Apparatus, method and ventilation apparatus for determining a measure of intrinsic end-tidal pressure

Abstract

Apparatus, method and ventilation device for determining a measure of intrinsic end-tidal pressure. The invention relates to a method and apparatus for determining a measure of intrinsic end-tidal pressure in the lungs of a patient. The possibility of determining a measure of intrinsic end-tidal pressure iPEEP in the lungs of a patient (300) is described. To this end, information about the respiratory pressure exerted by the muscle tissue of the patient at different points in time is detected and evaluated.

Description

Technical Field

[0001] This invention relates to a ventilation device, a method for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs, a computer program, and an apparatus, particularly, but not exclusively, to a protocol for determining iPEEP based on an assessment of the temporal changes in respiratory pressure exerted by the patient's muscle tissue. The maintenance and restoration of spontaneous breathing has long been a high priority in intensive care. For situations where spontaneous breathing is impossible for the patient, lung-protective ventilation is applied, which should cause as little damage to lung tissue as possible. Protection of respiratory muscles, particularly the diaphragm, has only recently become a focus of attention. Background Technology

[0002] Details regarding the background of this invention and the prior art can be found, for example, in the following documents: US 5,820560, WO2019154834A1, WO2019154837A1, WO2019154839A1, WO2020079266A1, DE 10 2019 006480A1, US20170252558A1, DE 10 2019 006 480A1, DE 102019007717B3, DE 10 2020 000014A1, DE 10 2007 062 214B3, WO2018143844A1, DE 10 2015 011 390 A1. Background information regarding the invention relating to a scheme for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs based on an assessment of the time-varying process of respiratory pressure exerted by the patient's muscle tissue should also be referenced to the publications listed below. The sources mentioned below provide additional information regarding the technical, medical, medical, and clinical background. The following list, in an incomplete form, includes exemplary selections of printed materials and publications concerning the detection and processing of various measurement signals or signals in / on the human body and their use in ventilation, ventilation control, and in the field of ventilation using respiratory stimuli.

[0003] Walker, DJ: “Prädiktion des Ösophagusdruckes durch den Mundverschlussdruck nach Magnetstimulation des Nervus Phrenicus”, DissertationUniversität Freiburg: 2006.

[0004] Kahl, L. et al.: "Comparison of algorithms to quantify muscle fatigue in upper limb muscles based on sEMG signals", Medical Engineering & Physics: 2016

[0005] Jansen D. et al.: "Estimation of the diaphragm neuromuscular efficiency index in mechanically ventilated critically ill patients", Critical Care: 2018

[0006] Liu L. et al.: "Neuroventilatory efficiency and extubation readiness in critically ill patients", Critical Care: 2012

[0007] Cattapan, S.E. et al.: "Can diaphragmatic contractility be assessed by airway twitch pressure in mechanically ventilated patients" ", Thorax: 2003

[0008] Younes, M. et al.'s "A method for monitoring and improving patient ventilator interaction", Intensive Care Med: 2007

[0009] Blanch Lluis et al.'s "Measurement of Air Trapping, Intrinsic Positive End-Expiratory Pressure, and Dynamic Hyperinflation in Mechanically Ventilated Patients", Respiratory Care: 2005

[0010] Purro A. et al., “Static Intrinsic PEEP in COPD Patients during Spontaneous Breathing”, AJRCCM: 1988.

[0011] "A New Ultrasound Method for Estimating DynamicIntrinsic Positive Airway Pressure: A Prospective Clinical Trial" by Bernardi E. et al., AJRCCM: 2018.

[0012] "Noninvasive detection of positive end-expiratory pressure in COPD patients recovering from acute respiratory failure" by Pisani L. et al., European Respiratory Journal: 2016.

[0013] Bellani, G. et al., “Clinical Assessment of Auto-positive End-expiratory Pressure by Diaphragmatic Electrical Activity during Pressure Support and Neurally Adjusted Ventilatory Assist,” Anesthesiology: 2014.

[0014] “Dynamic Intrinsic PEEP (PEEPi,dyn) Is It Worth Saving” by Younes, M. AJRCCM: 2000.

[0015] These and other documents, in part, relate to particular aspects of the invention in the course of the description.

[0016] To avoid ambiguity arising from language, some comprehension tips and explanations regarding terminology will be provided at the beginning of the application. In the specification and / or patent claims, within the scope of this invention or plural inventions, verbal and nominalized verbal expressions, such as “determine,” “measure,” “stimulate,” “execute,” “output,” and “detect,” are used in the design of a control unit in the invention's design scheme, and in particular, with the same meaning as expressions with nominalized forms, such as “determine,” “measure,” “execute,” “output,” “detect,” and “stimulate.” In view of the disclosure of this invention or plural inventions, expressions with nouns, nominalized verbs, and verbs are given corresponding and identical meanings, such that even with regard to features and details, the disclosure is always mutually referential or can be mutually referenced between verbal and nominalized forms. Here, expressions with “execute determination, measurement, detection, input, output, etc.” should also be considered to be included together with the corresponding and identical meanings.

[0017] The respiratory muscles consist of the primary muscles responsible for inspiration, the diaphragm, and accessory muscles. These include, in particular, the external (inspiratory) and internal (expiratory) intercostal muscles and the abdominal muscles responsible for expiration. It has been confirmed that prolonged ventilation time and excessive support for spontaneous breathing lead to diaphragmatic atrophy, making exhaustive decompression unavoidable. On the other hand, the respiratory muscles may become fatigued and damaged (exhausted) due to increased respiratory load (obstruction, restriction). Some patients, under certain circumstances, tend to exert high spontaneous respiratory effort, which can in turn damage the lungs. Recently, as also outlined in the background of this invention, novel systems and methods have been disclosed by means of stimulating the respiratory muscles. All muscles can be stimulated directly by activating muscle fibers or by supplying efferent nerves. For example, the muscle fibers of the diaphragm can be stimulated directly through the skin. Alternatively, the phrenic nerve, responsible for the contraction of the diaphragm, can be stimulated. In both cases, muscle activation and contraction occur. The goal of these methods is to improve decompression, promote the drainage of secretions, and may also avoid ventilation or respiratory support. In this case, unlike in cases of ventilated or assisted spontaneous breathing, the supply of breathing gas is not required. As described in the background of the invention, flow and pressure sensors can be used to determine the patient's work of breathing and adapt the stimulation to achieve the target range. However, there is no information technology connection to the ventilation device. The parameters of respiratory mechanics must be extracted from the ventilator's graphical user interface and manually entered in a separate stimulator. Furthermore, in conventional ventilation devices, as long as the patient is breathing forcefully and spontaneously, the displayed values ​​calculated from aerodynamic signals cannot be relied upon. That is, the measured measure of the work of breathing is only a rough estimate. Therefore, a method that can adequately adjust and coordinate ventilation and stimulation, particularly taking into account the work of breathing to be done, is unknown to date. As described in the background of the invention, it is self-evident and known that stimulation and ventilation must be coordinated in their basic mechanisms. However, a method that can predetermine the degree of support and stimulation, for example, according to the treatment goals, does not exist to date. Typically, thresholds and limits are set for the minute ventilation necessary for the patient and for the machine pressure support (trigger, pressure, frequency). The patient's share of the work of breathing is virtually impossible to prescribe, as there is currently no sufficiently precise possibility of allocating the work of breathing between the machine and the patient. A manually coordinated process, in which the respiratory mechanics parameters of the ventilation equipment used are manually transmitted separately and then used in the stimulator, is practically unenforceable. These parameters change after patient repositioning. Therefore, these parameters must be repeatedly entered. Furthermore, these parameters are highly imprecise as long as only pneumatic signals are used in the ventilation equipment to determine them. Therefore, it is almost impossible to know how much the patient actually does, as understanding the patient's contribution to the driving pressure (Pmus) or respiratory gas flow rate (FlowMus) is necessary for this.

[0018] For example, DE 102019006480 describes a method that allows for the separate estimation of these respiratory work shares by means of electromyography of the respiratory muscles.

[0019] Electromyography (EMG) is a neurological examination of a living organism in which the natural electrical activity of muscles is measured. EMG determines the force required to tense a muscle. Measurements of superficial muscles are also known as sEMG. Electrical impedance myometry (EIM) is a non-invasive technique used to evaluate muscle health, where impedance measurements can be used to examine the characteristics of individual muscles or muscle groups, or to examine muscle composition and its microstructure. Mechanomyography (MMG) is a method used to assess the elasticity, viscosity, and plasticity of muscles. The parameter Pmus represents a variable derived from the EMG signal (electro-myogram), sEMG signal (surface electro-myogram), EIM signal (Elektro-impedance-myogram), or MMG signal (mechanical myometry) detected by the measurement technique. Here, Pmus indicates the pressure level caused by the patient's muscular respiratory effort. Here, the cause of muscular respiratory effort can be initiated by the patient themselves through spontaneous breathing activities and / or induced by external stimuli such as electrical, magnetic, or electromagnetic stimulation. Muscular respiratory effort can also be indirectly derived from electrical, electromagnetic, or magnetic signals. It can also be directly detected by measurement techniques, such as pressure measurement at the patient's chest cavity, as a pressure difference relative to a reference pressure. Here, the reference pressure can be ambient pressure or a pressure level provided by the ventilation device. Pressure levels typically provided by ventilation devices include, for example, inspiratory pressure levels, often referred to as inspiratory pressure or inspiratory pressure Pinsp, and expiratory pressure levels, often referred to as expiratory pressure or expiratory pressure Pexp. A special case of expiratory pressure levels is the so-called PEEP (positive end-expiratory pressure), which describes the pressure level at the end of expiration in the patient's airway as a pressure difference relative to ambient pressure, detectable by measurement techniques. Both inspiratory pressure Pinsp and expiratory pressure Pexp are detected as pressure differences relative to ambient pressure and are mostly expressed in mBar. This parameter Pmus can also be called respiratory muscle pressure Pmus.

[0020] In the specification and / or patent claims, within the scope of this invention or the inventions, the terms “muscle airway pressure”, “respiratory muscle pressure”, and expressions such as “parameter Pmus”, “pressure parameter Pmus”, “pressure parameter or parameter P, Pmus indicating the pressure caused by the patient’s muscular respiratory effort”, and “respiratory pressure Pmus exerted by the patient’s muscle tissue” are used in a synonymous and identical manner, so that they can be referenced to each other in terms of terminology.

