic targets and device gain targets modify the device gain via changes in one or more pressure delivery characteristics. One or more pressure delivery characteristics may include one or more of the following: (i) baseline pressure, (ii) inspiratory pressure, and (iii) expiratory pressure.

[0119] In another embodiment, the loop gain decision module 84 further includes a flow-based gain scheduler. The flow-based gain scheduler is configured to (i) schedule a flow-based gain proportional to the amplitude and / or rate of change in the patient's increasing / decreasing breathing effort pattern. The flow-based gain scheduler is also configured to (ii) increase or decrease the patient's breathing effort to counteract unstable increasing / decreasing muscle effort in the patient's respiratory system. In other words, the flow-based gain scheduler is configured to (i) schedule a flow-based gain proportional to the amplitude and / or rate of change of a signal obtained via a condition monitoring module representing a sleep disorder breathing pattern, and (ii) increase or decrease airflow via a pressure delivery module to counteract unstable breathing effort in the patient's respiratory system. Furthermore, the therapy prescription decision module 86 is also configured to determine the therapy command pressure or delivery characteristics based at least on the loop gain input from the flow-based gain scheduler. The therapy command pressure or delivery characteristic is configured, when delivered, to generate a flow-based gain for providing pressure therapy in a manner sufficient to provide baseline pressure to overcome obstructive SDB events; or in other words, the therapy command pressure or delivery characteristic is configured, when delivered, to regulate the flow-based gain and device gain configured to normalize loop gain.

[0120] In another embodiment, the future ventilation characteristic target determined via the loop gain decision module includes a flow-based pressure amplification continuously calculated throughout the respiratory period. The calculated flow-based pressure amplification is the product of (i) the instantaneous patient airway gas flow rate and (ii) the flow-based gain factor. Furthermore, the sign of the instantaneous patient airway gas flow rate is positive during inspiration and negative during expiration. Additionally, for positive values ​​of the determined flow-based gain factor, the loop gain controller 60 drives ventilation via the pressure delivery module 88 and the airflow generator 52 to increase ventilation of the patient's respiratory system. For negative values ​​of the determined flow-based gain factor, the loop gain controller 60 restricts ventilation via the pressure delivery module 88 and the airflow generator 52 to reduce ventilation of the patient's respiratory system.

[0121] According to another embodiment, the loop gain decision module 84 is further configured to determine a flow-based gain factor, wherein determining the flow-based gain factor includes adjusting the flow-based gain factor. The determined or adjusted flow-based gain factor is based on the condition of the patient's respiratory system monitored during the current instability phase of the patient's respiratory cycle in response to the output signal generated by at least one sensor 74. Additionally, the loop gain decision module 84 adjusts the flow-based gain factor for a given condition, and the adjustment occurs only while the condition of the corresponding condition is occurring in the patient's respiratory system. In another embodiment, the condition monitoring module 82 is further configured to collect and monitor the output signal of at least one sensor 74, which corresponds to the input for determining the respiratory system loop gain in positive airway pressure (PAP) therapy.

[0122] Now for reference Figure 4 A flowchart view of a method 90 for positive airway pressure therapy utilizing loop gain for ventilation stability, according to an embodiment of the present disclosure, is shown. The method 90 for delivering airflow to the airway of a patient's respiratory system includes: generating airflow (in step 94), generating an output signal (in step 96), and selectively controlling (via a loop gain controller 60) Figure 3 The airflow to the patient's respiratory system (in step 98). The generation and delivery of airflow to the patient circuit (in step 94) is via airflow generator 54. Figure 3 This is accomplished to further deliver airflow to the patient's respiratory airway. The generation of an output signal associated with at least one characteristic related to the airflow (in step 96) is via at least one sensor 74. Figure 3 The selective control of airflow to the patient's respiratory system is further accomplished via a loop gain controller 60 in response to an output signal generated via at least one sensor 74, according to the positive airway pressure (PAP) therapy mode. Airflow into the patient's respiratory system from the airflow generator 52 via the patient loop 64 is positive, and airflow out of the patient's respiratory system is negative. The PAP therapy mode is configured to address insufficient respiratory loop gain corresponding to ventilatory instability by utilizing loop gain to achieve ventilatory stability.

