Pre-disease detection system and method

Abstract

The system includes a respiratory treatment system, a memory, and a control system. The respiratory treatment system includes a respiratory treatment device that supplies pressurized air and a user interface coupled to the respiratory treatment device via a conduit. The user interface engages with the individual and serves to direct the pressurized air to the individual's airway. The system is used to direct an acoustic signal to the individual's airway via the conduit and the user interface, generate acoustic data representing one or more reflections of the acoustic signal caused by a portion of the individual's airway, an obstruction in the individual's airway, or both, analyze the acoustic data to determine values ​​of parameters associated with the individual's airway, and perform an action based on the determined values ​​of the parameters.

Description

[Technical Field]

[0001] Cross-reference of related applications This application claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 072896, filed on 31 August 2020, which is incorporated herein by reference in its entirety.

[0002] This disclosure relates to systems and methods for monitoring an individual's airway in general, and more specifically, to systems and methods for detecting and identifying respiratory diseases prior to physical symptoms by monitoring an individual's airway. [Background technology]

[0003] Many people suffer from sleep-related and / or respiratory disorders such as periodic limb movement disorder (PLMD), restless legs syndrome (RLS), obstructive sleep apnea (OSA), central sleep apnea (CSA), and other types of apnea such as mixed apnea and hypopnea, as well as respiratory effort-related awakening (RERA), Cheyne-Stokes respiration (CSR), respiratory failure, obesity hypoventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disorders (NMD), rapid eye movement (REM) behavior disorder (also known as RBD), acting out dreams (DEB), hypertension, diabetes, stroke, insomnia, and chest wall disorders. These people also suffer from other respiratory diseases. Often, respiratory diseases cannot be detected and identified until an individual presents with externally detectable physical symptoms such as cough, feeling of obstruction, or fever. Therefore, it is advantageous to be able to accurately monitor an individual's airway and detect and identify potential respiratory diseases before they cause externally detectable physical symptoms. This disclosure relates to systems, devices, and methods that can more easily monitor an individual's airway. [Overview of the Initiative] [Means for solving the problem]

[0004] According to some implementations of the present disclosure, a method for monitoring a personal airway includes guiding an acoustic signal to the personal airway. The method further includes generating acoustic data representing one or more reflections of the acoustic signal. The reflections are caused by (i) a part of the personal airway, (ii) an obstacle within the personal airway, or (iii) both (i) and (ii). The method further includes analyzing the acoustic data to determine a value of a parameter related to the personal airway. The method further includes performing an operation based on the determined value of the parameter.

[0005] According to some implementations of the present disclosure, a system includes a respiratory therapy system, a memory storing machine-readable instructions, and a control system. The respiratory therapy system includes a respiratory therapy device and a user interface. The respiratory therapy device is configured to supply pressurized air. The user interface is connected to the respiratory therapy device via a conduit and is configured to engage with the individual and assist in guiding the supplied pressurized air to the personal airway. The control system includes one or more processors configured to execute the machine-readable instructions to guide an acoustic signal to the personal airway via the conduit and the user interface, generate acoustic data representing one or more reflections of the acoustic signal caused by (i) a part of the personal airway, (ii) an obstacle within the personal airway, or (iii) both (i) and (ii), analyze the acoustic data to determine a value of a parameter related to the personal airway, and perform an operation based on the determined value of the parameter.

[0006] The above summary is not intended to represent every implementation or every aspect of the present disclosure. Further features and advantages of the present disclosure will become apparent from the following detailed description and the drawings.

Brief Description of the Drawings

[0007] [Figure 1]A functional block diagram of a system for monitoring a sleep session, according to some implementations of the present disclosure. [Figure 2] A perspective view of the system of FIG. 1, a user of the system, and a co-sleeper of the user, according to some implementations of the present disclosure. [Figure 3] An exemplary timeline of a sleep session, according to some implementations of the present disclosure. [Figure 4] An exemplary hypnogram related to the sleep session of FIG. 3, according to some implementations of the present disclosure. [Figure 5] A schematic diagram of a respiratory therapy system for a user, according to some implementations of the present disclosure. [Figure 6A] An exemplary cepstrum plot representing a physical obstruction in a user's airway, according to some implementations of the present disclosure. [Figure 6B] A cross-sectional view of a user interface including a microphone and a speaker for characterizing a physical obstruction in a user's airway, according to some implementations of the present disclosure. [Figure 7A] An exemplary cepstrum plot representing the structure of a user's airway, according to some implementations of the present disclosure. [Figure 7B] A cross-sectional view of a user interface including a microphone and a speaker for characterizing a user's airway, according to some implementations of the present disclosure. [Figure 8] A process flow diagram of a method for monitoring a user's airway, according to some implementations of the present disclosure.

MODE FOR CARRYING OUT THE INVENTION

[0008] While various modifications and alternative forms are possible for this disclosure, specific implementations and embodiments of this disclosure are shown as examples in the drawings and are described in detail herein. However, it should be understood that this disclosure is not intended to limit this disclosure to any particular form disclosed, but rather to encompass all modifications, equivalents, and alternatives that fall within the spirit and scope of this disclosure as defined by the appended claims.

[0009] This disclosure is described with reference to the accompanying drawings, in which the same or equivalent components are given the same reference numeral. The drawings are not drawn to scale and are provided solely for illustrative purposes of this disclosure. Several aspects of this disclosure are described below with reference to illustrative applications.

[0010] Many people suffer from sleep-disordered breathing (SDB), such as periodic limb movement disorder (PLMD), restless legs syndrome (RLS), obstructive sleep apnea (OSA), central sleep apnea (CSA), and other types of apnea such as mixed apnea and hypopnea; respiratory effort-related awakening (RERA); Cheyne-Stokes respiration (CSR); respiratory failure; obesity hypoventilation syndrome (OHS); chronic obstructive pulmonary disease (COPD); neuromuscular disorders (NMD); rapid eye movement (REM) behavior disorder (also known as RBD); dream acting out (DEB); hypertension; diabetes mellitus; stroke; insomnia; and chest wall disorders.

[0011] Obstructive sleep apnea (OSA) is a form of sleep-disordered breathing (SDB) characterized by events such as obstruction or disturbance of the upper airway during sleep, resulting from a combination of an abnormally small upper airway and a normal loss of muscle tone in the areas of the tongue, soft palate, and posterior wall of the oropharynx.

[0012] Central sleep apnea (CSA) is another form of sleep apnea that occurs when the brain temporarily stops sending signals to the muscles that control breathing. More generally, apnea generally refers to the cessation of breathing or respiratory function caused by an obstruction of air. Typically, an individual stops breathing for about 15 to 30 seconds during an obstructive sleep apnea event. Mixed sleep apnea is another form of sleep apnea that is a combination of open sleep apnea (OSA) and CSA.

[0013] Other types of apnea include hypopnea, hyperpnea, and hypercapnia. Hypopnea is generally characterized by slow or shallow breathing resulting from narrowing of the airways rather than obstruction. Hyperpnea is generally characterized by an increase in the depth and / or rate of breathing. Hypercapnia is generally characterized by a sudden or excessive increase in the amount of carbon dioxide in the bloodstream, usually resulting from insufficient breathing.