[0021] The parameter Flowmus represents a variable derived from the parameter Pmus. Higher frequencies in the signal variation of parameter Pmus can provide a measure of the muscle-induced share of airway flow, the direction of flow, and the reversal of the flow direction. High-pass filtering of parameter Pmus can be used to determine parameter Flowmus. The term "airway flow" refers to the volume of airflow that flows into the patient during the inspiratory phase (i.e., inhaled) or flows out of the patient during the expiratory phase (i.e., exhaled). Parameter Flowmus here indicates flow with a flow direction, where the cause of the flow is based on the patient's muscular respiratory effort. Here, the cause of muscular respiratory effort can be initiated by the patient themselves in the form of spontaneous breathing activities and / or induced by external, such as electrical, magnetic, or electromagnetic stimulation. This parameter Flowmus can also be called muscular airway flow or respiratory muscle flowmus. Signal processing with high-pass filtering of the signal variation of parameter Pmus enables the identification of muscle-induced respiratory phase changes in parameter Flowmus and the moments when the sign of parameter Flowmus reverses.

[0022] The inversion of the sign of the parameter Flowmus here indicates a moment when there is a change in the respiratory phase between the inspiration and exspiration phases based on the patient's muscular respiratory effort. In the specification and / or patent claims, within the scope of this invention or the inventions, the terms "muscular airway flow," "respiratory muscle flow," and expressions such as "parameter Flowmus," "flow parameter Flowmus," "flow parameter or parameter Flow, Flowmus indicating the pressure caused by the patient's muscular respiratory effort," and "flow Flowmus generated through the patient's muscle tissue" are used synonymously and with the same function, allowing mutual reference in terminology. The following list clarifies some terms used within the scope of this application:

[0023] In the context of this invention, respiratory pressure is understood as the pressure or pressure level (mostly and usually above ambient pressure) in the respiratory tract, lungs, and trachea of ​​an organism.

[0024] In the context of this invention, muscle airway pressure or respiratory muscle pressure is understood as, particularly based on the muscle activity of biological (autonomous or stimulated) respiratory muscle tissue and / or the muscle activity of respiratory accessory muscle tissue, the share of respiratory pressure exerted by muscle tissue, airway pressure.

[0025] In the context of this invention, respiratory flow or respiratory gas flow is understood as any movement of inhaled gas toward or into an organism and as exhaled gas from or out of an organism.

[0026] In the context of this invention, muscular airway flow (or respiratory muscle flow) is understood as any movement of respiratory gas volume as the amount of inhaled gas toward and into the organism and as the amount of exhaled gas from and out of the organism, based on the muscular activity of the (autonomous or stimulated) respiratory muscle tissue and / or the muscular activity of the accessory muscle tissue, which is based on the biological (autonomous or stimulated) respiratory muscle tissue.

[0027] Within the scope of this invention, the terms "muscle-airway pressure" and "respiratory muscle pressure" are used synonymously.

[0028] Within the scope of this invention, the terms "muscle airway flow" and "respiratory muscle flow" are used synonymously.

[0029] In studies such as Sinderby et al., "Is one fixed level of assistance sufficient to mechanically ventilate spontaneously breathing patients?" In the “Neurally Adjusted Ventilatory Assist” (NAVA) method described in the Yearbook of Intensive Care and Emergency Medicine, 2007, and Sinderby et al., “Neural ontrol of mechanically ventilation in respiratory failure,” Nature Medicine, 1999, the electrical activity of the diaphragm (EAdi) is recorded by means of a modified gastric probe equipped with electrodes so that the pressure support of the ventilator can be adjusted in proportion to the electrical activity.

[0030] The NAVA method, which is specifically supported by a signal of the electrical activity of the diaphragm, is known from US 7,021,310 B1. This method is characterized by maintaining the electrical activity of the diaphragm (so-called neural ventilation efficiency) required for a given respiratory volume by means of a “closed-loop” control.

[0031] From US 2009 159 082 AA or DE 10 2007 062 214 B3, for example, how can one measure the pressure parameter Pmus or "muscle-airway pressure" or respiratory muscle pressure Pmus, p mus (t) variations should refer to the description and figures in the application, which also clearly state the terms such as “muscle tissue”, “respiratory muscle tissue”, “muscle airway pressure”, “respiratory muscle pressure”, “parameter Pmus”, “pressure parameter Pmus”, and “pressure parameter or parameter Pmus indicating the pressure caused by the patient’s muscular respiratory effort”.

[0032] For example, respiratory muscle pressure p mus (t) can be determined in the following way:

[0033] a) Calculate the volumetric flow rate Flow(t) based on the measured value of the airway pressure, and then obtain the respiratory volume Vol(t) by integration, as well as calculate the lung mechanical parameters R (resistance) and E (elasticity).

[0034] b) By means of the negative airway pressure -P measured during obstruction. okkl (t) is used to determine the lung mechanical parameters R and E, which are either calculated or given in advance.

[0035] c) Determined using an esophageal catheter equipped with a pressure sensor for measuring intrathoracic pressure Pes(t). The esophageal catheter may optionally be equipped with and used to measure intra-abdominal pressure P. abd (t).

[0036] d) Determined by means of a device that provides electromyographic or mechanomotor electrical signals in a manner arranged on the chest cavity, the electrical signals being determined by means of suitable allocation rules, tables, functions, or transformation parameters, such as so-called "neuromechanical efficiency" or "neuromuscular efficiency" (NME) and respiratory muscle pressure P. mus (t) is related to, or through the so-called "neural ventilation efficiency" (NVE), also correspondingly related to volume V. mus (t) related.

[0037] d) Determination is made using a gastric probe equipped with electrodes, the gastric probe providing a signal that can be correlated with respiratory muscle pressure P using appropriate assignment rules, tables, functions, or transformation parameters.mus (t) related.

[0038] The determination of P listed in a) through e) mus (t) or Pmus variants and other components required for their implementation in a device, system, or method, such as sensors, electrodes, surface electrodes, pressure sensors, flow sensors, gastric probes, and esophageal catheters, are derived according to the variants. Respiratory activity signal u emg (t) can be transformed into a pressure signal p using predetermined transformation rules. emg (u emg (t)). The transformation rule can be obtained through u emg (t) and p mus The linear or nonlinear regression between (t) can be used to determine this, or other methods such as using neural networks, machine learning, or simple scaling can also be employed. For example, the following linear regression equation p... mus (t)=a0+a1*u emg (t)+a2*u 2 emg (t)+a3*u 3 emg (t)+(t) can be used to determine the regression coefficients of the transformation rule being sought, based on which the transformed p finally exists. emg (t) signals are used for further purposes, such as for ventilation control and / or for stimulation.

[0039] So-called "intrinsic PEEP" or automatic PEEP (iPEEP) is the driving pressure required to exhale within the volume established by dynamic hyperinflation at the end of expiration (the so-called "trapped volume"). Impaired lung mechanics (e.g., expiratory airway flow restriction), disrupted spontaneous breathing, or misconfiguration of mechanical ventilation are considered causes. Therefore, iPEEP is an important diagnostic parameter for patients with obstruction, for example, due to COPD (chronic obstructive pulmonary disease). Treatment attempts to reduce iPEEP itself or its effects (e.g., by adapting external PEEP or CPAP levels). Therefore, dynamic hyperinflation should be reduced. Hyperinflation and excessive air distension. By shifting the working point of the pressure-volume curve into the linear range of compliance (lung extensibility), the increase in the work of breathing can be prevented. Simultaneously, the diaphragm muscle fibers can contract more efficiently. Finally, the advantage of resisting fatigue faced by spontaneously breathing patients can be achieved. There are generally two scenarios for determining iPEEP. In the case of passively ventilated patients, (static) iPEEP is determined by end-expiratory obstruction, where the following pressure increase is detected. The pressure increase corresponds to the pressure exerted by the unexpired volume “accumulated” in the case of relaxed respiratory muscles or chest wall. Conventional ventilation devices have a function for end-expiratory obstruction, making it possible to measure iPEEP. However, manual intervention (i.e., triggering the obstruction) is necessary. Furthermore, ventilation can be easily adapted, for example, by changing the I:E ratio (the ratio of inspiratory time to expiratory time) to reduce iPEEP. Spontaneously breathing patients, especially those with CO2... Patients with Parkinson's disease (PD) suffer significantly from iPEEP. iPEEP impedes spontaneous breathing because significant respiratory effort is required to completely stop (reach zero) expiratory flow, i.e., "flow," due to pretension (recoil, restorative force), yet exceeding zero is necessary for the normal pneumatic triggering of the respiratory stroke. However, spontaneously breathing patients often find end-expiratory obstruction difficult to tolerate, especially since the obstruction must be maintained long enough for effective results until the patient relaxes their muscle tissue. This may not be feasible in all cases. Sedation administration (Sedierungsgabe) solely for the purpose of determining iPEEP may only be reasonable in rare cases. Furthermore, reducing iPEEP after a single measurement cannot be easily achieved because the patient's respiratory drive and rhythm must be taken into account; that is, the obstruction manipulation must be repeated. In the case of spontaneously breathing patients, (dynamic) iPEEP can be better determined by the difference in esophageal pressure at two points in time:

[0040] - The first moment is the beginning of the inhalation effort.

[0041] - The second moment is when the flow crosses the zero line.

[0042] However, this measurement requires (invasively and difficultly) placement of an esophageal pressure catheter, which is often inconsistent with clinical practice. A reasonable value for esophageal pressure can only be measured when the catheter is correctly placed. The described method is disadvantageous for spontaneously breathing patients because either end-expiratory obstruction combined with sedation may have to be repeatedly performed, or invasive and difficult measurements of esophageal pressure are required.

[0043] The so-called p0.1 manipulation, which is known from existing technology and combined with ultrasound diagnosis, is used to avoid invasive esophageal manometry.

[0044] Other characteristics of ultrasound diagnosis can be found in, for example, Bernardi E. et al., “A New Ultrasound Method for Estimating Dynamic Intrinsic Positive Airway Pressure: A Prospective Clinical Trial,” AJRCCM, 2018, and Pisani L. et al., “Noninvasive detection of positive end-expiratory pressure in COPD patients recovering from acute respiratory failure,” European Respiratory Journal, 2016. However, this ultrasound method requires considerable experience and is often not available at the bedside.

