System for detecting asynchronous breathing events and associated methods and components

Abstract

A method includes retrieving a lung volume waveform from an electrical impedance tomography device. The method also includes retrieving at least one of a flow waveform and a pressure waveform. The method also includes aligning the lung volume waveform and at least one of the flow waveform and the pressure waveform relative to time. The method further includes comparing the lung volume waveform to at least one of the flow waveform and the pressure waveform. The method also includes determining whether an asynchronous breathing event occurs based on comparing the lung volume waveform to at least one of the flow waveform and the pressure waveform. The method also includes classifying the asynchronous breathing event. The method also includes providing an alert identifying the asynchronous breathing event. A system includes a receiver, a processor, and a memory device configured to perform the method.

Description

[0001] Priority declaration

[0002] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 367,807, filed on July 6, 2022, under 35 U.S.C. §119(e), the disclosure of which is hereby incorporated by reference in its entirety. Technical Field

[0003] Embodiments of the present invention generally relate to medical support systems. In particular, embodiments of the present invention relate to systems and associated methods and components for detecting asynchronous respiratory events. Background Art

[0004] Mechanical ventilation is a treatment commonly used in hospitals to assist the patient's breathing during treatment of respiratory failure, anesthesia, and other respiratory diseases such as acute respiratory distress syndrome ("ARDS"), as well as other treatments to maintain or restore the patient's breathing. Such control of human breathing involves a complex feedback mechanism between the lungs, the lungs themselves, the chest wall, and the nervous system of the respiratory muscles (chemoreceptors (central and peripheral), mechanical stimulation receptors) and the vagus nerve input. When mechanical ventilation is used, the synchronization between the ventilator and the patient's respiratory rhythm makes it possible to effectively and safely reduce the load on the inspiratory muscles, as well as to ensure body oxygenation. In addition, asynchronous events between the mechanical ventilator and the patient's respiratory rhythm can reduce the efficiency of the mechanical ventilator, and have the possibility of causing harm to the patient, such as by overinflation or underinflation of the patient's lungs. Summary of the invention

[0005] Embodiments of the present invention include a system configured to detect asynchronous respiratory events. The system includes a receiver configured to receive ventilation data from at least one of a mechanical ventilator, an airway flow sensor, or an airway pressure sensor and impedance data from an electrical impedance tomography device. The system also includes a processor, a memory device configured to store the ventilation data and the impedance data, and a non-transient computer-readable medium having instructions stored thereon. The instruction causes the processor to retrieve a volume tracing from the impedance data. The instruction also causes the processor to retrieve at least one of a flow waveform and a pressure waveform from the ventilation data. The instruction also causes the processor to compare the volume tracing with the at least one of the flow waveform and the pressure waveform. The instruction also causes the processor to determine whether an asynchronous event occurs based on comparing the volume tracing with the at least one of the flow waveform and the pressure waveform. The instruction also causes the processor to classify the asynchronous event. The instruction also causes the processor to provide a classification of the asynchronous event.

[0006] Other embodiments of the present invention include a method for detecting an asynchronous respiratory event. The method includes retrieving an impedance data waveform from an electrical impedance tomography device. The method also includes retrieving one or more of a flow waveform and a pressure waveform. The method also includes aligning the impedance data waveform and the one or more of the flow waveform and the pressure waveform with respect to time. The method also includes comparing the impedance data waveform with one or more of the flow waveform and the pressure waveform. The method also includes determining whether an asynchronous respiratory event has occurred based on comparing the impedance data waveform with the one or more of the flow waveform and the pressure waveform. The method also includes classifying the asynchronous respiratory event. The method also includes providing information identifying the asynchronous respiratory event.

[0007] Another embodiment of the present invention includes a method for detecting asynchronous respiratory events. The method includes retrieving lung impedance data from an electrical impedance tomography device, the lung impedance data including a plethysmogram from at least one region of interest. The method also includes retrieving one or more of a flow waveform and a pressure waveform. The method also includes comparing the impedance data with the one or more of the flow waveform and the pressure waveform. The method also includes identifying a combined cycle based at least on the impedance data, the flow waveform, and the pressure waveform. The method also includes classifying the combined cycle. The method also includes providing recommended adjustments to a mechanical ventilator. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] To easily identify the discussion of any particular component or act, the most significant digit or digits in a reference number refer to the figure number in which the component is first introduced.

[0009] Figure 1 is a schematic diagram of a portion of an EIT system according to one or more embodiments of the present invention, the schematic diagram showing a plurality of electrodes positioned around a region of interest of a patient;

[0010] Figure 2 is a schematic diagram showing a cross-section of a patient's chest along the plane of the electrodes according to one or more embodiments of the present invention;

[0011] Figure 3 is a schematic block diagram of an EIT system according to an embodiment of the present invention;

[0012] Figure 4 A schematic diagram of a system for mechanically ventilating and monitoring the lungs of a patient according to one or more embodiments of the present invention is shown;

[0013] Figure 5 illustrates a flow chart representing a process of assessing a respiratory cycle according to an embodiment of the present invention;

[0014] Fig. 6A and Figure 6B illustrates a flow waveform and a pressure waveform according to an embodiment of the present invention;

[0015] Figure 7 illustrates a flow chart representing a decision-making process according to an embodiment of the present invention;

[0016] Figure 8 illustrates a lung volume waveform for a respiratory cycle according to an embodiment of the present invention;

[0017] Fig. 9 illustrates an aligned lung volume waveform, pressure waveform, and flow waveform according to an embodiment of the present invention; and

[0018] Fig. 10A and Fig. 10B An EIT image of a patient's lungs according to an embodiment of the present invention is illustrated. DETAILED DESCRIPTION

[0019] The illustrations presented herein are not meant to be actual views of any particular system, method, or components thereof, but are merely idealized representations used to describe illustrative embodiments. The figures are not necessarily drawn to scale.

[0020] As used herein, the term "substantially" with respect to a given parameter means and includes to the extent that one skilled in the art would understand that the given parameter, characteristic, or condition is met with a small degree of variance (such as within acceptable manufacturing tolerances). For example, a substantially met parameter may be at least about 90% met, at least about 95% met, at least about 99% met, or even at least about 100% met.

[0021] As used herein, "about" with respect to a numerical value for a particular parameter includes the numerical value, and the degree of variance from the numerical value as understood by one of ordinary skill in the art is within an acceptable tolerance for the particular parameter. For example, "about" with respect to a numerical value may include additional numerical values ​​within the range of 90.0 percent to 110.0 percent of the numerical value (such as within the range of 95.0 percent to 105.0 percent of the numerical value, within the range of 97.5 percent to 102.5 percent of the numerical value, within the range of 99.0 percent to 101.0 percent of the numerical value, within the range of 99.5 percent to 100.5 percent of the numerical value, or within the range of 99.9 percent to 100.1 percent of the numerical value).