[0014] Respiratory effort-related arousal (RERA) events are typically characterized by an increase in respiratory effort lasting 10 seconds or more leading to awakening from sleep, and do not meet the criteria for apnea or hypopnea events. In 1999, the AASM Task Force defined RERA as "a series of breaths characterized by an increase in respiratory effort leading to awakening from sleep, but which do not meet the criteria for apnea or hypopnea." These events must meet both of the following criteria: 1. A pattern of gradually increasing negative intraesophageal pressure ends with a sudden change in pressure to a lower negative pressure level and awakening, and 2. The event lasts for 10 seconds or more. In 2000, a study conducted at New York University School of Medicine and published in Sleep, vol. 23, No. 6, pp. 763-771, "Non-Invasive Detection of Respiratory Effort-Related Arousals (RERAs) by a Nasal Cannula / Pressure Transducer System," demonstrated that a nasal cannula / pressure transducer system is appropriate and reliable in detecting RERAs. The RERA detector may be based on an actual flow signal derived from a respiratory therapy (e.g., PAP) device. For example, a flow restriction scale can be determined based on the flow signal. A scale of arousal can then be derived as a function of the flow restriction scale and a scale of tidal volume surge. Such methods are described in International Publication 2008 / 138040, U.S. Patent No. 9358353, U.S. Patent No. 10549053, and U.S. Patent Application Publication 2020 / 0197640, respectively, which are fully incorporated herein by reference.

[0015] Cheyne-Stokes respiration (CSR) is another form of sustained lung disease (SDB). CSR is a disorder of the patient's respiratory regulator, characterized by alternating and cyclical increases and decreases in ventilation known as the CSR cycle. CSR is characterized by repeated deoxygenation and reoxygenation of arterial blood.

[0016] Obesity hypoventilation syndrome (OHS) is defined as a combination of severe obesity and chronic hypercapnia during wakefulness, in the absence of other causes of hypoventilation. Symptoms include shortness of breath, morning headache, and excessive daytime sleepiness.

[0017] Chronic obstructive pulmonary disease (COPD) encompasses a group of lower respiratory tract diseases that share certain characteristics, such as increased resistance to air movement, prolonged expiratory phase of respiration, and loss of normal lung elasticity.

[0018] Neuromuscular diseases (NMDs) encompass a large number of illnesses and disorders that impair muscle function, either directly or indirectly through intrinsic muscle pathology. Chest wall disorders are a group of thoracic deformities that result in insufficient connection between the respiratory muscles and the rib cage.

[0019] These and other disorders are characterized by specific events that occur during an individual's sleep (e.g., snoring, apnea, hypopnea, inability to keep the lower limbs still, sleep disturbances, suffocation, increased heart rate, dyspnea, asthma attacks, epileptic interstitial episodes, seizures, or any combination thereof).

[0020] The Apnea-Hypopnea Index (AHI) is an index used to indicate the severity of sleep apnea during a sleep session. The AHI is calculated by dividing the number of apnea and / or hypopnea events experienced by the user during a sleep session by the total sleep duration in that session. These events may include, for example, pauses in breathing lasting at least 10 seconds. An AHI of less than 5 is considered normal. An AHI of 5 to less than 15 is considered mild sleep apnea. An AHI of 15 to less than 30 is considered moderate sleep apnea. An AHI of 30 or more is considered severe sleep apnea. In children, an AHI greater than 1 is considered abnormal. Sleep apnea can be considered "controlled" when the AHI is normal, or when the AHI is normal or mild. The AHI can also be used in combination with oxygen saturation to indicate the severity of obstructive sleep apnea.

[0021] Individuals who suffer from many of these disorders may also have other respiratory illnesses, such as lung disease, pneumonia, and other respiratory conditions. However, in many cases, these respiratory illnesses cannot be detected and identified until the individual presents with externally detectable physical symptoms such as cough, blockage, or fever. Therefore, it is advantageous to accurately monitor an individual's airways to detect and / or identify potential respiratory illnesses before they cause externally detectable physical symptoms.

[0022] Referring to Figure 1, several implementations of the System 100 of the present disclosure are shown. The System 100 can be used to detect and / or identify respiratory diseases before external physical symptoms appear. The System 100 includes a control system 110, a memory device 114, an electronic interface 119, one or more sensors 130, and, optionally, one or more user devices 170. In some implementations, the System 100 further includes a respiratory therapy system 120, which includes a respiratory therapy device 122.

[0023] The control system 110 includes one or more processors 112 (hereinafter, processor 112). The control system 110 is generally used to control (e.g., operate) various components of system 100 and / or to analyze data acquired and / or generated by the components of system 100. The processors 112 may be general-purpose or special-purpose processors or microprocessors. Although one processor 112 is shown in Figure 1, the control system 110 may include any appropriate number of processors (e.g., one processor, two processors, five processors, ten processors, etc.) that may reside in a single housing or be located apart from one another. One or more steps of the methods described herein and / or claimed can be performed using the control system 110 (or any other control system) or a part of the control system 110 such as a processor 112 (or any other processor or part of any other control system). The control system 110 may be coupled to and / or located inside, for example, the housing of the user device 170 and / or the housing of one or more sensors 130. The control system 110 may be centralized (within one such enclosure) or dispersed (within two or more such enclosures that are physically separate). In such an implementation configuration, which includes two or more enclosures housing the control system 110, the enclosures may be located close to and / or far apart from one another.

[0024] The storage device 114 stores machine-readable instructions that can be executed by the processor 112 of the control system 110. The storage device 114 may be any suitable computer-readable storage device or medium, such as a random access memory device or a serial access memory device, a hard drive, a solid-state drive, or a flash memory device. Although one storage device 114 is shown in Figure 1, the system 100 may include any suitable number of storage devices 114 (e.g., one, two, five, or ten storage devices). The storage devices 114 may be connected to and / or located inside the housing of the respiratory therapy device 122 of the respiratory therapy system 120, the housing of the user device 170, the housing of one or more sensors 130, or any combination thereof. Similar to the control system 110, the storage devices 114 may be centralized (in one such housing) or distributed (in two or more physically separate housings).

[0025] In some implementations, the storage device 114 stores a user profile related to the user. The user profile may include, for example, demographic information related to the user, biometric information related to the user, medical information related to the user, self-reported user feedback, sleep parameters related to the user (e.g., sleep-related parameters recorded from one or more previous sleep sessions), or any combination thereof. Demographic information may include, for example, information indicating the user's age, social gender role, race, family history (e.g., family history of insomnia or sleep apnea), employment status, education level, socioeconomic status, or any combination thereof. Medical information may include, for example, information indicating one or more medical conditions related to the user, the amount of medication used by the user, or both. The medical information data may further include a fall risk assessment related to the user (e.g., a fall risk score on the Morse Fall Scale), the results or score of an Multiple Sleep Latency Test (MSLT), and / or a score or value of the Pittsburgh Sleep Quality Index (PSQI). Self-reported user feedback may include information indicating the user's subjective sleep score (e.g., poor, average, good), the user's subjective stress level, the user's subjective fatigue level, the user's subjective health status, recent life events experienced by the user, or any combination thereof.

[0026] The electronic interface 119 is configured to receive data (e.g., physiological data and / or acoustic data) from one or more sensors 130 so that the data can be stored in a storage device 114 and / or analyzed by a processor 112 of the control system 110. The electronic interface 119 can communicate with one or more sensors 130 using a wired or wireless connection (e.g., RF communication protocol, WiFi communication protocol, Bluetooth® communication protocol, IR communication protocol, cellular network, or other optical communication protocol). The electronic interface 119 may include an antenna, a receiver (e.g., an RF receiver), a transmitter (e.g., an RF transmitter), a transceiver, or any combination thereof. The electronic interface 119 may also include another processor and / or another storage device that is identical or similar to the processor 112 and storage device 114 described herein. In some implementations, the electronic interface 119 is connected to or integrated with a user device 170. In other implementations, the electronic interface 119 is connected to or integrated (for example, within the enclosure) with the control system 110 and / or the storage device 114.