[0045] The literature Bellani, G. et al., “Clinical Assessment of Auto-positive End-expiratory Pressure by Diaphragmatic Electrical Activity during Pressure Support and Neurally Adjusted Ventilatory Assist” (Anesthesiology 2014), describes a method within the scope of clinical research. Here, the electrical activity signal EAdi of the diaphragm (kruralen Zwerchfelllappen) is invasively detected via an esophageal catheter equipped with electrodes (Maquet NAVA). To determine the dynamic intrinsic PEEP, the EAdi signal is read at the onset of inspiratory flow and multiplied by a factor. A disadvantage is the need for an invasive esophageal catheter to extract the EAdi activity signal and to perform a painful end-expiratory obstruction to determine the factor.

[0046] The following names will be used in the text, where the following variables are variable over time, as shown in Table 1 below:

[0047]

[0048] Table 1. Summary of the Invention

[0049] Based on this, the purpose of this invention is to create an improved method for determining the measurement of intrinsic end-expiratory pressure in a patient's lungs.

[0050] This task is addressed based on the subject matter of the pending independent claims.

[0051] This task is solved in particular by means of a device having the features of claim 1.

[0052] Advantageous embodiments of the invention are derived from the dependent claims and are explained in more detail in the following description with reference to the partial figures.

[0053] An embodiment based on the following core idea can avoid the aforementioned drawbacks if a non-invasive, continuous Pmus estimation is used instead of invasive measurements of esophageal pressure or diaphragmatic electrical activity. As described in DE 10 2007 062 214B3, Pmus can be estimated continuously, for example, in conjunction with measurements of respiratory surface electromyography (sEMG). Esophageal pressure Pes and respiratory muscle pressure Pmus are estimated via equations...

[0054] (1) Pes = Ecw V-Pmus

[0055] These are correlated (Ecw is the restoring force / elasticity of the chest wall). At the start of respiration, the accumulated volume is still zero, making Pes and Pmus (except for their sign) the same. Instead of now using esophageal pressure for differential formation, the estimated Pmus can be used. For example, the start of respiratory effort (tA) and the moment when the flow crosses the zero line (tB) are chosen as the times. The latter (e.g., also in the ventilation device) is known. To determine the moment when respiratory effort begins, the zero-crossing of the share of the flow signal caused by spontaneous breathing, V'mus, can be used, for example. Alternatively, the zero-crossing can be determined by the threshold crossing of any respiratory effort signal (e.g., Pmus).

[0056] For example, the intrinsic PEEP is therefore derived as

[0057] (2)iPEEP=ΔPmus=Pmus(tB)-Pmus(tA)

[0058] Since the repetition of this measurement and calculation is not disadvantageous compared to the execution of a longer obstruction, an improved value of iPEEP can be obtained by averaging more than one measurement, if necessary, over multiple breaths. Therefore, the embodiments create a method for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs. The method includes determining or establishing first information regarding a first respiratory pressure Pmus(tA) applied through the patient's muscle tissue at a first time tA, at which time the patient's inhalation attempt exists or begins. The method further includes determining second information regarding a second respiratory pressure Pmus(tB) applied through the patient's muscle tissue at a second time tB, at which time the inhalation gas flow towards the patient begins. Furthermore, the method includes measuring or determining a measure of iPEEP based on the first information and based on the second information. Therefore, the embodiments can allow iPEEP to be determined from the applied respiratory pressure. This measurement may include determining a measure of the difference or weighted difference between Pmus(tA) and Pmus(tB). Thus, an effective basis for determining iPEEP can be provided. Additionally or alternatively, the measurement may include a measure of determining the quotient and / or weighted quotient between Pmus(tA) and Pmus(tB). Consideration of the quotient may also help to efficiently determine iPEEP. Furthermore, the measurement may include averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases, for example, to make the estimation of respiratory muscle pressure more robust.

[0059] In other embodiments, determining the first and second information may include estimating the respiratory pressure exerted through the patient's muscle tissue based on electromyographic signals. Electromyographic signals can form the basis for a robust and non-invasive detection method for estimating respiratory muscle pressure.

[0060] For example, determining the first and second information may include estimating the respiratory pressure exerted through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volumetric flow rate V' generated at the patient. These variables can contribute to efficient or robust estimation and may, for example, be detected pneumatically.

[0061] In some embodiments, the method may also include receiving information from the ventilation system ventilating the patient regarding the generated airway pressure Paw, respiratory volume V, and respiratory volume flow V'. Therefore, pneumatic signals or signals detected pneumatically (pressure sensors) may also be included in the estimation.

[0062] Determining the first information may include estimating the first moment tA based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue. The process or start of the change in respiratory gas flow can form a valid basis for estimating the first moment.

[0063] For example, determining the first information may include estimating the first moment tA based on a threshold crossover of the patient's respiratory effort signal. The threshold crossover can be implemented and detected in a low-cost manner.

[0064] Determining the first information may also include estimating the first moment tA based on the onset of the patient's spontaneous breathing. The onset of spontaneous breathing can be determined, for example, from activation signals of the respiratory muscles.

[0065] Alternatively or supplementally, determining the second information may include estimating the second time step based on the start of the respiratory gas flow rate toward the patient. The start of this change or respiratory gas flow rate is also an effective measure or basis for estimating the second time step tB.

[0066] Furthermore, the method may include averaging, smoothing, outlier suppression, or median determination of multiple time-sequentially determined measures of iPEEP to obtain an improved measure of iPEEP. Therefore, embodiments can determine a more reliable measure of iPEEP.

[0067] In other embodiments, the method may include determining a measurement of iPEEP based on measurements taken by the ventilation device during obstruction. Calibration can help determine a more reliable measurement of iPEEP.

[0068] Another embodiment is a computer program having program code for performing one of the methods described herein when the program code is executed on a computer, processor, or programmable hardware component.

[0069] Furthermore, the embodiments create a device for a ventilation apparatus and for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs. The device includes one or more interfaces configured for exchanging information with the ventilation apparatus. Additionally, the device includes a control unit configured to determine first information regarding a first respiratory pressure Pmus(tA) applied through the patient's muscle tissue at a first time tA, at which time an inhalation attempt by the patient is present or initiated. The control unit is configured to determine second information regarding a second respiratory pressure Pmus(tB) applied through the patient's muscle tissue at a second time tB, at which time a respiratory gas flow towards the patient begins. Furthermore, the control unit is configured to measure the iPEEP based on both the first and second information. Therefore, the embodiments may also provide a device for determining iPEEP from applied respiratory pressures.

[0070] In other embodiments, the device may include one or more sensors for detecting measurements during patient ventilation. For example, the device may be configured to detect pressure measurements or pressure measurement signals during patient ventilation.

[0071] In embodiments, the control unit may be configured to perform one of the explained methods or method steps. Thus, the measurement may include a measure of determining the difference or weighted difference between Pmus(tA) and Pmus(tB). Alternatively or additionally, the measurement may include a measure of determining the quotient and / or weighted quotient between Pmus(tA) and Pmus(tB). The measurement may also include averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases.

[0072] The control unit can be configured to perform the determination of first and second information based on an estimate of the respiratory pressure exerted through the patient's muscle tissue according to electromyographic signals. Determining the first and second information may include estimating the respiratory pressure exerted through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volumetric flow rate V' generated at the patient.

[0073] In other embodiments, the control unit may be configured to receive information from the ventilation device currently ventilating the patient regarding the generated airway pressure Paw, respiratory volume V, and / or respiratory volume flow rate V'.

[0074] In some embodiments, determining the first information may include estimating a first moment tA based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue. Alternatively or additionally, determining the first information may include estimating the first moment tA based on a threshold crossing of the patient's respiratory effort signal.

[0075] Determining the first information may include estimating a first time point tA based on the start of the patient's spontaneous breathing. Determining the second information may include estimating a second time point tB based on the start of respiratory gas flow toward the patient.

[0076] In other embodiments, the control unit may be configured to average, smooth, suppress outliers, or thereby determine the median of multiple time-sequentially determined measures of iPEEP in order to obtain an improved measure of iPEEP. The control unit may also be configured to determine a measure of iPEEP based on measurements taken by the ventilation equipment during obstruction.

[0077] An embodiment of the invention discloses a device for a ventilation apparatus and for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs. The device has one or more interfaces configured for exchanging information with the ventilation apparatus, and a control unit configured for...

[0078] - Determine first information about the first respiratory pressure Pmus(tA) exerted by tA through the patient's muscle tissue at the first moment, during which the patient's inhalation attempt is present.

[0079] - Determine second information regarding the second respiratory pressure Pmus(tB) exerted by the patient's muscle tissue at the second time tB, and the respiratory gas flow rate toward the patient at the start of the second time.

[0080] - The measurement of iPEEP is determined based on the first information and the second information.

[0081] In a preferred embodiment of the device, the device may include one or more sensors for detecting measurements during patient ventilation.

[0082] In a preferred embodiment, the device can be configured to detect pressure measurements or pressure measurement signals during patient ventilation.

[0083] In a preferred embodiment, the determination may include determining a measure of the difference or weighted difference between Pmus(tA) and Pmus(tB), and / or determining a measure of the quotient or weighted quotient between Pmus(tA) and Pmus(tB).

[0084] In a preferred embodiment of the device, the measurement includes averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases.

[0085] In a preferred embodiment of the device, determining the first and second information may include estimating the respiratory pressure exerted by the patient’s muscle tissue based on electromyography signals and / or estimating the respiratory pressure exerted by the patient’s muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volume flow rate V' generated at the patient.

[0086] In a preferred embodiment of the device, the control unit may be configured to receive information from the ventilation device ventilating the patient regarding the generated airway pressure Paw, respiratory volume V, and respiratory volume flow rate V'.

[0087] In a preferred embodiment of the device, determining the first information may include estimating the first moment based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue.

[0088] In a preferred embodiment of the device, determining the first information includes:

[0089] - Based on the threshold of the patient's breathing effort signal crossing the estimated first moment, and / or

[0090] - Estimate the first moment based on the onset of the patient's spontaneous breathing.

[0091] In a preferred embodiment of the device, determining the second information may include estimating a second moment based on the start of respiratory gas flow toward the patient.

[0092] In a preferred embodiment of the device, the control unit may be configured to average, smooth, suppress outliers, or thereby determine the median of multiple time-sequentially determined measures of iPEEP in order to obtain an improved measure of iPEEP. Outliers are, for example, measurements or values ​​that deviate from a group of values ​​or measurements observed over a longer observation time interval due to interference superimposed on the measurements. If such deviation is significant relative to the group of values ​​or measurements, such outliers can be identified and suppressed by means of signal or data processing.

[0093] In a preferred embodiment of the device, the control unit may be configured to calibrate the measurement of iPEEP based on measurements of the ventilation device during obstruction.