[0022] As used herein, unless the context clearly indicates otherwise, relational terms (such as "first", "second", "top", "bottom", "upper", "lower", "right", "left", etc.) are generally used for clarity and convenience in understanding the present invention and the drawings, and do not imply or rely on any particular preference, orientation, or order.

[0023] As used herein, the term "and / or" means and includes any and all combinations of one or more of the associated listed items.

[0024] As used herein, the terms "vertical" and "horizontal" refer to the orientation as depicted in the figures.

[0025] Mechanical ventilation (MV) is a treatment commonly used in hospitals to maintain and / or assist patient breathing. When using assisted mechanical ventilation, the synchronization between the ventilator and the patient's breathing rhythm makes it possible to effectively and safely reduce the load on the inspiratory muscles and ensure body oxygenation. Patient-ventilator asynchrony (PVA) can be defined as the mismatch between the patient's needs and the time, flow, tidal volume and / or pressure waveform delivered according to the ventilator settings. PVA can be a subtle change that can be observed in time, flow, tidal volume and / or pressure waveform during monitoring of respiratory mechanics or even in monitoring of the patient's clinical condition. However, their detection requires professional, real-time attention from trained professionals at the bedside. Identifying PVA when there is no trained professional can reduce the occurrence of PVA by reducing the time before PVA is detected and adjustments are made to the mechanical ventilation system, which can reduce the harmful effects of PVA on patients.

[0026] Embodiments of the present invention may include an electrical impedance tomography (EIT) device configured to measure a regional distribution of lung impedance or changes in a patient, which is related to the regional distribution of lung volume and the regional distribution of tidal volume, which is the volume or air received by the patient during the respiratory cycle. A plethysmogram is a waveform of the sum of impedance changes in a region of interest plotted over time. Therefore, the plethysmogram waveform is related to regional lung volume. In some embodiments, other known processes and / or devices such as ultrasonic flow measurement, MRI, tracer gas, etc. are used to measure the patient's lung volume and ventilation distribution.

[0027] EIT is an imaging technique that involves positioning electrodes via an electrode strip placed around an area of ​​a patient's body, e.g., around a patient's chest for lung imaging, injecting an electrical excitation signal through a pair of electrodes, and measuring the induced response signal detected by the other electrodes of the electrode strip. Thus, an EIT system can generate an image based on voltage measurements indicative of estimated impedance values. Compared to other imaging techniques, EIT is non-invasive and does not have certain exposure risks that may limit the number and frequency of monitoring actions, e.g., as with techniques utilizing such as X-rays. Thus, EIT is suitable for continuous monitoring of a patient's condition, and particularly for monitoring a patient's lungs, as the measurements can be used to determine the patient's respiratory and hemodynamic parameters and monitor real-time two-dimensional images.

[0028] Figure 1 1 is a schematic diagram of a portion of an EIT system 100 showing a plurality of electrodes 110 positioned around a region of interest, such as a chest, of a patient 105. The electrodes 110 of the EIT system 100 may be physically held in place by an electrode strap 103. The arrangement of the electrodes 110 may be transverse to the cranio-caudal axis 104 of the patient. Although the electrodes 110 may be positioned transversely to the cranio-caudal axis 104 of the patient, the electrodes 110 may be positioned transversely to the cranio-caudal axis 104 of the patient. Figure 1 105, but the electrodes 110 may be placed around the entire patient 105, depending on the specific region of interest available for measurement or desired for measurement. The electrodes 110 may be coupled to a computing system configured to control the operation of the electrodes 110 and perform reconstruction of the EIT image.

[0029] Figure 2 1 is a schematic diagram showing a cross section of the chest of a patient 105 along the plane of the electrodes. A voltage may be applied to a pair of electrodes 110 (shown by electrodes with + and - symbols) to inject an excitation current into the patient between the pair of electrodes. Thus, the voltages (e.g., V1, V2, V3, ... V n ) may be detected by other electrodes and measured by the EIT system 100. Current injection may be performed according to a circular pattern for a measurement cycle using different electrode pairs to generate the excitation current.

[0030] Figure 33 is a schematic block diagram of an EIT system 300 according to one embodiment of the present invention. The EIT system 300 may include an electrode belt 310 operably coupled to a data processing system 320. The electrode belt 310 and the data processing system 320 may be coupled together via a wired connection, for example, a cable and / or may have a communication module for wirelessly communicating with each other. The data processing system 320 may include a processor 322, which is operably coupled to an electronic display 324, an input device 326, and a memory device 328. The electronic display 324 may be configured together with the data processing system 320 as a singular form factor of an EIT device coupled to the electrode belt 310. In some embodiments, the electronic display 324 and the data processing system 320 may be separate units of the EIT device coupled to the electrode belt 310. In yet other embodiments, the EIT system 300 may be integrated within another host system that is configured to perform additional medical measurements and / or procedures, wherein the electrode belt 310 may be coupled to a port of the host system that already has its own input devices, memory devices, and electronic displays. Thus, the host system may have the EIT processing software installed therein. Such software may be built into the host system prior to field use or updated after installation.

[0031] The processor 322 may coordinate communications between various devices and execute instructions stored in the computer-readable medium of the memory device 328 to direct current excitation, data acquisition, data analysis, and / or image reconstruction. As an example, the memory device 328 may include a finite element mesh library used by the processor 322 to model the patient's body in the region of interest in order to perform image reconstruction. The input device 326 may include devices such as a keyboard, a touch screen interface, a computer mouse, a remote control, a mobile device, or other devices configured to receive information, which the processor 322 may use to receive input from an operator of the EIT system 300. Therefore, for a touch screen interface, the electronic display 324 and the input device 326 that receives user input may be integrated into the same device. The electronic display 324 may be configured to receive the data and output an EIT image reconstructed by the processor for viewing by the operator. The processor 322 may also generate additional data (e.g., numerical data, graphs, trend information, and other information that is considered useful to the operator) using the measured EIT data alone or in combination with other non-EIT data from other equipment coupled thereto. Such additional data may be displayed on the electronic display 324.

[0032] As will be appreciated by one of ordinary skill in the art, the EIT system 300 may include components not shown in the figure but may also be included to facilitate communication with the electrode belt 310 and / or current excitation, such as one or more analog-to-digital converters, signal processing circuits, demodulation circuits, power supplies, etc.