[0027] As described above, in some implementations, system 100 may include a respiratory therapy system 120 (also called a respiratory pressure therapy system) as needed. The respiratory therapy system 120 may include a respiratory therapy device 122 (also called a respiratory pressure device), a user interface 124 (also called a mask or patient interface), a conduit 126 (also called a tube or air circuit), a display device 128, a humidifier tank 129, or a combination thereof. In some implementations, the control system 110, memory device 114, display device 128, one or more sensors 130, and humidifier tank 129 are part of the respiratory therapy device 122. Respiratory pressure therapy refers to an application that supplies air to the inlet of a user's airway at a controlled target pressure that is nominally positive to the atmosphere throughout the user's entire respiratory cycle (as opposed to negative pressure therapy such as an iron lung or chest protector). The respiratory therapy system 120 is generally used to treat individuals suffering from one or more sleep-related breathing disorders (e.g., obstructive sleep apnea, central sleep apnea, mixed sleep apnea), other respiratory disorders such as COPD, or other disorders that lead to respiratory failure and which may manifest during sleep or wakefulness.

[0028] The respiratory therapy device 122 is generally used to generate pressurized air to be delivered to the user (for example, using one or more motors (e.g., blower motors) that drive one or more compressors). In some implementations, the respiratory therapy device 122 generates a continuous constant air pressure to be delivered to the user. In other implementations, the respiratory therapy device 122 generates two or more predetermined pressures (e.g., a first predetermined air pressure and a second predetermined air pressure). In yet another implementation, the respiratory therapy device 122 is configured to generate various different air pressures within a predetermined range. For example, the respiratory therapy device 122 can deliver at least about 6 cmH2O, at least about 10 cmH2O, at least about 20 cmH2O, between about 6 cmH2O and about 10 cmH2O, between about 7 cmH2O and about 12 cmH2O, etc. The respiratory therapy device 122 can also deliver pressurized air at a predetermined flow rate between, for example, about -20 L / min and about 150 L / min while maintaining positive pressure (relative to ambient pressure). In some implementations, the control system 110, the storage device 114, the electronic interface 119, or any combination thereof may be connected to and / or located within the housing of the respiratory therapy device 122.

[0029] The user interface 124 engages with a portion of the user's face and helps to transport pressurized air from the respiratory therapy device 122 into the user's airway, preventing airway narrowing and / or obstruction during sleep. This can also increase the user's oxygen intake during sleep. Depending on the therapy applied, the user interface 124 can, for example, form a seal with an area or portion of the user's face to facilitate the transport of gas at a pressure sufficiently different from the ambient pressure, e.g., a positive pressure of about 10 cmH2O relative to the ambient pressure, in order to activate the therapy. In other forms of therapy, such as oxygen transport, the user interface may not include a seal sufficient to facilitate the transport of supply gas to the airway at a positive pressure of about 10 cmH2O.

[0030] In some implementations, the user interface 124 is or includes a face mask that covers the user's nose and mouth (see, for example, Figure 2). Alternatively, the user interface 124 is or includes a nasal mask that provides air to the user's nose or a nasal pillow mask that directly delivers air to the user's nostrils. The user interface 124 may also include a strap assembly that includes multiple straps (e.g., including hook-and-loop fasteners) for positioning and / or stabilizing the user interface 124 or a portion of the user interface 124 in a desired position on the user (e.g., on the face), and an equiangular cushion (e.g., silicone, plastic, foam, etc.) that helps provide an airtight seal between the user interface 124 and the user. In some implementations, the user interface 124 may also include a connector 127 and one or more vents 125. One or more vents 125 can be used to release carbon dioxide and other gases exhaled by the user. In other implementations, the user interface 124 includes a mouthpiece (e.g., a night guard mouthpiece molded to fit the user's teeth, a mandibular repositioning device, etc.). In some implementations, the connector 127 is separate from the user interface 124 (and / or conduit 126) but is connectable. The connector 127 is configured to fluidly connect the user interface 124 to the conduit 126.

[0031] The conduit 126 allows air to flow between two components of the respiratory therapy system 120, for example, the respiratory therapy device 122 and the user interface 124. In some implementations, the conduit may have separate branches for inspiration and expiration. In other implementations, a single branch conduit is used for both inspiration and expiration. Generally, the respiratory therapy system 120 forms an air path extending between the motor of the respiratory therapy device 122 and the user and / or the user's airway. Thus, the air path generally includes at least the motor of the respiratory therapy device 122, the user interface 124, and the conduit 126.

[0032] One or more of the respiratory therapy device 122, user interface 124, conduit 126, display device 128, and humidifier tank 129 may include one or more sensors (e.g., pressure sensors, flow sensors, or any of the other sensors 130 more commonly described herein). These one or more sensors can be used, for example, to measure the air pressure and / or flow rate of the pressurized air supplied by the respiratory therapy device 122.

[0033] The display device 128 is generally used to display images and / or information relating to the respiratory therapy device 122, including still images, moving images, or both. For example, the display device 128 may display information relating to the status of the respiratory therapy device 122 (e.g., whether the respiratory therapy device 122 is on / off, the pressure of the air being transported by the respiratory therapy device 122, the temperature of the air being transported by the respiratory therapy device 122, etc.) and / or other information (e.g., sleep score or treatment score, as described in International Publication No. 2016 / 061629 and U.S. Patent Application Publication No. 2017 / 0311879, respectively, which are incorporated herein by reference in their entirety). TM It can provide information such as scores, the current date / time, user personal information, and user surveys. In some implementations, the display device 128 functions as a human-machine interface (HMI) that includes a graphical user interface (GUI) configured to display images as an input interface. The display device 128 may be an LED display, OLED display, LCD display, etc. The input interface may be, for example, a touchscreen or touch sensor board, a mouse, a keyboard, or any sensor system configured to sense input made by a human user interacting with the respiratory therapy device 122.

[0034] The humidifying tank 129 is connected to or integrated with the respiratory therapy device 122 and includes a water reservoir capable of humidifying the pressurized air transported from the respiratory therapy device 122. The respiratory therapy device 122 may include a heater for heating the water in the humidifying tank 129 in order to humidify the pressurized air provided to the user. Additionally, in some implementations, the conduit 126 may also include a heating element (e.g., connected to and / or embedded in the conduit 126) for heating the pressurized air transported to the user. The humidifying tank 129 may be fluidically connected to a water vapor inlet in the air path and transport water vapor into the air path via the water vapor inlet, or it may be formed in line with the air path as part of the air path itself. In other implementations, the respiratory therapy device 122 or the conduit 126 may include an anhydrous humidifier. The anhydrous humidifier may incorporate sensors that interface with other sensors located elsewhere in the system 100.

[0035] The respiratory therapy system 120 can be used as, for example, a ventilator, or a positive airway pressure (PAP) system such as a continuous positive airway pressure (CPAP) system, an automated positive airway pressure (APAP) system, a bilevel or variable positive airway pressure (BPAP or VPAP) system, or any combination thereof. A CPAP system delivers a predetermined air pressure (determined, for example, by a sleep physician) to the user. An APAP system automatically changes the air pressure delivered to the user, for example, based at least in part on respiratory data related to the user. A BPAP or VPAP system is configured to deliver a first predetermined pressure (e.g., inspiratory positive airway pressure or IPAP) and a second predetermined pressure lower than the first predetermined pressure (e.g., expiratory positive airway pressure or EPAP).