[0123] Now for reference Figure 5 This shows another flowchart view of a portion of a method for positive airway pressure therapy utilizing loop gain for ventilation stability according to an embodiment of the present disclosure, corresponding to step 98 ( Figure 4 That is, selectively controlled via loop gain controller 60. The method includes wherein selective control via loop gain controller 60 (step 98) includes: (a) via stability measurement module 80 ( Figure 3(a) Determine at least one stability metric (step 100), (b) Monitor the ventilation characteristics of airflow in the patient's respiratory system via the condition monitoring module 82 and provide an output indicating the monitored ventilation characteristics (step 102), wherein the monitored ventilation characteristics correspond at least to the occurrence of a sleep-disordered breathing (SDB) event in the patient's respiratory system, (c) Determine future ventilation characteristic targets and device gain targets via the loop gain decision module based on the determined at least one stability metric and the output from the condition monitoring module (step 104), (d) Determine a therapy command pressure or delivery characteristic via the therapy prescription decision module 86 based on the determined future ventilation characteristic targets and device gain targets (step 106), wherein the therapy command pressure or delivery characteristic includes a single command pressure or delivery characteristic or a combination of more than one command pressure or delivery characteristic, and (e) Control the airflow generator 52 via the pressure delivery module 88 to deliver airflow to the airways of the patient's respiratory system at the therapy command pressure or delivery characteristic for future breathing (step 108).

[0124] After the airflow is delivered in step 108, the loop gain controller queries whether to continue the therapy (step 110). In response to continuing the therapy, the method returns to step 100, where at least one stability metric is determined via the stability metric module 80. Conversely, in response to not continuing the therapy, the method terminates.

[0125] According to another embodiment, the method includes future ventilation characteristic targets and device gain targets determined via loop gain decision module 84: (i) including amplitude and / or phase information of airflow in the airway of the patient's respiratory system; (ii) providing loop gain control in response to the delivery of a therapy command pressure or delivery characteristic via pressure delivery module 88; and (iii) modifying the loop gain in the patient's respiratory system by increasing or decreasing, based on amplitude and / or phase information, via a backflow-based gain, to achieve ventilation stability. Furthermore, the future ventilation characteristic targets and device gain targets determined via loop gain decision module 84 modify the device gain of one or more device components of the patient's respiratory system via changes in one or more pressure delivery characteristics. One or more pressure delivery characteristics include one or more of the following: (i) baseline pressure, (ii) inspiratory pressure, and (iii) expiratory pressure.

[0126] According to another embodiment, the method includes, via loop gain controller 60, selectively controlling: (c)(i) scheduling a flow-based gain via a flow-based gain scheduler of the loop gain decision module, the flow-based gain being proportional to the magnitude and / or rate of change in the pattern of increase or decrease in the patient's respiratory effort; and (c)(ii) increasing or decreasing the patient's respiratory effort via determined future ventilation characteristic targets and device gain targets, thereby counteracting unstable increase or decrease in muscle effort in the patient's respiratory system. In another embodiment, the method includes, via loop gain controller 60, selectively controlling: (d)(i) determining a therapy command pressure or delivery characteristic via therapy prescription decision module 86 based at least on loop gain input from the flow-based gain scheduler, wherein the therapy command pressure or delivery characteristic, when delivered, is configured to generate a flow-based gain that provides pressure therapy in a manner sufficient to overcome obstructive SDB events, or in other words, the therapy command pressure or delivery characteristic, when delivered, is configured to regulate the flow-based gain and device gain configured to normalize the loop gain.