[0033] Figure 4 A schematic diagram of a system 400 for mechanically ventilating a patient is depicted. The system 400 includes a ventilator system 402, an EIT system 404, and a controller 406 for operating the system 400. The ventilator system 402 and the EIT system 404 are operably coupled to the controller 406, for example.

[0034] In some embodiments, the ventilator system 402 includes a mechanical ventilator 408 that provides respiratory support or respiratory assistance to a patient 410. For example, the mechanical ventilator 408 can provide a flow of medical gas that can include one or more of air, oxygen, nitrogen, and helium. In some embodiments, the flow of medical gas can also include additives, such as aerosol drugs or anesthetics. The ventilator system 402 can also include a breathing circuit 412, an inspiratory limb 414, a patient limb 416, and a patient connector 418. In some embodiments, the mechanical ventilator 408 can provide a flow of medical gas to the breathing circuit 412 through the inspiratory limb 414, which is connected to the inspiratory port 420 of the mechanical ventilator 408. The medical gas can flow (e.g., travel) through the inspiratory limb 414 and enter the patient limb 416 of the breathing circuit 412. Therefore, the mechanical ventilator 408 can provide medical gas to the patient 410 through the patient connector 418.

[0035] Exhaled gases from the patient 410 may be delivered back to the mechanical ventilator 408 through the patient connector 418 and the patient limb 416. In some embodiments, the exhaled gases may be directed into the expiratory limb 422 of the breathing circuit 412 via one or more valves, e.g., check valves. For example, the ventilator system 402 may also include a plurality of check valves that may be placed at various points along the breathing circuit 412, such as to allow only medical gases to flow in a desired direction along an appropriate path toward or away from the patient 410.

[0036] Additionally, exhaled gases may be returned to the mechanical ventilator 408 through an exhalation port 424 of the mechanical ventilator 408 .

[0037] In some embodiments, the exhalation port 424 includes a controllable flow valve that can be adjusted to regulate the pressure within the breathing circuit 412. Adjusting the flow valve can generate a back pressure that is applied to the patient 410 during exhalation to generate positive end expiratory pressure (PEEP). Therefore, the system 400 can include any conventional system for providing PEEP therapy to the patient 410. In addition, other systems and configurations recognized by a person of ordinary skill in the art fall within the scope of the present invention.

[0038] The ventilator system 402 may also include one or more gas monitoring sensors 426. In some embodiments, the one or more gas monitoring sensors 426 may be disposed within the patient connection 418 of the breathing circuit 412. In alternative embodiments, the one or more gas monitoring sensors 426 may be fluidly connected to the breathing circuit 412 or any other component of the ventilator system 402. In some embodiments, the gas monitoring sensors 426 include one or more of a pressure sensor, a flow sensor, and a gas concentration sensor. As described in further detail below, the controller 406 and the mechanical ventilator 408 may utilize the one or more gas monitoring sensors 426 to monitor and ultimately control the operation of the mechanical ventilator 408 and provide information (e.g., feedback to a user (e.g., a clinician)). The one or more gas monitoring sensors 426 may include, but are not limited to, any conventional gas sensor.

[0039] The EIT system 404 may include the above referenced Figures 1 to 3 404 and may be operated according to any of the above-described embodiments. The EIT system 404 may include, but is not limited to, a conventional EIT system. In addition, as described above, the EIT system 404 can be operably coupled to the controller 406 and can provide information about measurements performed by the EIT system 404 to the controller 406. In some embodiments, the EIT system 404 is completely independent of the ventilator system 402. In one or more embodiments, the EIT system 404 also has a corresponding electronic display and input device that is separate from the display and / or input device of the ventilator system 402.

[0040] The controller 406 may include a processor 428 coupled to a memory 430 and an input / output component 432. The processor 428 may include a microprocessor, a field programmable gate array, and / or other suitable logic device. The memory 430 may include volatile and / or non-volatile media (e.g., ROM, RAM, magnetic disk storage media, optical storage media, flash memory devices, and / or other suitable storage media) and / or other types of computer-readable storage media configured to store data. The memory 430 may store algorithms and / or instructions for operating the ventilator system 402 and the EIT system 404 to be executed by the processor 428. For example, the controller 406 may include the above-referenced Figure 3 The data processing system 320 described above. In some embodiments, the processor 428 is operably coupled to send data to a computing device, such as a server or a personal computer, that is operably coupled (e.g., via the Internet) to the controller 406. The input / output component 432 may include a display, a touch screen, a keyboard, a mouse, and / or other suitable types of input / output devices configured to accept input from an operator and provide output to the operator.

[0041] Still reference Figure 4 , as referenced below Figure 5 to Figure 1 As described in more detail, the system 400 can utilize the ventilator system 402 to apply a PEEP level to the patient when determining the likelihood of a recruitment value of the patient's vital capacity (e.g., collapsed parenchyma) during RAM. PEEP increases the baseline pressure within the patient's respiratory system so that the patient's natural exhalation maintains a higher airway pressure than a breath without PEEP therapy. Conventional PEEP pressures range up to 40 cmH2O, but higher PEEP pressures can also be used. High PEEP refers to PEEP therapy applied above 10 cmH2O, and more specifically 10-30 cmH2O. Low PEEP refers to PEEP pressures below 10 cmH2O and it is usually applied at 5-8 cmH2O.

[0042] In some embodiments, the effect of applying PEEP to a patient is measured by measuring the volume of the patient's lungs in response to the application of PEEP. After PEEP is applied, the volume of the patient's lungs is measured as end-expiratory lung volume (EELV) and is measured for a specific PEEP pressure applied to the patient. In some embodiments, EELV is measured at zero PEEP ("ZEEP"). The measurement of EELV at ZEEP is referred to herein as functional residual capacity (FRC) and is a measurement of the volume of air retained in the lungs at the end of natural exhalation. In some embodiments, when the EIT system 404 is used to measure and / or determine EELV, in some cases, FRC can be considered to be zero so that FRC does not affect certain calculations. In view of the foregoing, EELV is the FRC plus the lung volume increased by the applied PEEP.