[0036] Referring to Figure 2, parts of system 100 (Figure 1) relating to several implementation forms are shown. The user 210 and co-habitant 220 of the respiratory therapy system 120 are positioned in a bed 230 and lying on a mattress 232. A user interface 124 (e.g., a full-face mask) can be worn by the user 210 during a sleep session. The user interface 124 is fluidically connected to and / or connected to a respiratory therapy device 122 via a conduit 126. The respiratory therapy device 122 then delivers pressurized air to the user 210 via the conduit 126 and the user interface 124, increasing the air pressure in the user's throat to help prevent airway closure and / or narrowing during sleep. The respiratory therapy device 122 may include a display device 128 that allows the user to interact with the respiratory therapy device 122. The respiratory therapy device 122 may further include a humidification tank 129 that stores water for humidifying the pressurized air. The respiratory therapy device 122 may be placed on a nightstand 240 directly adjacent to the bed 230, as shown in Figure 2, or more generally, on any surface or structure substantially adjacent to the bed 230 and / or the user 210. The user may also wear a blood pressure monitor 180 and an activity tracker 190 while lying on the mattress 232 of the bed 230.

[0037] Referring again to Figure 1, one or more sensors 130 of system 100 include a pressure sensor 132, a flow sensor 134, a temperature sensor 136, a motion sensor 138, a microphone 140, a speaker 142, a radio frequency (RF) receiver 146, an RF transmitter 148, a camera 150, an infrared (IR) sensor 152, a photoplethysmogram (PPG) sensor 154, an electrocardiogram (ECG) sensor 156, an electroencephalogram (EEG) sensor 158, a volume sensor 160, a force sensor 162, a strain gauge sensor 164, an electromyogram (EMG) sensor 166, an oxygen sensor 168, a sample sensor 174, a moisture sensor 176, a LiDAR sensor 178, or any combination thereof. Generally, each of the one or more sensors 130 is configured to output sensor data received and stored by the storage device 114 or one or more other storage devices. The sensor 130 may further include an electrooculography (EOG) sensor, a peripheral blood oxygen saturation (SpO2) sensor, a galvanic skin response (GSR) sensor, a carbon dioxide (CO2) sensor, or any combination thereof.

[0038] One or more sensors 130 are shown and described as including each of the following: pressure sensor 132, flow sensor 134, temperature sensor 136, motion sensor 138, microphone 140, speaker 142, RF receiver 146, RF transmitter 148, camera 150, IR sensor 152, PPG sensor 154, ECG sensor 156, EEG sensor 158, capacity sensor 160, force sensor 162, strain gauge sensor 164, EMG sensor 166, oxygen sensor 168, sample sensor 174, moisture sensor 176, and LiDAR sensor 178, but more generally, one or more sensors 130 may include any combination and any number of each of the sensors described and / or shown herein.

[0039] One or more sensors 130 can be used to generate physiological data, acoustic data, or both, related to, for example, a user of the respiratory therapy system 120 (e.g., user 210 in Figure 2), the respiratory therapy system 120, both the user and the respiratory therapy system 120, or other entities, objects, activities, etc. The physiological data generated by one or more sensors 130 can be used by the control system 110 to determine sleep-wake signals related to the user during a sleep session and one or more sleep-related parameters. The sleep-wake signals can indicate one or more sleep stages (sometimes called sleep states) including distinct sleep stages such as sleep, wakefulness, relaxed wakefulness, micro-wakefulness, or rapid eye movement (REM) stages (which may include both typical and atypical REM stages), a first non-REM stage (often referred to as "N1"), a second non-REM stage (often referred to as "N2"), a third non-REM stage (often referred to as "N3"), or any combination thereof. Methods for determining sleep stages based on physiological data generated by one or more sensors, such as sensor 130, are described, for example, in International Publication 2014 / 047310, U.S. Patent No. 10,492,720, U.S. Patent No. 10,660,563, U.S. Patent Application Publication 2020 / 0337634, International Publication 2017 / 132726, International Publication 2019 / 122413, U.S. Patent Application Publication 2021 / 0150873, International Publication 2019 / 122414, and U.S. Patent Application Publication 2020 / 0383580, each of which is incorporated herein by reference in its entirety.

[0040] The sleep-wake signal can also be time-stamped to indicate the time the user goes to bed, the time the user gets out of bed, the time the user attempts to fall asleep, etc. For example, the sleep-wake signal can be measured by one or more sensors 130 during a sleep session at a predetermined sampling rate such as 1 sample / second, 1 sample / 30 seconds, or 1 sample / minute. Examples of one or more sleep-related parameters that can be determined for the user during a sleep session based at least partially on the sleep-wake signal include total bedtime, total sleep time, total wake time, sleep latency, wake-up parameters, sleep efficiency, fragmentation index, sleep onset time, respiratory rate consistency, sleep onset time, wake time, sleep disturbance rate, number of movements, or any combination thereof.

[0041] Furthermore, physiological and / or acoustic data generated by one or more sensors 130 can be used to determine respiratory signals relevant to the user during a sleep session. Respiratory signals generally indicate the user's breathing during a sleep session. Respiratory signals can, for example, indicate respiratory rate, respiratory rate variability, inspiratory amplitude, expiratory amplitude, inspiratory / expiratory amplitude ratio, inspiratory / expiratory duration ratio, number of events per hour, event patterns, pressure settings of the respiratory therapy device 122, or any combination thereof. Events may include, for example, snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, RERA, flow restriction (e.g., an event resulting in no increase in flow despite an increase in negative intrathoracic pressure indicating increased effort), mask leakage (e.g., from user interface 124), lower limb immobility, sleep disturbance, suffocation, increased heart rate, heart rate variability, dyspnea, asthma attack, epileptic interstitial, seizure, fever, cough, sneeze, snoring, gasping, the presence of an illness such as a cold or influenza, and an increase in stress levels. Events can be detected by any means known in the art, such as those described in U.S. Patent No. 5,245,995, U.S. Patent No. 6,502,572, International Publication No. 2018 / 050913, and International Publication No. 2020 / 104465, each of which is incorporated herein by reference in whole.

[0042] The pressure sensor 132 outputs pressure data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. In some implementations, the pressure sensor 132 is an air pressure sensor (e.g., a barometric pressure sensor) that generates sensor data indicating the user's respiration (e.g., inhalation and / or exhalation) and / or ambient pressure of the respiratory therapy system 120. In such implementations, the pressure sensor 132 can be connected to or integrated with the respiratory therapy device 122. The pressure sensor 132 may be, for example, a capacitive sensor, an electromagnetic sensor, an inductive sensor, a resistance sensor, a piezoelectric sensor, a strain gauge sensor, an optical sensor, a potentiometric sensor, or any combination thereof. In one example, the pressure sensor 132 can be used to determine the user's blood pressure.

[0043] The flow sensor 134 outputs flow data that can be stored in the storage device 114 and / or analyzed by the processor 112 of the control system 110. In some implementations, the flow sensor 134 is used to determine the airflow rate from the respiratory therapy device 122, the airflow rate through the conduit 126, the airflow rate through the user interface 124, or any combination thereof. In such implementations, the flow sensor 134 can be connected to or integrated with the respiratory therapy device 122, the user interface 124, or the conduit 126. The flow sensor 134 may be a mass flow sensor such as a rotary flow meter (e.g., a Hall effect flow meter), a turbine flow meter, an orifice flow meter, an ultrasonic flow meter, a hot-wire sensor, a vortex sensor, a membrane sensor, or any combination thereof.

[0044] The temperature sensor 136 outputs temperature data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. In some implementations, the temperature sensor 136 generates temperature data indicating the user's core body temperature, the user 210's skin temperature, the temperature of the air flowing from and / or through the conduit 126, the temperature within the user interface 124, the ambient temperature, or any combination thereof. The temperature sensor 136 may be, for example, a thermocouple sensor, a thermistor sensor, a silicon bandgap temperature sensor or a semiconductor-based sensor, a resistance temperature detector, or any combination thereof.