[0094] A preferred embodiment may be configured as a ventilation device having a device based on the previously described embodiment.

[0095] A preferred embodiment can be formed by a method for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs, the method comprising:

[0096] - Determine first information about the first respiratory pressure Pmus(tA) exerted by the patient's muscle tissue at a first moment tA, during which the patient's inhalation attempt is present.

[0097] - Determine second information regarding the second respiratory pressure Pmus(tB) exerted by the patient's muscle tissue at the second time tB, and the respiratory gas flow rate toward the patient at the start of the second time.

[0098] - The measurement of iPEEP is determined based on the first information and the second information.

[0099] A preferred embodiment can be formed by a computer program having program code that is used to perform the method when the program code is executed on a computer, processor, or programmable hardware component. Attached Figure Description

[0100] The following examples of devices and / or methods are explained in more detail with reference to the accompanying drawings.

[0101] Figure 1 An embodiment of a method for determining the measurement of intrinsic end-expiratory pressure (iPEEP) in a patient's lungs is shown;

[0102] Figure 2 A block diagram illustrating an embodiment of a ventilation device and a device for determining the measurement of intrinsic end-expiratory pressure (iPEEP) in a patient's lungs;

[0103] Figure 3 An overview diagram is shown for patient ventilation and for detecting electromyography signals;

[0104] Figure 4 The time-varying process of pressure generated by the ventilation device, the volumetric flow rate between the ventilation device and the patient, and the changes in the patient's own respiratory effort are shown.

[0105] Figure 5 The time-varying processes of volumetric flow rate Vol' and respiratory pressure Paw are shown in one embodiment.

[0106] Figure 6 The diagram illustrates the signal changes of EMG signal, respiratory muscle pressure, airway pressure, and volumetric flow rate in one embodiment.

[0107] Figure 7 This illustrates, in one embodiment, the signal variations of sEMG signals, volumetric flow rate Vol', and volumetric flow rate Vol'mus generated by the patient's muscle; and

[0108] Figure 8The signal changes of volumetric flow rate (Flow), respiratory pressure (Paw), esophageal pressure (Pes), and gastric pressure (Pga) are shown.

[0109] Different examples will now be described in more detail with reference to the accompanying drawings. In the drawings, the intensity of lines, layers, and / or regions may be exaggerated for clarity.

[0110] Other examples may cover modifications, equivalents, and alternatives that fall within the scope of this disclosure. Throughout the description of the figures, the same or similar reference numerals denote the same or similar elements that may be implemented identically or modified when compared with each other, and that provide the same or similar functions. Detailed Implementation

[0111] It is readily understood that when elements are referred to as being "connected" or "coupled" to another element, these elements can be connected or coupled directly or via one or more intermediate elements. When two elements A and B are combined using "or," this should be understood to disclose all possible combinations, i.e., only A, only B, and A and B, unless otherwise explicitly or implicitly defined. Alternative expressions for the same combination are "at least one of A and B" or "A and / or B." With necessary modifications to the details, the same applies to combinations of more than two elements.

[0112] Figure 1 An embodiment of a method 10 for determining the measurement of intrinsic end-expiratory pressure (iPEEP) in a patient's lungs is shown. The method includes determining 12 first information regarding a first respiratory pressure Pmus(tA) exerted through the patient's muscle tissue at a first time tA, at which time an inhalation attempt by the patient is present or begins. The method further includes determining 14 second information regarding a second respiratory pressure Pmus(tB) exerted through the patient's muscle tissue at a second time tB, at which time a flow of exhaled gas toward the patient begins. The method includes measuring 16 the iPEEP based on the first information and based on the second information, or measuring the iPEEP itself.

[0113] Figure 2A block diagram illustrating one embodiment of a ventilation device 200 and a device 20 for determining a measurement of the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs is shown. The device 20 includes one or more interfaces 22 configured for exchanging information with the ventilation device 200 and coupled to a control unit 24 also included by the device 20. The control unit 24 is configured to determine 12 first information regarding a first respiratory pressure Pmus(tA) applied through the patient's muscle tissue at a first time tA, at which a patient's inhalation attempt is present or initiated, and to determine 14 second information regarding a second respiratory pressure Pmus(tB) applied through the patient's muscle tissue at a second time tB, at which a respiratory gas flow towards the patient begins. The control unit 24 is configured to measure 16 the iPEEP based on the first information and based on the second information. Figure 2 The illustration also shows an embodiment of a ventilation device 200 having device 20. Furthermore, device 20 may include one or more sensors (e.g., pressure sensors, strain sensors, electrical sensors, etc.) for detecting measurements during patient ventilation. For example, device 20 may be configured to detect pressure measurements or pressure measurement signals during patient ventilation.

[0114] Device 20 includes one or more interfaces 22 coupled to control unit 24. The one or more interfaces 22 may be configured as machine interfaces or software interfaces, for example.

[0115] In embodiments, the one or more interfaces 22 may be configured as typical interfaces for communication within a network or between network components or medical devices (e.g., ventilation devices, sensors or measurement units, stimulators, etc.). For example, the interfaces may be configured with corresponding contacts in embodiments. In embodiments, the interfaces may also be implemented as separate hardware and include a memory that at least temporarily stores signals to be transmitted or received. The one or more interfaces 22 may be configured for receiving electrical signals, such as bus interfaces, optical interfaces, Ethernet interfaces, radio interfaces, fieldbus interfaces, etc. Furthermore, the interfaces may be configured for radio transmission and include a radio front end and associated antennas in embodiments. Input and / or output devices, such as screens, keyboards, and mice, may also be connected via the one or more interfaces 22 to detect user input and / or enable output.

[0116] In embodiments, control unit 24 may include one or more arbitrary controllers, microcontrollers, network processors, processor cores such as digital signal processor cores (DSPs), programmable hardware components, etc. Embodiments are not limited to a specific type of processor core. Any processor core or multiple processor cores or microcontrollers can be envisioned for implementing control unit 24. Implementations integrating with other devices are also envisioned, for example, where the control unit additionally includes one or more other functions. In embodiments, control unit 24 may be implemented as the core of one or more modules using a processor core, computer processor core (CPU), graphics processing unit core (GPU), application-specific integrated circuit (ASIC), integrated circuit (IC), system on chip (SOC), programmable logic element, or field-programmable gate array (FPGA) with a microprocessor.

[0117] The following terms and definitions are used in this specification:

[0118] (Muscle) Breathing effort:

[0119] This term is used in a general sense. It refers to the muscular effort a patient makes to generate respiratory muscle pressure in order to achieve airway flow. If respiratory effort is obstructed, i.e., airway flow is interrupted due to obstruction, then although respiratory muscle pressure is generated (which can be measured as "mouth pressure" in the case of an open airway), no airway flow occurs. This involves equal contraction of the respiratory muscle tissue. Respiratory effort always corresponds to physiological work, but this physiological work cannot be directly measured. Measurable physical work is only performed when the contraction is not equal, i.e., only when airway flow is generated.

[0120] Respiratory support:

[0121] Respiratory support is a ventilatory response to muscular respiratory effort. The ventilation device supports the patient's (triggered) detected respiratory effort in sync with the support process. Thus, the patient establishes a respiratory rhythm. This can involve pressure-controlled support (establishing airway pressure) or (more rarely) volume-controlled support (establishing respiratory volume). In all cases, the ventilation device performs the physical work, that is, it performs a portion of the total respiratory work required on behalf of the patient.

[0122] (Forced) ventilation:

[0123] During forced ventilation, the machine performs the full work of breathing for the patient. The respiratory rhythm is determined by the machine. Typically, the patient is passive during forced ventilation to avoid conflict between the person / patient and the machine. Patient passivity is often achieved through the administration of sedatives and relaxants.

[0124] WOB - Breathing Exercises:

[0125] This is the physiological or physical work done for breathing and / or ventilation. In the case of isometric contraction, no physical work is done in the sense of the equation of motion (see below). However, other definitions of work can be used, such as the so-called pressure-time product (time integral).

[0126] WOBtot - Total Breathing Exercise:

[0127] This is the total physiological or physical work done for breathing and / or ventilation.

[0128] WOBvent - Machine / ventilator-side breathing work:

[0129] This is the share of breathing work done by the ventilator.

[0130] WOBmus - Patient-side (muscle) breathing exercises:

[0131] This is the share of respiratory work performed by the patient alone, not only with stimulation of muscle tissue but also without stimulation of muscle tissue.

[0132] WOBspon - Spontaneous (Patient-side) Breathing Work:

[0133] This is the work of breathing performed by the patient through their own voluntary breathing. In this case, the muscle tissue is not stimulated.

[0134] WOBstim - Stimulated (patient-side) work of breathing:

[0135] This is the work of breathing done by stimulating the patient's respiratory muscle tissue.

[0136] Pdrv - Drive pressure:

[0137] Pdrv is the sum of the pressure applied by the ventilation equipment and the pressure applied by the patient.

[0138] Pvent - Ventilation pressure:

[0139] Pvent is the pressure applied by the ventilation equipment.

[0140] Pmus - Muscle stress:

[0141] Pmus is the pressure applied by the patient's muscle tissue not only when the muscle tissue is stimulated, but also when the muscle tissue is not stimulated.

[0142] Pspon - Autonomous Muscle Pressure:

[0143] Pspon is the share of muscle pressure that is applied voluntarily by the patient, i.e., without stimulation.

[0144] Pstim - Stimulated muscle pressure:

[0145] Pstim is the share of muscle pressure exerted by the patient solely due to stimulation of muscle tissue.

[0146] WOBbase or PmusBase - Basic Respiratory Load:

[0147] The basic respiratory load can be equated to the work of breathing or driving pressure, which is the pressure required to overcome viscous, elastic, and potentially other resistances and achieve sufficient volume (e.g., minute ventilation set by the clinician) under healthy breathing patterns. The breathing pattern is preferably based on an energy-optimized mode. The work of breathing or driving pressure can be applied on the patient side and / or the machine side. The latter will be the case during (forced) ventilation.

[0148] Respiratory load:

[0149] Respiratory load can be determined by measuring the actual work of breathing or driving pressure required for ventilation. Respiratory load is typically higher than the basic respiratory load because the patient's breathing rhythm is not energy-optimized, the patient may be seeking a larger volume than needed due to air shortage, or there may be asynchrony between the patient and the ventilation equipment. In cases of respiratory support, the ventilation equipment bears a portion of the respiratory load.