[0043] The increase in EELV associated with the application of PEEP comes from two physiological sources. The first physiological source of volume increase is the result of applying additional pressure on lung tissue. Applying additional pressure on lung tissue causes the lung and the already opened alveoli to expand (e.g., expand due to the pressure inside the lung), thereby creating more lung volume. Expanding the lung brings patients a risk in the form of volume injury (i.e., local over-expansion of normal alveoli), which damages the lungs. Volume trauma can cause patients to suffer from medical complications similar to acute respiratory distress syndrome (ARDS). The second physiological source of increased lung volume is the "re-expansion" of alveoli in a process called "sudden opening", in which the internal volume of one alveolus suddenly jumps from zero volume (e.g., collapses) to the volume obtained by adjacent alveoli (e.g., adjacent units). As known in the art, alveoli are air sacs in the lungs that promote gas exchange with the patient's blood. Some alveoli (especially diseased or damaged alveoli) collapse when the pressure in the lung drops too low, where the alveoli (e.g., units) take or reach zero volume. Applying PEEP to a patient (eg, applying PEEP therapy) can maintain a minimum airway pressure within the lungs and, in some cases, cause alveoli (eg, collapsed alveoli) to remain open.

[0044] Alveoli can only generate a certain gas exchange when they are open. Therefore, in order to maintain a certain gas exchange when PEEP is insufficient, a higher driving inspiratory pressure is required to hyperventilate the already opened alveoli in order to compensate for the lack of function of the closed alveoli (e.g., units). The increased respiratory effort causes greater expansion on the remaining open alveoli, which can lead to further damage to the lung tissue. In contrast, when PEEP is sufficient, gas exchange is shared among most of the alveoli (e.g., units), which reduces the driving inspiratory pressure and, in some cases, reduces lung damage. Therefore, the recruitment of alveoli also increases EELV, which corresponds to the additional volume generated by the sudden opening of multiple alveolar units. The additional volume generated by the opened alveolar units is called the volume gain of the lung at a specific pressure (or vertical displacement in a pressure-volume plot). In a graph with two pressure-volume plots representing lung inflation, wherein the first plot represents inflation of the lung without recruitment and wherein the second plot represents conditional inflation of the lung when the alveoli (e.g., units) are opened from the beginning of inflation, the vertical distance between the two curves (see Figure 7 and Figure 8 ) represents the volume gain caused by recruitment.

[0045] Figure 5 A flow chart showing a process 500 for evaluating a respiratory cycle is illustrated. FIG. 6A to FIG. 1 1 further describes individual process actions in detail. Process actions may be performed by a controller such as controller 406 ( Figure 4 ) using a mechanical ventilator, for example, mechanical ventilator 408 ( Figure 4 ), gas flow or gas pressure sensor such as gas monitoring sensor 426 ( Figure 4 ) and EIT systems such as EIT system 404 ( Figure 4 ) is performed based on mechanical ventilation data received by the ventilator. The data may include gas flow values ​​over time, such as gas flow waveforms, gas pressure values ​​over time, such as gas pressure waveforms, ventilator cycles, inspiratory signals, such as inspiratory event triggers or inspiratory event trigger points, expiratory signals, such as expiratory event triggers or expiratory event trigger points, EIT images, and basic data (e.g., plethysmographic data, lung impedance values ​​over time, lung volume values ​​over time, lung volume waveforms, plethysmographic graphs, regional lung volume values ​​over time), etc.

[0046] The combination of mechanical ventilator and gas monitoring sensor can provide gas flow waveform and gas pressure waveform to controller.Gas monitoring sensor can also provide inhalation trigger and exhalation trigger.Inhalation trigger and exhalation trigger can be the trigger point that indicates when patient switches from inhalation to exhalation or switches from exhalation to inhalation.In some embodiments, inhalation trigger and exhalation trigger are transmitted to mechanical ventilator, to trigger mechanical ventilator to provide pressurized air (inhalation event) to patient or remove pressure and allow air to leave patient's lung or provide negative pressure to extract air from patient's lung (expiration event).Gas monitoring sensor can determine the existence of inhalation trigger point or exhalation trigger point based on the sudden change of one or more of gas flow, gas pressure or flow volume in the breathing circuit between mechanical ventilator and patient.Inhalation trigger and exhalation trigger are used to define breathing cycle.Breathing cycle can start at the beginning of inhalation event and end at the end of subsequent exhalation event or end at the transition from exhalation event to the next inhalation event.

[0047] The process 500 of evaluating a breathing cycle may begin by determining whether any triggering events (e.g., an inspiratory trigger or an expiratory trigger) are missed, such that a cycle is missed or misidentified in act 502. Asynchronous events between the mechanical ventilator and the patient may cause the gas monitoring sensor to miss one or more triggering events. Therefore, the process may begin by analyzing the gas pressure waveform and the gas flow waveform and identifying triggering events from the gas monitoring sensor that are not included in the inspiratory trigger and the expiratory trigger. Fig. 6A and Figure 6B The identification of missed triggering events is described in more detail.

[0048] After identifying a missed triggering event, the process 500 of evaluating the breathing cycle can search for artifacts in action 504. As used herein, an "artifact" is an event that will cause (e.g., lead to, achieve) an inaccurate reading, such as a sensor disconnect, a change in a parameter (e.g., pressure, PEEP, flow, etc.), a purge, aspiration, etc. If an artifact is detected, the associated breathing cycle is marked as an invalid cycle. This can substantially prevent the controller from erroneously identifying asynchrony during an artifact event. Figure 7 The detection of artifacts is described in more detail.

[0049] After identifying artifacts in act 504, the process 500 of evaluating the breathing cycle searches for data for asynchrony in act 506. As used herein, "asynchrony" is a situation where the mechanical ventilator and the patient are not synchronized. Asynchrony can include combined cycles, double triggering, reverse triggering, breath stacking, breath stacking volume, trapped volume, and / or stacking volume. Asynchrony can be identified by comparing the lung volume data from the EIT system with the gas pressure waveform and the gas flow waveform from the gas monitoring sensor. Figure 8 to Figure 1 1 describes the detection of different asynchronies in more detail.

[0050] After identifying artifacts in act 504 and asynchrony in act 506, the controller combines the artifacts and asynchrony in act 508. The controller may display the artifacts and asynchrony as a report on a display, such as input / output component 432 or electronic display 324. The controller may also create an index for the patient that includes one or more of the number of asynchronies, the number of artifacts, the type of each of the asynchronies and artifacts, the frequency of each occurrence, etc.

[0051] In some embodiments, the controller provides recommendations to the mechanical ventilator for parameter adjustments, such as adjustments to PEEP, sensitivity adjustments, etc. In other embodiments, the controller sends a signal to the mechanical ventilator configured to adjust one or more parameters of the mechanical ventilator based on the asynchrony detected in act 506. Different types of asynchrony can be corrected by different adjustments to mechanical ventilator settings, such as PEEP and plateau pressure, inspiratory and expiratory times, ventilation mode, sensitivity level, and respiratory rate.