[0045] The motion sensor 138 outputs motion data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. The motion sensor 138 can be used to detect the user's movements during a sleep session and / or the movements of any component of the respiratory therapy system 120, such as the respiratory therapy device 122, the user interface 124, or the conduit 126. The motion sensor 138 may include one or more inertial sensors, such as an accelerometer, a gyroscope, and a magnetometer. The motion sensor 138 can be used to detect movements or accelerations related to arterial pulsations, such as pulsations in or around the user's face and pulsations proximal to the user interface 124, and is configured to detect features such as shape, velocity, amplitude, or volume of the pulsation. In some implementations, the motion sensor 138 can optionally or additionally generate one or more signals representing the user's body movements, from which signals representing the user's sleep state can be obtained, for example, via the user's respiratory movements.

[0046] The microphone 140 outputs acoustic data that can be stored in the storage device 114 and / or analyzed by the processor 112 of the control system 110. As described in further detail herein, the acoustic data generated by the microphone 140 can be reproduced as one or more sounds (e.g., sounds from the user) during a sleep session to determine one or more sleep-related parameters (e.g., using the control system 110). As described in further detail herein, the acoustic data from the microphone 140 can also be used to identify events experienced by the user during a sleep session (e.g., using the control system 110). In other implementations, the acoustic data from the microphone 140 represents noise associated with the respiratory therapy system 120. In some implementations, the system 100 includes multiple microphones (e.g., two or more microphones and / or an array of microphones using beamforming) so that the audio data generated by each of the multiple microphones can be used to identify audio data generated by other microphones among the multiple microphones. The microphone 140 may be connected to or integrated with the respiratory therapy system 120 (or system 100) in generally any configuration. For example, the microphone 140 may be located inside the respiratory therapy device 122, the user interface 124, the conduit 126, or other components. The microphone 140 may also be located adjacent to or connected to the outside of the respiratory therapy device 122, the outside of the user interface 124, the outside of the conduit 126, or any other components. The microphone 140 may also be a component of the user device 170 (for example, the microphone 140 is the microphone of a smartphone). The microphone 140 may be integrated into the user interface 124, the conduit 126, the respiratory therapy device 122, or any combination thereof. Generally, the microphone 140 may be located at any point within or adjacent to the air path of the respiratory therapy system 120, which includes at least the motor of the respiratory therapy device 122, the user interface 124, and the conduit 126. Thus, the air path is also called the acoustic path.

[0047] Speaker 142 outputs sound waves that are audible to the user. In one or more implementations, the sound waves may be audible to the user of system 100 or inaudible to the user of system (e.g., ultrasound). Speaker 142 can be used, for example, as an alarm clock or to play a warning or message to the user (e.g., in response to an event). In some implementations, speaker 142 can be used to transmit acoustic data generated by microphone 140 to the user. Speaker 142 can be connected to or integrated with the respiratory therapy device 122, user interface 124, conduit 126, or user device 170.

[0048] The microphone 140 and speaker 142 can be used as independent devices. In some implementations, the microphone 140 and speaker 142 can be combined with an acoustic sensor 141 (e.g., a SONAR sensor), for example, as described in International Publication No. 2018 / 050913 and International Publication No. 2020 / 104465, which are incorporated herein by reference in their entirety. In such implementations, the speaker 142 generates or emits sound waves at predetermined intervals and / or predetermined frequencies, and the microphone 140 detects reflections of the sound waves emitted from the speaker 142. The sound waves generated or emitted by the speaker 142 have frequencies inaudible to the human ear (e.g., less than 20 Hz or greater than about 18 kHz) so as not to disturb the sleep of the user or the user's bedmate (e.g., bedmate 220 in Figure 2). The control system 110 can determine, at least in part, the user's position and / or one or more sleep-related parameters as specified herein, such as respiratory signal, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-to-expiratory ratio, number of events per hour, pattern of events, sleep stage, pressure setting of the respiratory therapy device 122, mouth leak status, or any combination thereof. In this context, the SONAR sensor may be understood as relating to active acoustic sensing, such as generating / transmitting an ultrasonic or low-frequency ultrasonic sensing signal (e.g., within a frequency range of approximately 17–23 kHz, 18–22 kHz, or 17–18 kHz) through the air. Such a system can be considered in relation to the aforementioned International Publication No. 2018 / 050913 and International Publication No. 2020 / 104465. In some implementations, the speaker 142 is a bone conduction speaker. In some implementations, one or more sensors 130 include (i) a first microphone which is identical or similar to microphone 140 and integrated into acoustic sensor 141, and (ii) a second microphone which is identical or similar to microphone 140 but is independent of and separate from the first microphone integrated into acoustic sensor 141.

[0049] The RF transmitter 148 generates and / or emits radio waves having a predetermined frequency and / or amplitude (e.g., within the high frequency band, within the low frequency band, long wave signal, short wave signal, etc.). The RF receiver 146 detects the reflection of the radio waves emitted from the RF transmitter 148, and by analyzing this data by the control system 110, the user's location and / or one or more sleep-related parameters described herein can be determined. An RF receiver (either the RF receiver 146 and the RF transmitter 148, or another RF pair) can also be used for wireless communication between the control system 110, the respiratory therapy device 122, one or more sensors 130, the user device 170, or any combination thereof. Although the RF receiver 146 and the RF transmitter 148 are shown as separate elements in Figure 1, in some implementations the RF receiver 146 and the RF transmitter 148 are combined as part of an RF sensor 147 (e.g., a RADAR sensor). In some such implementations, the RF sensor 147 includes a control circuit. The specific format of RF communication may be Wi-Fi, Bluetooth (registered trademark), or other similar technologies.

[0050] In some implementations, the RF sensor 147 is part of a mesh system. An example of a mesh system is a WiFi mesh system which may include mesh nodes, mesh routers, and mesh gateways, each of which may be mobile / movable or fixed. In such an implementation, the WiFi mesh system includes WiFi routers and / or WiFi controllers, each containing an RF sensor identical or similar to the RF sensor 147, as well as one or more satellites (e.g., access points). The WiFi routers and satellites communicate continuously with each other using WiFi signals. Using the WiFi mesh system, motion data can be generated at least partially based on changes in the WiFi signal between the routers and satellites (e.g., differences in received signal strength) due to the movement of objects or people partially interfering with the signal. This motion data may represent exercise, respiration, heart rate, walking, falls, behavior, or any combination thereof.

[0051] Camera 150 outputs image data that can be reproduced as one or more images (e.g., still images, moving images, thermal images, or a combination thereof) that can be stored in the storage device 114. Image data from camera 150 can be used by the control system 110 to determine one or more sleep-related parameters as described herein. For example, image data from camera 150 can be used to locate the user's position, determine the time the user goes to bed (e.g., bed 230 in Figure 2), and determine the time the user gets out of bed 230. Camera 150 can also be used to track eye movements, pupil dilation (if one or both of the user's eyes are open), blink rate, or any changes during REM sleep. Camera 150 can also be used to track the user's position, which may affect the duration and / or severity of apnea episodes in users suffering from position-obstructive sleep apnea.

[0052] The IR sensor 152 outputs infrared image data that can be reproduced as one or more infrared images (e.g., still images, moving images, or both) that can be stored in the storage device 114. Using the infrared data from the IR sensor 152, one or more sleep-related parameters during a sleep session, including the user's temperature and / or movement, can be determined. The IR sensor 152 can also be used in combination with the camera 150 to measure the user's presence, position, and / or movement. The IR sensor 152 can detect infrared light with wavelengths between approximately 700 nm and 1 mm, for example, while the camera 150 can detect visible light with wavelengths between approximately 380 nm and 740 nm.

