Acoustic analysis of respiratory therapy systems

Abstract

Methods and apparatus for obtaining information about a patient and / or a respiratory therapy system configured to deliver respiratory therapy to the patient. The respiratory therapy system may include a flow generator configured to generate a pressurized air supply along an air loop to a patient interface. Acoustic signals representing sound in the air loop can be processed to obtain cepstral data. A time series of delay estimates can be generated based on acoustic signatures of the cepstral data. Each acoustic signature can represent a reflection of sound from the patient interface along the air loop. Variations in the time series of delay estimates can be analyzed. One or more output indicators based on these variations can be generated. The one or more output indicators can relate to patient and / or system status.

Description

[0001] 1. Cross-references to related applications

[0002] This application claims the benefit of U.S. Provisional Application No. 62 / 908,364, filed September 30, 2019, and Australian Provisional Application No. 2019903799, filed October 9, 2019, the entire disclosure of each of which is incorporated herein by reference. Background Technology 2.1 Technical Field

[0004] This technology relates to one or more of the following: detection, diagnosis, treatment, prevention, and improvement of respiratory-related conditions. This technology also relates to medical devices or apparatuses and their uses.

[0005] 2.2 Description of relevant technologies

[0006] 2.2.1 The Human Respiratory System and Its Disorders

[0007] The human respiratory system facilitates gas exchange. The nose and mouth form the airway entrance for the patient.

[0008] The airways consist of a series of branching tubes, which become narrower, shorter, and more numerous as they penetrate deeper into the lungs. The primary function of the lungs is gas exchange, allowing oxygen to enter the venous blood from inhaled air and carbon dioxide to be expelled in the opposite direction. The trachea divides into the left and right main bronchioles, which eventually further divide into terminal bronchioles. The bronchi form the airway tubes and do not participate in gas exchange. Further branching of the airways leads to the respiratory bronchioles and ultimately to the alveoli. The alveolar region of the lungs is where gas exchange occurs and is called the respiratory zone. See *Respiratory Physiology*, 9th edition, published in 2012 by John B. West, Lippincott Williams & Wilkins.

[0009] A range of breathing disorders exist. Some disorders may be characterized by specific events, such as apnea, hypoventilation, and hyperventilation.

[0010] Obstructive sleep apnea (OSA) is a sleep-disordered breathing (SDB) characterized by events involving closure or obstruction of the upper airway during sleep. This is caused by an abnormally small upper airway in the areas of the tongue, soft palate, and posterior oropharyngeal wall during sleep, coupled with a loss of normal muscle tone. The condition causes affected patients to stop breathing, typically for periods ranging from 30 to 120 seconds, sometimes 200 to 300 times per night. It often leads to excessive daytime sleepiness and can potentially cause cardiovascular disease and brain damage. Concomitant symptoms are common, especially in middle-aged overweight men, but those affected may not be aware of the problem. See U.S. Patent No. 4,944,310 (Sullivan).

[0011] A range of treatments have been used to treat or improve these symptoms. Furthermore, other healthy individuals may utilize these treatments to prevent respiratory distress. However, these treatments have many drawbacks.

[0012] 2.2.2 Treatment

[0013] Various treatments, such as continuous positive airway pressure (CPAP), high-flow therapy (HFT), non-invasive ventilation (NIV), and invasive ventilation (IV), have been used to treat one or more of the above-mentioned respiratory disorders.

[0014] 2.2.3 Treatment System

[0015] These respiratory therapies can be provided by treatment systems or devices. Such systems and devices can also be used to diagnose conditions without treating them.

[0016] A respiratory therapy system may include a respiratory therapy device (RT device), an air circuit, a humidifier, a patient interface, and data management.

[0017] 2.2.3.1 Patient Interface

[0018] A patient interface can be used to attach a breathing device to its wearer, for example, by providing an airflow into the airway. The airflow can be provided to the patient's nose and / or mouth via a mask, to the mouth via a tube, or to the patient's trachea via a tracheostomy tube. Depending on the treatment to be applied, the patient interface can form a seal with an area such as the patient's face, thereby facilitating the delivery of gas at a pressure sufficiently different from ambient pressure (e.g., a positive pressure of approximately 10 cmH2O relative to ambient pressure) to achieve the treatment. For other forms of treatment, such as oxygen delivery, the patient interface may not include a seal sufficient to deliver gas at a positive pressure of approximately 10 cmH2O into the airway.

[0019] 2.2.3.2 Respiratory Therapy (RT) Equipment

[0020] Respiratory therapy (RT) devices, such as respiratory pressure therapy (RPT) devices, can be used to deliver one or more of the aforementioned treatments, such as by generating an airflow for delivery to the airway inlet. The airflow can be pressurized. Examples of RPT devices include CPAP devices and ventilators. In some cases, respiratory therapy (RT) devices can be high-flow therapy (HFT) devices, which provide high-flow respiratory therapy.

[0021] Pneumatic generators are known in applications such as industrial-scale ventilation systems. However, pneumatic generators for medical applications have specific requirements that more general pneumatic generators cannot meet, such as the reliability, size, and weight requirements of medical devices.

[0022] Examples of RPT devices include the S9 sleep therapy system manufactured by ResMed Limited, and ventilators such as the ResMed Stellar. TM A range of adult and pediatric ventilators, including ResMed Astral. TM 150 ventilators.

[0023] 2.2.3.3 Air Circuit

[0024] An air circuit is a conduit or tube constructed and arranged to allow airflow to travel between two components of a respiratory therapy system, such as an RT device and a patient interface, during use. In some cases, there may be separate branches of the air circuit for inhalation and exhalation. In other cases, a single branch air circuit is used for both inhalation and exhalation.

[0025] 2.2.3.4 Humidifier

[0026] Delivering an unhumidified airflow can lead to airway dryness. Using a humidifier with an RT device and patient interface to produce humidified gas minimizes dryness of the nasal mucosa and increases patient airway comfort. Furthermore, in colder climates, warm air applied to the patient interface and the facial area around the patient interface is generally more comfortable than cold air.

[0027] 2.2.3.5 Ventilation port technology

[0028] Some forms of respiratory therapy systems may include vents to allow the removal of exhaled carbon dioxide. Exhaust vents allow gas to flow from the internal space of the patient interface (e.g., an inflation chamber) to the external space of the patient interface, such as into the environment.

[0029] 2.2.3.6 Sensing and Data Management

[0030] Patients, caregivers, clinicians, insurance companies, or technicians may wish to collect data related to respiratory therapy, whether or not it relates to the patient, the individual components used in the therapy, or the therapy system as a whole. There are numerous situations during the provision of respiratory therapy to patients in which one or more parties involved can benefit from the collection and utilization of treatment-related data.

[0031] 2.2.4 Component Identification

[0032] As previously mentioned, respiratory therapy systems typically include an RPT device, a humidifier, an air circuit, and a patient interface. Various types of patient interfaces can be used with a given RPT device, such as a nasal pillow, nasal fork, nasal mask, nasal and oral (oronasal) mask, or full-face mask. Furthermore, different types of tubing (length, diameter) can be used, as in the air circuit. To provide improved control over the therapy delivered to the patient interface, estimating treatment parameters such as pressure, leakage flow, and ventilation flow rate at the patient interface can be advantageous. In systems using treatment parameter estimation, knowing the type of component the patient is using can improve the accuracy of the estimation and thus the efficacy of the therapy. To understand these, some RPT devices include menu systems that allow the patient to select the type of system component, including the patient interface being used, such as brand, form, model, etc. Once the patient has entered the component type, the RPT device can select the appropriate operating parameters of the airflow generator that best matches the selected component and can monitor treatment parameters more accurately during therapy. However, patients may not be able to correctly enter the component type, or the RPT device may not allow errors or may ignore the type of component in use.

[0033] Some components of a respiratory therapy system require replacement more frequently than others for effective treatment. For example, some patients may have their patient interfaces, including silicone seal-forming parts, replaced every few months (e.g., 3 months), while RT devices may be replaced or upgraded every few years (e.g., 3 years). For components that will be replaced at relatively frequent intervals (e.g., patient interfaces), patients or caregivers often face challenges in obtaining reliable and accurate notification at low cost when their components are due for replacement. When replacing it, it may be necessary to change one or more settings in the treatment system (e.g., software settings in an RT device) to ensure the system makes full use of the new component. Therefore, the ability to automatically identify components of a respiratory therapy system is important for optimizing treatment and keeping patients and caregivers informed of replacement schedules.

[0034] In the past, a number of solutions have been adopted or proposed in the field of respiratory therapy related to component identification. For example, sensors / converters have been used and proposed in various forms to collect data related to environmental conditions, patient and component identification, and treatment operation conditions. In fact, many RT devices include one or more sensors, such as flow sensors, pressure sensors, humidity sensors, and temperature sensors. The signals generated by such sensors can be analyzed to generate treatment-related data, such as the identification of specific components (e.g., patient interfaces) in the respiratory therapy system.

[0035] However, sensors / converters typically require a set of additional components, which can hinder their adoption in many forms. For example, data collected by a sensor / converter must then be transferred for storage and / or analysis, such as from the sensor to memory and / or processor. This, along with the aforementioned sensors, can further increase the design, testing, and / or manufacturing costs for medical device manufacturers, and / or potentially increase costs and complexity for patients.

[0036] Furthermore, integrating expensive electrical and / or mechanical features into frequently replaced components (e.g., patient interfaces) may be detrimental to providing the most cost-effective treatment and may be environmentally unsustainable due to increased waste.

[0037] Furthermore, many proposed solutions related to sensors and / or converters may be limited because positioning the sensors far from where their data will be stored and / or analyzed can often further increase implementation complexity and / or cost. For example, in cases where the patient interface includes sensors, an electrical connection to an RT device may be required, which could further increase implementation complexity and / or cost.

[0038] Furthermore, designers of RT devices face numerous choices, often arriving at different solutions compared to other devices on the market (e.g., competitors', or even those from the same manufacturer but produced at different times). As a result, the supplied electrical connectors may only be compatible with a specific RT device. This can lead to unintended incompatibility effects, potentially adversely impacting specific consumer segments and / or reducing consumer choice.

[0039] 2.2.5 Composition of Exhaled Gas

[0040] The composition of a patient's exhaled breath is a useful indicator of their health status. In particular, carbon dioxide plethysmography sensors are configured to measure the fractional concentration of exhaled carbon dioxide for diagnostic and monitoring purposes, such as during anesthesia and intensive care, or over longer periods of COPD progression.

[0041] Cardiac output is an important hemodynamic parameter for patients. It can be used by physicians, clinicians, technicians, nurses, etc., to define treatment and / or assess a patient's response to medical treatment or intervention. Cardiac output describes the volume of blood pumped by the heart per unit time. It is the product of heart rate (HR) and stroke volume (SV). HR is the number of heartbeats per unit time, such as heart rate per minute (bpm). SV is the volume of blood pumped from the ventricles with each stroke. Typically, cardiac output is provided in liters per minute (L / min).

[0042] The Fick method is a method used to determine cardiac output. It involves the measurement of oxygen (O2), carbon dioxide (CO2), and para-aminohippuric acid (PAH). Typically, the Fick method involves monitoring oxygen consumption in an enclosed space to calculate carbon dioxide exchange. However, a modified Fick method can be used to estimate cardiac output. The modified Fick method involves carbon dioxide production and assumes a known relationship (e.g., linear relationship) between oxygen consumption and carbon dioxide production.

[0043] Integrating carbon dioxide mapping sensors into respiratory therapy systems is costly, and even if they exist, they may have such large delays that they are unsuitable for real-time CO2 monitoring. Therefore, respiratory systems may require a low-cost method to estimate CO2 concentrations in their air loops, or even better, a method capable of supporting such estimations in near real-time. Summary of the Invention

[0044] This technology relates to providing medical devices for diagnosing, improving, treating or preventing respiratory disorders, which have one or more of the following: improved comfort, cost, efficacy, ease of use, patient management and manufacturability.

[0045] The first aspect of this technology relates to a device for diagnosing, improving, treating or preventing respiratory disorders.

[0046] Another aspect of this technology relates to methods for diagnosing, improving, treating, or preventing respiratory disorders.

[0047] This technique can provide improvements to known devices to obtain useful information about respiratory therapy systems through acoustic analysis, particularly by analyzing the temporal variations of delays in acoustic reflection signals across different time scales. As one example, variations in delays within the respiratory band can provide a measurement of exhaled carbon dioxide concentration, which can then be used for diagnostic and therapeutic purposes, such as estimating a patient's cardiac output.

[0048] Some implementations of this technology include a method for generating patient and / or system status indications using one or more processors configured to deliver respiratory therapy to a patient. The respiratory therapy system may include a flow generator configured to generate a pressurized air supply along an air loop to a patient interface. The method may include processing an acoustic signal representing sound in the air loop from a microphone to obtain cepstral data. The method may include generating a time series of delay estimates based on acoustic signatures of the cepstral data. Each acoustic signature may represent a reflection of sound from the patient interface along the air loop. The method may include analyzing changes in the time series of delay estimates. The method may include generating one or more output indicators based on these changes, the one or more output indicators relating to patient and / or system status.

[0049] In some implementations, generating the time series may include separating the acoustic signature from the cepstral data. Generating the time series may include estimating the delay of the acoustic signature against a time series of delay estimates. Generating the time series may include repeated separation and estimation. Analysis may include filtering the time series of delay estimates to allow frequencies within the respiratory rate band to pass through. Analysis may also include converting the time series of delay estimates into an indication of carbon dioxide concentration in the air loop. One or more output indicators may include an indication of the patient's end-tidal carbon dioxide concentration (EtCO2). The method may also include adjusting parameters of the respiratory therapy system based on the EtCO2 indication.

[0050] In some implementations, one or more output indicators may include an estimate of the patient's cardiac output. The method may also include applying a modified Fick technique function and measuring changes in the indication of EtCO2 generated over a time series of delayed estimates to generate an estimate of cardiac output. The method may further include repeated analysis to generate multiple estimates of the patient's cardiac output. The method may further include determining a trend among the multiple estimates of the patient's cardiac output. The method may further include taking action based on the trend determined among the multiple estimates. Taking action may include generating output communication and / or output on a display. The analysis may further: determine one or more environmental parameters of the respiratory therapy system; and correct the one or more environmental parameters during the determination of carbon dioxide concentration. The one or more environmental parameters may include air temperature, ambient pressure, ambient carbon dioxide concentration, background noise, or a combination thereof. Background noise may be generated by a different sound sensor than the sound sensor that generates the sound signal.

[0051] In some implementations, the analysis may include removing respiratory rate band variations from the time series of the delay estimates to obtain a time series of non-respiratory delay estimates. The one or more output indicators may include indications of replacement status of components of the air circuit and / or patient interface. The analysis may further include mapping the time series of non-respiratory internal delay estimates to a time series of values ​​for the mask tube length. The analysis may further include determining whether an increase in the length of the air circuit during numerous treatment procedures can exceed a threshold. The analysis may further include determining the variability of the air circuit length during respiratory therapy procedures. Processing may include removing background noise from the environment of the respiratory therapy system from the acoustic signal.

[0052] In some implementations, one or more output indicators may further include (a) control signals for controlling the regulation of the therapeutic output of the therapeutic device; and / or (b) outputs for output communication or display.

[0053] Some implementations of this technology include an apparatus for generating patient and / or system status indications using a respiratory therapy system configured to deliver respiratory therapy to a patient. The respiratory therapy system may include a flow generator configured to generate a pressurized air supply to a patient interface along an air circuit. The apparatus may include sensors configured to generate acoustic signals representing sound in the air circuit. The apparatus may include a controller, which may include one or more processors and a memory. The one or more processors may be configured by program instructions stored in the memory to perform any one or more aspects of the methods described herein. In some implementations, the apparatus may further include a blower, wherein the controller may be configured to control the operation of the blower.

[0054] Some implementations of this technology include an apparatus for generating patient and / or system status indications using a respiratory therapy system configured to deliver respiratory therapy to a patient. The respiratory therapy system may include a flow generator configured to generate a pressurized air supply to a patient interface along an air loop. The apparatus may include sensors configured to generate acoustic signals representing sound in the air loop. The apparatus may include a controller. The controller may be configured to process the acoustic signals representing sound in the air loop to obtain cepstral data. The controller may be configured to generate a time series of delay estimates based on acoustic signatures in the cepstral data. Each acoustic signature may represent a reflection of sound from the patient interface along the air loop. The controller may be configured to analyze changes in the time series of delay estimates. The controller may be configured to generate one or more output indicators based on these changes, the one or more output indicators relating to patient and / or system status.