[0052] Fig. 6A and Figure 6B A pressure waveform 602 and a flow waveform 610 are illustrated that are aligned in time. Fig. 6A illustrates a pressure waveform 602 and a flow waveform 610 before analyzing the pressure waveform 602 and the flow waveform 610 for a missed trigger, and Figure 6B A pressure waveform 602 and a flow waveform 610 are illustrated after insertion of a missed trigger.

[0053] Pressure waveform 602 includes peaks 606 corresponding to high pressure points and valleys 604 corresponding to low pressure points. Trigger points 608 detected by the gas monitoring sensor are also plotted along pressure waveform 602. Fig. 6A and Figure 6B The illustrated trigger point 608 corresponds to an inspiratory trigger point that occurs near the valley 604 in the pressure waveform 602 due to the decrease in pressure caused by the patient's inspiration.

[0054] The flow waveform 610 also includes a peak 614 corresponding to a high gas flow and a valley 612 corresponding to a low gas flow. A trigger point 608 corresponding to an inflection trigger point is also plotted on the flow waveform 610.

[0055] As discussed above, the gas monitoring sensor may fail to identify a trigger point. In some cases, the missed trigger point corresponds to an asynchrony between the mechanical ventilator and the patient, such as a double trigger event or a reverse trigger event. In order to detect the missed trigger, the controller may apply waveform filtering to the pressure waveform 602 and the flow waveform 610. The waveform filtering may be a moving average filter that averages the corresponding pressure waveform 602 or flow waveform 610 at each point over a limited number of frames, such as in a range of about 2 frames to about 20 frames, about 2 frames to about 10 frames, or about 5 frames.

[0056] After filtering the waveform, the controller may identify a potentially unidentified trigger point. For example, the controller may identify a potentially unidentified trigger point where the flow value is greater than a threshold flow, the flow difference between two adjacent points on the flow waveform 610 is greater than a threshold amount, and the pressure difference between two adjacent points on 602 is greater than a threshold amount. The threshold flow value may be in the range of about 0.2 L / s to about 0.7 L / s, such as about 1.5 e / s. -1 The threshold flow rate difference between adjacent points on the flow waveform 610 may be in the range of about 0.0 L / s to about 0.1 L / s. The threshold pressure difference between adjacent points on the pressure waveform 602 may be in the range of from 0.8 cmH2O to about 1.1 cmH2O, such as about 2.6 e -1 cmH2O.

[0057] The controller may then compare the potential unidentified trigger point with the trigger point 608 previously identified by the gas monitoring sensor. The controller may then remove the potential unidentified trigger point that is close to the previously identified trigger point 608. For example, a potential unidentified trigger point that occurs within a short time from one of the previously identified trigger points 608 may be the same trigger point. Therefore, a potential unidentified trigger point that occurs less than about 200 milliseconds (ms) (such as less than about 100 ms) from the previously identified trigger point 608 may not be considered. The controller may also remove potential unidentified trigger points that occur close in time to other potential unidentified trigger points. For example, a potential unidentified trigger point that occurs within about 200 ms (such as within about 100 ms of another unidentified trigger point) may not be considered.

[0058] The remaining potential unidentified trigger points after comparing the potential unidentified trigger points to the previously identified trigger points 608 can then be tracked to the closest local minimum pressure (e.g., the closest valley 604 in the pressure waveform 602). The flow rate at each of the potential unidentified triggers can also be considered. For example, at the trigger point, the flow should change direction. Therefore, the flow should be low at the trigger point. Therefore, the controller can eliminate potential unidentified trigger points where the gas flow rate is greater than about 0.1L / s, such as greater than about 0.2L / s. In some embodiments, the controller also considers the flow volume at the potential unidentified trigger point. For example, the controller can eliminate potential unidentified trigger points where the flow volume is lower than the expected amount, such as less than about 1.2 milliliters / kilogram (mL / kg), or less than about 1mL / kg.

[0059] The remaining potential unidentified trigger points can then be plotted on the pressure waveform 602 and flow waveform 610 as missed trigger points 616, as shown in FIG. Figure 6B shown.

[0060] The controller may similarly detect an unidentified exhalation trigger point corresponding to the unidentified inhalation trigger point. The controller may detect the unidentified exhalation trigger point following steps similar to the steps for detecting the unidentified inhalation trigger point.

[0061] Figure 7 A flowchart 700 is illustrated representing a decision process for determining whether an identified cycle (including both inspiratory and expiratory trigger points) is a valid cycle. As discussed above, artifacts (such as sensor disconnection, changes in parameters (e.g., pressure, PEEP, flow, etc.), purges, suction, etc.) may result in erroneous readings. Therefore, the controller may determine whether an artifact is associated with a cycle to determine whether a portion of the pressure waveform 602, a portion of the flow waveform 610, and other data associated with the cycle is valid. If an artifact is detected, the controller may determine whether an artifact is associated with the cycle. Figure 7 The decision process shown marks the associated breathing cycle as an invalid cycle.

[0062] In decision 702, the controller may determine whether a recent purge occurred. For example, the controller may determine whether a purge occurred during the cycle in question or the cycle immediately preceding the cycle in question. If the controller determines that a recent purge event occurred, then in action 704 it is determined that the cycle in question is invalid.

[0063] In decision 706, the controller may determine whether the sensor was recently disconnected. For example, the controller may determine whether the sensor was disconnected during the cycle in question or the cycle immediately before the cycle in question. If the controller determines that the sensor was recently disconnected, then in action 708 it is determined that the cycle in question is invalid.

[0064] In decision 710, the controller may determine whether the patient is under ventilatory support. For example, if the mechanical ventilator is operating at a higher pressure, the ventilator is breathing for the patient rather than assisting the patient in breathing. For example, if the mean pressure is greater than 4 cmH2O, it may be determined that the patient is under ventilatory support. When the ventilator is breathing for the patient, asynchrony will not occur because the mechanical ventilator does not rely on signals from the patient to move through the breathing cycle. If the controller determines that the patient is under ventilatory support, it is determined in action 712 that the cycle is invalid.

[0065] In decision 714, the controller may determine if there is a leak in the system. The controller may monitor the volume of gas for each cycle. The controller may analyze multiple cycles, such as in the range of about 4 cycles to about 16 cycles, or about 8 cycles to about 12 cycles. If the controller determines that the change in gas volume occurs across multiple cycles, the controller may determine that a leak has been detected. If a leak is detected, then in action 716 it is determined that the cycle is invalid.