[0053] The IR sensor 152 outputs infrared image data that can be reproduced as one or more infrared images (e.g., still images, moving images, or both) that can be stored in the storage device 114. Using the infrared data from the IR sensor 152, one or more sleep-related parameters during a sleep session, including the user's temperature and / or movement, can be determined. The IR sensor 152 can also be used in combination with the camera 150 to measure the user's presence, position, and / or movement. The IR sensor 152 can detect infrared light with wavelengths between approximately 700 nm and 1 mm, for example, while the camera 150 can detect visible light with wavelengths between approximately 380 nm and 740 nm.

[0054] The PPG sensor 154 outputs user-related physiological data that can be used to determine one or more sleep-related parameters, such as heart rate, heart rate pattern, heart rate variability, cardiac cycle, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-to-expiratory ratio, estimated blood pressure parameters, or any combination thereof. The PPG sensor 154 can be worn by the user, embedded in the clothing and / or fabric worn by the user, embedded in the user interface 124 and / or its associated headgear (e.g., a strap), and / or connected.

[0055] The ECG sensor 156 outputs physiological data related to the electrical activity of the user's heart. In some implementations, the ECG sensor 156 includes one or more electrodes placed on or around the user during a sleep session. The physiological data from the ECG sensor 156 can be used to determine, for example, one or more sleep-related parameters as described herein.

[0056] The EEG sensor 158 outputs physiological data related to the electrical activity of the user's brain. In some implementations, the EEG sensor 158 includes one or more electrodes placed on or around the user's scalp during a sleep session. The physiological data from the EEG sensor 158 can be used, for example, to determine the user's sleep stage at any given time during a sleep session. In some implementations, the EEG sensor 158 can be integrated into the user interface 124 and / or its associated headgear (e.g., a strap).

[0057] The capacitance sensor 160, force sensor 162, and strain gauge sensor 164 output data that can be stored in the memory device 114 and used by the control system 110 to determine one or more sleep-related parameters as described herein. The EMG sensor 166 outputs physiological data related to the electrical activity produced by one or more muscles. The oxygen sensor 168 outputs oxygen data indicating the oxygen concentration of the gas (e.g., in the conduit 126 or in the user interface 124). The oxygen sensor 168 may be, for example, an ultrasonic oxygen sensor, an electro-oxygen sensor, a chemical oxygen sensor, an optical oxygen sensor, or any combination thereof. In some implementations, one or more sensors 130 also include a galvanic skin response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a blood pressure sensor, an oxygen measurement sensor, or any combination thereof.

[0058] The sample sensor 174 can be used to detect the presence of a sample in the user's exhaled breath. The data output by the sample sensor 174 is stored in the storage device 114 and can be used by the control system 110 to determine the identity and concentration of any sample in the user's respiration. In some implementations, the sample sensor 174 is positioned near the user's mouth to detect a sample in the exhaled breath from the user's mouth. For example, if the user interface 124 is a face mask that covers the user's nose and mouth, the sample sensor 174 can be placed inside the face mask to monitor the user's breathing. In other implementations, if the user interface 124 is a nasal mask or nasal pillow mask, the sample sensor 174 can be positioned near the user's nose to detect a sample in the exhaled breath from the user's nose. In yet another implementation, if the user interface 124 is a nasal mask or nasal pillow mask, the sample sensor 174 can be positioned near the user's mouth. In this implementation, the sample sensor 174 can be used to detect whether or not air is inadvertently leaking from the user's mouth. In some implementations, the sample sensor 174 is a volatile organic compound (VOC) sensor that can be used to detect carbon-based chemicals or compounds such as carbon dioxide. In some implementations, the sample sensor 174 can also be used to detect whether the user is breathing through their nose or mouth. For example, if the presence of a sample is detected by data output from the sample sensor 174 placed near the user's mouth or (in implementations where the user interface 124 is a face mask) inside the face mask, the control system 110 can use this data as an indication that the user is breathing through their mouth.

[0059] The moisture sensor 176 outputs data that is stored in the storage device 114 and can be used by the control system 110. The moisture sensor 176 can be used to detect moisture in various areas surrounding the user (e.g., inside the conduit 126 or user interface 124, near the user's face, near the connection between the conduit 126 and the user interface 124, near the connection between the conduit 126 and the respiratory therapy device 122, etc.). Therefore, in some implementations, the moisture sensor 176 can be connected or integrated into the user interface 124 or conduit 126 to monitor the humidity of the pressurized air from the respiratory therapy device 122. In other implementations, the moisture sensor 176 can be placed near any area where moisture levels need to be monitored. The moisture sensor 176 can also be used to monitor the surrounding environment of the user, for example, the humidity of the air in the user's bedroom. Furthermore, the moisture sensor 176 can be used to track the user's biological responses to environmental changes.

[0060] One or more LiDAR sensors 178 can be used to sense depth. Using such optical sensors (e.g., laser sensors), objects can be detected and a three-dimensional (3D) map of the surrounding environment, such as a living space, can be created. LiDAR typically uses pulsed lasers to measure time of flight. LiDAR is also called 3D laser scanning. In one use case of such sensors, a stationary device or mobile device (such as a smartphone) with a LiDAR sensor 178 can measure and map an area more than 5 meters away from the sensor. LiDAR data can be fused with point cloud data estimated by, for example, an electromagnetic RADAR sensor. The LiDAR sensor 178 can also use artificial intelligence (AI) to automatically create geofencing for the RADAR system by detecting and classifying spatial features that could cause problems for the RADAR system, such as glass windows (which may be highly reflective to RADAR). LiDAR can also be used to estimate, for example, a person's height, as well as changes in height, such as when a person is sitting or lying down. LiDAR can be used to form a 3D mesh representation of the environment. In further applications, for solid surfaces through which radio waves pass (e.g., radio wave-transparent materials), LiDAR reflects off such surfaces, enabling the classification of different types of obstacles.

[0061] Although shown independently in Figure 1, any combination of one or more sensors 130 can be integrated and / or connected to any one or more components of system 100, including the respiratory therapy device 122, user interface 124, conduit 126, humidifier tank 129, control system 110, user device 170, or any combination thereof. For example, an acoustic sensor 141 and / or an RF sensor 147 can be integrated and / or connected to the user device 170. In such an implementation, the user device 170 is considered a secondary device that generates additional or secondary data used by system 100 (e.g., the control system 110) according to some aspects of the present disclosure. In some implementations, a pressure sensor 132 and / or a flow sensor 134 are integrated and / or connected to the respiratory therapy device 122. In some implementations, at least one of the one or more sensors 130 is not connected to the respiratory therapy device 122, the control system 110, or the user device 170, but is positioned near the user during a sleep session (e.g., positioned on or in contact with a part of the user, worn by the user, connected to or placed on a nightstand, connected to the mattress, connected to the ceiling, etc.). More generally, one or more sensors 130 can be positioned at any suitable location relative to the user so as to be able to generate physiological data related to the user and / or co-sleep companions 220 during one or more sleep sessions.

[0062] By analyzing data from one or more sensors 130, one or more sleep-related parameters can be determined, which may include respiratory signals, respiratory rate, respiratory pattern, inspiratory amplitude, expiratory amplitude, inspiratory-to-expiratory ratio, occurrence of one or more events, number of events per hour, pattern of events, mean duration of events, range of event durations, ratio of different event counts, sleep stages, apnea-hypopnea index (AHI), or any combination thereof. One or more events may include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, intentional user interface leak, unintentional user interface leak, mouth leak, cough, inability to rest the lower limbs, sleep disturbance, suffocation, increased heart rate, dyspnea, asthma attack, epileptic interstitial, seizure, increased blood pressure, hyperventilation, or any combination thereof. Many of these sleep-related parameters are physiological parameters, but some are considered non-physiological parameters. Other types of physiological and non-physiological parameters can also be determined based on data from one or more sensors 130 or other types of data.