[0055] In some implementations, the device may further include a second sensor configured to generate an acoustic signal representing background noise in the environment of the respiratory therapy system. The controller may be further configured to use the generated acoustic signal representing background noise in the environment of the respiratory therapy system to remove the background noise from the environment of the respiratory therapy system from a generated acoustic signal representing sound in the air loop. To generate a time series, the controller may be configured to separate the acoustic signature from the cepstrum of the cepstrum data. To generate a time series, the controller may be configured to estimate the delay of the acoustic signature for a time series of delay estimation. To generate a time series, the controller may be configured to repeat the separation and estimation.

[0056] In some implementations, to analyze variations, the controller can be configured to filter the time series of the delay estimates to allow frequencies within the respiratory rate band to pass through. To analyze variations, the controller can be configured to convert the time series of the delay estimates into an indication of carbon dioxide concentration in the air loop. One or more output indicators may include an indication of the patient's end-tidal carbon dioxide concentration (EtCO2). The controller can also be configured to adjust parameters of the respiratory therapy system based on the EtCO2 indication. One or more output indicators may include an estimate of the patient's cardiac output. The controller can be configured to apply a modified Fick technique function and measure changes in the EtCO2 indication generated with the time series of the delay estimates to generate an estimate of cardiac output. The controller can be configured to repeat the analysis to generate multiple estimates of the patient's cardiac output. The controller can be further configured to determine trends among the multiple estimates of the patient's cardiac output. The controller can be further configured to take actions based on the trends determined among the multiple estimates. Actions may include generating output communications and / or outputs on a display. To analyze variations, the controller can be configured to remove respiratory rate band variations from the time series of the delay estimates to obtain a time series of non-respiratory-related delay estimates. The one or more output indicators may include indications of the replacement status of components of the air circuit and / or patient interface.

[0057] In some implementations, to analyze variation, the controller can be configured to map the time series of non-respiratory-related delay estimates to the time series of air loop length values. To analyze variation, the controller can be configured to determine whether an increase in the air loop length during numerous treatment procedures can exceed a threshold. To analyze variation, the controller can be configured to determine the variability of the air loop length during respiratory therapy. One or more output indicators may further include: (a) control signals for controlling the regulation of the therapeutic output of the treatment device; and / or (b) outputs for output communication or display.

[0058] Some implementations of this technology include an apparatus that may include tools for generating an acoustic signal representing sound in an air circuit of a respiratory therapy system, the respiratory therapy system including a flow generator configured to generate a supply of pressurized air from an outlet along the air circuit to a patient interface. The apparatus may include tools for processing the acoustic signal representing sound in the air circuit to obtain cepstral data. The apparatus may include tools for generating a time series of delay estimates based on acoustic signatures in the cepstral data, wherein each acoustic signature represents a reflection of sound from the patient interface along the air circuit. The apparatus may include tools for analyzing variations in the time series of delay estimates. The apparatus may include tools for generating one or more output indicators based on these variations, the one or more output indicators relating to patient and / or system status.

[0059] Some implementations of this technology include a method for generating state indications of one or more processors regarding a patient interface associated with a respiratory therapy system configured to deliver respiratory therapy to a patient. The respiratory therapy system includes a flow generator configured to generate a pressurized air supply along an air loop to the patient interface. The method may include processing an acoustic signal representing sound in the air loop to obtain cepstral data. The method may include separating an acoustic signature from the cepstral data, the acoustic signature representing reflections of sound from the patient interface along the air loop. The method may include estimating an internal delay of the acoustic signature, wherein the internal delay may be a delay between two portions of the acoustic signature, each portion representing a reflection from a corresponding component separated by a mask tube from the patient interface. The method may include repeating the processing, separation, and estimation to generate a time-series estimate of the internal delay. The method may include analyzing the time-series of the internal delay estimate. The method may include generating one or more output indicators based on the analysis, the one or more output indicators relating to the state of the patient interface.

[0060] In some implementations, the analysis may include filtering the time series of the internal delay estimates to allow frequencies within the respiratory rate band to pass through. The analysis may further include analyzing the filtered time series of the internal delay estimates to generate an indication of carbon dioxide concentration in the mask tube. The analysis may include removing respiratory rate band variations from the time series of the internal delay estimates to obtain a time series of non-respiratory-related internal delay estimates. The analysis may further include mapping the time series of non-respiratory-related internal delay estimates to a time series of mask tube length values. The analysis may further include determining whether an increase in mask tube length during numerous treatment sessions exceeds a threshold. The analysis may further include determining the variability of mask tube length during respiratory therapy.

[0061] Some implementations of this technology include a device for generating status indications for a patient interface associated with a respiratory therapy system configured to deliver respiratory therapy to a patient. The respiratory therapy system includes a flow generator configured to generate a pressurized air supply along an air loop to the patient interface. The device may include sensors configured to generate acoustic signals representing sounds in the air loop. The device may include a controller. The controller may include one or more processors and a memory. The one or more processors may be configured by program instructions stored in the memory to perform any or more aspects of the methods described herein.

[0062] Some implementations of this technology include an apparatus for generating a state indication of a patient interface, the patient interface being used in a respiratory therapy system configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to the patient interface. The apparatus may include a sensor configured to generate an acoustic signal representing sound in the air loop. The apparatus may include a controller. The controller may be configured to process the acoustic signal representing sound in the air loop to obtain cepstral data. The controller may be configured to separate an acoustic signature from the cepstral data. The acoustic signature may represent the reflection of sound from the patient interface along the air loop. The controller may be configured to estimate an internal delay of the acoustic signature. The internal delay may be the delay between two parts of the acoustic signature. Each part may represent a reflection from a corresponding part of the patient interface separated from the mask tube. The controller may be configured to repeatedly process, separate, and estimate to generate a time-series estimate of the internal delay. The controller may be configured to analyze the time-series of the internal delay estimate. The controller may be configured to generate one or more output indicators based on the analysis, the one or more output indicators relating to the state of the patient interface.

[0063] In some implementations, to analyze the time series, the controller can be configured to filter the time series of the internal delay estimates to allow frequencies within the respiratory rate band to pass through. To analyze the time series, the controller can be further configured to analyze the filtered time series of the internal delay estimates to generate an indication of the carbon dioxide concentration in the mask tube. To analyze the time series, the controller can be configured to remove respiratory rate band variations from the time series of the internal delay estimates to obtain a time series of non-respiratory-related internal delay estimates. To analyze the time series, the controller can be further configured to map the time series of non-respiratory-related internal delay estimates to a time series of mask tube length values. To analyze the time series, the controller can be further configured to determine whether an increase in the mask tube length during numerous treatment sessions exceeds a threshold. To analyze the time series, the controller can be further configured to determine the variability of the mask tube length during respiratory therapy.

[0064] Some implementations of this technology include an apparatus that may include tools for generating an acoustic signal representing sound in an air circuit of a respiratory therapy system, which may include a flow generator configured to generate a supply of pressurized air from an outlet along the air circuit to a patient interface. The apparatus may include tools for processing the acoustic signal representing sound in the air circuit to obtain cepstral data. The apparatus may include tools for separating an acoustic signature from the cepstral data, the acoustic signature representing reflections of sound from the patient interface along the air circuit. The apparatus may include tools for estimating an internal delay of the acoustic signature, wherein the internal delay may be a delay between two portions of the acoustic signature, each portion representing reflections from a corresponding component separated by a mask tube from the patient interface; the apparatus may include tools for repeatedly processing, separating, and estimating to generate a time-series estimate of the internal delay. The apparatus may include tools for analyzing the time series of the internal delay estimate. The apparatus may include tools for generating one or more output indicators based on the analysis, the one or more output indicators relating to the patient interface state.

[0065] Some implementations of this technology include a respiratory therapy system for delivering respiratory therapy to a patient. The system may include a flow generator configured to generate a supply of pressurized air. The system may include an air circuit connected to the flow generator to deliver the supply of pressurized air to a patient interface. The system may include devices for generating patient and / or system status indications using the respiratory therapy system, wherein the devices may include any one or more of the features described herein.

[0066] Some implementations of this technology include a respiratory therapy system for delivering respiratory therapy to a patient. The system may include a flow generator configured to generate a supply of pressurized air. The system may include an air circuit connected to the flow generator to deliver the supply of pressurized air to the patient interface. The system may include devices for generating status indications regarding the patient interface, the devices including any one or more of the features described herein.

[0067] The methods, systems, devices, and apparatuses described herein can provide improved functionality in processors, such as dedicated computers, processors for respiratory monitors, and / or respiratory therapy devices. Furthermore, the described methods, systems, devices, and apparatuses can provide improvements in the technical field of automated management, monitoring, and / or treatment of respiratory conditions, including, for example, sleep-disordered breathing.

[0068] Of course, some of these aspects can form sub-aspects of this technology. Sub-aspects and / or aspects of the aspects can be combined in various ways and also constitute other aspects or sub-aspects of this technology.

[0069] Other features of the present technology will become apparent from the information contained in the following detailed description, abstract, drawings and claims. Attached Figure Description

[0070] This technology is illustrated by way of example and not limitation in the figures, and similar reference numerals in the figures refer to similar elements, including:

[0071] 4.1 Respiratory Therapy System

[0072] Figure 1A A system is shown in which a patient 1000 wearing a patient interface 3000 via a nose pillow receives a positive-pressure air supply from an RPT device 4000. The air from the RPT device 4000 is humidified in a humidifier 5000 and delivered to the patient 1000 along an air circuit 4170. A bed companion 1100 is also shown. The patient sleeps in a supine position.

[0073] Figure 1B A system is shown in which a patient 1000 wearing a patient interface 3000 in the form of a nasal mask receives a positive pressure air supply from an RPT device 4000. The air from the RPT device is humidified in a humidifier 5000 and delivered to the patient 1000 along an air circuit 4170.

[0074] Figure 1C A system is shown in which a patient 1000 wearing a patient interface 3000 in a full-face mask receives a positive-pressure air supply from an RPT device 4000. The air from the RPT device is humidified in a humidifier 5000 and delivered to the patient 1000 along an air circuit 4170. The patient sleeps in a side-lying position.

[0075] 4.2 Respiratory System and Facial Anatomy

[0076] Figure 2 A schematic diagram of the human respiratory system is shown, including the nasal cavity and oral cavity, larynx, vocal cords, esophagus, trachea, bronchi, lungs, alveolar sacs, heart, and diaphragm.

[0077] 4.3 Patient Interface

[0078] Figure 3 An example of a patient interface in the form of a nasal mask according to the present technology is shown.

[0079] 4.4RPT equipment

[0080] Figure 4A An exploded view of an exemplary respiratory pressure therapy (RPT) device 4000 according to one form of the present technology is shown.

[0081] Figure 4BThis is a schematic diagram of the pneumatic path of one form of RPT device according to this technology. The upstream and downstream directions are indicated.

[0082] 4.5 Humidifier

[0083] Figure 5A An isometric view of one form of humidifier according to the present technology is shown.

[0084] Figure 5B An isometric view of one form of humidifier according to the present technology is shown, which shows the humidifier reservoir 5110 removed from the humidifier reservoir base 5130.

[0085] 4.6 Respiratory waveform

[0086] Figure 6 The diagram shows a typical respiratory waveform of a sleeping human. The horizontal axis represents time, and the vertical axis represents respiratory flow. Parameter values ​​can vary, and a typical respiratory pattern can be approximated by the following: tidal volume Vt 0.5 L, inspiratory time Ti 1.6 s, and peak inspiratory flow rate Q. 峰值 0.4 L / s, expiratory time Te 2.4 s, peak expiratory flow rate Q 峰值 -0.5 L / s. Total duration of respiration T 总 Approximately 4 seconds. Humans typically breathe at a rate of about 15 breaths per minute (BPM) with a ventilation rate of approximately 7.5 L / min. Typical duty cycles, Ti and T... 总 The ratio is approximately 40%.

[0087] 4.7 Acoustic Analysis

[0088] Figure 7 This is a schematic diagram of a respiratory therapy system according to an example of the present technology, which may include an acoustic analysis device as described in more detail herein.

[0089] Figure 8 It includes Figure 7 A graph illustrating the impulse response function of an example respiratory therapy system;

[0090] Figure 9 It includes information about... Figure 7 Plots of the cepstrum of different exemplary masks in a respiratory therapy system at different blower speeds;

[0091] Figure 10 This is a schematic diagram of a respiratory therapy system based on one aspect of this technology;

[0092] Figure 11 This is an estimate illustrating an example according to the present technology. Figure 7 A flowchart of a method for acoustic signature delay of the air circuit in a respiratory therapy system.

[0093] Figure 12 Includes two concurrent time series plotted on the same time axis: Figure 7 Acoustic signature delay (upper trace) and measured carbon dioxide concentration (lower trace) in the catheter of the respiratory therapy system.

[0094] Figure 13 It is a graph containing the inverted spectrum of a pillowcase, which includes... Figure 7 The mask tube in a respiratory therapy system.

[0095] Figure 14 This is a schematic diagram of a respiratory therapy system according to an example of the present technology, which may include an acoustic analysis device as described in more detail herein.

[0096] Figure 15 This is a flowchart illustrating an example process for determining a patient's cardiac output according to one aspect of the present technology.

[0097] Figure 16 It is based on one aspect of this technology, such as Figure 7 or Figure 14 A diagram of an example component of an acoustic analysis device. Detailed Implementation

[0098] Before describing this technology in further detail, it should be understood that this technology is not limited to the specific examples described herein, and the specific examples described herein may be modified. It should also be understood that the terminology used in this disclosure is for the purpose of describing the specific examples described herein only and is not intended to be limiting.

[0099] The following description is provided in relation to various examples that may share one or more common features and / or characteristics. It should be understood that one or more features of any example may be combined with one or more features of another example or other examples. In addition, in any example, any single feature or combination of features may constitute another example.

[0100] In this specification, the term "identification" for a component refers to an identifier for the type of that component. For the sake of brevity, "face shield" and "patient interface" are used interchangeably in this specification, even if a patient interface is not typically described as a "face shield".

[0101] 5.1 Treatment

[0102] In one form, the technology includes a method for treating respiratory distress, the method comprising the step of applying positive pressure to the airway inlet of a patient 1000.

[0103] 5.2 Treatment System

[0104] In one form, the technology includes a system for treating respiratory disorders. The respiratory therapy (RT) system may include an RPT device 4000 and a humidifier 5000 for delivering a positive-pressure humidified air supply to a patient 1000 via an air path including an air circuit 4170 and a patient interface 3000.

[0105] 5.3 Patient Interface

[0106] like Figure 3 The exemplary non-invasive patient interface 3000 shown includes the following functional aspects: a seal-forming structure 3100, an inflation chamber 3200, a positioning and stabilizing structure 3300, an air vent 3400, a connection port 3600 for connection to an air circuit 4170, and a forehead support 3700. In some forms, the functional aspects may be provided by one or more physical components. In some forms, a single physical component may provide one or more functional aspects. In use, the seal-forming structure 3100 is arranged around the inlet of the patient's airway to facilitate the supply of positive pressure air to the airway.

[0107] According to one form of the present technology, a patient interface 3000 is constructed and arranged to provide an air supply at a positive pressure of, for example, at least 4 cmH2O, or at least 10 cmH2O, or at least 20 cmH2O, or at least 25 cmH2O relative to the surrounding environment.

[0108] 5.3.1 Sealing Formation Structure

[0109] In one form of this technology, the seal-forming structure 3100 provides a target seal-forming area and may additionally provide a cushioning function. The target seal-forming area is the area on the seal-forming structure 3100 where a seal may occur. The actual area where a seal occurs—the actual sealing surface—can vary from day to day and from patient to patient within a given treatment course, depending on a range of factors, including, for example, the position of the patient interface on the face, the tension in the positioning and stabilizing structure, and the shape of the patient's face.

[0110] 5.3.2 Inflation Chamber

[0111] In the area forming a seal during use, the air chamber 3200 has a periphery shaped to complement the surface contours of a typical human face. During use, the boundary edges of the air chamber 3200 are positioned very close to the adjacent surfaces of the face. Actual contact with the face is provided by the sealing structure 3100. The sealing structure 3100 may extend along the entire periphery of the air chamber 3200 during use. In some forms, the air chamber 3200 and the sealing structure 3100 are formed from a single sheet of homogeneous material.