[0127] Embodiments of this disclosure advantageously provide a PAP device with integrated ventilatory stability features, wherein stability is based on loop gain. Various examples of PAP interventions and corresponding mechanisms for reducing ventilatory instability (i.e., loop gain) can be briefly summarized below. For optimized treatment interventions for heart failure, mechanisms for reducing ventilatory instability may reduce chemosensitivity and circulatory delay. For continuous positive airway pressure (CPAP) interventions, mechanisms for reducing ventilatory instability (i) increase lung volume, (ii) may have effects on cardiogenic pulmonary edema and related effects on chemosensitivity, and (iii) provide possible long-term effects on cardiac function and circulatory delay. For supplemental oxygen interventions, mechanisms for reducing ventilatory instability reduce carotid body chemosensitivity. For interventions with ventilatory stimulants (e.g., acetazolamide and supplemental CO2), mechanisms for reducing ventilatory instability include acetazolamide reducing alveolar PCO2 and supplemental CO2 increasing inhaled PCO2, both of which reduce the alveolar inhaled PCO2 gradient. Interventions in body posture (e.g., lateral or upright position relative to supine position) reduce ventilatory instability by increasing lung volume. Additional interventions and corresponding mechanisms for reducing ventilatory instability are possible.

[0128] Although several exemplary embodiments have been described in detail above, those skilled in the art will readily understand that many modifications may be made to the exemplary embodiments without substantially departing from the novel teachings and advantages of the embodiments of this disclosure. Therefore, all such modifications are intended to be included within the scope of the embodiments of this disclosure as defined in the following claims. In the claims, the apparatus plus function clause is intended to cover structures described herein as performing said functions, and includes not only structural equivalents but also equivalent structures.

[0129] Furthermore, any reference numerals placed in parentheses within one or more claims should not be construed as limiting the claims. The terms "comprising" and "comprises," etc., do not exclude the presence of elements or steps other than those listed in any claim or the entire specification. A singular reference to an element does not exclude a plural reference to such an element, and vice versa. One or more embodiments may be implemented by hardware comprising several different elements and / or by a suitably programmed computer. In a device claim enumerating several means, several of these means may be embodied by the same hardware item. The fact that certain measures are enumerated only in mutually different dependent claims does not indicate that a combination of these measures cannot be used advantageously.

Claims

1. A system (50) for delivering airflow to the airways of a patient's respiratory system, the system comprising: An airflow generator (52) is configured to generate the airflow, wherein the airflow generator is also configured to deliver the airflow to a patient circuit (64); At least one sensor (74) is configured to generate an output signal associated with at least one characteristic related to the airflow; as well as The controller, characterized in that the controller comprises: A loop gain controller (60) is configured to selectively control the airflow from the airflow generator (52) via the patient circuit (64) according to a positive airway pressure (PAP) therapy mode targeting insufficient loop gain, in response to the generated output signal, wherein the loop gain controller (60) includes: (a) A stability metric module (80) is configured to determine at least one ventilation stability metric related to loop gain, the at least one ventilation stability metric describing ventilation stability. (b) A condition monitoring module (82) is configured to monitor the ventilation characteristics of the airflow and provide an output indicating the monitored ventilation characteristics, wherein the monitored ventilation characteristics correspond at least to the occurrence of a sleep-disordered breathing (SDB) event. (c) A loop gain decision module (84) is configured to determine future ventilation characteristic targets and device gain targets based on the determined ventilation stability metric and the output from the condition monitoring module (82), wherein the future ventilation characteristic targets and the device gain targets modify the loop gain in the patient's respiratory system by increasing or decreasing to achieve ventilation stability. (d) A therapy prescription decision module (86) is configured to determine a therapy command pressure or delivery characteristic based on the determined future ventilation characteristic target and the device gain target, and (e) A pressure delivery module (88) is configured to control the airflow generator to deliver the airflow for future breathing at the determined therapeutic command pressure or delivery characteristics to overcome the loop gain deficiency and provide ventilation stability. The future ventilation characteristic target determined by the loop gain decision module includes a flow-based pressure amplification continuously calculated throughout the respiratory period, wherein the calculated flow-based pressure amplification is the product of (i) the instantaneous patient airway gas flow rate and (ii) a flow-based gain factor, wherein the loop gain decision module is further configured to determine the flow-based gain factor, and wherein the loop gain decision module adjusts the flow-based gain factor for a given condition, and the adjustment occurs only when a condition corresponding to the condition determined by the condition monitoring module is occurring.