[0150] Activation signal:

[0151] This is a signal used to detect neuronal activation in muscles (whether induced by stimulation or spontaneous respiratory effort), such as (s) EMG (surface electromyography), EIM (electrokinetic imaging), and MMG (mechanical kinetic imaging). Alternatively, signals that can be detected using novel optical or acoustic techniques (e.g., ultrasound) may also be considered. In the following text, without excluding other signals, the envelope curve of EMG is used as the activation signal (referred to as "EMG" for simplicity). Therefore, it should not be excluded that different muscle groups (e.g., the diaphragm and intercostal muscles) provide their own activation signals. In the context of diaphragmatic stimulation (e.g., magnetic stimulation via the phrenic nerve), diaphragmatic activation signals are in the foreground.

[0152] Activatability:

[0153] This refers to the ability to electrically stimulate (activate) muscle tissue, for example, through electrical or magnetic stimulation. Activation is preferably caused by so-called magnetic twitching stimulation, which involves a high-intensity transient stimulation pulse that results in maximal contraction of the stimulated muscle. Other stimulation modes are also conceivable. Activation can be detected by means of an activation signal, preferably using EMG.

[0154] Validity:

[0155] Efficacy is the pneumatic target variable (pressure or volume) achieved through muscle activation. Neuromechanical efficiency (NME) correlates the generated muscle pressure with EMG, for example see WO2018143844A1, and Jansen D. et al., “Estimation of the diaphragm neuromuscular efficiency index in mechanically ventilated critically ill patients”, CriticalCare (2018) 22:238.

[0156] Neuroventilatory efficiency (NVE) correlates the volume produced with EMG; for this, see, for example, Liu L. et al., “Neuroventilatory efficiency and extubation readiness in critically ill patients,” Critical Care 2012, 16:R143. Determining effectiveness often requires manipulation, such as obstruction or modification of respiratory support. As illustrated therein, these values ​​are diagnostically significant, for example, in assessing the progress of ventilator withdrawal.

[0157] Maximum achievable respiratory effort:

[0158] This corresponds to the work of breathing (WOBmusMax), volume (VolMusMax), or muscle pressure (PmusMax) achievable through the maximum effort of the respiratory muscles. PmusMax is most likely to be measured in a standardized manner. Therefore, the value PImax is often used in the literature as a measure of the maximum achievable muscle pressure, i.e., the maximum pressure generated during inspiration when the mouth is closed. Since intentional contraction of the diaphragm leads to unreliable results, so-called (usually magnetic) twitch stimulation is frequently used recently to trigger contraction; this stimulation can be performed independently of the patient's cooperation. PmusMax is typically detected via an esophageal pressure catheter, but oral closure pressure, which can be measured more easily, has proven equally convincing; see also: Cattaban, SE et al.: "Can diaphragmatic contractility be assessed by airway twitch pressure in mechanically ventilated patients". "Thorax 2003;58:58–62. The triggering of the stimulus can be advantageous here."

[0159] LI - Load Index :

[0160] This is a measure related to the ratio of the work of breathing produced to the maximum work of breathing that can be produced, where muscle stress or other measures can be used instead of "work". For muscle stress, the load can be defined as:

[0161] LI = Pmus / PmusMax.

[0162] LBC - Load Bearing Capacity:

[0163] This is the ability of muscle tissue to generate a defined force or (in the case of respiratory muscle tissue) pressure through contraction and thus to perform work. To quantify load capacity, the muscle pressure / work of breathing generated by muscle tissue can be readily correlated with the maximum producible muscle pressure / work of breathing. Thus, load capacity can be quantitatively determined based on the ratio of basic respiratory load to maximum producible respiratory effort. If the basic respiratory load exceeds a defined portion of the maximum producible respiratory effort, there is no longer a load capacity for a single spontaneous breath, and ventilation is involuntary.

[0164] For muscle stress, load capacity can be defined as...

[0165] LBC = 1 - PmusBase / PmuxMax.

[0166] fatigue:

[0167] If the respiratory muscle tissue has a low load-bearing capacity, such that the patient-generated share of the respiratory load exceeds a certain portion of the maximum achievable respiratory effort, such as 50%, then fatigue will occur after some time.

[0168] Fatigue level:

[0169] The degree of fatigue is related to load capacity, respiratory effort, and its duration, but it cannot be calculated directly from these factors alone. However, there are quantifiable values ​​(Maßzahlen) that can be calculated, for example, from the electromyography (EMG) of muscle tissue and used as a substitute for the degree of fatigue. For this purpose, see, for example, DE 10 2015 011 390A1 and Kahl, L. et al., “Comparison of algorithms to quantify muscle fatigue in upper limb muscles based on sEMG signals,” Medical Engineering & Physics, September 2016.

[0170] The relationships between related variables can also be described by formulas, some of which are shown below.

[0171] The work of breathing can be calculated as the integral of the corresponding pressure with respect to volume, for example, for the total work of breathing:

[0172] WOBtot=∫Pdrv(t)dV =∫Pdrv(t) Flow(t) dt.

[0173] Alternative locations (especially for situations with equal loads)

[0174] The pressure-time product can be used:

[0175] WOBtot~ = ∫Pdrv(t) dt.

[0176] The driving pressure (similar to the work of breathing) is divided into different portions:

[0177] Pdrv = Pvent + Pmus = Pvent + Pspon + Pstim

[0178] WOBtot = WOBvent + WOBmus = WOBvent + WOBspon + WOBstim.

[0179] Flow rate or volume can be divided into different shares in a similar way to breathing work:

[0180] Flow = FlowVent + FlowMus = FlowVent + FlowSpon + FlowStim, or

[0181] Vol = VolVent + VolMus = VolVent + VolSpon + VolStim.

[0182] Applicable to the basic equations of motion in the respiratory circuit:

[0183] Pdrv=Pvent+Pmus=R Flow+E Vol+const.

[0184] If flow rate or volume (as described above) is defined as the sum of the shares of the ventilation device and the patient, respectively,

[0185] Then for Pvent and Pmus, we get:

[0186] Pvent=R Flow+E Vol+ const, and

[0187] Pmus = R FlowMus + E VolMus + const.

[0188] Therefore, the work of breathing of the ventilation equipment and the work of breathing of the patient can be calculated:

[0189] WOBvent = ∫ Pvent Flow dt = ∫ Pdrv FlowVent dt,

[0190] WOBmus = ∫ Pmus Flow dt = ∫ Pdrv FlowMus dt.

[0191] There are two possibilities, derived from the equations of motion (see above) and proven by substitution and integration. In a simplified assumption, Pmus can be assumed to be proportional to the EMG signal:

[0192] Pmus = NME EMG

[0193] Or, for example, assumed to be a linear combination of EMG signals from two muscle groups:

[0194] Pmus = NME1 EMG1 + NME2 EMG2

[0195] Where NME, NME1, and NME2 represent the neuromechanical efficiencies of each muscle group. Therefore, the motion equation is:

[0196] Pvent + Pmus = R Flow+E Vol+const

[0197] The change is as follows:

[0198] Pvent = R Flow + E Vol + const – NME EMG.

[0199] How can it be determined that NME is already known and within the scope of this invention, the aspect of "effectiveness" is described. Muscle activation is the sum of voluntary activity and activity triggered by stimulation:

[0200] EMG = EMGspon + EMGstim

[0201] It is assumed that the amplitude of the activity triggered by the stimulus, EMGstim^, is multiplicatively related to the activatability k and the amplitude of the stimulus intensity, Istim^.

[0202] EMGstim^ = k Istim^.

[0203] If the stimulus intensity and activation measures are applicable over a large time range, such as a complete breath (ganzeAtemzüge), then scalar relations can be applied. Stimulation is now performed, typically as a sequence of weighted pulses with intervals of 20-100 ms corresponding to 10-50 Hz (preferably 40-50 ms corresponding to 20-25 Hz). Each individual pulse (twitch) triggers a single activation, but only after the entire pulse sequence is a breath-like shape of the activation signal obtained. That is, the temporal variation of the triggered activity EMGstim(t) is significantly different from the temporal variation of the stimulus intensity Istim(t). Activatability can only be expressed as a simple constant (or characteristic line) in the case of a time-averaged variable. For the time response, kernel-based estimation is possible, for example, under simple assumptions:

[0204] EMGstim(t) = Istim(t) * k(t)

[0205] Here, * denotes the convolution symbol, and k(t) is the kernel of activatability to be estimated, i.e., the core of the model. The steady-state component (offset) of activation in the sense of tonic tone is ignored here. Typically, Istim(t) is a sequence of transient stimulus impulses. Then, k(t) corresponds to the impulse response of activation to stimulus impulses of intensity Istim(t). Many methods exist for estimating the kernel k(t), such as system identification methods, stimulus-related averaging (e.g., similar to a histogram of peripheral stimuli), or least-squares estimation methods.

[0206] In the following equations:

[0207] EMG = EMGspon + Istim(t) * k(t)

[0208] EMGspon is assumed to be an error signal, which is minimized by an adaptive kernel. Finally, this also determines the autonomous activity EMGspon, resulting in the motion equations:

[0209] Pvent(t) = R Flow(t) + E Vol(t) + const – NME [EMGspon(t) + k(t) *Istim(t)]

[0210] All factors are known. Therefore, the total work of breathing and the share of driving pressure can be determined and used to control ventilation and stimulation. Instead of estimating the sampled values ​​of the kernel, parameter estimation can also be performed. In this way, the kernel can be understood as the system's impulse response, and its parameters can be identified. For example, for the activation of two muscle groups when necessary by stimulation, the appropriate parameters can be applied accordingly.

[0211] EMG = EMG1 + EMG2

[0212] = EMG1spon+EMG1stim+EMG2spon+EMG2stim

[0213] and

[0214] Pvent(t) = R Flow(t)+E Vol(t) + const

[0215] – NME1 [EMG1spon(t) + k1(t) * Istim1(t)]

[0216] – NME2 [EMG2spon(t) + k2(t) * Istim2(t)].

[0217] Therefore, the share of respiratory work performed by different muscle groups can be determined. That is, a specific stimulus achieves targeted manipulation of a specific muscle group and results in activation. Thus, the estimation of neuromechanical efficiency and core or stimulus impulse response is relatively straightforward. Instead of using respiratory work (WOB) or muscle pressure (Pmus) as the target variable for stimulation, the share of flow rate (FlowMus) caused by muscle tissue can also be used. In some cases, FlowMus (flow rate) or its time integral (VolMus) can be advantageous, as understood according to the literature US20170252558 A1. It will be advantageous for clinicians that the terms “flow” and “volume” are very commonly used in comparison to muscle pressure or respiratory work. Dividing flow rate or volume into patient and machine shares is the basis of this implementation. If FlowMus is available, it can be determined very simply by integrating VolMus (as a time-varying process) and VTmus (tidal volume performed by muscles) or MVmus (muscle minute ventilation). These variables can be important for the diagnosis and treatment of breathing.