[0063] The user device 170 includes a display device 172. The user device 170 may be a mobile device such as a smartphone, tablet, laptop, game console, or smartwatch. Alternatively, the user device 170 may be an external sensing system, a television (e.g., a smart TV), or another smart home device (e.g., a smart speaker such as Google Home, Amazon Echo, or Alexa). In some implementations, the user device 170 is a wearable device (e.g., a smartwatch). The display device 172 is generally used to display images, including still images, moving images, or both. In some implementations, the display device 172 functions as a human-machine interface (HMI) including a graphical user interface (GUI) and an input interface configured to display images. The display device 172 may be an LED display, an OLED display, an LCD display, etc. The input interface may be a touchscreen or touch sensor board, a mouse, a keyboard, or any sensor system configured to sense input made by a human user interacting with the user device 170. In some implementations, one or more user devices 170 may be used by and / or included in the system 100.

[0064] The blood pressure device 180 is generally used to help generate physiological data for determining one or more blood pressure measurements relevant to the user. The blood pressure device 180 may include, for example, at least one of one or more sensors 130 to measure systolic and / or diastolic blood pressure components.

[0065] In some implementations, the blood pressure device 180 is a blood pressure monitor that includes a wearable inflatable cuff and a pressure sensor (e.g., the pressure sensor 132 described herein). For example, as shown in the example in Figure 2, the blood pressure device 180 can be worn on the user's upper arm. In such implementations where the blood pressure device 180 is a blood pressure monitor, the blood pressure device 180 also includes a pump (e.g., a manually operated valve) for inflating the cuff. In some implementations, the blood pressure device 180 is connected to a respiratory therapy device 122 of a respiratory therapy system 120, which then delivers pressurized air to inflate the cuff. More generally, the blood pressure device 180 can be communicably connected to and / or physically integrated (e.g., within a housing) with a control system 110, a storage device 114, a respiratory therapy system 120, a user device 170 and / or an activity tracker 190.

[0066] The activity tracker 190 is generally used to help generate physiological data for determining activity metrics relevant to the user. Activity metrics may include, for example, steps taken, distance traveled, steps climbed, duration of physical activity, type of physical activity, intensity of physical activity, time spent standing, respiratory rate, mean respiratory rate, resting respiratory rate, maximum respiratory rate, respiratory rate variability, heart rate, mean heart rate, resting heart rate, maximum heart rate, heart rate variability, calorie expenditure, blood oxygen saturation, skin electrical activity (also known as skin conductance or galvanic skin response) or any combination thereof. The activity tracker 190 may include, for example, one or more sensors 130 as described herein, such as a motion sensor 138 (e.g., one or more accelerometers and / or gyroscopes), a PPG sensor 154 and / or an ECG sensor 156.

[0067] In some implementations, the activity tracker 190 is a wearable device that can be worn by the user, such as a smartwatch, wristband, ring, or patch. For example, referring to Figure 2, the activity tracker 190 is worn on the user's wrist. The activity tracker 190 can also be linked to or integrated with clothing or garments worn by the user. Alternatively, the activity tracker 190 may also be linked to or integrated (e.g., within the same housing) with the user device 170. More generally, the activity tracker 190 may be communicatively linked to or physically integrated (e.g., within the housing) with the control system 110, the storage device 114, the respiratory therapy system 120, the user device 170, and / or the blood pressure device 180.

[0068] The control system 110 and the storage device 114 are described and shown in Figure 1 as separate components of system 100, but in some implementations, the control system 110 and / or the storage device 114 are integrated into the user device 170 and / or the respiratory therapy device 122. Alternatively, in some implementations, the control system 110 or a part thereof (e.g., the processor 112) may be located in the cloud (e.g., integrated into a server, integrated into an Internet of Things (IoT) device, connected to the cloud, receiving edge cloud processing, etc.), or located on one or more servers (e.g., remote servers, local servers, etc., or any combination thereof).

[0069] System 100 is shown as including all of the above components, but according to the implementations of this disclosure, a system used by a user to identify a user interface may include more or fewer components. For example, a first alternative system includes a control system 110, a storage device 114, and at least one of one or more sensors 130. Another example is a second alternative system including a control system 110, a storage device 114, at least one of one or more sensors 130, and a user device 170. Yet another example is a third alternative system including a control system 110, a storage device 114, a respiratory therapy system 120, at least one of one or more sensors 130, and a user device 170. Yet another example is a fourth alternative system including a control system 110, a storage device 114, a respiratory therapy system 120, at least one of one or more sensors 130, a user device 170, a blood pressure device 180, and / or an activity tracker 190. Therefore, various systems for changing pressure settings can be formed by using any part of the components shown and described herein, and / or by combining them with one or more other components.

[0070] Referring again to Figure 2, in some implementations, the control system 110, the storage device 114, one or more sensors 130, or any combination thereof, may be located on and / or within any surface and / or structure substantially adjacent to the bed 230 and / or user 210. For example, in some implementations, at least one of the one or more sensors 130 may be located on and / or within a first position on one or more components of the respiratory therapy system 120 adjacent to the bed 230 and / or user 210. One or more sensors 130 may be connected to the respiratory therapy system 120, the user interface 124, the conduit 126, the display device 128, the humidification tank 129, or a combination thereof.

[0071] Alternatively or additionally, at least one of the one or more sensors 130 may be positioned at a second location on and / or within the bed 230 (for example, one or more sensors 130 may be connected to and / or integrated with the bed 230). Furthermore, alternatively or additionally, at least one of the one or more sensors 130 may be positioned at a third location on and / or within the mattress 232 adjacent to the bed 230 and / or the user 210 (for example, one or more sensors 130 may be connected to and / or integrated with the mattress 232). Alternatively or additionally, at least one of the one or more sensors 130 may be positioned at a fourth location on and / or within the pillow substantially adjacent to the bed 230 and / or the user 210.

[0072] Alternatively or additionally, at least one of the one or more sensors 130 may be positioned in a fifth position on the bed 230 and / or on the nightstand 240 and / or within the night table 240, substantially adjacent to the user 210. Alternatively or additionally, at least one of the one or more sensors 130 may be positioned in a sixth position so as to be connected to and / or positioned in relation to the user 210 (for example, one or more sensors 130 may be embedded in or connected to fabrics, clothing and / or smart devices worn by the user 210). More generally, at least one of the one or more sensors 130 may be positioned in any suitable position relative to the user 210 so as to be able to generate sensor data relevant to the user 210.

[0073] In some implementations, a primary sensor, such as a microphone 140, is configured to generate acoustic data relevant to the user 210 during a sleep session. For example, one or more microphones (identical or similar to microphone 140 in Figure 1) may be integrated into and / or connected to (i) the circuit board of the respiratory therapy device 122, (ii) the conduit 126, (iii) a connector between components of the respiratory therapy system 120, (iv) the user interface 124, (v) headgear (e.g., a strap) associated with the user interface, or (vi) a combination thereof.

[0074] In some implementations, additional data can be generated using one or more secondary sensors in addition to the primary sensor. In some such implementations, one or more secondary sensors include a microphone (e.g., microphone 140 of system 100), a flow sensor (e.g., flow sensor 134 of system 100), a pressure sensor (e.g., pressure sensor 132 of system 100), a temperature sensor (e.g., temperature sensor 136 of system 100), a camera (e.g., camera 150 of system 100), a vane sensor (VAF), a thermal airflow sensor (MAF), a cold airflow sensor, a laminar flow sensor, an ultrasonic sensor, an inertial sensor, or a combination thereof.