2. The system (50) according to claim 1, wherein the at least one ventilation stability measure includes one or more of the following: (a) Clinical loop gain, defined as follows: ， in G Describing the dynamic responsiveness of the respiratory system controller, PACO2-PICO2 is the PCO2 gradient of alveolar inhalation used for gas exchange, and lung volume represents the volume of gas in the patient's lungs that can be used to buffer changes in alveolar CO2. T It is a complex time factor, which is determined primarily by the cycle delay and in part by the time constant for gas exchange in the lungs; (b) The statistical correlation between the clinical loop gain described in (a) and the statistical correlation generated based on respiratory characteristics; and (c) A composite metric, wherein the composite metric corresponds to a model representing loop gain, wherein the model is constructed based on respiratory features via artificial intelligence, machine learning or a combination thereof.

3. The system (50) of claim 2, wherein the respiratory characteristics determined via the stability measurement module for generating the statistical correlation or composite measurement of the at least one ventilation stability measurement include one or more of the following: i) Rate of change of minute ventilation ii) Ventilation overshoot detection, iii) Ventilation under-adjustment detection, iv) The period, phase, and amplitude of periodic breathing. v) Models that handle CO2 consumption vi) Models for handling sleep stages and / or central nervous system arousal. vii) Simple average minute ventilation when opening windows, and viii) Any combination of the above items.

4. The system (50) of claim 1, wherein the future ventilation characteristic target and the device gain target determined via the loop gain decision module (84) include: (i) amplitude and / or phase information of the airflow; (ii) loop gain control in response to the delivery of the therapeutic command pressure or delivery characteristic via the pressure delivery module (88); and (iii) the loop gain is modified for ventilation stability by increasing or decreasing, based on the amplitude and / or phase information, via a gain based on the reverse flow.

5. The system (50) of claim 1, wherein the future ventilation characteristic target and the device gain target determined via the loop gain decision module (84) modify the device gain of one or more device components via changes in one or more pressure delivery characteristics.

6. The system (50) of claim 1, wherein the loop gain decision module (84) further comprises a flow-based gain scheduler, the flow-based gain scheduler being configured to increase or decrease the patient’s respiratory effort to counteract unstable increases or decreases in muscle effort in the patient’s respiratory system.

7. The system (50) of claim 6, wherein the flow-based gain scheduler is configured to: (i) schedule a flow-based gain proportional to the amplitude and / or rate of change of a signal obtained via the condition monitoring module, the signal representing a sleep disorder breathing pattern; and (ii) increase or decrease the airflow via the pressure delivery module to counteract unstable breathing efforts in the patient's respiratory system.

8. The system (50) of claim 6, wherein the therapy prescription decision module (86) is further configured to determine the therapy command pressure or delivery characteristic based at least on the loop gain input from the flow-based gain scheduler, wherein the therapy command pressure or delivery characteristic is configured, when delivered, to generate a flow-based gain that provides pressure therapy in a manner sufficient to overcome a baseline pressure of a blocking SDB event, or the therapy command pressure or delivery characteristic is configured, when delivered, to adjust a flow-based gain and a device gain configured to normalize the loop gain.

9. The system (50) according to claim 1, wherein the sign of the instantaneous patient airway gas flow rate is positive during inspiration and negative during expiration.

10. The system (50) of claim 1, wherein for a positive value of the flow-based gain factor, the loop gain controller (60) drives ventilation via the pressure delivery module (88) and the airflow generator (52) to increase ventilation, and wherein for a negative value of the flow-based gain factor, the loop gain controller (60) restricts ventilation via the pressure delivery module (88) and the airflow generator (52) to reduce ventilation.

11. The system (50) of claim 1, wherein determining the flow-based gain factor includes adjusting the flow-based gain factor, and wherein the determined or adjusted flow-based gain factor is based on the condition monitored at the current stage of respiratory cycle instability in response to the generated output signal.

12. The system (50) of claim 1, wherein the condition monitoring module (82) is further configured to collect and monitor the output signal of the at least one sensor (74), the output signal corresponding to the input for determining the respiratory loop gain in the positive airway pressure (PAP) therapy mode.

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