[0112] 5.3.3 Positioning and Stabilization Structure

[0113] The sealing structure 3100 of the patient interface 3000 of this technology can be kept in a sealed state during use by positioning and stabilizing structure 3300, such as a headband.

[0114] 5.3.4 Vent

[0115] In one form, the patient interface 3000 includes a ventilation port 3400 constructed and arranged to allow flushing of exhaled gases such as carbon dioxide.

[0116] In some forms, the airway 3400 is configured to allow continuous ventilation flow from the interior of the inflation chamber 3200 to the surrounding environment, while the pressure within the inflation chamber is positive relative to the surrounding environment. The airway 3400 is configured such that the airway flow rate is sufficient to reduce the patient's rebreathing of exhaled carbon dioxide, while maintaining the therapeutic pressure within the inflation chamber during use. One form of the airway 3400 according to the present technology includes a plurality of orifices, for example, about 20 to about 80 orifices, or about 40 to about 60 orifices, or about 45 to about 55 orifices.

[0117] The vent 3400 may be located in the inflation chamber 3200. Alternatively, the vent 3400 may be located in a decoupling structure such as a rotary joint.

[0118] 5.3.5 Connection Port

[0119] Connection port 3600 allows the patient interface 3000 to be connected to the air circuit 4170.

[0120] In some implementations, a flexible tube (not shown) may be present to separate the inflation chamber 3200 and the connection port 3600. This length of tube is referred to herein as the "mask tube" to distinguish it from the conduit or tube constituting the air circuit 4170.

[0121] 5.4 RPT equipment

[0122] According to one aspect of this technology, the respiratory pressure therapy (RPT) device 4000 is in... Figure 4A The diagram is shown in exploded view, including mechanical, pneumatic, and / or electronic components, and is configured to execute one or more algorithms 4300. The RPT device 4000 can be configured to generate an airflow for delivery to a patient's airway, for example, for treating one or more respiratory conditions described elsewhere in this document. While the acoustic techniques and methods described herein are generally illustrated with respect to the example RPT device 4000, such techniques and methods can be similarly implemented in or with other RT devices, such as in or with HFT devices.

[0123] In one configuration, the RPT device 4000 is constructed and arranged to deliver an airflow in the range of -20 L / min to +150 L / min while maintaining a positive pressure of at least 4 cmH2O, or at least 10 cmH2O, or at least 20 cmH2O, or at least 25 cmH2O.

[0124] The RPT device may have an outer housing 4010, which is composed of two parts: an upper part 4012 and a lower part 4014. Furthermore, the outer housing 4010 may include one or more panels 4015. The RPT device 4000 includes a chassis 4016 that supports one or more internal components of the RPT device 4000. The RPT device 4000 may include a handle 4018.

[0125] The pneumatic path of the RPT device 4000 may include one or more air path components, such as an inlet air filter 4112, an inlet silencer 4122, a pressure generator 4140 (e.g., a blower 4142) capable of supplying positive pressure air, an outlet silencer 4124, and one or more converters 4270, such as pressure sensors and flow sensors.

[0126] One or more air path components may be housed within a detachable, separate structure, referred to as pneumatic block 4020. Pneumatic block 4020 may be housed within an outer housing 4010. In one embodiment, pneumatic block 4020 is supported by, or forms part of, a chassis 4016.

[0127] The RPT device 4000 may include a power supply 4210, one or more input devices 4220, a central controller 4230, a treatment device controller 4240, a pressure generator 4140, one or more protection circuits 4250, a memory 4260, a converter 4270, a data communication interface 4280, and one or more output devices 4290. Electrical components 4200 may be mounted on a single printed circuit board assembly (PCBA) 4202. In an alternative form, the RPT device 4000 may include more than one PCBA 4202.

[0128] 5.4.1 Mechanical and pneumatic components of RPT equipment

[0129] RPT equipment may include one or more of the following components in a single unit. In an alternative form, one or more of the following components may be configured as separate units.

[0130] 5.4.1.1 Pressure Generator

[0131] In one form of this technology, the pressure generator 4140 for generating a downstream airflow, such as a positive pressure airflow or air supply, is a controllable blower 4142. The blower can deliver the air supply, for example, at a rate up to about 120 liters per minute and at a positive pressure ranging from about 4 cm H2O to about 20 cm H2O, or in other forms up to about 30 cm H2O. The blower may be as described in any of the following patents or patent applications, which are incorporated herein by reference in their entirety: U.S. Patent No. 7,866,944; U.S. Patent No. 8,638,14; U.S. Patent No. 8,636,479; and PCT Patent Application No. WO 2013 / 020167.

[0132] The pressure generator 4140 is controlled by the treatment device controller 4240.

[0133] In other words, the pressure generator 4140 can be a piston-driven pump, a pressure regulator (e.g., a compressed air reservoir) connected to a high-pressure source, or a bellows.

[0134] 5.4.1.2 Memory

[0135] According to one embodiment of the present technology, the RPT device 4000 includes a memory 4260, such as non-volatile memory. In some embodiments, the memory 4260 may include battery-powered static RAM. In some embodiments, the memory 4260 may include volatile RAM.

[0136] The memory 4260 may be located on PCBA 4202. The memory 4260 may be in the form of EEPROM or NAND flash memory.

[0137] Alternatively or alternatively, the RPT device 4000 includes a removable form of memory 4260, such as a memory card made according to the Secure Digital (SD) standard.

[0138] In one form of the present technology, memory 4260 acts as a non-transitory computer-readable storage medium on which computer program instructions or processor control instructions are stored, which express one or more methods described herein, such as one or more algorithms 4300.

[0139] 5.4.1.3 Data Communication System

[0140] In one embodiment of this technology, a data communication interface 4280 is provided and connected to a central controller 4230. The data communication interface 4280 can be connected to a remote external communication network 4282 and / or a local external communication network 4284. The remote external communication network 4282 can be connected to a remote external device 4286. The local external communication network 4284 can be connected to a local external device 4288.

[0141] In one embodiment, the data communication interface 4280 is part of the central controller 4230. In another embodiment, the data communication interface 4280 is separate from the central controller 4230 and may include an integrated circuit or a processor.

[0142] In one embodiment, the remote external communication network 4282 is the Internet. The data communication interface 4280 can connect to the Internet using wired communication (e.g., via Ethernet or fiber optic) or wireless protocols (e.g., CDMA, GSM, LTE).

[0143] In one form, the local external communication network 4284 utilizes one or more communication standards, such as Bluetooth or consumer infrared protocols.

[0144] In one form, the remote external device 4286 can be one or more computers, such as a cluster of networked computers. In another form, the remote external device 4286 can be a virtual computer rather than a physical computer. In either case, this remote external device 4286 can be accessed by appropriately authorized personnel, such as clinicians.

[0145] The local external device 4288 can be a personal computer, a mobile computing device such as a smartphone or tablet, or a remote control.

[0146] 5.4.2 RPT Device Algorithm

[0147] As described above, in some forms of this technology, the central controller 4230 may be configured to implement one or more algorithms 4300 represented as computer programs stored in a non-transient computer-readable storage medium (such as memory 4260). The algorithms 4300 are generally grouped into groups called modules.

[0148] 5.5 Humidifier

[0149] 5.5.1 Humidifier Overview

[0150] In one form of this technology, the RT system includes an RPT device 4000 and an air circuit 4170 (e.g., ...). Figure 4AThe humidifier 5000 (as shown) alters the absolute humidity of the air delivered to the patient relative to the absolute humidity of the surrounding air. Typically, the humidifier 5000 is used to increase the absolute humidity of the airflow and increase the temperature of the airflow (relative to ambient air) before it is delivered to the patient's airway.

[0151] Humidifier 5000 (e.g., such as Figure 5A (As shown) may include a humidifier reservoir 5110, a humidifier inlet 5002 for receiving airflow, and a humidifier outlet 5004 for delivering humidified airflow. In some forms, such as Figure 5A and Figure 5B As shown, the inlet and outlet of the humidifier reservoir 5110 can be a humidifier inlet 5002 and a humidifier outlet 5004, respectively. The humidifier 5000 may also include a humidifier base 5006, which is adapted to receive the humidifier reservoir 5110 and includes a heating element 5240.

[0152] 5.5.2 Humidifier Components

[0153] 5.5.2.1 Water Storage Tank

[0154] According to one arrangement, the humidifier 5000 may include a water reservoir 5110 configured to maintain or retain a liquid (e.g., water) capacity for evaporation to humidify the airflow. The water reservoir 5110 may be configured to maintain a predetermined maximum water capacity to provide adequate humidification for at least the duration of a respiratory therapy session, such as one night's sleep. Typically, the reservoir 5110 is configured to hold several hundred milliliters of water, for example, 300 milliliters (ml), 325 ml, 350 ml, or 400 ml. In other forms, the humidifier 5000 may be configured to receive a water supply from an external water source, such as a building's water supply system.

[0155] According to one aspect, the water reservoir 5110 is configured to increase the humidity of an airflow from the RPT device 4000 as airflow passes through it. In one form, the water reservoir 5110 may be configured to facilitate the airflow's travel in a curved path through the reservoir 5110 while in contact with the water volume therein.

[0156] According to one form, the storage 5110 can, for example, be along such a path. Figure 5A and Figure 5B The lateral direction shown is removed from the humidifier 5000.

[0157] The reservoir 5110 may also be configured to prevent liquid from flowing out of it, such as through any orifice and / or between its sub-components, when the reservoir 5110 is displaced and / or rotated from its normal operating direction. Since the airflow to be humidified by the humidifier 5000 is typically pressurized, the reservoir 5110 may also be configured to prevent loss of pneumatic pressure due to leakage and / or flow resistance.

[0158] 5.5.2.2 Conductivity Component

[0159] According to one arrangement, the reservoir 5110 includes a conductive portion 5120 configured to allow efficient heat transfer from the heating element 5240 to the liquid volume within the reservoir 5110. In one form, the conductive portion 5120 may be arranged as a plate, but other shapes are equally applicable. All or part of the conductive portion 5120 may be made of a thermally conductive material, such as aluminum (e.g., with a thickness of approximately 2 mm, such as 1 mm, 1.5 mm, 2.5 mm, or 3 mm), another thermally conductive metal, or some plastics. In some cases, suitable thermal conductivity can be achieved using materials with appropriate geometries and lower thermal conductivity.

[0160] 5.5.2.3 Humidifier reservoir dock

[0161] In one form, the humidifier 5000 may include a humidifier reservoir base 5130 (e.g., Figure 5B As shown), it is configured to receive a humidifier reservoir 5110. In some arrangements, the humidifier reservoir base 5130 may include a locking mechanism, such as a locking lever 5135 configured to hold the reservoir 5110 in the humidifier reservoir base 5130.

[0162] 5.5.2.4 Water level indicator

[0163] The humidifier storage unit 5110 may include, for example: Figures 5A-5B The water level indicator 5150 is shown. In some forms, the water level indicator 5150 may provide a user (such as a patient 1000 or a caregiver) with one or more indications regarding the amount of water in the humidifier reservoir 5110. The one or more indications provided by the water level indicator 5150 may include an indication of the maximum predetermined volume of water, any portion thereof, such as 25%, 50%, 75%, or a volume such as 200 ml, 300 ml, or 400 ml.

[0164] 5.5.2.5 Humidifier Transducer

[0165] The humidifier 5000 may include one or more humidifier converters (sensors) 5210, in addition to or replacing the converter 4270 described above. The humidifier converter 5210 may include one or more of an air pressure sensor 5212, an air flow converter 5214, a temperature sensor 5216, or a humidity sensor 5218. The humidifier converter 5210 may generate one or more output signals that can communicate with a controller (such as a central controller 4230 and / or a humidifier controller 5250). In some forms, the humidifier converter may be externally located to the humidifier 5000 (e.g., in the air circuit 4170) when communicating the output signal to the controller 5250.

[0166] 5.6 Air Circuit

[0167] According to one aspect of the technology, the air circuit 4170 is a conduit or tube that is constructed and arranged to allow pressurized airflow to travel between two components, such as a humidifier 5000 and a patient interface 3000, during use.

[0168] Specifically, the air circuit 4170 can be in fluid communication with the outlet 5004 of the humidifier 5000 and the connection port 3600 of the patient interface 3000.

[0169] 5.7 Transducer

[0170] The RT system may include one or more transducers (sensors) 4270 configured to measure one or more of any number of parameters relating to the RT system, its patient, and / or its environment. The transducer may be configured to generate an output signal representing one or more parameters that the transducer is configured to measure.

[0171] The output signal can be one or more of electrical signals, magnetic signals, mechanical signals, visual signals, optical signals, sound signals, or any number of other signals known in the art.

[0172] The converter can be integrated with another component of the RT system, with one exemplary arrangement being that the converter is located inside the RPT device. The transducer can also be essentially a 'standalone' component of the RT system, with an exemplary arrangement being that the transducer is located outside the RPT device.

[0173] The transducer can be configured to transmit its output signal to one or more components of the RT system, such as an RPT device, a local external device, or a remote external device. The external transducer can be located, for example, on the patient interface, or in an external computing device such as a smartphone. The external transducer can be positioned, for example, on an air circuit such as the patient interface, or form part of it.

[0174] One or more transducers 4270 may be configured and arranged to generate signals representing air properties such as flow rate, pressure, or temperature. The air may be an airflow from the RT device to the patient, an airflow from the patient to the atmosphere, ambient air, or anything else. The signal may represent the characteristics of the airflow at a specific point, such as the airflow rate in the air path between the RT device and the patient. In one form of the technology, one or more transducers 4270 are located in the pneumatic path of the RT device, such as downstream of a humidifier 5000.

[0175] 5.7.1 Pressure Sensor

[0176] According to one aspect of this technology, one or more transducers 4270 include a pressure sensor in fluid communication with the pneumatic path of the RT device. An example of a suitable pressure sensor is a transducer from the HONEYWELL ASDX series. An alternative suitable pressure sensor is a transducer from the GENERAL ELECTRIC NPA series. In one implementation, the pressure sensor is located in the air circuit 4170, adjacent to the outlet 5004 of the humidifier 5000.

[0177] The pressure sensor (microphone) 4270 is configured to generate an acoustic signal representing pressure changes within the air circuit 4170. The microphone 4270 can be directly exposed to the airflow within the air circuit 4170 to enhance its sensitivity to sound, or it can be encapsulated behind a thin layer of flexible membrane material. This membrane can protect the microphone 4270 from heat and / or humidity.

[0178] The audio signal from microphone 4270 can be received by a central controller 4230, which serves as an acoustic analysis device, for acoustic processing and analysis according to one or more algorithms / methods described herein and below. Alternatively, the audio signal from microphone 4270 can be received by other acoustic analysis devices for acoustic processing and analysis according to one or more of the algorithms / methods described herein and below.

[0179] 5.8 Acoustic Analysis

[0180] According to one or more aspects of this technology, acoustic analysis can be performed, for example, by means of the apparatus described herein, to determine one or more parameters related to respiratory disorders or systems used to treat respiratory disorders.

[0181] Acoustic analysis based on various aspects of this technology can provide one or more advantages over existing technologies, such as reduced care costs, provision of higher quality treatment, improved ease of use of treatment systems, reduced waste, and provision of digital connectivity at low cost.

[0182] As will be apparent in the context of the remainder of this document, the terms “acoustic,” “sound,” or “noise” as used herein are generally intended to include airborne vibrations, whether audible or inaudible. Therefore, unless otherwise specifically stated, the terms “acoustic,” “sound,” or “noise” as used herein are intended to include airborne vibrations in the ultrasonic or subsonic range.

[0183] Some implementations of the disclosed acoustic analysis techniques can achieve cepstral analysis. The cepstral can be considered as the logarithmic inverse Fourier transform of the forward Fourier transform of a signal. This operation essentially converts the convolution of the impulse response function (IRF) and the input acoustic signal into an addition operation, making it easier to consider or remove the input acoustic signal to separate the IRF data for analysis. Cepstral analysis techniques are described in detail in the scientific papers entitled "Cepstral: A Processing Guide" (Childers et al., IEEE Transactions on Physics, Vol. 65, No. 10, October 1977) and Randall RB, Frequency Analysis, Copenhagen: Bruel & Kjaer, p. 344 (1977, revised 1987). The application of cepstral analysis in determining the air path characteristics of respiratory therapy systems is described in detail in PCT Publication No. WO2010 / 091462, entitled "Acoustic Detection for Respiratory Treatment Apparatus," the entire contents of which are incorporated herein by reference.