[0066] In decision 718, the controller may determine whether the pressure in the system (such as PEEP pressure) has changed recently. For example, the controller may determine whether the pressure in the system has changed during the cycle of interest or in the previous cycle. The previous cycle may include cycles in the range of immediately preceding the previous cycle to the previous ten cycles (such as the previous two cycles to the previous eight cycles). If a pressure change has occurred in the previous cycle, then in action 720, it is determined that the cycle is invalid.

[0067] If the artifacts listed and discussed above are not detected, then the cycle in question may be determined to be valid in action 722. Figure 5 ) The controller may then determine whether the cycle includes asynchronous events such as combined cycles, double triggers, reverse triggers, breath accumulation, breath accumulation volume, trapped volume, or accumulation volume.

[0068] Figure 8 An exemplary view of a combined cycle in a lung volume waveform 800 is illustrated. Lung volume waveform 800 may be provided by an EIT system such as EIT system 404 ( Figure 4 ) is provided. Combined cycling occurs when a single patient effort triggers two consecutive breathing cycles with a short exhalation time between them (double triggering) or when the first cycle is triggered by the ventilator (without muscle effort) and the second cycle is triggered by the patient's effort (reverse triggering). Combined cycling can lead to breath pile-up. Breath pile-up is an unintentional tidal volume that compromises low tidal volume (VT) protective strategies and increases the risk of lung injury. Breath pile-up can also cause hyperinflation of the lungs, leading to hypoxemia and hypercapnia.

[0069] Figure 8 Lung volume waveform 800 includes a first peak 802 and a second peak 804 separated by an intermediate valley 806. The intermediate valley 806 represents a short exhalation time between two breathing cycles, characterized by the first peak 802 and the second peak 804. The intermediate valley 806 can define a trapped volume 808. The trapped volume 808 is the volume of air within the lungs that is not expelled during the short exhalation time. The second peak 804 defines a cumulative volume 810, which is the additional volume of air added to the lungs beyond what would be added by a normal cycle. The cumulative volume 810 is the volume of air that has the potential to damage the lungs.

[0070] Fig. 9 Lung volume waveform 902, pressure waveform 904, and flow waveform 906 are illustrated indicating a double trigger event 908 and a reverse trigger event 910. Lung volume waveform 902 illustrates changes in the volume of the patient's lungs over time as measured by the EIT system. Pressure waveform 904 illustrates increases and decreases in pressure in the breathing circuit as measured by a gas monitoring sensor or a mechanical ventilator. Flow waveform 906 illustrates changes in flow velocity within the breathing circuit as measured by a gas monitoring sensor or a mechanical ventilator. Flow waveform 906 also indicates flow direction, for example, a flow velocity less than 0 is in an expiratory flow direction away from the patient, and a flow velocity greater than 0 is in an inspiratory flow direction toward the patient.

[0071] As discussed above, a double triggering event 908 occurs when a single patient attempts to trigger two subsequent breathing cycles from a mechanical ventilator with a short exhalation time between the two subsequent breathing cycles. As shown, the lung volume waveform 902 includes a smaller first peak 912 and a larger second peak 914 separated by an intermediate valley 916 representing a short exhalation time. The double triggering event 908 can result in a significant increase in lung volume relative to a conventional cycle. The pressure waveform 904 illustrates a larger first peak 922 and a smaller second peak 926 separated by an intermediate valley 924. The flow waveform 906 illustrates a first peak 934 and a second peak 936 separated by a valley 938, wherein the flow changes from an inspiratory flow at the first peak 934 to an expiratory flow at the valley 938 and back to an inspiratory flow at 936.

[0072] A reverse trigger event 910 occurs when a first cycle is triggered by the ventilator without patient effort and a second cycle is triggered by patient effort. As shown, the lung volume waveform 902 includes a first peak 918 and a second peak 920, but no intermediate valley because there is no expiratory time between the two inspirations. Similar to the double trigger event 908, the reverse trigger event 910 can result in a significant increase in lung volume relative to a conventional cycle due to two inspirations without intervening exhalations. The pressure waveform 904 illustrates a smaller first peak 928 and a larger second peak 932 separated by an intermediate valley 930. The flow waveform 906 illustrates a first peak 940 and a second peak 944 separated by a valley 942. In the reverse trigger event 910, the flow does not change from an inspiratory flow to an expiratory flow, but the flow velocity decreases at the valley 942, but continues in the inspiratory direction.

[0073] To detect different asynchronous events, the controller may begin by applying filters to the lung volume waveform 902, the pressure waveform 904, and the flow waveform 906. The pressure waveform 904 and the flow waveform 906 may be filtered by a moving average filter that averages the data of the respective waveforms 904, 906 across multiple frames, such as in the range of 5 frames to about 20 frames or about 10 frames. The lung volume waveform 902 may be filtered using a high pass filter, such as a high pass Butterworth filter (with a cutoff frequency in the range of about 0.01 Hz to about 0.03 Hz, such as about 0.02 Hz).

[0074] After filtering the lung volume waveform 902, the pressure waveform 904, and the flow waveform 906, the controller may analyze the characteristics of each cycle in the waveforms 902, 904, 906 to determine whether a combined cycle occurs. For example, the controller may determine the capture volume 808 during each cycle. If the capture volume 808 is greater than a threshold volume, the cycle may be identified for further analysis. The threshold volume may be in the range of about 0.5 mL / kg to about 2 mL / kg, such as 1 mL / kg. The controller may also determine whether the expiratory time between two cycles (such as a marking cycle) is less than a threshold time. The threshold time may be in the range of about 0.5 s to about 2 s, such as about 1 s. The controller may also compare the expiratory time between two cycles with the previous expiratory time. For example, the controller may use the following formula to calculate the value G:

[0075]

[0076] in is a trimmed average of several past cycles, such as the past ten cycles, the past fifteen cycles, or the past twenty cycles. If the calculated value G is greater than a threshold, the controller determines that the associated two cycles are combined cycles. The threshold may be in the range of about 0.3 to about 0.8, such as about 0.5. One cycle or two cycles that meet the above threshold are defined as asynchronous cycles.

[0077] Once an asynchronous cycle is identified, the controller can then classify the type of asynchrony. For example, the distinction between whether a cycle is double-triggered or reverse-triggered depends on the nature of the first cycle: if the first cycle is triggered by the patient's muscle effort, it is labeled as double-triggered; if the first cycle is triggered by the ventilator, it is labeled as reverse-triggered.