[0218] Figure 3 An overview diagram is shown for patient ventilation and for detecting electromyography signals. Figure 3The ventilation device 200 for ventilating patient 300 is shown on the right. Electromyography (EMG) signals are detected at the patient's respiratory muscle tissue (diaphragm and accessory muscles) via sensors, and the raw EMG(t) signal is transmitted to a signal processing unit 310, which determines the envelope from the raw signal. Then, another signal processing device 320 from the envelope Furthermore, the changes in respiratory muscle pressure Pmus of patient 300 are determined from signals (airway pressure Paw(t), volumetric flow rate V'(t), and respiratory volume V(t)) provided by ventilation device 200.

[0219] Therefore, determining the first and second information 12 and 14 may include estimating the respiratory pressure exerted through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volumetric flow rate V' generated at the patient. The method 10 may include receiving information about the generated airway pressure Paw, respiratory volume V, and respiratory volumetric flow rate V' from a ventilation system 200 ventilating the patient 300.

[0220] iPEEP is the pressure the lungs have at the end of exhalation. If iPEEP is very high, the patient has not successfully inhaled enough air into the lungs relative to the iPEEP. Therefore, understanding iPEEP is important for diagnosis and for controlling ventilation devices. This embodiment calculates iPEEP without placing a catheter and measuring probe in the patient's esophagus, i.e., without knowing the esophageal pressure Pes. In the following, Pvent represents the pressure generated by the ventilation device; Vol, Vol' represent the total volume or total volumetric flow rate flowing from the ventilation device to the patient or vice versa; and Volmus, Vol'mus represent the volume or volumetric flow rate obtained by the patient using their respiratory muscle tissue.

[0221] Figure 4 The diagram illustrates the time-varying process 410 of the pressure Pvent generated by the ventilation device, the volumetric flow rate 420, Vol' between the ventilation device and the patient, and the change in the patient's own respiratory effort 430, Pes. In this embodiment, the ventilation device operates in a pressure-controlled manner, i.e., a flow rate is generated at a pre-given pressure. Alternatively, it can be regulated in the exact opposite way, where it is not used during spontaneous breathing but only during forced ventilation. The lower curve 430 shows the patient's own respiratory effort as measured by the esophageal pressure Pes. It can be seen that the spontaneous breathing rate is twice the frequency of the ventilation stroke. The ventilation device is not optimally synchronized with the patient's own respiratory activity.

[0222] The embodiments herein may use the process of changes in respiratory muscle pressure to, for example, perform automatic detection of the moment when a patient begins to attempt inhalation.

[0223] Figure 5 The diagram illustrates the time variation of volumetric flow rate Vol' 510 and airway pressure Paw 520 in one embodiment. In the time variation of volumetric flow rate Vol' 510, expressed in [l / sec], the segment above the zero line represents the inhalation process. Paw is the time variation of pressure Pvent 520, expressed in [mbar], obtained by the ventilation device and always greater than or equal to zero. Vertical dashed lines 570 indicate the moment when respiratory effort begins, and line 590 indicates the moment when respiratory effort ends. The patient has COPD (chronic obstructive pulmonary disease) and suffers from "dynamic hyperinflation" or intrinsic PEEP. This is identified by the fact that the Paw signal has already decreased before the flow rate 510 has its zero-crossing point. Therefore, the patient must work forcefully to obtain a flow rate 510 from negative (exhaled) to zero. At time t = 396.5 sec, p0.1 obstruction is triggered. Each vertical dashed line 570 indicates the start of the patient's inhalation attempt. This time is denoted by tA. Here, determining the first information 12 includes estimating a first moment tA based on the start of respiratory gas flow towards the patient caused by the flow through the patient's muscle tissue. Determining the first information 12 can be done by estimating this first moment tA based on a threshold of the patient's respiratory effort signal. The first moment tA can also be estimated based on the start of the patient's spontaneous breathing. Each zero-crossing 580 of Vol' indicates the moment from which airway flow begins towards the patient. This does not yet correspond to active delivery. For this, the ventilation device must first be triggered, which typically occurs shortly thereafter, so that the pressure support stroke is then triggered. This moment is denoted by tB. Determining the second information 12 may include estimating a second moment tB based on the start of respiratory gas flow towards the patient. Because the ventilation stroke of the ventilation device lags, referring to the change in total volumetric flow rate 510, tB is temporally behind tA. The temporal change of Pmus can be calculated using sEMG. Therefore, determining the first and second information 12 and 14 may include estimating the respiratory pressure applied through the patient's muscle tissue based on electromyographic signals.

[0224] In an embodiment, determination 16 may include determining a measure of the difference or weighted difference between Pmus(tA) and Pmus(tB). For example, in one embodiment, a measure is derived...

[0225] (3) iPEEP=Pmus(tB)-Pmus(tA).

[0226] Here, the addends can also be weighted. In other embodiments, it is also conceivable that determination 16 includes determining a measure of the quotient or weighted quotient between Pmus(tA) and Pmus(tB). Determination 16 may include averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases. This could be done, for example, by calculating the differences multiple times consecutively according to the equation described above, and then forming an average.

[0227] Figure 6 The diagram illustrates the signal variations of EMG signals 610, 620, respiratory muscle pressure Pmus 630, airway pressure Paw 640, and respiratory gas volumetric flow rate Vol' 650 in one embodiment. Figure 6 The topmost curve shows the time variation of the EMG signals 610 and 620 generated by sEMG. Costmar 620 shows the time variation obtained from two measuring electrodes near the diaphragm, and Intercost 610 shows the time variation obtained from two electrodes at the height of the ribs (respiratory accessory muscle tissue). See also... Figure 3 In the two original signals, the heart rate cycle was removed computationally (EcgR = ECG removal), which resulted in a gap. In the plot shown, the gap is interpolated. The two related solid lines 612 and 622 (curves, envelope) are measures of the patient's spontaneous breathing. Pmus 630 here is based on formula (1) Pmus = Ecw Vol-Pes is used for estimation. Each vertical line 670 represents time tA (Pmus > threshold), i.e., the start of the patient's inhalation attempt. Alternatively or supplementarily, Pmus can also be estimated based on Costmar 620 and Intercost 610, for example as described in DE 10 2020 133460A1. Generally, Pmus 630 can be estimated based on Costmar 620 and Intercost 610. For example, Pmus 630 can be calculated based on Costmar 620 and Intercost 610 as a linear combination (with coefficients NME1 and NME2).

[0228] The third curve shows the airway pressure Paw 640. The fourth curve shows the respiratory gas volumetric flow rate Vol' 650 and clarifies that the ventilation duration is not optimally synchronized with the patient's own breathing effort. Vertical line 680 indicates the start of the actual flow towards the patient (the start of the inspiratory phase, tB), and line 690 indicates the start of the actual flow away from the patient (the start of the expiratory phase). Vertical lines 680 and 690 respectively indicate the phase changes in the corresponding signals, and the phase changes of airway pressure Paw 640 and respiratory gas volumetric flow rate 650 catch up with the moment tA when the patient spontaneously attempts to inhale. Here, the phase change represents the change in respiratory phase (between inspiration and expiration) identified by the ventilation device (slightly later).

[0229] Figure 7 The diagram illustrates the signal variations of sEMG signals 710, 720, volumetric flow rate Vol' 730, and volumetric flow rate Vol'mus 740 generated by the patient's muscles in one embodiment. Figure 7 This illustrates a typical situation where a patient has COPD and therefore exhibits high iPEEP: Vol'730 represents the total volumetric flow rate between the ventilation device and the patient, and Vol'mus = Flow-mus = fmus. 740 represents the patient-generated share of the total volumetric flow rate. The vertical line 770 indicates when the patient begins attempting inhalation. The zero-crossing of the total volumetric flow rate Vol'730 at 780 always occurs after line 770 in time. At time t=396.5, an obstruction with a duration of 100 ms is performed.

[0230] Figure 8The signal variations of volumetric flow rate Flow 810, airway pressure Paw 820, esophageal pressure Pes 830, and gastric pressure Pga 840 are illustrated. When detecting esophageal pressure Pes, gastric pressure is often also detected together via the second lumen of the esophageal tube. The difference between esophageal and gastric pressures provides another measure of the muscular pressure exerted by the diaphragm. In this case, Flow 810 represents the generated volumetric flow rate, Vol', Paw 820 represents the pressure applied to the ventilation device, Paw, and P0.1 represents an obstruction triggered by Vol' 810 crossing from - to +, i.e., at time tB, and lasting, for example, Δt = 100 msec. Pes has already decreased at time tA. In some embodiments, obstruction may be triggered separately at multiple times tB. Therefore, method 10 may include averaging, smoothing, outlier suppression, or determining the median of multiple temporally sequentially determined measures of iPEEP to obtain an improved measure of iPEEP. The ventilation device measures airway pressure using the signal Paw820. During obstruction, specifically within a 100 ms time window, this signal Paw is in good agreement with the pressure Pmus generated by the patient's own breathing effort, except for its sign. Furthermore, within the time window between tA and tB+Δt, Pmus can be assumed to increase linearly. Therefore, Pmus increases linearly from the value Pmus(tB) to the value Pmus(tB+Δt).

[0231] Therefore, it applies to:

[0232] (3) iPEEP=Pmus(tB)–Pmus(tA), see above.

[0233] as well as

[0234] (4) P0.1=Paw(tB)–Paw(tB+Δt),

[0235] The pressure difference measured during the blockage.

[0236] Because the change of Pmus in the interval [tA, tB+Δt] is considered linear, it is applicable as follows:

[0237] (5) [Pmus(tB)–Pmus(tA)] / [tB–tA]=[Paw(tB)–Paw(tB+Δt)] / Δt.

[0238] Based on this, and from (3) we can deduce

[0239] (6)iPEEP=[Paw(tB)–Paw(tB+Δt)] [tB–tA] / Δt.

[0240] In the embodiment, the blocking duration Δt can, for example, be a value of approximately 100 ms. In the generalization of (3) is...