[0184] Cepstral analysis can be understood based on the properties of convolution. The convolution of f and g can be written as f*g. This operation can be the integral of the product of two functions (f and g) after being inverted and shifted. Therefore, it is an integral transform, as follows:

[0185]

[0186] Although the symbol t is used above, it does not need to represent the time domain. However, in this context, the convolution formula can be described as a weighted average of the function f(τ) at time t, where the weights are given by g(-τ) with a simple shift of t. As t changes, the weighting function emphasizes different parts of the input function.

[0187] A mathematical model that can correlate the output with the input of a time-constant linear acoustic system (e.g., the air path of a respiratory therapy system) can be based on convolution. The sound signal generated by a microphone 4270 suitable for sensing sound in the air loop 4170 can be regarded as the input (sound) signal “convolved” with the system impulse response function (IRF) as a function of time (t).

[0188] y(t)=s1(t)*h1(t) (2)

[0189] Where y(t) is the output (sound) signal generated by microphone 4270; s1(t) is the input signal representing the sound (e.g., motor operating noise) generated by or in the pressure generator 4140 of the respiratory therapy device 4000; and h1(t) is the system IRF from the sound source to microphone 4270. The system IRF h1(t) can be considered as the system response to a unit pulse input. In a linear acoustic system such as the air path of a respiratory therapy system, the system IRF h1(t) is the reflection of a unit pulse from any discontinuity in the air path (such as the junction between two parts).

[0190] By performing a Fourier transform on the sound signal y(t) (e.g., a Discrete Fourier Transform (“DFT”) or a Fast Fourier Transform (“FFT”)) and considering the convolution theorem, transforming the equation to the frequency domain yields the following equation:

[0191] Y(f)=S1(f)H1(f) (3)

[0192] Where Y(f) is the Fourier transform (spectrum) of y(t); S1(f) is the Fourier transform of s1(t); and H1(f) is the Fourier transform of h1(t). In other words, convolution in the time domain becomes multiplication in the frequency domain.

[0193] Logarithmic operations can be applied to equation (3) to convert multiplication into addition:

[0194] Log{Y(f)}=Log{S1(f)}+Log{H1(f)} (4)

[0195] Equation (4) can then be transformed back to the time domain by the inverse Fourier transform (IFT) (e.g., inverse DFT or inverse FFT), which yields the inverse Fourier transform of the logarithm of the complex-valued “cephalon” – the spectrum Y(f):

[0196]

[0197] The horizontal axis τ is a real-valued variable called the inverse frequency, measured in seconds. Therefore, the convolution effect in the time domain becomes additivity in the logarithm of the spectrum, and this remains true in the cepstrum or inverse frequency domain. Specifically, the output cepstrum... It consists of two additive components: the cepstrum of the input signal s1(t) and the cepstral of the system IRF h1(t)

[0198] Considering data from cepstral analysis, such as examining data values ​​in the cepstral domain, can provide information about an RT system. For example, by comparing the system's cepstral data with a previous or known baseline of the system's cepstral data, the comparison (e.g., the difference) can be used to identify differences or similarities in the system, which can then be used to implement automatic controls for changing functions or purposes.

[0199] 5.8.1 Acoustic Signature Extraction

[0200] One implementation of this technology includes means, apparatus, and / or methods for extracting acoustic signatures of components such as a mask in a respiratory therapy system. This implementation may utilize analysis of sound signals generated by a sound sensor, such as microphone 4270, positioned as described above.

[0201] This technology includes an analysis method that can separate acoustic mask reflections from other system noises and responses (including but not limited to blower noise).

[0202] An example method for extracting the acoustic signature of the mask is to sample the output signal y(t) generated by the microphone 4270 at a desired sampling rate (e.g., at least the Nyquist rate, such as 20 kHz). The cepstrum can be calculated from the sampled output signal. The cepstral reflection component can then be separated from the cepstral input signal component. The cepstral reflection component comprises the acoustic reflection of the input signal from the mask and is therefore referred to as the mask's "acoustic signature." The acoustic signature map can then be compared with a predefined or predetermined database (e.g., any suitable type of data storage structure) of previously measured acoustic signature maps obtained from a system containing a known mask to identify the mask from its acoustic signature. Optionally, some criteria can be set to determine appropriate similarity. In one example implementation, the comparison can be performed based on a single maximum data peak in the cross-correlation between the measured and stored acoustic signatures. However, the method can be improved by comparing several data peaks, or alternatively, the comparison can be performed on a unique set of extracted cepstral features.

[0203] Figure 7 This is a schematic diagram of an RT system 7000 according to one aspect of this technology. In such... Figure 7In this exemplary embodiment shown, the duct 7010 (of length L) effectively acts as an acoustic waveguide for sound generated by the RPT device 7040 (which may include a humidifier), such as sound from a speaker, or alternatively, only noise from the operation of a blower (e.g., an electric motor and / or impeller). In this exemplary embodiment, the input signal is sound emitted by the RPT device / humidifier 7040 (i.e., sound from a speaker is not required or is used). The input signal (e.g., a pulse) enters a microphone 7050 located at one end of the duct 7010, travels along the duct 7010 to a mask 7020, and is reflected back along the duct 7010 by features in the air path (including the duct and mask) to re-enter the microphone 7050. Therefore, the system IRF (output signal generated by the input pulse) contains both an input signal component and a reflected component. A key feature of the RT system 7000 is the time it takes for sound to travel from one end of the air path to the other. This interval is reflected in the system IRF, as microphone 7050 receives the input signal from RPT device / humidifier 7040, and then, after some time, receives the input signal filtered by catheter 7010 and reflected and filtered by mask 7020 (as well as any other system 7030 that may be connected to the mask, such as the human respiratory system when mask 7020 is placed on a patient). This means that the component of the system IRF associated with the reflection from the mask end of catheter 7010 (the reflected component) is delayed relative to the component of the system IRF associated with the input signal (the input signal component), arriving at the microphone after a relatively short delay. (In practice, this short delay can be ignored, and zero time is approximated by the time when microphone 7050 first responds to the input signal.) The delay of the reflected component is equal to 2L / c (where L is the length of the catheter and c is the speed of sound in the catheter).

[0204] System 7000 includes an acoustic analysis device 7015 that communicates with a microphone 7050 via a connection 7025. For example, the acoustic analysis device may include an input interface to receive signals from the microphone. As described in further detail below, the acoustic analysis device 7015 includes one or more processors configured to implement specific methods for determining the carbon dioxide concentration within catheter 7010 from the carbon dioxide concentration and subsequently determining the patient's cardiac output. Therefore, the acoustic analysis device 7015 may include an integrated chip, memory, and / or other control instructions, data, or information storage media for performing the methods. For example, programming instructions containing such a detection method may be encoded on an integrated chip in the memory of the acoustic analysis device 7015. Such instructions may also, or optionally, be loaded as software or firmware using a suitable non-transient data storage medium.

[0205] Another feature of the RT system 7000 is that, due to the ease with which the air path can be lost, if the duct is long enough, the input signal component attenuates to a negligible amount at the start of the reflection component of the system's IRF. If this is the case, the input signal component can be separated from the reflection component of the system's IRF. As an example, Figure 8 An example of such a system IRF from an exemplary treatment system is shown, wherein the input signal may originate from the blower 4142 of the RPT device. Alternatively, the input signal may include sound from a speaker at the device end of the air path (with or without sound generated by the RPT device / humidifier 7040). Figure 8 The reflection component 8020 of the system IRF is shown to be delayed relative to the input signal component 8010 in the system IRF, with a delay of 2L / c.

[0206] The cepstrum of the system IRF associated with equations (2) and (4) described earlier It typically exhibits the same characteristics as the system IRF h1(t). That is, the cepstrum. This includes reflection components concentrated around the inverted frequency of 2L / c and input signal components concentrated around the inverted frequency of zero. In this technique, cepstral analysis is configured, for example, to analyze the output cepstral data by examining the position and amplitude of the output cepstral data. The reflection component and other system artifacts (including but not limited to the input signal component) Separation.

[0207] This separation can be achieved if the input signal s1(t) is instantaneous (e.g., pulse) or stationary random. In either case, the cepstral components of the input signal... The frequency will be concentrated near zero. For example, the input signal could be the sound produced by an RPT device running at a constant speed during the time period measured by the microphone. This sound can be described as “cyclically stationary”. That is, it is stationary random and statistically periodic. This means that the input signal and reflected components of the system IRF can be “smeared” over all measurement times of the output signal y(t), since at any point in time, the output signal y(t) is a function of all previous values ​​of the input signal and the system IRF (see Equation (2)). However, the above cepstral analysis can be performed to obtain the output cepstral. The reflection component is separated from the convolutional mixture.

[0208] Figure 9 Describing the effects of respiratory therapy systems (e.g.) Figure 7The system measures the real part of various exemplary inverse frequencies of the frequency, which is achieved using three different masks, where the input signal is sound generated by the blower of the RPT device. In this embodiment, each mask is tested at two different blower operating speeds, namely 10 krpm and 15 krpm. Although these speeds are used in the example, the method can be implemented with other blower speeds, especially if the generated sound can be detected by a microphone.

[0209] exist Figure 9 In the spectrum, the reflection component is clearly visible in all six cepstral frequencies, starting at a frequency of approximately twelve milliseconds (12 ms). This location is consistent with expectations (2 L / c) because a two-meter catheter was used in the exemplary treatment system, and the speed of sound was 343 m / s. Figure 9 In the graph, the inverted spectrum from the mask is shown in the following order from top to bottom:

[0210] ResMed Ultra Mirage TM 10krpm;

[0211] ResMed Ultra Mirage TM 15krpm;

[0212] ResMed Mirage Quattro TM Use at 10krpm;

[0213] ResMed Mirage Quattro TM 15krpm;

[0214] ResMed Swift II TM 10krpm; and

[0215] ResMed Swift II TM 15krpm.

[0216] Although Figure 7 A system 7000 with a single microphone 7050 is shown, but in one or more alternative implementations, there may be multiple microphones. Figure 14 The figure illustrates such a system 1400 according to one aspect of the present technology. System 1400 and Figure 7 The system is the same as 7000, except for the differences described below. Therefore, unless otherwise stated, Figure 14 Features and references in Figure 7 The features described and labeled with similar numbers are the same.

[0217] System 7000 includes a first microphone 1450 and a second microphone 1460, both similar to microphone 7050. The first microphone 1450 is separated from the second microphone 1460 along an air loop. In one implementation, the separation distance is L, the length of duct 1410. System 1400 includes an acoustic analysis device 1415 that communicates with the first microphone 1450 via connection 1425 and with the second microphone 1460 via connection 1435.

[0218] In one or more implementations, the second microphone 1460 may provide higher accuracy, such as providing additional ranging information (simulating time-of-flight from one or more sound sources), noise reduction, or other functionalities. In some implementations, the first microphone 1450 senses sound within the catheter 1410, and the second microphone 1460 senses the environment (e.g., background noise) outside the catheter 1410 or the RPT device / humidifier 1440. For systems with two or more microphones, signal processing may be configured to remove patient sounds or other interfering noise from the environment from reflections of sound generated by the RPT device / humidifier 1440, thereby increasing the signal-to-noise ratio of the system 1400.

[0219] In other implementations, the second microphone 1460 is used to sense sound within the conduit 1410. Sound is generated by the RPT device / humidifier 1440 and propagates downwards along the conduit 1410. The time required for sound to propagate from the RPT device / humidifier 1440 to the first microphone 1450, and then from the first microphone 1450 to the second microphone 1460, depends on the speed of sound c within the conduit 1410.

[0220] Typically, the time it takes for the generated sound to appear at the first microphone 1450 and the time it takes for the same generated sound to appear at the second microphone 1460 is approximately L / c, where L is the length of the conduit 1410 between the first microphone 1450 and the second microphone 1460, and c is the speed of sound in the conduit 1410. This implementation is referred to as a "transmission-based system" to distinguish it from reflection-based systems, in which the delay is approximately 2L / c.

[0221] In a transmission-based system, the cepstral spectrum of the signal generated by the first microphone 1450 Including input signal components concentrated around the inverted frequency zero Signal generated by the second microphone 1460 The cepstrum includes components added to the input signal. IRF cepstral (Acoustic signature of the transmission-based system), which is approximated as a single peak at the quasi-frequency of L / c. Therefore, it can be obtained from the cepstrum. Subtracting the cepstral spectrum To obtain an acoustic signature Then, the delay of the acoustic signature can be estimated as the acoustic signature. The quasi-current position of the peak. In transmission-based systems such as system 1400, the acoustic signature does not represent the characteristics of mask 1420, but only the characteristics of conduit 1410, and is therefore unsuitable for mask identification or other mask feature analysis.

[0222] 5.8.1.1 Minimize back reflection

[0223] One complicating factor in acoustic signature extraction is the acoustic “back reflection” from the device (RPT device) end of duct 7010. Due to the change in acoustic impedance between duct 7010 and the interior of the RPT device / humidifier 7040 connected to duct 7010, these back reflections occur from the device end of duct 7010 after the sound reflected from mask 7020 has propagated backward along duct 7010. This back reflection has a blurring effect on the acoustic signature of the mask. For some implementations, acoustic signature analysis will become more accurate if back reflection can be reduced or minimized. For example, when the mask size has a physical scale similar to the distance between any discontinuities in the cross-sectional area within the acoustic sensor and the airflow generator, reflections from the mask can be superimposed on the output signal of the airflow generator’s back reflection response. In some cases, it may be desirable to characterize the back reflections and deconvolve them from the component reflections. However, it may be desirable to minimize back reflections through design.

[0224] In one such implementation, such as Figure 10 As shown, the end of the conduit 1010 closest to the microphone 1050 includes a structure 1060 configured to reduce back reflection. Structure 1060 is shown as a horn extending from the device end of the conduit 1010 into the cavity of the RPT device / humidifier 1040, wherein the diameter of the horn is the same as the diameter of the conduit 1010, and the cavity of the RPT device / humidifier has a gradually increasing diameter. Because the acoustic impedance of an acoustic waveguide is related to its diameter, the horn structure 1060 minimizes back reflection by gradually varying the acoustic impedance between the conduit 1010 and the cavity of the RPT device / humidifier 1040. The horn structure 1060 can be as follows: Figure 10 The conical profile shown, or the cross-section of the horn, can be bent in the manner of a brass bell. The function of the horn structure 1060 is to reduce the back-reflection component in the acoustic signature of system component 1020.

[0225] 5.8.1.2 Spectrum Flattening

[0226] Perform the IFT in equation (5) to calculate the cepstrum. Previously, a low-pass filtered version of subtracting the logarithmic spectrum Log{Y(f)} from itself, such as subtracting the moving average of the logarithmic spectrum Log{Y(f)} from the logarithmic spectrum Log{Y(f)}, could flatten the overall shape of the logarithmic spectrum and reduce the sensitivity of acoustic signature separation to the randomness of the input signal s1(t). In other words, even if the input signal s1(t) is not particularly random in terms of characters, this flattening will flatten the input signal components. The output cepstrum is concentrated near the origin (τ=0). This concentration increases the number of input signal components. With output cepstral The separability of the reflection components of the system's IRF (acoustic signature) needs to be carefully considered. The filter needs to be carefully configured so that the duct resonance frequencies are not removed during flattening. For example, the filter cutoff point should be low enough (or the moving average window should be long enough) so that the duct resonances are significantly eliminated by the filter and thus preserved by the flattening process. In an alternative implementation, the logarithmic spectrum Log{Y(f)} can be high-pass filtered to compute the cepstrum before performing the IFT in equation (5).

[0227] 5.8.2 Acoustic Signature Delay Analysis

[0228] The cepstral of the output signal y(t) can be calculated over a finite time window. A longer window can produce a cleaner separation between the acoustic signature and the input signal components. However, the acoustic characteristics of the air passage can change over time due to factors such as variations in gas composition during the breathing cycle, humidity variations, and tube resistance (which can unpredictably lengthen the air passage). Therefore, the window should not be made so long that significant changes in the air passage characteristics can be expected within the window. In one example, the window duration is approximately 200 ms. Other suitable window durations can be achieved.