[0078] The controller determines an estimate of the patient's muscle effort using the following formula:

[0079]

[0080] in:

[0081]

[0082] A rough muscle effort estimate is used to assess the grade G. First, the window (W) is defined using the following formula:

[0083] W={P est (t i )|t i ∈[t ins -0.2s,t ins +0.2s]},

[0084] G is then estimated using the following relationship:

[0085] If f(W) = t ins –20, then G=0, where t0 is the trigger point;

[0086] If f(W)≠t ins –20, then G=max(W)–min(W1), where

[0087] W1={P est (t i )|t i ∈[t ins -0.2,f(W)]}

[0088] After estimating G through the above relationship, G can be used to determine which type of asynchronous event is associated with the cycle in question. For example, if G is greater than a threshold, the controller can determine that the event is triggered by the patient and is a double trigger. On the other hand, if G is less than a threshold, the controller can determine that the event is triggered by the ventilator and is a reverse trigger. For example, the threshold can be set to 1.38. Therefore, if G is greater than or equal to 1.38, the second cycle is determined to be a double trigger asynchronous. On the other hand, if G is less than 1.38, the cycle is determined to be a reverse trigger.

[0089] When the capture volume is 808 ( Figure 8 ) and the accumulation volume 810( Figure 8 ) is greater than a threshold, breath accumulation is identified. The threshold can be set to a value close to the volume change of a regular breath, such as in the range of about 0.8 mL / kg to about 1.5 mL / kg or about 1 mL / kg. Therefore, if both the trapped volume 808 and the accumulated volume 810 are greater than the threshold, the controller determines that the asynchronous event includes breath accumulation.

[0090] An asynchronous event may include more than one asynchronous event. For example, a double trigger event may also include a respiratory accumulation event caused by the double trigger.

[0091] In some cases, the asynchronous event affects only a region of the patient's lungs. Fig. 10A As shown, asynchronous events may cause one region of a patient's lungs to overinflate without inflating other regions. Therefore, monitoring the global flow volume of a patient's lungs may not capture the event, while monitoring regional volumes may provide additional data to determine whether such a condition exists.

[0092] like Fig. 10A As shown, pixel data from EIT image 1002 may provide data about the volume of the patient's lungs in anterior region 1004, posterior region 1006, right region 1008, and left region 1010. The pixel data may facilitate defining an area of ​​the patient's lungs as an over-inflated area 1012, and defining another area of ​​the patient's lungs as an under-inflated area 1014. The pixel data may also facilitate determining the locations of the over-inflated area 1012 and the under-inflated area 1014. The pixel data may be used in one or more of the above processes to detect asynchrony. For example, area stretching may be associated with a reverse triggering asynchronous event. Therefore, the controller may use the pixel data to detect and classify asynchronous events.

[0093] Embodiments of the present invention provide a tool that can provide additional information to a physician about a mechanically ventilated patient. This information can be used to reduce and / or prevent asynchrony between a mechanical ventilator and the patient, which can reduce the risk of ventilator-related injury. By evaluating information in the manner discussed herein, embodiments of the present invention can detect asynchrony that would otherwise be missed by a physician who would otherwise be aware of it. In addition, embodiments of the present invention can replace experienced physicians watching monitors by detecting asynchrony and alerting the attending physician when asynchrony is detected, which can reduce costs for the hospital and the workload of the attending physician and staff.

[0094] Non-limiting exemplary embodiments of the present invention include:

[0095] Embodiment 1: A system configured to detect asynchronous respiratory events; the system includes: a receiver, the receiver configured to receive ventilation data from at least one of a mechanical ventilator, an airway flow sensor or an airway pressure sensor and impedance data from an electrical impedance tomography device; a processor; a memory device, the memory device configured to store the ventilation data and the impedance data; and a non-transitory computer-readable medium, on which instructions are stored, the instructions, when executed by the processor, cause the processor to perform the following steps: retrieving a volume tracing from the impedance data; retrieving at least one of a flow waveform and a pressure waveform from the ventilation data; comparing the volume tracing with the at least one of the flow waveform and the pressure waveform; determining whether an asynchronous event has occurred based on comparing the volume tracing with the at least one of the flow waveform and the pressure waveform; classifying the asynchronous event; and providing a classification of the asynchronous event.

[0096] Embodiment 2: A system according to embodiment 1, wherein the instructions cause the processor to: determine the capture volume during the cycle; determine whether the exhalation time between two cycles is less than a threshold time; and compare the exhalation time between the two cycles with a previous exhalation time.

[0097] Embodiment 3: The system of Embodiment 2, wherein the instructions cause the processor to determine whether the asynchronous event occurs when the trapping volume is greater than a threshold volume.

[0098] Embodiment 4: A system according to Embodiment 3, wherein the threshold volume is in the range of about 0.5 mL / kg to about 2 mL / kg.

[0099] Embodiment 5: A system according to embodiment 2 or embodiment 3, wherein the instructions cause the processor to determine that the asynchronous event has occurred when: the accumulation volume during the cycle is greater than the threshold volume; the exhalation time between the two cycles is lower than the threshold time; and the exhalation time between the two cycles is less than the previous exhalation time.

[0100] Embodiment 6: A system according to any one of Embodiments 2 to 5, wherein the threshold time is in the range of about 0.5 seconds to about 2 seconds.

[0101] Embodiment 7: The system of any one of Embodiments 2 to 6, wherein the previous exhalation time comprises exhalation times from at least four previous cycles.

[0102] Embodiment 8: A system according to any one of Embodiments 1 to 7, wherein the instructions cause the processor to communicate the recommended adjustment to the user.

[0103] Embodiment 9: The system of any one of Embodiments 1 to 8, wherein the instructions cause the processor to send a signal to the mechanical ventilator providing an adjustment.

[0104] Embodiment 10: A system according to any one of embodiments 1 to 9, wherein the instructions cause the processor to determine whether the breathing cycle is valid by determining that no artifacts affect the breathing cycle.

[0105] Embodiment 11: The system of embodiment 10, wherein the artifact comprises one of a sensor disconnect, a change in PEEP, a purge, and a leak.

[0106] Embodiment 12: A method for detecting asynchronous breathing events, the method comprising: retrieving an impedance data waveform from an electrical impedance tomography device; retrieving one or more of a flow waveform and a pressure waveform; aligning the impedance data waveform and the one or more of the flow waveform and the pressure waveform with respect to time; comparing the impedance data waveform with the one or more of the flow waveform and the pressure waveform; determining whether an asynchronous breathing event has occurred based on comparing the impedance data waveform with the one or more of the flow waveform and the pressure waveform; classifying the asynchronous breathing event; and providing information for identifying the asynchronous breathing event.

[0107] Embodiment 13: The method of embodiment 12, wherein classifying the asynchronous respiratory event comprises determining whether the asynchronous respiratory event is a double-trigger event or a reverse-trigger event.