[0241] (7) iPEEP=f(ΔPmus), where ΔPmus=Pmus(tB)–Pmus(tA).

[0242] For example, f(x) = a x + b, where slope a and offset b.

[0243] From equations (6) and (7)

[0244] (8)a [Pmus(tB)–Pmus(tA)] + b

[0245] = [Paw(tB)–Paw(tB+Δt)] [tB–tA] / Δt.

[0246] Multiple blocking provides samples, and linear regression analysis provides estimates of the two parameters a and b.

[0247] exist Figure 8 In this process, p0.1 obstruction is triggered after crossing the zero flow line. However, respiratory effort has already begun beforehand. This can be identified by the drop in esophageal pressure Pes 830, which corresponds to a drop in Pmus (since the volume of respiration is negligible at this moment). Furthermore, the Pmus signal used can be calibrated by spreading routine and clinically accepted p0.1 obstructions, see Figure 8 and Equation (8). Method 10 can therefore include a determination 16 of the measurement of iPEEP based on measurements of the ventilation device 200 during obstruction. These obstructions last for approximately 100 ms, making the obstruction barely perceptible to the patient. Spreading can be performed periodically, initiated by the physician or triggered based on the characteristics of the signal quality involved in the Pmus signal or sEMG signal, for which see, for example, DE 10 2019 007 717B3. The pressure signal Paw detected by the ventilation device 200 during p0.1 obstruction is a near-ideal measure of muscle pressure Pmus within this small (100 ms) time window. Furthermore, it can be expected that the increase in Pmus is continuous near time tA. That is, the increase in Pmus during the interval [tA, tB] corresponds to the increase during the blocking period, i.e.:

[0248] (9) ΔPmus / (tB–tA)

[0249] = (Pmus(tB)–Pmus(tA)) / (tB-tA)

[0250] = iPEEP / (tB-tA)=p0.1 / 100 ms,

[0251] and

[0252] (10) iPEEP

[0253] = p0.1 (tB-tA) / 100 ms

[0254] See also equation (6).

[0255] Using this continuity condition, the Pmus signal can be tested and scaled / calibrated as necessary by using p0.1 occlusion, or the value iPEEP can be tested and scaled / calibrated as necessary by direct testing (see below, equations (11) and (12)). Furthermore, equation (10) is also used in the context of ultrasound measurements, as known from Bernardi E. et al., “A New Ultrasound Method for Estimating Dynamic Intrinsic Positive Airway Pressure: A Prospective Clinical Trial”, AJRCCM, 2018, and Pisani L. et al., “Noninvasive detection of positive end-expiratory pressure in COPD patients recovering from acute respiratory failure”, European Respiratory Journal 2016. The calculation of dynamic intrinsic PEEP does not necessarily have to be performed as shown in equation (2), as a correction term may be required (see Younes, M., “Dynamic Intrinsic PEEP (PEEPi,dyn) Is It Worth Saving”). (Discussion in AJRCCM).

[0256] However, it can be assumed that it applies.

[0257] (11) iPEEP=f (Pmus) = f (Pmus(tB) – Pmus(tA))

[0258] The function f(x) is preferably a linear function.

[0259] (12) f(x) = a x + b.

[0260] For example, factor a and offset b can be determined by regression (calibration) with p0.1 blocking. The regression equation is derived after equating iPEEP in equations (10) and (11).

[0261] (13) p0.1 (tB – tA) / 100 ms = a ΔPmus + b,

[0262] See equation (8).

[0263] Since the repeatability of the measurements of p0.1 and ΔPmus is not complex, a and b can be determined directly, for example, using linear regression. In an embodiment, the above-described method steps can be performed by the control unit 24 of the device 20. The control unit can be configured to perform a measurement 16 for performing iPEEP measurements, which may include, for example, determining a measure of the difference or weighted difference between Pmus(tA) and Pmus(tB), determining a measure of the quotient or weighted quotient between Pmus(tA) and Pmus(tB), or averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases.

[0264] The control unit 24 may be configured to perform the determination of first information and second information 12, 14 by estimating the respiratory pressure applied through the patient's muscle tissue based on electromyography signals and / or by estimating the respiratory pressure applied through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volume flow rate V' generated at the patient.

[0265] The control unit 24 may be configured to receive, for example via one or more interfaces 22, information from the ventilation device 200 ventilating the patient 300 regarding the generated airway pressure Paw, respiratory volume V, and respiratory volume flow rate V'.

[0266] In some embodiments, the control unit 24 may be configured to determine the first information by estimating a first time tA based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue, by estimating the first time tA based on a threshold of the patient's respiratory effort signal, and / or by estimating the first time tA based on the start of the patient's spontaneous breathing.

[0267] In other embodiments, control unit 24 may be configured to determine second information by estimating a second time tB based on the start of respiratory gas flow toward the patient. Control unit 24 may be configured to average, smooth, suppress outliers, or thereby determine the median of multiple temporally determined measures of iPEEP to obtain an improved measure of iPEEP. Control unit 24 may be configured to calibrate the measure 16 of iPEEP based on measurements taken by the ventilation device during one or more obstructions. For example, the aforementioned p0.1 obstructions are used for this purpose because they are short in duration and are available as a function in many ventilation devices.

[0268] The aspects and features described together with one or more of the examples and figures described in the previous detailed descriptions may also be combined with one or more of the other examples in order to replace the same features in the other examples or additionally introduce the feature into another example.

[0269] Furthermore, examples may be or relate to computer programs having program code that performs one or more of the methods described above when the computer program is executed on a computer or processor. The steps, operations, or processes of the different methods described above can be performed by a programmed computer or processor. Examples may also cover program storage devices, such as digital data storage media, which are machine-, processor-, or computer-readable program codes encoding machine-executable, processor-executable, or computer-executable instructions. The instructions perform some or all of the steps of the methods described above or cause the execution of the steps. Program storage devices may include, for example, digital memories, magnetic storage media such as disks and tapes, hard disk drives, or optically readable digital data storage media. Other examples may also cover computers, processors, or control units programmed to perform the steps of the methods described above, or field-programmable logic arrays ((F)PLAs = (Field) Programmable Logic Arrays) or field-programmable gate arrays ((F)PGA = (Field) Programmable Gate Arrays) programmed to perform the steps of the methods described above.

[0270] The principles of this disclosure are illustrated only by way of the specification and accompanying drawings. Furthermore, all examples listed herein are intended, in principle, explicitly for illustrative purposes only, to aid the reader in understanding the principles of this disclosure and the solutions for technological advancement contributed by the inventors(s). All statements herein regarding the principles, aspects, and examples of the disclosure, as well as specific examples thereof, include their equivalents.

[0271] A function block, referred to as a "component for performing a defined function," can involve a circuit that is configured to perform the defined function. Therefore, a "component for something" can be implemented as a "component that constitutes or is suitable for something," such as components and circuits that are constituted or suitable for a corresponding task.

[0272] The functions of the various elements shown in the figures (including any functional blocks referred to as "components," "components for providing signals," "components for generating signals," etc.) can be implemented in dedicated hardware, such as "signal providers," "signal processing units," "processors," "controllers," etc., or as hardware capable of executing software in conjunction with related software. When provided via a processor, the function can be provided by a single dedicated processor, by a single shared processor, or by multiple separate processors, some or all of which can be used jointly. However, the terms "processor" or "control device" are not limited to hardware capable of executing software alone, but can include digital signal processor hardware (DSP hardware; DSP = Digital Signal Processor), network processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), read-only memory (ROMs) for storing software, random access memory (RAMs), and non-volatile storage devices. Other hardware, conventional and / or user-specific hardware may also be included.

[0273] For example, a block diagram can represent a preliminary circuit diagram of the principles implementing the present disclosure. Similarly, flowcharts, program diagrams, state transition diagrams, pseudocode, etc., can represent various processes, operations, or steps, which are, for example, substantially represented in a computer-readable medium and thus executed by a computer or processor, regardless of whether such computer or processor is explicitly shown. The methods disclosed in the specification or patent claims can be implemented by components having elements for performing each of the various steps of these methods.

[0274] It is readily understood that the disclosure of multiple steps, processes, operations, or functions in the specification or claims should not be construed as being in a definite order, unless this is explicitly or implicitly stated otherwise, for example, for technical reasons. Therefore, the disclosure of these steps, processes, operations, or functions through multiple steps or functions is not limited to a definite order, unless these steps or functions are not interchangeable for technical reasons. Furthermore, in some examples, a single step, function, process, or operation may include and / or be broken down into multiple sub-steps, sub-functions, sub-processes, or sub-operations. Such sub-steps may be included and are part of the disclosure of that single step, unless such sub-steps are expressly excluded.

[0275] Furthermore, the following claims are hereby included in the detailed description, wherein each claim may stand alone as a separate example. While each claim may stand alone as a separate example, it should be noted that although a dependent claim may relate to a specific combination with one or more other claims in the claims statement, other examples may also include combinations of the subject matter of that dependent claim with any other dependent or independent claim. Such combinations are expressly suggested herein, and unless otherwise stated, specific combinations are not intentional. Moreover, the features of a claim should also be included with respect to any other independent claim, even if that claim is not directly dependent on that independent claim.

[0276] Other and preferred embodiments of the invention are described in more detail below, which have a scheme for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs based on an assessment of the time-varying process of respiratory pressure applied through the patient's muscle tissue.

[0277] A basic embodiment illustrates a device for a ventilation apparatus and for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs. The device has one or more interfaces configured for exchanging information with the ventilation apparatus and a control unit configured for...

[0278] - Determine first information about the first respiratory pressure Pmus(tA) exerted by tA through the patient's muscle tissue at the first moment, during which the patient's inhalation attempt is present.

[0279] - Determine second information regarding the second respiratory pressure Pmus(tB) exerted by the patient's muscle tissue at a second time tB, at which the respiratory gas flow towards the patient begins.

[0280] - The measurement of iPEEP is determined based on the first information and the second information.

[0281] A preferred embodiment based on the previously described implementation may include one or more sensors for detecting measurements during patient ventilation.

[0282] A preferred embodiment based on at least one of the previously described embodiments can be configured for detecting pressure measurements or pressure measurement signals during patient ventilation.

[0283] In a preferred embodiment based on at least one of the previously described embodiments, the determination may include a measure of the difference or weighted difference between Pmus(tA) and Pmus(tB).

[0284] In a preferred embodiment based on at least one of the previously described embodiments, the determination may include a measure of determining the quotient or weighted quotient between Pmus(tA) and Pmus(tB).