[0229] Multiple output cepstrums can be calculated over multiple windows. Furthermore, the delay of the acoustic signature extracted from each window can be estimated. The result is a time series of acoustic signature delay estimates. This can be implemented using any suitable data structure for analysis or processing, such as arrays, vectors, buffers, etc. As mentioned above, in a reflection-based system, the acoustic signature delay is equal to 2L / c (where L is the length of the conduit and c is the velocity of sound in the conduit), while in a transmission-based system, the acoustic signature delay is equal to L / c. Therefore, the variation in acoustic signature delay reflects the variation in conduit length and / or the velocity of sound in the conduit.

[0230] The speed of sound in a gas mixture varies with the composition of the mixture. In particular, the speed of sound c in the catheter of a respiratory therapy system decreases when the carbon dioxide concentration in the catheter increases.

[0231] For example, if a two-meter conduit appears to be two meters long (based on the speed of sound in the atmosphere at room temperature and pressure), its effective length will change once it is filled with a higher concentration of carbon dioxide. This is because the speed of sound in carbon dioxide gas at 20°C is approximately 267 meters per second (m / s), and the speed of sound in atmospheric air at 20°C is approximately 343 m / s. Therefore, this property of sound can be used to estimate the concentration of carbon dioxide in the conduit by analyzing the sound inside the conduit using cepstral analysis or other signal processing techniques.

[0232] Typically, the carbon dioxide concentration in the catheter of a respiratory therapy system varies throughout the respiratory cycle, reaching its maximum at end-expiration and its minimum at end-inspiration. According to one estimate, at 20°C, the velocity of sound in the respiratory catheter varies by approximately 0.67% during the respiratory cycle due to this variation in CO2 concentration. This variation will be reflected as a periodic change in the acoustic signature delay at the respiratory rate. It is safe to assume that the catheter length L does not change with the respiratory cycle. Therefore, analysis of the time series of the acoustic signature delay estimate, particularly the variation in the delay estimate itself, such as the variation related to its components in the frequency bands surrounding the patient's respiratory rate, will yield information about the CO2 concentration in the catheter of the respiratory therapy system. Optionally, determining the CO2 concentration may involve correcting for one or more environmental parameters, such as temperature, humidity, pressure, ambient CO2 concentration, background noise, etc. (e.g., based on device setup, the humidifier in use or its configuration, and the catheter type, whether heating is used, etc.).

[0233] Figure 11 This is a flowchart illustrating a method 11000 for estimating the acoustic signature delay of the airway in a respiratory therapy system according to one aspect of the present technology. Method 11000 may begin at step 1110, which calculates the output cepstrum from the output signal y(t) during a window period. As described above with respect to equation (5). Step 1110 may optionally involve calculating the output cepstrum as described above. Previously, the logarithmic spectrum Log{Y(f)} was flattened.

[0234] Next is step 1120, in which the reflection component (acoustic signature) is separated from the cepstral calculated in step 1110. In the next step 1130, the delay of the acoustic signature and the corresponding window time are estimated and recorded.

[0235] Then, step 1140 checks whether more acoustic signature delay is desired. If yes (“Y”), method 11000 proceeds to step 1160, which waits for the next window to compute a new cepstral from the next window before returning to step 1110. If not (“N”), method 11000 terminates at step 1150.

[0236] 5.8.2.1 Respiratory rate band analysis (e.g., CO2 concentration and / or cardiac output)

[0237] The time series of acoustic signature delay estimation can be bandpass filtered to the respiratory rate band to extract the acoustic signature delay time series, the variation of which is mainly due to changes in CO2 concentration in the catheter. The respiratory rate band of a normal adult at rest is approximately 0.1 Hz to 0.5 Hz.

[0238] For example, in a transmission-based system, the time series of delays from a bandpass filter can be converted into a time series of sound velocity estimates c by dividing the current length L of the air loop by each delay estimate. In a reflection-based system such as System 7000, the resulting estimate can then be multiplied by two. Utilizing the properties of nitrogen, oxygen, and CO2, the sound velocity estimate c can be conversely converted into an estimate of the CO2 concentration in the air loop.

[0239] In one implementation, a simple model of the speed of sound c in a gas mixture can be used as a function of its fractional concentration p. i The speed of sound c in a weighted mixture of gases i Weighted sum:

[0240]

[0241] Table 1 contains the speeds of sound (c) in their pure forms for the four main components of the atmosphere at room temperature. i Estimates of their values ​​and their typical fractional concentrations p in the atmosphere i .

[0242] i pure gas <![CDATA[Sound velocity c i (m / s)]]> <![CDATA[Fractional concentration in air (p i )]]> 1 nitrogen 349 .78 2 Argon 319 .0097 3 oxygen 326 .21 4 carbon dioxide 267 .0003

[0243] Table 1: Properties of gases in the atmosphere

[0244] Assuming that the fractional concentrations p1 and p2 of nitrogen and argon in the air loop remain unchanged during the breathing cycle, the concentrations of oxygen and carbon dioxide in the air loop change in a complementary manner during the breathing cycle. This means that if the fractional concentration of carbon dioxide is written as p at any given moment, then the fractional concentration of oxygen can be written as (1-(p1+p2)-p). Substituting these values ​​into equation (6), we can derive the expression for the fractional concentration p of CO2 based on the speed of sound c measured in the air loop:

[0245]

[0246] Using the values ​​from Table 1, equation (7) can be simplified to the following equation relating the measured speed of sound c to the fractional concentration p of CO2 in the air loop:

[0247]

[0248] Therefore, the system can be configured to generate one or more CO2 concentration indicators or variations thereof based on a filtered time series of acoustic signature delay estimates, wherein filtering is used to isolate or include frequencies associated with respiratory rate. Such generation may include one or more output signals, including displayed or transmitted messages and / or control signals, which modify or alter the administered treatment (e.g., pressure or flow rate) based on the indicator and / or its assessment, such modification may be made, for example, if the determined concentration indicator meets (e.g., exceeds) a threshold.

[0249] For example, Figure 12 This contains two time series plotted on the same time axis. The upper trace 1200 is a time series of estimated acoustic signature delay values ​​bandpass filtered to the respiratory rate band. The lower trace 1250 is a time series of concurrent CO2 concentration measurements from a CO2 sensor in the inflatable chamber of a mask, for which the acoustic signature that produces trace 1200 is reflected. It can be seen that the peak in the acoustic signature delay trace 1200 (e.g., 1210), i.e., the instant of increased delay or slowest sound velocity, coincides with the peak in the CO2 concentration measured due to exhalation (e.g., 1260), as expected, because the speed of sound in air decreases with increasing CO2 concentration in the air.

[0250] Other actionable information can be extracted from the indication of changes in CO2 concentration in the catheter during the respiratory cycle, through another example. In one example, the fractional concentration of CO2 in the catheter at the end of expiration (end-expiratory CO2 concentration or EtCO2), i.e., the peak CO2 concentration during the respiratory cycle, can be used in an improved Fick technique to measure a patient's cardiac output. The improved Fick technique [1] involves applying a step change to the dead space of the respiratory therapy system and measuring the effect on EtCO2 to estimate the patient's cardiac output. In one implementation of the improved Fick technique, the effective volume of the dead space can be altered by changing the CPAP treatment pressure or HFT flow rate. For example, a lower pressure or flow rate increases the effective dead space by reducing the flushing flow through the system ventilator. The final change in EtCO2 can be estimated and converted into an estimate of the patient's cardiac output.

[0251] Figure 15This is a flowchart illustrating an example of a process 1500 for determining a patient's cardiac output according to one aspect of the present technology. Although process 1500 is described below as being performed by an acoustic analysis device such as acoustic analysis device 7015, process 1500 may also be performed by a central controller 4230 as part of algorithm 4300 as described above.

[0252] In step 1510, the acoustic analysis device uses at least one sound sensor coupled to the catheter within the patient to determine a sound measurement. The sound sensor may be a microphone 7050 that detects various sounds within the catheter 7010 of a respiratory therapy system 7000. In one or more embodiments, sound may be generated within the catheter by a sound source before or simultaneously with step 1510. The sound source may be a component of the respiratory therapy system, such as an RPT device / humidifier 7040, where the catheter is part of the air passage of the respiratory therapy system, such as a continuous positive pressure (“CPAP”) system or a similar system. Alternatively, the sound source may be a loudspeaker, where the catheter is part of the air passage of the respiratory therapy system and where the catheter is separate from the air passage of the respiratory therapy system. The sound measurement may be a measurement of the sound generated by the sound source within the catheter. In one or more embodiments, at least one sound sensor may be a microphone, and the catheter may be part of the air passage of the respiratory therapy system to which the microphone is coupled.

[0253] In step 1520, the acoustic analysis device determines the carbon dioxide concentration within the catheter based at least in part on the measurement of sound. In one or more embodiments, determining the carbon dioxide concentration may include calculating a Fourier transform of a data sample representing the sound measurement. In one or more embodiments, determining the carbon dioxide concentration may further include calculating the logarithm of the Fourier transform of the data sample representing the sound measurement. In one or more embodiments, determining the carbon dioxide concentration may further include calculating the inverse Fourier transform of the logarithm of the Fourier transform of the data sample representing the sound measurement. In one or more embodiments, determining the carbon dioxide concentration further includes calculating the difference between (a) the inverse Fourier transform of the logarithm of the Fourier transform of the data sample representing the sound measurement and (b) the inverse Fourier transform of the logarithm of the Fourier transform of a data sample representing the baseline carbon dioxide concentration in the air passage of the respiratory therapy system.

[0254] In one or more embodiments, the acoustic analysis device can determine one or more environmental parameters of the catheter or respiratory therapy system, such as using sensors configured to detect these parameters and / or other data input to the system. The one or more environmental parameters may include any one or more of air temperature, ambient pressure, ambient carbon dioxide concentration, background noise, or combinations thereof. Subsequently, when determining the carbon dioxide concentration, the acoustic analysis device can correct for one or more environmental parameters. For example, temperature can affect the velocity of sound within the catheter. Temperature calculations account for the effect of temperature on the velocity of sound, making the subsequent determination of the carbon dioxide concentration more accurate.

[0255] Regarding ambient carbon dioxide concentration, in one or more embodiments, when the catheter is not connected to the patient, the acoustic analysis device can determine a baseline carbon dioxide concentration in the catheter. In these cases, the concentration of carbon dioxide within the catheter represents the ambient concentration of carbon dioxide. Alternatively or additionally, the acoustic analysis device can query one or more external databases containing information on carbon dioxide concentration at the location of the acoustic analysis device. Alternatively or additionally, the acoustic analysis device can include a carbon dioxide sensor that directly senses the carbon dioxide concentration in the catheter, rather than indirectly by determining a measurement of sound. The acoustic analysis device can verify the carbon dioxide concentration by comparing the determined carbon dioxide concentration with the carbon dioxide concentration from the carbon dioxide sensor by determining the sound measurement.

[0256] In one or more embodiments, the sound sensor can detect background noise. For example, the sound sensor can detect background noise before the patient is connected to the catheter. For example, in the case where the catheter is part of the airway of a respiratory therapy system, at least one sound sensor can detect background noise before the patient begins using the respiratory therapy system. Alternatively, in the case where the sound measurement is based on a sound source within the catheter, at least one sound sensor can detect background noise before or after the sound source generates sound, or both before and after the sound source generates sound.

[0257] In step 1530, the acoustic analysis device determines the patient's cardiac output based at least in part on carbon dioxide concentration. The determination of the patient's cardiac output can be based at least in part on the improved Fick method described above, and at least in part on carbon dioxide concentration. The improved Fick method relies on equation (8):

[0258]

[0259] Where CO is cardiac output; VCO2 is the concentration of exhaled carbon dioxide; CvCO2 is the venous carbon dioxide content; and CaCO2 is the arterial carbon dioxide content.

[0260] Assuming that cardiac output remains constant under normal (N) and rebreathing (R) conditions, equation (9) yields:

[0261]

[0262] By subtracting the normal and rebreathing ratios, we obtain the following difference Fick equation:

[0263]

[0264] Because carbon dioxide diffuses rapidly in the blood (i.e., 22 times faster than oxygen), it can be assumed that CvCO2 is no different between normal and rebreathing conditions, and therefore the venous contents disappear from the molecules of equation (11), leaving equation (12):

[0265]

[0266] The δ in CaCO2 can be approximated by multiplying the δ in etCO2 by the slope (S) of the carbon dioxide dissociation curve. This curve represents the relationship between the volume of carbon dioxide (used to calculate carbon dioxide content) and the partial pressure of carbon dioxide. Between 15 and 70 mmHg of partial pressure of carbon dioxide, this relationship can be considered linear, thus yielding equation (13):

[0267]

[0268] Based on the above, a patient's cardiac output can be determined based on the concentration of carbon dioxide in their exhaled breath. Therefore, the patient can use the respiratory therapy system throughout the entire sleep session, such as throughout the night. During use, the acoustic analysis device of this technology, either within or separate from the respiratory therapy system, can determine the patient's cardiac output. This determination can be performed non-invasively without disturbing the patient. However, the patient or other users can gain additional insight into the patient's cardiac output.

[0269] Figure 15 The process 1500 can be performed once to determine the patient's discrete cardiac output. Alternatively, one or more steps of process 600 can be repeated. For example, determining carbon dioxide concentration and determining cardiac output can both be performed multiple times in a single treatment session to determine multiple discrete cardiac outputs for the patient. As described above, when the catheter is part of a respiratory therapy system, sessions can be conducted during the use of the respiratory therapy system during a single night or over multiple different nights. The acoustic analysis device can then determine the trend of cardiac output during the session. Based on this trend, one or more actions can be taken. For example, the trend can indicate a deterioration in cardiac output. In this case, the patient can be notified to seek medical attention. Alternatively, the trend can indicate an improvement in cardiac output. In this case, medical treatment can be stopped or reduced.

[0270] Cardiac output for a single or multiple treatment sessions can be compared to population-standard values ​​for age, sex, cardiac health, medication regimens, etc., as one or more thresholds. Under the conditions of comparison, such as if the determined cardiac output meets (e.g., exceeds) a threshold, actions can be taken, such as generating one or more output signals including displayed or communicative messages and / or control signals, which alter or change the setpoint of the treatment device producing the therapy (e.g., pressure or flow) based on cardiac output and / or its assessment. Trend data can be used to detect a patient's typical baseline to (a) help the acoustic analysis device identify inaccurate cardiac output based on one or more issues with the acoustic analysis device, and (b) detect changes in patient data indicating a worsening (or improving) trend in their cardiac output. In the event of an observed worsening trend, the system can generate an output to recommend examination by a healthcare professional. For example, heart failure via edema can be seen through a decrease in cardiac output. Detection of a decrease in cardiac output can represent heart failure. Detection of a decrease in cardiac output by this acoustic analysis device allows the patient to seek medical attention in response to the output message generated based on the analysis. This method can also be used to predict or detect the worsening of chronic obstructive pulmonary disease (COPD).

[0271] In one or more implementations, respiratory rate and depth (increased rate and shallower breathing) can be analyzed from signals from pressure sensors, flow sensors, velocity sensors, or other sensors within the respiratory therapy system. This information can be used in conjunction with heart rate and / or cardiac output to predict or detect cardiac decompensation. Other parameters of patients using the respiratory therapy system can be combined with cardiac output. These parameters may include tidal volume, minute ventilation, etc.

[0272] Although this technology considers integrated acoustic analysis devices and respiratory therapy systems with cardiac output detection, the methods used for the components of this device can be shared across multiple components within the system. For example, the measuring device can simply perform a measurement process to determine catheter delay and transmit the data to another processing system. A second processing system can then analyze the data to determine carbon dioxide concentration, which in turn can send the data to another device to determine cardiac output, as previously described. A third processing system then indicates the cardiac output as described herein, for example, by electronically sending one or more of the described messages back to the measuring device or other device for display to the patient, clinician, or physician.

[0273] Other examples of using EtCO2 are:

[0274] • Monitor the progression of COPD.

[0275] • Titrate ventilation parameters, such as pressure support, volume delivery, and minute ventilation targets.

[0276] • Ensure the endotracheal tube is correctly placed in the trachea.