[0108] Embodiment 14: The method of Embodiment 12 or Embodiment 13, wherein classifying the asynchronous respiratory event comprises determining whether the asynchronous respiratory event is a respiratory pile-up.

[0109] Embodiment 15: The method according to any one of embodiments 12 to 14, further comprising estimating the moment of the patient's muscle effort.

[0110] Embodiment 16: The method of embodiment 15, wherein classifying the asynchronous breathing event comprises determining whether the moment of the patient's muscle effort triggered a first cycle of the asynchronous breathing event.

[0111] Embodiment 17: A method for detecting asynchronous respiratory events, the method comprising: retrieving lung impedance data from an electrical impedance tomography device, the lung impedance data comprising a volume tracing from at least one region of interest; retrieving one or more of a flow waveform and a pressure waveform; comparing the impedance data to the one or more of the flow waveform and the pressure waveform; identifying a combined cycle based at least on the impedance data, the flow waveform, and the pressure waveform; classifying the combined cycle; and providing recommended adjustments to a mechanical ventilator.

[0112] Embodiment 18: The method of Embodiment 17, wherein classifying the combined cycle comprises determining at least one of a capture volume or an accumulation volume based on the impedance data.

[0113] Embodiment 19: The method of Embodiment 17 or Embodiment 18, wherein identifying the combined cycle comprises determining whether a region of the patient's lungs is hyperinflated.

[0114] Embodiment 20: The method of Embodiment 19, wherein determining whether a region of the patient's lung is hyperinflated comprises comparing one cycle of inflation to at least four previous cycles of inflation.

[0115] The embodiments of the present invention described above and illustrated in the accompanying drawings do not limit the scope of the present invention, because these embodiments are merely examples of embodiments of the present invention, and the scope of the present invention is limited by the attached claims and their legal equivalents. Any equivalent embodiments are intended to be within the scope of the present invention. In fact, in addition to those shown and described herein, various modifications of the present invention (such as the alternative useful combination of the described elements) can become obvious to those skilled in the art from the specification. Such modifications and embodiments are also intended to fall within the scope of the attached claims and their legal equivalents.

Claims

1. A system configured to detect asynchronous respiratory events; the system comprising: a receiver configured to receive ventilation data from at least one of a mechanical ventilator, an airway flow sensor, or an airway pressure sensor and impedance data from an electrical impedance tomography device; processor; a memory device configured to store the ventilation data and the impedance data; and A non-transitory computer readable medium having instructions stored thereon, the instructions, when executed by the processor, causing the processor to perform the following steps: retrieving a plethysmogram from the impedance data; retrieving at least one of a flow waveform and a pressure waveform from the ventilation data; comparing the plethysmogram to the at least one of the flow waveform and the pressure waveform; determining whether an asynchronous event has occurred based on comparing the plethysmogram to the at least one of the flow waveform and the pressure waveform; Classifying the asynchronous events; as well as A classification of the asynchronous event is provided.

2. The system of claim 1 , wherein the instructions cause the processor to: Determine the trapped volume during the cycle; determining whether the exhalation time between two cycles is less than a threshold time; and The exhalation time between the two cycles is compared with the previous exhalation time. 3 . The system of claim 2 , wherein the instructions cause the processor to determine whether the asynchronous event occurs if the trapped volume is greater than a threshold volume.

4. The system of claim 3, wherein the threshold volume is in the range of about 0.5 mL / kg to about 2 mL / kg.

5. The system of claim 3, wherein the instructions cause the processor to determine that the asynchronous event occurs when: The accumulation volume during the cycle is greater than the threshold volume; The exhalation time between the two cycles is lower than the threshold time; and The exhalation time between the two cycles is less than the previous exhalation time.

6. The system of any one of claims 2 to 5, wherein the threshold time is in the range of about 0.5 seconds to about 2 seconds.

7. The system of any one of claims 2 to 5, wherein the previous exhalation times include exhalation times from at least four previous cycles.

8. The system of any one of claims 1 to 5, wherein the instructions cause the processor to communicate the recommended adjustment to a user.

9. The system of any one of claims 1 to 5, wherein the instructions cause the processor to send a signal to the mechanical ventilator to provide an adjustment.

10. The system of any one of claims 1 to 5, wherein the instructions cause the processor to determine whether the breathing cycle is valid by determining that no artifacts affect the breathing cycle.

11. The system of claim 10, wherein the artifact comprises one of a sensor disconnect, a change in PEEP, a purge, and a leak.

12. A method for detecting an asynchronous respiratory event, the method comprising: retrieving an impedance data waveform from an electrical impedance tomography device; retrieving one or more of a flow waveform and a pressure waveform; aligning the impedance data waveform and the one or more of the flow waveform and the pressure waveform with respect to time; comparing the impedance data waveform to the one or more of the flow waveform and the pressure waveform; determining whether an asynchronous breathing event has occurred based on comparing the impedance data waveform to the one or more of the flow waveform and the pressure waveform; classifying the asynchronous respiratory events; as well as Information identifying the asynchronous respiratory event is provided.

13. The method of claim 12, wherein classifying the asynchronous respiratory event comprises determining whether the asynchronous respiratory event is a double-triggered event or an inversely triggered event.

14. The method of claim 12, wherein classifying the asynchronous respiratory event comprises determining whether the asynchronous respiratory event is a respiratory pile-up.

15. The method according to any one of claims 12 to 14, further comprising estimating the moment of the patient's muscle effort.

16. The method of claim 15, wherein classifying the asynchronous breathing event comprises determining whether the moment of the patient's muscular effort triggered a first cycle of the asynchronous breathing event.

17. A method for detecting an asynchronous respiratory event, the method comprising: retrieving lung impedance data from an electrical impedance tomography device, the lung impedance data comprising a plethysmogram from at least one region of interest; retrieving one or more of a flow waveform and a pressure waveform; comparing the impedance data to the one or more of the flow waveform and the pressure waveform; identifying a combined cycle based at least on the impedance data, the flow waveform, and the pressure waveform; classifying the combined cycle; and Provides recommended adjustments for mechanical ventilators.

18. The method of claim 17, wherein classifying the combined cycle comprises: At least one of a trapped volume or an accumulation volume is determined based on the impedance data.

19. The method of claim 17 or claim 18, wherein identifying the combined cycle comprises: Determine if areas of the patient's lungs are hyperinflated.

20. The method of claim 19, wherein determining whether a region of the patient's lung is hyperinflated comprises comparing inflation of one cycle to inflation of at least four previous cycles.

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