[0285] In a preferred embodiment based on at least one of the previously described embodiments, the measurement may include averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases.

[0286] In a preferred embodiment based on at least one of the previously described embodiments, determining the first and second information may include estimating the respiratory pressure applied through the patient's muscle tissue based on electromyography signals.

[0287] In a preferred embodiment based on at least one of the previously described embodiments, determining the first and second information may include estimating the respiratory pressure applied through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volume flow rate V' generated at the patient.

[0288] In a preferred embodiment based on at least one of the previously described embodiments, the control unit may be configured to receive information from a ventilation device ventilating a patient regarding the generated airway pressure Paw, respiratory volume V, and respiratory volume flow rate V'.

[0289] In a preferred embodiment based on at least one of the previously described embodiments, determining the first information may include estimating a first moment based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue.

[0290] In a preferred embodiment based on at least one of the previously described embodiments, determining the first information may include estimating a first moment based on a threshold crossing of the patient’s respiratory effort signal.

[0291] In a preferred embodiment based on at least one of the previously described embodiments, determining the first information may include estimating a first moment based on the onset of the patient’s spontaneous breathing.

[0292] In a preferred embodiment based on at least one of the previously described embodiments, determining the second information may include estimating a second moment based on the start of respiratory gas flow toward the patient.

[0293] In a preferred embodiment based on at least one of the previously described embodiments, the control unit may be configured to average, smooth, suppress outliers, or thereby determine the median of a plurality of time-sequentially determined measures of iPEEP in order to obtain an improved measure of iPEEP.

[0294] In a preferred embodiment based on the previously described implementation, the control unit may be configured to calibrate the measurement of iPEEP based on measurements of the ventilation device during obstruction.

[0295] In a preferred embodiment based on at least one of the previously described embodiments, the device may be configured as a ventilation device.

[0296] The basic implementation illustrates a method for measuring the intrinsic end-expiratory pressure (iPEEP) in a patient's lungs, comprising:

[0297] - Determine first information about the first respiratory pressure Pmus(tA) exerted by tA through the patient's muscle tissue at the first moment, at which the patient's inhalation attempt exists;

[0298] - Determine second information regarding the second respiratory pressure Pmus(tB) exerted by the patient's muscle tissue at the second time point tB, at which the respiratory gas flow towards the patient begins.

[0299] - The measurement of (16) iPEEP is determined based on the first information and the second information.

[0300] In a preferred embodiment based on the previously described implementation, the determination may include a measure of the difference or weighted difference between Pmus(tA) and Pmus(tB).

[0301] In a preferred embodiment based on at least one of the previously described embodiments, the determination may include a measure of determining the quotient and / or weighted quotient between Pmus(tA) and Pmus(tB).

[0302] In a preferred embodiment based on at least one of the previously described embodiments, the measurement may include averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases.

[0303] In a preferred embodiment based on at least one of the previously described embodiments, determining the first and second information may include estimating the respiratory pressure applied through the patient's muscle tissue based on electromyography signals.

[0304] In a preferred embodiment based on at least one of the previously described embodiments, determining the first and second information may include estimating the respiratory pressure applied through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volume flow rate V' generated at the patient.

[0305] A preferred embodiment based on at least one of the previously described embodiments may include receiving information from a ventilation system ventilating a patient regarding the generated airway pressure Paw, respiratory volume V, and respiratory volume flow rate V'.

[0306] In a preferred embodiment based on at least one of the previously described embodiments, determining the first information may include estimating a first moment tA based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue.

[0307] In a preferred embodiment based on at least one of the previously described embodiments, determining the first information may include estimating a first moment tA based on a threshold crossing of the patient’s respiratory effort signal.

[0308] In a preferred embodiment based on at least one of the previously described embodiments, determining the first information may include estimating a first moment tA based on the start of the patient’s spontaneous breathing.

[0309] In a preferred embodiment based on at least one of the previously described embodiments, determining the second information may include estimating a second time tB based on the start of respiratory gas flow toward the patient.

[0310] A preferred embodiment based on at least one of the previously described embodiments may include averaging, smoothing, suppressing outliers, or determining the median of a plurality of time-sequentially determined measures of iPEEP in order to obtain an improved measure of iPEEP.

[0311] A preferred embodiment based on at least one of the previously described embodiments may include the determination of a measure of iPEEP calibrated based on measurements of the ventilation device during obstruction.

[0312] A basic implementation may include a computer program having program code for performing at least one of the previously described implementations. Advantageously, the program code may be executed on a computer, a processor, or a programmable hardware component.

[0313] Table 2 below includes the abbreviations and names used within the scope of this invention, along with brief explanations for each.

[0314]

[0315]

[0316] Table 2.

[0317] Table 3 below lists all patent documents and publications referenced in this specification, along with their publication numbers or short titles. Full titles may be found in the description of the prior art in the introduction to the specification. In the specification, reference numbers [E1] to [E38] listed in Table 3 are used in part, instead of extensive references.

[0318]

[0319]

[0320] Table 3.

[0321] List of reference numerals

[0322] 10. Methods for measuring intrinsic end-expiratory pressure (iPEEP)

[0323] 12. Determine the first information

[0324] 14. Determine the second information

[0325] 16. Measurement of iPEEP

[0326] 20. Devices for measuring intrinsic end-expiratory pressure (iPEEP)

[0327] 22 One or more interfaces

[0328] 24 Control Unit

[0329] 200 ventilation equipment

[0330] 300 patients

[0331] 310 Signal Processing

[0332] 320 Signal Processing

[0333] 410 Pvent, the pressure generated by the ventilation equipment.

[0334] 420 Vol', volumetric flow rate

[0335] 430 Pes, the process of changing one's own breathing effort

[0336] 510 Volumetric flow rate Vol' in [l / sec]

[0337] 520 Paw, the time-varying process of pressure Pvent in [mbar].

[0338] 570 The moment the effort to breathe begins, tA

[0339] 580 Vol' zero crossing, tB

[0340] 590 Breathing effort ends

[0341] 610 Intercost

[0342] 612 Intercost envelope

[0343] 620 Costmar

[0344] 622 Costmar's envelope

[0345] 630 Respiratory muscle pressure Pmus

[0346] 640 respiratory pressure Paw

[0347] 650 Volumetric Flow Rate Vol'

[0348] The start of actual flow towards the patient at 680, tB

[0349] 690 The start of actual flow leaving the patient

[0350] 710 sEMG signal, Intercost

[0351] 720 sEMG signal, Costmar

[0352] 730 volumetric flow rate, Vol'

[0353] 740. Volumetric flow rate produced by muscle, Vol'mus

[0354] 770 Inhalation trial, tA

[0355] The zero crossing of the total volumetric flow rate Vol' of 780, tB

[0356] 810 Volumetric Flow

[0357] 820 respiratory pressure Paw

[0358] 830 esophageal pressure Pes

[0359] 840 gastric pressure Pga.

Claims

1. A device (20) for measuring the intrinsic end-expiratory pressure (iPEEP) in the lungs of a patient (300), the device having one or more interfaces (22) configured for exchanging information with a ventilation device (200), and having a control unit (24) configured for... - Determine first information regarding the first respiratory pressure Pmus(tA) exerted by the patient through the patient's muscle tissue at a first moment tA, during which the patient has an inhalation attempt. - Determine second information regarding the second respiratory pressure Pmus(tB) exerted by the patient's muscle tissue at a second time tB, and the respiratory gas flow rate that begins to flow to the patient at that second time. - Based on the first information and based on the second information, a measure of the iPEEP is determined, wherein the determination includes determining a measure of the weighted difference between Pmus(tA) and Pmus(tB) and / or determining a measure of the weighted quotient between Pmus(tA) and Pmus(tB).

2. The device (20) according to claim 1. The device includes one or more sensors for detecting measurements during ventilation of the patient (300).

3. The device (20) according to any one of claims 1 or 2. The control unit (24) is configured to detect pressure measurements or pressure measurement signals during ventilation of the patient (300).

4. The device (20) according to any one of claims 1 to 2. The determination includes averaging, classifying, and / or evaluating pressure measurements from multiple respiratory phases.

5. The device (20) according to any one of claims 1 to 2. Determining the first information and the second information includes: - Estimate the respiratory pressure exerted through the patient's muscle tissue based on electromyography signals, and / or - Estimate the respiratory pressure exerted through the patient's muscle tissue based on the airway pressure Paw, respiratory volume V, and respiratory volume flow rate V' generated at the patient.

6. The device (20) according to any one of claims 1 to 2. The control unit (24) is configured to receive information from the ventilation device currently ventilating the patient regarding the generated airway pressure Paw, respiratory volume V, and / or respiratory volume flow rate V'.

7. The device (20) according to any one of claims 1 to 2. Determining the first information includes estimating the first moment based on the start of respiratory gas flow toward the patient caused by the patient's muscle tissue.

8. The device (20) according to any one of claims 1 to 2. Determining the first information includes: - Estimate the first moment based on the threshold crossing of the patient's respiratory effort signal, and / or - The first moment is estimated based on the onset of the patient's spontaneous breathing.

9. The device (20) according to any one of claims 1 to 2. Determining the second information includes estimating the second moment based on the start of respiratory gas flow toward the patient.

10. The device (20) according to any one of claims 1 to 2. The control unit (24) thereunder is configured to average, smooth, suppress outliers, or thereby determine the median of a plurality of time-sequentially determined measures of the iPEEP in order to obtain an improved measure of the iPEEP.

11. The device (20) according to any one of claims 1 to 2. The control unit (24) therein is configured to determine the measure of iPEEP based on measurements of the ventilation device during blockage.

12. A ventilation device (200) having the device (20) according to any one of claims 1 to 11.

13. A method for measuring the intrinsic end-expiratory pressure (iPEEP) in the lungs of a patient (300), comprising: - Determine first information regarding the first respiratory pressure Pmus(tA) exerted by the patient through the patient's muscle tissue at a first moment tA, during which the patient has an inhalation attempt. - Determine second information regarding the second respiratory pressure Pmus(tB) exerted by the patient's muscle tissue at a second time tB, and the respiratory gas flow rate that begins to flow to the patient at that second time. - Based on the first information and based on the second information, a measure of the iPEEP is determined, wherein the determination includes determining a measure of the weighted difference between Pmus(tA) and Pmus(tB) and / or determining a measure of the weighted quotient between Pmus(tA) and Pmus(tB).

14. A computer program having program code that, when executed on a computer, processor, or programmable hardware component, performs the method of claim 13.

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