[0277] 5.8.2.2 Additional respiratory rate band analysis (e.g., CO2 distribution)

[0278] Similar to the overall acoustic signature delay, a series of internal delay estimates within the acoustic signature were analyzed, particularly components of its surrounding frequency bands, including the patient's respiratory rate. This analysis yields information about the CO2 concentration in the mask tube. More generally, the respiratory frequency band variations within the acoustic signature structure of any type of mask were analyzed, including a series of discrete reflection components corresponding to different structures of the mask's air passage. This analysis can produce information about the relative CO2 concentration distribution at various points within the mask. Combining this with the analysis of the acoustic signature delay representing the CO2 concentration within the catheter 7010, a picture of the CO2 distribution within the pneumatic circuit and its evolution over time can be established. Actionable information can be extracted from this picture. In one example, an increase in the relative concentration of CO2 toward the RPT device / humidifier 7040 could indicate insufficient flushing of exhaled CO2 by system ventilation and therefore excessive CO2 rebreathing, which can lead to central sleep apnea, headache, or a feeling of suffocation. Therefore, the system can be configured to generate one or more output signals, including displayed or communicated messages and / or control signals that alter or vary the provided treatment based on the distribution of CO2 or changes in that distribution (e.g., pressure or flow rate or controlled adjustment of the ventilation area such as a mask ventilator).

[0279] 5.8.2.3 Non-respiratory rate band analysis (e.g., catheter length)

[0280] Variations in the acoustic signature delay time series outside the respiratory rate band are independent of respiration. Therefore, removing respiratory rate-band variations from the original delay time series, for example by subtracting a bandpass-filtered version of the delay time series, yields a time series for estimating non-respiratory delays. The primary source of non-respiratory delay variation is variation in the catheter length L. Each delay value in the non-respiratory-related time series can be mapped to a value of catheter length L. This is achieved by multiplying the delay value by c / 2 (for reflection-based systems) or c (for transmission-based systems), where c is the speed of sound in the atmosphere (approximately 343 m / s at 20°C).

[0281] Changes in catheter length L detected using non-respiratory acoustic delay time series can serve as an indicator of the patient's or respiratory therapy system's state. For example, as mentioned above, catheter resistance is a possible cause of catheter length changes. Catheter resistance changes as the patient's sleep position changes during treatment. Therefore, changes in catheter length during treatment can serve as an indicator of patient activity or restlessness. This patient activity can be used or realized in the system in several ways:

[0282] • As an indicator of treatment effectiveness.

[0283] • As an indicator of sleep state (sleep / wake).

[0284] • As an adjunct to the detection of apnea or insufficiency. Apnea or insufficiency consistent with high-activity periods may be ignored or discounted by the treatment algorithm because they are unlikely to represent true airway obstruction.

[0285] Furthermore, the cumulative measurement of catheter resistance can be used as an indicator of catheter life, as continuous resistance causes catheter 7010 to lose its elasticity. In one example, a long-term increase in catheter length can serve as an indicator that catheter 7010 has been permanently stretched. Therefore, the respiratory therapy system can determine or predict when the increase in catheter length exceeds or will exceed a threshold during multiple treatments by analyzing statistics of catheter length changes over multiple treatments, and thus estimate or predict when the catheter should be replaced. Based on such an assessment, the system can trigger the generation of one or more output messages to indicate or provide replacement.

[0286] 5.8.3 Acoustic signature shape analysis (e.g., mask tube or headband)

[0287] In other embodiments of this technology, the shape of the acoustic signature in the reflection-based system can be analyzed by the system to detect specific characteristics of the mask. For example, the system can analyze the acoustic signature to detect characteristics of the mask. These characteristics may include: diameter, construction material, volume of air cavities, overall structure of the mask, etc.

[0288] One such characteristic of the mask is the length of the mask tube, which can be detected from the shape analysis of the acoustic signature. The acoustic signature of a mask with a mask tube comprises two separate parts: a portion corresponding to sound reflections from the connection port 3600 between the air circuit 4170 and the mask tube, and a portion corresponding to sound reflections from the body of the mask 3000 that is delayed from the first portion. The delay between these two portions is equal to twice the length of the mask tube divided by the speed of sound in the mask tube.

[0289] Figure 13This is a diagram of the cepstral spectrum 1300 of the pillow mask 7020, which includes a mask tube in the respiratory therapy system 7000. The portion of the cepstral spectrum 1300 corresponding to the acoustic signature is denoted as 1350. The portion 1310 of the acoustic signature 1350 corresponds to the sound reflection from the connection port 3600 between the air circuit 4170 and the mask tube. The portion 1320 of the acoustic signature corresponds to the sound reflection from the body of the pillow mask. The “internal delay” 1330 between the two portions 1310 and 1320 is equal to twice the length l of the mask tube divided by c (the speed of sound in the mask tube).

[0290] Another feature of the mask is the elasticity of the headband. When the headband is used as a positioning and stabilizing structure 3300, it stretches. The effect of stretching is that the sealing forming structure 3100 experiences less compression relative to the patient's face. This reduction in compression can manifest as a change in the acoustic signature portion corresponding to the reflection of sound from the mask body. Therefore, by analyzing various parts of the treatment process, the respiratory therapy system can estimate or predict when the mask is ready for replacement due to headband stretching. For example, detecting displacement or other changes in the shape of the portion from its previous shape or position can serve as a basis for replacement indication. Thus, based on this assessment, the system can trigger the generation of one or more output messages to indicate or provide replacement.

[0291] 5.8.3.1 Non-respiratory rate band analysis (e.g., mask tube length)

[0292] Similar to the overall acoustic signature delay, the non-breathing-related variations in the internal delay of the mask signature can be obtained by removing the breathing rate bandgap from the original internal delay time series, such as by subtracting a bandpass-filtered version of the internal delay time series from the original internal delay time series. The non-breathing-related variations in the resulting internal delay time series can be multiplied by c / 2 to obtain the time series of variations in the mask tube length l. Therefore, in addition to or as an alternative to the aforementioned shape analysis, the mask tube length variation can be obtained through filtering.

[0293] Tube resistance causes changes in the mask tube length *l* and the air circuit length *L*. In one implementation, a long-term increase in the mask tube length indicates permanent stretching of the mask tube. Therefore, a respiratory therapy system can assess the current lifespan of the mask by analyzing statistical data on changes in mask tube length over numerous treatment sessions. Specifically, by analyzing this statistics to determine or predict when the increase in mask tube length over numerous treatment sessions exceeds or will exceed a threshold, the respiratory therapy system can estimate or predict when the mask will need to be replaced due to mask tube stretching.

[0294] In another implementation, the variability in the length of the mask tube during the treatment process can be used as a representation or indication of patient activity or distress during the treatment process.

[0295] 5.8.4 Example System Design and Implementation

[0296] about Figure 11 and 15 The signal processing analysis described herein, along with the additional methods described herein using the aforementioned delay detection and cepstral or quasi-frequency correlation analysis, can be implemented by a controller or processor, for example, using firmware, hardware, and / or software, as previously described. In some exemplary implementations, such a controller can estimate the CO2 concentration at one or more locations within the respiratory therapy system. This CO2 concentration data and / or cardiac output data from the improved Fick technology can then be transmitted to another controller, processor, system, or computer, or used by the controller itself. This information can then be used to adjust the treatment or other settings for controlling the RPT device during the delivery of respiratory therapy within the respiratory therapy system.

[0297] For example, the above-mentioned technology can be implemented as part of the controller of a respiratory therapy system such as a CPAP device.

[0298] Alternatively, the above-mentioned technologies can be implemented through, for example... Figure 7 The acoustic analysis device 7015 is used to achieve this, and this acoustic analysis device can be external to the CPAP device, so that the acoustic analysis device itself does not include a pressure generator (e.g., a flow generator). For example, such a monitoring device can be as follows: Figure 16 This is achieved as shown. At this point, Figure 16 This is based on one aspect of the technology. Figure 7 A diagram showing the components implementing the acoustic analysis device 7015. As an example, Figure 16 In addition to performing the other functions described above, the acoustic analysis device 1600 also includes one or more components for determining the user's cardiac output. It is conceivable that the functions of these components may be combined in one or more components, or performed by other components with equivalent functions.

[0299] One or more processors (e.g., processor 1602) perform a set of operations on information (e.g., data samples representing acoustic measurements from an acoustic transducer), as specified by computer program code. In addition to any one or more methods discussed herein, the code may also process this data to produce a CO2 concentration indication and / or other outputs as previously described, such as outputs related to detecting a user's cardiac output. Computer program code is a set of instructions or statements that provide control instructions for the operation of processor 1602 to perform a specified function. For example, the code may be written in a computer programming language that is compiled into the native instruction set of processor 1602. The code may also be written directly using a native instruction set (e.g., machine language). This set of operations typically includes comparing two or more units of information, shifting the positions of units of information, and combining two or more units of information, for example, by addition or multiplication, or logical operations such as OR, XOR, etc. Each operation in this set of operations that can be performed by processor 1602 is represented to processor 1602 by information called an instruction, such as an opcode for one or more numbers. The sequence of operations (e.g., opcode sequences) executed by the processor 1602 constitutes processor instructions, also known as computer system instructions or simply computer instructions.

[0300] Memory 1604 stores information, including processor control instructions as previously described, such as those for determining a user's cardiac output, and other methods disclosed herein. It may also store generated or received data, such as audio signal data and output data, such as cepstral data, acoustic signature data, delay data, delay time series data (filtered and / or unfiltered), CO2 concentration data, cardiac output data, etc. Memory 1604 may be random access memory (RAM) or any other dynamic storage device. Dynamic memory allows information stored therein to be modified by processor 1602. RAM allows information stored at adjacent addresses to be used to store and retrieve information units stored at a location (e.g., memory address). Processor 1602 also uses memory 1604 to store temporary values ​​during instruction execution. Alternatively or additionally, memory 1604 may be read-only memory (ROM) or any other static storage device coupled to store static information including unmodified instructions.

[0301] In one or more embodiments, memory 1604 may include stored processor control instructions for sound signal processing and acoustic analysis, such as measurement filtering, Fourier transform, logarithmic operations, position determination, range determination, difference determination, etc. In one or more embodiments, processor control instructions and data for controlling the disclosed methods may be included as software in memory 1604 for use by processor 1602 as a dedicated processor for any method discussed herein.

[0302] In one or more embodiments, the acoustic analysis device 1600 may optionally include a display 1606 for presenting output data, such as a monitor, LCD panel, touch screen, etc. The acoustic analysis device 1600 may also optionally include a control interface 1608, such as a keyboard, touch panel, control buttons, mouse, etc., for inputting data or activating or operating the methods described herein. The acoustic analysis device 1600 may also optionally include a data interface 1610, such as a bus, for receiving / transmitting data such as programming instructions, setting data, sound data, etc., to another device, such as the sound sensor 104.

[0303] Additionally, in some implementations, information obtained from latency analysis can be selectively sent to other systems, such as one or more servers, for transmission to manufacturers, doctors, or clinicians, enabling the information to be used to help patients troubleshoot. For example, such data can be transmitted via wired and / or wireless communication protocols, including, for example, Bluetooth. TM and / or WiFi TM Or other communication protocols.

[0304] Additionally, in some implementations, information obtained from latency analysis can be used to trigger actions, such as the manual or automated deployment of personalized coaching or training content related to a specific mask, such as tutorials on adjusting the mask. This material can be delivered to the user via the treatment device screen or a supported mobile device app, or other means of communication such as email or SMS messages. In one example, excessively high or low CO2 concentrations could trigger suggestions to increase or decrease treatment pressure or flow, or to change the type of mask.

[0305] In some implementations, blower speeds greater than those described above can be achieved during acoustic signature delay estimation. For example, some ducts use materials with noise-reducing properties. In such systems, the acoustic loss may fluctuate. If an increase in loss (e.g., a decrease in amplitude) is detected by the measured signal, the effect of the sound or noise source can be overcome by increasing the decibel level. This can be achieved by increasing the blower speed during the test measurement. Additionally, other components included in the air path can increase acoustic losses. These components may include humidifiers, noise dampers, and valves. Similarly, losses that may be caused by these components can be overcome by increasing the noise source level or amplitude. Typically, the appropriate sound level for the input signal can be approximately 20 dBa or greater.

[0306] The frequency range of microphone 4270 can be selected based on the geometric resolution required for delay estimation. Analyzing information about small dimensions typically requires high-frequency content in the generated sound signal. A typical air circuit for respiratory therapy may exhibit tube resonances with a fundamental frequency less than 100 Hz, but higher harmonics appear in the spectrum as integer multiples of the fundamental frequency, reaching up to 10 kHz and above. The frequency range of microphone 4270 can be selected to be large enough to allow sensing sufficient resonant harmonics such that the period associated with the harmonic interval exists in the inverse Fourier transform of the logarithmic spectrum. Therefore, in one implementation, microphone 4270 can be configured to detect frequencies up to a frequency upper limit of at least 10 kHz.

[0307] As previously mentioned, some embodiments may utilize a sound source such as a loudspeaker to generate sound impulses or white noise. This is particularly useful for respiratory therapy systems with very quiet blowers that do not produce a lot of noise. For example, when ResMed is used at a speed typically less than 6 krpm. TM When using an RPT device, the blower is very quiet. In this situation, using only the sound of the blower as the sound source to generate the input signal may be insufficient for acoustic signature delay estimation. This can be overcome by including an additional sound source in the air path. This can be activated during the measurement period, such as when the mask is initially attached to the duct. While the additional sound source can be a loudspeaker, other sound emitters can also be used. For example, a simple acoustic generator can be configured to vibrate in response to airflow from the RPT device, such as a reed that can be selectively activated and deactivated (e.g., mechanically applied to and removed from the air path of the system). This can be used to selectively generate sound pulses. Alternatively, an actuator valve of the RPT device can be used as an additional sound source.

[0308] Additionally, sound sources such as loudspeakers can be used to fill gaps in the sound spectrum produced by the blower. For example, loudspeakers can be used to generate signals designed with a specific spectrum, so that the addition of blower noise and loudspeaker sound creates a white spectrum. This can improve the detection accuracy of the system and enhance the perceived quality of sound for the user of the treatment device.

[0309] In some embodiments, autocorrelation (i.e., inverse Fourier transform of the power spectrum) can be implemented instead of cepstral analysis.

[0310] 5.9 Aspects of this technology

[0311] The following descriptive paragraphs explain other embodiments of the foregoing technology:

[0312] Example 1. A method for determining cardiac output, comprising:

[0313] Sound measurements are determined by at least one sound sensor within the catheter connected to the user's respiratory therapy device;

[0314] The concentration of carbon dioxide within the catheter is determined, at least in part, based on acoustic measurements; and

[0315] The user's cardiac output is determined at least in part based on carbon dioxide concentration.

[0316] Example 2. The method as described in Example 1, wherein the catheter is an airway of a respiratory therapy device.

[0317] Example 3. The method as described in Example 1, wherein determining the carbon dioxide concentration includes calculating a Fourier transform from a data sample representing a sound metric.

[0318] Example 4. The method as described in Example 3, wherein determining the carbon dioxide concentration further includes calculating the logarithm of the Fourier transform from a data sample representing a sound metric.

[0319] Example 5. The method as described in Example 4, wherein determining the carbon dioxide concentration further includes calculating the inverse logarithmic transform of the Fourier transform from a data sample representing a sound metric.

[0320] Example 6. The method as described in Example 5, wherein determining the carbon dioxide concentration further comprises calculating the difference between (a) the inverse logarithmic transform of the Fourier transform of a data sample representing a sound metric and (b) the inverse logarithmic transform of the Fourier transform of a data sample representing a baseline carbon dioxide concentration in the catheter.

[0321] Example 7. The method as described in Example 1 further includes:

[0322] Sound is generated using a sound source inside the catheter.

[0323] The determination of the sound metric is based on the detection of sound from a sound source by at least one sound sensor.

[0324] Example 8. The method as described in Example 7, wherein the sound source is a flow generator within a respiratory therapy device.

[0325] Example 9. The method as described in Example 7, wherein the sound source is a loudspeaker inside the duct.

[0326] Example 10. The method as described in Example 1, wherein the at least one sound sensor is a microphone, and the conduit is the airway of a respiratory therapy device, with the microphone connected to the airway.

[0327] Example 11. The method as described in Example 1 further includes:

[0328] Determine one or more environmental parameters of the respiratory therapy device; and

[0329] One or more environmental parameters are considered when determining carbon dioxide concentration.

[0330] Example 12. The method as described in Example 11, wherein one or more environmental parameters include air temperature, ambient pressure, ambient carbon dioxide concentration, background noise, or a combination thereof.

[0331] Example 13. The method as described in Example 12, wherein background noise is detected by at least one sound sensor.

[0332] Example 14. The method as described in Example 12, wherein background noise is detected by a second sound sensor, which is different from at least one sound sensor that determines the sound metric.

[0333] Example 15. The method as described in Example 1, wherein at least one sound sensor includes a first sound sensor and a second sound sensor, the first sound sensor being located in a different position in the conduit than the second sound sensor.

[0334] Example 16. The method as described in Example 15, wherein the sound measurement includes the time of flight between the first sound sensor and the second sound sensor.

[0335] Example 17. The method as described in Example 15, further comprising increasing the signal-to-noise ratio of the sound quanta based at least in part on the sound quanta of the first sound sensor and the second sound sensor.

[0336] Example 18. The method as described in Example 1, wherein the determination of the carbon dioxide concentration in the conduit is based at least in part on the cepstrum of a data sample representing a sound metric.

[0337] Example 19. The method as described in Example 1, wherein the determination of the user's cardiac output is based at least in part on a modified Fick method, which is based at least in part on carbon dioxide concentration.

[0338] Example 20. The method as described in Example 1, further comprising:

[0339] The determination of carbon dioxide concentration and cardiac output was repeated multiple times during a single process; and

[0340] The carbon dioxide concentration, cardiac output, or combination thereof of the individual process are determined at least in part based on the carbon dioxide concentration, cardiac output, or combination thereof within the threshold range of the process.

[0341] Example 21. The method as described in Example 1, further comprising:

[0342] During the process, carbon dioxide concentration and cardiac output were repeatedly determined; and

[0343] Determine the trend of cardiac output during the process.

[0344] Example 22. The method as described in Example 1, further comprising:

[0345] Determine the background carbon dioxide level at the location of the respiratory therapy device.

[0346] The determination of a user's cardiac output is based at least in part on the background carbon dioxide level at the location.

[0347] Example 23. The method as described in Example 22 further includes:

[0348] Based on the trend, the core output volume is deteriorating; and

[0349] Intervention was deemed necessary based on the deterioration of cardiac output.

[0350] Example 24. The method as described in Example 1, wherein the carbon dioxide concentration within the catheter is determined based on the analysis of the catheter's standing waves and harmonics.

[0351] Example 25. A system for determining cardiac output, comprising:

[0352] A respiratory therapy device having a catheter that connects to the user;

[0353] At least one sensor configured to detect acoustic measurements within the catheter;

[0354] Memory that stores machine-readable instructions; and

[0355] A control system comprising one or more processors configured to execute the machine-readable instructions, to:

[0356] The concentration of carbon dioxide within the catheter is determined, at least in part, based on acoustic measurements; and

[0357] The user's cardiac output is determined at least in part based on carbon dioxide concentration.

[0358] Example 26. The system as described in Example 25, wherein the catheter is the airway of a respiratory therapy device.

[0359] Example 27. A system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to determine carbon dioxide concentration based on a Fourier transform calculated from data samples representing sound quanta.

[0360] Example 28. A system as described in Example 27, wherein one or more processors are configured to execute machine-readable instructions to determine carbon dioxide concentration based on calculating the logarithm of the Fourier transform from data samples representing sound quanta.

[0361] Example 29. A system as described in Example 28, wherein one or more processors are configured to execute machine-readable instructions to determine carbon dioxide concentration based on the inverse logarithmic transform of the Fourier transform calculated from data samples representing sound quanta.

[0362] Example 30. The system as described in Example 29, wherein one or more processors are configured to execute machine-readable instructions to determine carbon dioxide concentration based on calculating the difference between (a) the inverse logarithmic transform of the Fourier transform of data samples representing sound metric and (b) the inverse logarithmic transform of the Fourier transform of data samples representing baseline carbon dioxide concentration in the duct.

[0363] Example 31. The system as described in Example 25 further includes:

[0364] A sound source, configured to generate sound within the duct.

[0365] One or more processors are configured to execute machine-readable instructions to determine a sound metric based on sound detected from a sound source by at least one sound sensor.

[0366] Example 32. The system as described in Example 31, wherein the sound source is a flow generator within a respiratory therapy device.

[0367] Example 33. The system as described in Example 31, wherein the sound source is a loudspeaker inside the duct.

[0368] Example 34. The system as described in Example 25, wherein at least one sound sensor is a microphone, and the conduit is the airway of the respiratory therapy device, with the microphone connected to the airway.

[0369] Example 35. A system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to:

[0370] Determine one or more environmental parameters of the respiratory therapy device; and

[0371] One or more environmental parameters are considered when determining carbon dioxide concentration.

[0372] Example 36. The system as described in Example 35, wherein one or more environmental parameters include air temperature, ambient pressure, ambient carbon dioxide concentration, background noise, or a combination thereof.

[0373] Example 37. The system as described in Example 36, wherein background noise is detected by at least one sound sensor.

[0374] Example 38. The system as described in Example 36, wherein background noise is detected by a second sound sensor, which is different from at least one sound sensor configured to determine the sound metric.

[0375] Example 39. The system as described in Example 25, wherein at least one sound sensor includes a first sound sensor and a second sound sensor, the first sound sensor being located in a different position in the conduit than the second sound sensor.

[0376] Example 40. The system as described in Example 39, wherein the sound measurement includes the time of flight between the first sound sensor and the second sound sensor.

[0377] Example 41. The system as described in Example 39, wherein one or more processors are configured to execute machine-readable instructions to increase the signal-to-noise ratio of the sound quanta, at least in part, based on the sound quanta of the first sound sensor and the second sound sensor.

[0378] Example 42. The system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to determine the carbon dioxide concentration within the duct based at least in part on the cepstral of a data sample representing a sound metric.

[0379] Example 43. The system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to determine a user’s cardiac output based at least in part on a modified Fick method based at least in part on carbon dioxide concentration.

[0380] Example 44. A system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to:

[0381] The determination of carbon dioxide concentration and cardiac output was repeated multiple times during a single process; and

[0382] The carbon dioxide concentration, cardiac output, or combination thereof of the individual process are determined at least in part based on the carbon dioxide concentration, cardiac output, or combination thereof within the threshold range of the process.

[0383] Example 45. A system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to:

[0384] During the process, carbon dioxide concentration and cardiac output were repeatedly determined; and

[0385] Determine the trend of cardiac output during the process.

[0386] Example 46. A system as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to:

[0387] Determine the background carbon dioxide level at the location of the respiratory therapy device.

[0388] The determination of a user's cardiac output is based at least in part on the background carbon dioxide level at the location.

[0389] Example 47. A system as described in Example 46, wherein one or more processors are configured to execute machine-readable instructions to:

[0390] Based on the trend, the core output volume is deteriorating; and

[0391] Whether intervention is needed is determined based on the deterioration of cardiac output.

[0392] Example 48. The method as described in Example 25, wherein one or more processors are configured to execute machine-readable instructions to determine the carbon dioxide concentration in the catheter based on analysis of standing waves and harmonics within the catheter.

[0393] 5.10 Glossary

[0394] To achieve the purposes of this technical disclosure, one or more of the following definitions may be applied in certain forms of this technology. Alternative definitions may be applied in other forms of this technology.

[0395] 5.10.1 General Rules

[0396] Air: In some forms of this technology, air may be considered to mean atmospheric air, and in other forms of this technology, air may be considered to mean some other combination of breathable gases, such as oxygen-rich atmospheric air.

[0397] Environment: In some forms of this technology, the term environment may have the following meanings: (i) outside the respiratory therapy system or the patient, and (ii) directly surrounding the respiratory therapy system or the patient.

[0398] For example, the ambient humidity relative to a humidifier can be the humidity of the air directly surrounding the humidifier, such as the humidity inside the patient's sleeping room. This ambient humidity can differ from the humidity outside the patient's sleeping room.

[0399] Automated positive airway pressure (APAP) therapy: CPAP therapy in which the treatment pressure is automatically adjusted between a minimum and a maximum, for example, varying with each breath, depending on the presence of an indication of an SBD event.

[0400] Continuous positive airway pressure (CPAP) therapy: In this therapy, the treatment pressure can be approximately constant throughout the patient's respiratory cycle. In some forms, the pressure at the airway inlet will be slightly higher during expiration and slightly lower during inspiration. In other forms, the pressure will vary between different respiratory cycles, for example, increasing in response to an indication of partial upper airway obstruction and decreasing in response to the absence of such an indication.

[0401] Flow rate: The volume (or mass) of air delivered per unit time. Flow rate can refer to an instantaneous quantity. In some cases, the reference to flow rate will be a scalar quantity, that is, a quantity that only has a magnitude. In other cases, the reference to flow rate will be a vector quantity, that is, a quantity that has both magnitude and direction. Flow rate can be given by the symbol Q. 'Flow rate' is sometimes simply abbreviated as 'flow' or 'airflow'.

[0402] Leakage: The word "leakage" is considered to refer to undesirable airflow. In one example, leakage may occur due to an incomplete seal between the mask and the patient's face. In another example, leakage into the surrounding environment may occur in a rotating bend.

[0403] Patient: A person, regardless of whether they have a respiratory illness.

[0404] Pressure: Force per unit area. Pressure can be expressed in units of area, including cmH2O and gf / cm². 2 1000 Pascals. 1 cmH2O equals 1 g-f / cm³ 2 It is approximately 0.98 hectopascals. In this specification, unless otherwise stated, pressure is given in cmH2O.

[0405] Respiratory pressure therapy (RPT): Applying air supply to the airway inlet at a therapeutic pressure that is typically positive relative to the atmosphere.

[0406] Sealing: can be the noun form of a structure (sealant) or the verb form of the effect (seal). Two elements can be constructed and / or arranged to 'seal' or to achieve 'sealing' between them, without the need for a separate 'sealing' element itself.

[0407] 5.10.2 Patient Interface

[0408] Inflation chamber: The mask inflation chamber is considered to refer to the portion of the patient interface having walls that at least partially enclose a volume of space, which, during use, contains air pressurized therein to above atmospheric pressure. A housing may form part of the wall of the mask inflation chamber.

[0409] Shell: A shell is considered to mean a curved and relatively thin structure with bendable, stretchable, and compressible stiffness. For example, the curved structural walls of a face mask can be a shell. In some forms, the shell can be multifaceted. In some forms, the shell can be airtight. In some forms, the shell may not be airtight.

[0410] Ventilation port: (noun): A structure that allows airflow from inside the mask or tubing to ambient air, for example, to effectively flush out exhaled gases. For example, clinically effective flushing can involve a flow rate of approximately 10 liters per minute to approximately 100 liters per minute, depending on the mask design and treatment pressure.

[0411] 5.11 Other Remarks

[0412] This patent document contains a portion of copyrighted material. The copyright holder does not object to the reproduction of these patent documents or patent disclosures by any person in the form they appear in the patent office documents or records, but otherwise reserves all copyright rights.

[0413] Unless explicitly stated in the context and a numerical range is provided, it should be understood that every intermediate value between the upper and lower limits of the range, up to one-tenth of the lower limit unit, and any other value or intermediate value within the range are broadly included within this technique. The upper and lower limits of these intermediate ranges may be included independently within the intermediate range and within the scope of this technique, but are subject to any explicitly excluded boundaries within the range. Where a range includes one or both of the limit values, this technique also includes ranges that exclude any one or both of those included limit values.

[0414] Furthermore, where one or more values ​​described herein are implemented as part of this technique, it should be understood that such values ​​may be approximate unless otherwise stated, and such values ​​may be used to the extent permitted or required by the practical implementation of the technique for any appropriate valid digits.

[0415] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. While any methods and materials similar to or equivalent to those described herein may also be used in the practice or testing of this technology, a limited number of exemplary methods and materials are described herein.

[0416] When a particular material is determined to be used for constructing a component, obvious alternative materials with similar properties may be used as substitutes. Furthermore, unless otherwise stated, any and all components described herein are to be understood as being capable of being manufactured and therefore can be manufactured together or separately.

[0417] It must be noted that, unless the context clearly specifies otherwise, the singular forms “a,” “an,” and “the” used herein and in the appended claims include their plural equivalents.

[0418] As used herein, the term "about" refers to a quantity that varies by up to 30%, preferably up to 20%, and more preferably up to 10% relative to a reference quantity. The use of the word "about" to limit a number is merely a clear indication that the number should not be interpreted as a precise value.

[0419] All publications mentioned herein are incorporated herein by reference in their entirety to disclose and describe the methods and / or materials that are the subject of those publications. The publications discussed herein are provided solely for their publication prior to the filing date of this application. Nothing herein should be construed as an admission that the present invention is not entitled to priority of those publications due to prior art. Furthermore, the publication dates provided may differ from the actual publication dates and may require separate verification.

[0420] The terms “comprises” and “comprising” should be understood as referring to each element, component, or step in a non-exclusive manner, indicating the marked element, component, or step that may be present or utilized, or a combination with other unmarked elements, components, or steps. Therefore, throughout this specification, unless the context otherwise requires, the words “comprise,” “comprises,” and “comprising” will be understood to imply inclusion of the stated steps or elements or groups of steps or elements, but do not exclude any other steps or elements or groups of steps or elements. Any of the following terms, such as “including,” “which includes,” or “that includes” as used herein, are also open-ended terms, meaning that at least the element / feature following the term is included, but other elements / features are not excluded. Therefore, “including” is synonymous with “comprising” and means “including.”

[0421] The various methods or processes outlined in this article can be encoded as software that can be executed on one or more processors employing any of a variety of operating systems or platforms. Furthermore, such software can be written using any of a variety of suitable programming languages ​​and / or programming or scripting tools, and can also be compiled into executable machine language code or intermediate code that executes on a framework or virtual machine.

[0422] In this regard, various inventive concepts can be embodied in a processor-readable medium or computer-readable storage medium (or multiple such storage media) encoded with one or more program or processor control instructions (e.g., circuit configurations in a computer memory, one or more floppy disks, compact disks, optical disks, magnetic tapes, flash memory, field-programmable gate arrays or other semiconductor devices, or other non-transient media or tangible computer storage media), wherein the program or processor control instructions, when executed on one or more computers or other processors, perform methods implementing various embodiments of the above-described technology. One or more computer-readable media may be transportable, such that one or more programs stored thereon can be loaded onto one or more different computers or other processors to implement various aspects of the present technology as described above.

[0423] The terms “program” or “software” are used herein in a general sense to refer to any type of computer code or set of computer-executable instructions that can be used to program a computer or other processor to implement the various aspects of the embodiments discussed above. Additionally, it should be understood that, according to one aspect, one or more computer programs that perform the methods of this technology when executed do not need to reside on a single computer or processor, but can be distributed in a modular manner among multiple different computers or processors to implement the various aspects of this technology. For example, some versions of this technology may include a server that can access any computer-readable or processor-readable medium described herein. The server may be configured to receive, via a network such as a communications network, the Internet, or the Internet, a request to download processor control instructions or processor-executable instructions of the medium to an electronic device such as a smartphone or smart speaker. Thus, the electronic device may also include a medium that executes the instructions of the medium. Similarly, this technology may be implemented as a method of a server accessing any medium described herein. The method may include receiving at the server a request to download processor-executable instructions of the medium to an electronic device via a network; and, in response to the request, sending instructions of the medium to the electronic device. Optionally, the server may access the medium to execute the instructions of the medium.

[0424] Computer-executable instructions can take many forms, such as program modules, and can be executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. Typically, the functionality of a program module can be combined or distributed as needed in various implementations.

[0425] Furthermore, data structures can be stored in any suitable form on a computer-readable medium. For simplicity, a data structure can be shown as having fields related by position within the data structure. This relationship can also be implemented by allocating memory in a computer-readable medium to the fields, with locations that convey the relationship between the fields. However, any suitable mechanism can be used to establish relationships between information in the fields of a data structure, including by using pointers, labels, or other mechanisms that establish relationships between data elements.

[0426] Although the techniques described herein have been illustrated with reference to specific examples, it should be understood that these examples are merely illustrative of the principles and applications of the techniques. For instance, while acoustic generators and acoustic monitoring techniques are described in specific examples relating to the use and components of RPT devices, it should be understood that such acoustic generators and acoustic monitoring techniques can be implemented similarly to components of any respiratory therapy (RT) device, such as a high-flow-rate therapy (HFT) device that provides controlled airflow at therapeutic flow levels via a patient interface. Thus, an HFT device is similar to a pressure-controlled RPT device, but is configured with a controller suitable for flow control. In such an example, the acoustic generator can be configured to measure gas characteristics associated with high-flow-rate therapy generated by the HFT device and can be integrated to sample airflow in the patient circuit, its catheter connector, and / or patient interface of the HFT device. Thus, the HFT device may optionally include an acoustic receiver, as well as the processing techniques described herein for acoustic analysis, for receiving acoustic / sound signals generated by the acoustic generator implementing the HFT device.

[0427] In some cases, terms and symbols may imply specific details not required for the practice of this technique. For example, although the terms "first" and "second" may be used, unless otherwise stated, they are not intended to indicate an arbitrary order but are used to distinguish different elements. Furthermore, although process steps in a method may be described or illustrated in sequence, such order is not required. Those skilled in the art will recognize that such order can be modified and / or aspects can be performed simultaneously or even concurrently.

[0428] Therefore, it should be understood that many modifications can be made to the illustrative examples and other arrangements can be designed without departing from the spirit and scope of this technology.

[0429] 5.12 List of Reference Symbols

[0430]

[0431]

[0432]

[0433] 5.13 References cited

[0434] [1] Partial CO2 rebreathing Fick technique for noninvasive measurement of cardiac output. Bailey, PL; Haryadi, DG; Orr, JA.; Westenskow, DRAnesthesia&Analgesia, April 1998, Vol.86Issue 4S, page 53ff.

Claims

1. A computer-readable storage medium storing machine-readable instructions that, when executed by one or more processors, perform a method for generating patient and / or system status indications using a respiratory therapy system, the respiratory therapy system being configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to a patient interface, the method comprising: Process the audio signal from the microphone representing the sound in the air loop to obtain cepstral data; Based on the acoustic signatures of the cepstral data, a time-series data structure is generated including a time series of delay estimates, wherein each of the acoustic signatures represents a reflection of sound from the patient interface along the air loop, and wherein each delay estimate of the time-series data structure is a delay estimate from a different time window and a different one of the acoustic signatures of the cepstral data; Analyze the changes in the time series of the delay estimate of the time series data structure; as well as One or more output indicators are generated based on the changes, the one or more output indicators relating to the patient and / or system status.

2. The computer-readable storage medium of claim 1, wherein generating the time series comprises: Separate the acoustic signature from the cepstral data; The delay of the acoustic signature is estimated based on the time series of the aforementioned delay estimate; as well as Repeat the separation and estimation process.

3. The computer-readable storage medium of any one of claims 1 to 2, wherein the analysis includes filtering the time series of the delay estimate to allow frequencies within the respiratory rate band to pass through.

4. The computer-readable storage medium of any one of claims 1 to 2, wherein the analysis further comprises converting the time series of the delay estimate into an indication of the carbon dioxide concentration in the air circuit.

5. The computer-readable storage medium of any one of claims 1 to 2, wherein the one or more output indications include an indication of the patient's end-tidal carbon dioxide concentration (EtCO2).

6. The computer-readable storage medium of claim 5, wherein the method further comprises adjusting parameters of the respiratory therapy system based on EtCO2 indication.

7. The computer-readable storage medium of any one of claims 1 to 2, wherein the one or more output indicators include an estimate of the patient's cardiac output.

8. The computer-readable storage medium of claim 7, wherein the method further comprises applying a modified Fick technique function and measuring the change in an indication of EtCO2 generated over the time series of the delay estimate to generate an estimate of the cardiac output.

9. The computer-readable storage medium of claim 7, wherein the method further comprises repeating the analysis to generate multiple estimates of the patient's cardiac output.

10. The computer-readable storage medium of claim 9, wherein the method further comprises determining a trend among multiple estimates of the patient's cardiac output.

11. The computer-readable storage medium of claim 10, wherein the method further comprises taking action based on a determined trend among the plurality of estimates.

12. The computer-readable storage medium of claim 11, wherein the taking action includes generating output communication and / or output on the display.

13. The computer-readable storage medium of claim 4, wherein the analysis further comprises: Determine one or more environmental parameters of the respiratory therapy system; as well as The one or more environmental parameters are corrected during the determination of carbon dioxide concentration.

14. The computer-readable storage medium of claim 13, wherein the one or more environmental parameters include air temperature, ambient pressure, ambient carbon dioxide concentration, background noise, or a combination thereof.

15. The computer-readable storage medium of claim 14, wherein the background noise is generated by a different sound sensor than the sound sensor that generates the sound signal.

16. The computer-readable storage medium of any one of claims 1 to 2, wherein the analysis includes removing respiratory rate band variations from the time series of the delay estimate to obtain a time series of non-respiratory delay estimates.

17. The computer-readable storage medium of claim 16, wherein the one or more output indicators include an indication of the replacement status of components of the air circuit and / or the patient interface.

18. The computer-readable storage medium of claim 16, wherein the analysis further comprises mapping the time series of the non-respiratory-related delay estimate to a time series of values ​​for the length of the air loop.

19. The computer-readable storage medium of claim 18, wherein the analysis further comprises determining whether an increase in the length of the air circuit during a plurality of treatment sessions is greater than a threshold.

20. The computer-readable storage medium of claim 18, wherein the analysis further comprises determining the variability of the length of the air circuit during a respiratory therapy procedure.

21. The computer-readable storage medium of any one of claims 1 to 2, wherein the processing includes removing background noise from the environment of the respiratory therapy system from the sound signal.

22. The computer-readable storage medium of any one of claims 1 to 2, wherein the one or more output indicators further comprise: (a) A control signal used to regulate the therapeutic output of a therapeutic device; and / or (b) Output of communication or display.

23. An apparatus for generating patient and / or system status indications using a respiratory therapy system, the respiratory therapy system being configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to a patient interface, the apparatus comprising: A sensor configured to generate an acoustic signal representing sound in the air circuit; as well as A controller comprising one or more processors and memory, wherein the one or more processors are configured by program instructions stored in the memory, wherein the controller is configured to access a computer-readable storage medium according to any one of claims 1 to 22 to perform a method.

24. The apparatus of claim 23, further comprising a blower, wherein the controller is configured to control the operation of the blower.

25. An apparatus for generating patient and / or system status indications using a respiratory therapy system, the respiratory therapy system being configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to a patient interface, the apparatus comprising: A sensor configured to generate an acoustic signal representing sound in the air circuit; as well as The controller is configured as follows: Process the sound signal representing the sound in the air circuit to obtain cepstral data; A time-series data structure including delay estimates is generated based on the acoustic signatures in the cepstral data, wherein each of the acoustic signatures represents a reflection of sound from the patient interface along the air loop, and wherein each delay estimate of the time-series data structure is a delay estimate from a different time window and a different one of the acoustic signatures in the cepstral data. Analyze the changes in the time series of the delay estimate in the time series of the time series data structure; as well as One or more output indicators are generated based on the changes, the one or more output indicators relating to the patient and / or system status.

26. The device of claim 25, further comprising a second sensor configured to generate an acoustic signal representing background noise in the environment of the respiratory therapy system.

27. The device of claim 26, wherein the controller is further configured to remove background noise from the environment of the respiratory therapy system from a generated sound signal representing sound in the air circuit using a generated sound signal representing background noise in the environment of the respiratory therapy system.

28. The device of any one of claims 25 to 27, wherein, in order to generate the time series, the controller is configured to: Separate the acoustic signature from the cepstral data; Estimate the delay of the acoustic signature based on the time series of the delay estimation; and Repeat the separation and the estimation.

29. The device of any one of claims 25 to 27, wherein, in order to analyze variations, the controller is configured to filter the time series of the delay estimate to allow frequencies within the respiratory rate band to pass through.

30. The device of any one of claims 25 to 27, wherein, in order to analyze the changes, the controller is configured to convert the time series of the delay estimate into an indication of the carbon dioxide concentration in the air loop.

31. The device of any one of claims 25 to 27, wherein the one or more output indications include an indication of the patient's end-tidal carbon dioxide concentration (EtCO2).

32. The device of claim 31, wherein the controller is further configured to adjust the parameters of the respiratory therapy system based on an indication of EtCO2.

33. The device of any one of claims 25 to 27, wherein the one or more output indicators include an estimate of the patient's cardiac output.

34. The device of claim 33, wherein the controller is configured to apply a modified Fick technique function and measure changes in the indication of EtCO2 generated with the time series of the delay estimation to generate an estimate of the cardiac output.

35. The device of claim 33, wherein the controller is configured to repeat the analysis to generate multiple estimates of the patient's cardiac output.

36. The device of claim 35, wherein the controller is further configured to determine a trend among the plurality of estimates of the patient's cardiac output.

37. The device of claim 36, wherein the controller is further configured to take action based on a determined trend among the plurality of estimates.

38. The device of claim 37, wherein the action includes generating output communication and / or output on the display.

39. The device of any one of claims 25 to 27, wherein, in order to analyze variations, the controller is configured to remove respiratory rate band variations from the time series of the delay estimates to obtain a time series of non-respiratory delay estimates.

40. The device of claim 39, wherein the one or more output indicators include an indication of the replacement status of components of the air circuit and / or the patient interface.

41. The device of claim 39, wherein, in order to analyze variations, the controller is configured to map the time series of the non-respiratory-related delay estimate to a time series of the values ​​of the length of the air loop.

42. The device of claim 41, wherein, in order to analyze the changes, the controller is configured to determine whether an increase in the length of the air circuit during a plurality of treatment procedures is greater than a threshold.

43. The device of claim 41, wherein, in order to analyze variations, the controller is configured to determine the variability of the length of the air circuit during the respiratory therapy process.

44. The device of any one of claims 25 to 27, wherein the one or more output indicators further comprise: (a) A control signal used to regulate the therapeutic output of a therapeutic device; and / or (b) Output of communication or display.

45. An apparatus comprising: A tool for generating an acoustic signal representing sound in an air circuit of a respiratory therapy system, the respiratory therapy system including a flow generator configured to generate a pressurized air supply from an outlet along the air circuit to a patient interface; A tool for processing sound signals representing sound in the air circuit to obtain cepstral data; A tool for generating a time-series data structure including delay estimates based on acoustic signatures in the cepstral data, wherein each of the acoustic signatures represents a reflection of sound from the patient interface along the air loop, and wherein each delay estimate of the time-series data structure is a delay estimate from a different time window and a different one of the acoustic signatures in the cepstral data; A tool for analyzing the time series data structure for delay estimation of time series changes; as well as A tool for generating one or more output indicators based on the changes, the one or more output indicators relating to patient and / or system status.

46. ​​A computer-readable storage medium storing machine-readable instructions that, when executed by one or more processors, perform a method for generating a status indication regarding a patient interface associated with a respiratory therapy system configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to the patient interface, the method comprising: Process the sound signal representing the sound in the air circuit to obtain cepstral data; The acoustic signature is separated from the cepstral data, the acoustic signature representing the reflection of sound from the patient interface along the air loop; Estimate the internal delay of the acoustic signature, wherein the internal delay is the delay between a first portion and a second portion of the acoustic signature, the first and second portions representing reflections from the corresponding first and second portions of the patient interface separated from the mask tube; Repeat the aforementioned processing, separation, and estimation to generate a time-series data structure that includes the internal delay estimation of the time series; Analyze the time series of the internal delay estimation of the time series data structure; as well as Based on the analysis, one or more output indicators are generated, which are related to the patient interface state.

47. The computer-readable storage medium of claim 46, wherein the analysis includes filtering the time series of the internal delay estimate to allow frequencies within the respiratory rate band to pass through.

48. The computer-readable storage medium of claim 47, wherein the analysis further comprises analyzing a time series of filtered internal delay estimates to generate an indication of the carbon dioxide concentration in the mask tube.

49. The computer-readable storage medium of any one of claims 46 to 48, wherein the analysis includes removing respiratory rate band variations from the time series of the internal delay estimation to obtain a time series of non-respiratory internal delay estimation.

50. The computer-readable storage medium of claim 49, wherein the analysis further comprises mapping the time series of the non-breathing-related internal delay estimate to a time series of values ​​for the length of the mask tube.

51. The computer-readable storage medium of claim 50, wherein the analysis further comprises determining whether an increase in the length of the mask tube during multiple treatments is greater than a threshold.

52. The computer-readable storage medium of claim 50, wherein the analysis further comprises determining the variability of the length of the mask tube during respiratory therapy.

53. An apparatus for generating status indications regarding a patient interface associated with a respiratory therapy system configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to the patient interface, the apparatus comprising: A sensor configured to generate an acoustic signal representing sound in the air circuit; as well as A controller comprising one or more processors and memory, wherein the one or more processors are configured by program instructions stored in the memory, wherein the controller is configured to access a computer-readable storage medium according to any one of claims 46 to 48 to perform a method.

54. An apparatus for generating status indications regarding a patient interface, the patient interface being connected to a respiratory therapy system configured to deliver respiratory therapy to a patient, the respiratory therapy system including a flow generator configured to generate a pressurized air supply along an air loop to the patient interface, the apparatus comprising: A sensor configured to generate an acoustic signal representing sound in the air circuit; as well as The controller is configured as follows: The sound signal representing sound is processed in the air circuit to obtain cepstral data; The acoustic signature is separated from the cepstral data, the acoustic signature representing the reflection of sound from the patient interface along the air loop; Estimate the internal delay of the acoustic signature, wherein the internal delay is the delay between a first portion and a second portion of the acoustic signature, the first and second portions representing reflections from the corresponding first and second portions of the patient interface separated from the mask tube; Repeat the aforementioned processing, separation, and estimation to generate a time-series data structure that includes the time series of the internal delay estimates from the acoustic signature; Analyze the time series of the internal delay estimation of the time series data structure; as well as Based on the analysis, one or more output indicators are generated, which are related to the patient interface state.

55. The device of claim 54, wherein, in order to analyze the time series, the controller is configured to filter the time series of the internal delay estimation to allow frequencies within the respiratory rate band to pass through.

56. The device of claim 55, wherein, in order to analyze the time series, the controller is further configured to analyze the time series of the filtered internal delay estimate to generate an indication of the carbon dioxide concentration in the mask tube.

57. The device of any one of claims 54 to 56, wherein, in order to analyze the time series, the controller is configured to remove respiratory rate band variations from the time series of the internal delay estimates to obtain a time series of non-respiratory internal delay estimates.

58. The device of claim 57, wherein, in order to analyze the time series, the controller is further configured to map the time series of the non-breathing-related internal delay estimation to a time series of the length values ​​of the mask tube.

59. The device of claim 58, wherein, in order to analyze the time series, the controller is further configured to determine whether the increase in the length of the mask tube during multiple treatment processes is greater than a threshold.

60. The device of claim 59, wherein, in order to analyze the time series, the controller is further configured to determine the variability of the length of the mask tube during the respiratory therapy process.

61. An apparatus comprising: A tool for generating an acoustic signal representing sound in an air circuit of a respiratory therapy system, the respiratory therapy system including a flow generator configured to generate a pressurized air supply from an outlet along the air circuit to a patient interface; A tool for processing sound signals representing sound in the air circuit to obtain cepstral data; A tool for separating an acoustic signature from the cepstral spectrum, the acoustic signature representing the reflection of sound from the patient interface along the air circuit; A tool for estimating the internal delay of the acoustic signature, wherein the internal delay is the delay between a first portion and a second portion of the acoustic signature, the first and second portions representing reflections from the corresponding first and second portions of the patient interface separated from the mask tube; A tool for repeating the processing, separation, and estimation to generate a time-series data structure that includes the time-series internal delay estimates from the acoustic signature; Tools for analyzing the time series data structure for estimating the internal delay of the time series data; as well as A tool for generating one or more output indicators based on the analysis, the one or more output indicators relating to the patient interface state.

62. A respiratory therapy system for delivering respiratory therapy to a patient, the system comprising: A flow generator configured to produce a pressurized air supply; An air circuit, connected to the flow generator, is provided to deliver the pressurized air supply to the patient interface; as well as Device for generating patient and / or system status indications using a respiratory therapy system, said device being the device as claimed in any one of claims 25 to 27.

63. A respiratory therapy system for delivering respiratory therapy to a patient, the system comprising: A flow generator configured to produce a pressurized air supply; An air circuit, connected to the flow generator, is provided to deliver the pressurized air supply to the patient interface; as well as Device for generating status indications regarding the patient interface, the device being the device as described in any one of claims 54 to 56.

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