[0075] Alternatively or additionally, one or more microphones (identical or similar to microphone 140 in Figure 1) may be integrated with and / or connected to a co-located smart device such as a user device 170, a TV, a watch (e.g., a mechanical watch worn by the user or another smart device), a pendant, a mattress 232, a bed 230, bedding placed on the bed 230, a pillow, a speaker (e.g., speaker 142 in Figure 1), a radio, a tablet device, an anhydrous humidifier, or a combination thereof. The co-located smart device may be any smart device within range of detecting sounds emitted by the user, the respiratory therapy system 120, and / or any part of the system 100. In some implementations, the co-located smart device is a smart device located in the same room as the user during the sleep session.

[0076] Alternatively or additionally, in some implementations, one or more microphones (identical or similar to microphone 140 in Figure 1) may be located away from the system 100 (Figure 1) and / or user 210 (Figure 2), provided there is an air passage through which acoustic signals can be transmitted to them. For example, one or more microphones may be installed in a different room from the room in which the system 100 is housed.

[0077] As used herein, a sleep session can be defined in several ways, for example, based at least in part on an initial start time and an end time. In some implementations, a sleep session is the duration of time a user is asleep, i.e., a sleep session has a start time and an end time, and the user does not wake up until the end time during the sleep session. In other words, time the user is awake is not included in the sleep session. According to this first definition of a sleep session, if a user wakes up and falls asleep multiple times during the night, each sleep interval separated by an awake interval becomes a sleep session.

[0078] Alternatively, in some implementations, a sleep session has a start time and an end time, and during the sleep session, the user can wake up without the sleep session ending, as long as the cumulative duration of the user's wakefulness falls below a wakefulness threshold. The wakefulness threshold can be defined as a percentage of the sleep session. The wakefulness threshold may be, for example, about 20 percent of the sleep session, about 15 percent of the sleep session duration, about 10 percent of the sleep session duration, about 5 percent of the sleep session duration, about 2 percent of the sleep session duration, or any other arbitrary threshold percentage. In some implementations, the wakefulness threshold may be defined as a fixed amount of time, or any other arbitrary time, such as about 1 hour, about 30 minutes, about 15 minutes, about 10 minutes, about 5 minutes, about 2 minutes, etc.

[0079] In some implementations, a sleep session is defined as the total time from when the user first goes to bed at night until when they last get out of bed the following morning. In other words, a sleep session may be defined as the period that begins at a first time (e.g., 10 p.m.) on a first date that could be called tonight (e.g., Monday, January 6, 2020) when the user first goes to bed with the intention of sleeping (unless the user intends to watch TV or enjoy their smartphone before going to sleep), and ends at a second time (e.g., 7 a.m.) on a second date that could be called the following morning (e.g., Tuesday, January 7, 2020) when the user first gets out of bed with the intention of not sleeping again the following morning.

[0080] In some implementations, users can manually start and / or end sleep sessions. For example, a user can manually start or end a sleep session by selecting one or more user-selectable elements displayed on the display device 172 of the user device 170 (Figure 1) (e.g., by clicking or tapping).

[0081] Referring to FIG. 3, an exemplary timeline 301 of a sleep session is shown. The timeline 301 includes the time of going to bed (t bed ), the time of falling asleep (t GTS ), the initial sleep time (t sleep ), the first micro-awakening MA1, the second micro-awakening MA2, the awakening A, the waking time (t wake ), and the time of waking up (t rise ).

[0082] The time of going to bed t bed is related to the time when the user first goes to bed (e.g., the bed 230 in FIG. 2) before falling asleep (e.g., the user lies down or sits on the bed). The time of going to bed t bed can be specified based at least in part on the time of going to bed threshold duration to distinguish between the time when the user goes to bed to sleep and the time when the user goes to bed for other reasons (e.g., watching TV). For example, the time of going to bed threshold duration may be at least about 10 minutes, at least about 20 minutes, at least about 30 minutes, at least about 45 minutes, at least about 1 hour, at least about 2 hours, etc. In this specification, the time of going to bed t bed is described with reference to the bed, but more generally, the time of going to bed t bed may represent the time when the user first takes a seat at some place (e.g., a sofa, a chair, a sleeping bag, etc.) to sleep.

[0083] The time of falling asleep (GTS) is related to the time when the user first tries to fall asleep after going to bed (t bed ). For example, after going to bed, the user may engage in one or more activities (e.g., reading, watching TV, listening to music, using the user device 170, etc.) to relax before trying to fall asleep. The initial sleep time (t sleep ) is the time when the user first falls asleep. For example, the initial sleep time (t sleep ) may be the time when the user first enters the first non-REM stage.

[0084] The waking time t wakeThis is the time associated with the user waking up without falling back asleep (for example, a time different from when the user wakes up in the middle of the night and falls back asleep). After initially falling asleep, the user may experience one of several more unconscious micro-awakenings (e.g., micro-awakenings MA1 and MA2) that have a short duration (e.g., 5 seconds, 10 seconds, 30 seconds, 1 minute, etc.). Wake-up time t wake In contrast, the user falls back asleep twice after each minor awakening MA1 and MA2. Similarly, the user may experience one or more conscious awakenings (e.g., awakening A) after initially falling asleep (e.g., getting up to go to the toilet, caring for a child or pet, sleepwalking, etc.). However, the user falls back asleep twice after awakening A. Therefore, the wake-up time t wake This may be defined, for example, at least in part, on the wake-up threshold duration (for example, the duration during which the user is awake for 15 minutes or more, 20 minutes or more, 30 minutes or more, 1 hour or more, etc.).

[0085] Similarly, wake-up time t rise This relates to the time a user is out of bed and away from their bed with the intention of ending a sleep session (for example, getting up at night to go to the toilet, caring for a child or pet, or sleepwalking). In other words, wake-up time t rise This is the time when the user last left bed without returning to bed until the next sleep session (e.g., the next night). Therefore, the wake-up time t rise This may be defined, for example, at least in part, on the wake-up threshold duration (e.g., when the user is away from bed for 15 minutes or more, 20 minutes or more, 30 minutes or more, 1 hour or more, etc.). The second and subsequent bedtimes t bed The subsequent sleep session can also be defined at least in part on the wake-up threshold duration (for example, when the user is away from bed for more than 4 hours, 6 hours, 8 hours, 12 hours, etc.).

[0086] As mentioned above, the user first t bed from the last t riseBetween then and the last wake time t, there is a possibility of waking up and getting out of bed at least once during the night. In some implementations, the last wake time t wake and / or last wake-up time t rise This is identified or determined at least in part on a predetermined threshold duration of time following an event (e.g., falling asleep or getting out of bed). Such a threshold duration can be customized for the user. For a standard user who goes to bed at night and wakes up and gets out of bed in the morning, this would be any time between approximately 12 and 18 hours (when the user wakes up (t wake ) or get up (t rise ) from bedtime (t bed ) and fall asleep (t GTS ) or sleep (t sleep A threshold period of up to ) can be used. For users with longer sleep durations, a shorter threshold period (e.g., between approximately 8 and 14 hours) can be used. The threshold period may be initially selected and / or adjusted later, at least in part, based on a system that monitors the user's sleep behavior.

[0087] Total sleep time (TIB) refers to the time spent in bed. bed From wake time rise This is the duration up to t. Total sleep time (TST) is the duration from the initial sleep time to the wake time, excluding conscious and unconscious wakefulness and / or minute awakenings. Generally, total sleep time (TST) is shorter than total bedtime (TIB) (e.g., 1 minute shorter, 10 minutes shorter, 1 hour shorter, etc.). For example, referring to time axis 301 in Figure 3, total sleep time (TST) is from the initial sleep time t sleep and alarm time t wake Although it spans between these periods, the durations of the first micro-awakening MA1, the second micro-awakening MA2, and awakening A are excluded. As illustrated, in this example, total sleep time (TST) is shorter than total time spent asleep (TIB).

[0088] In some implementations, total sleep time (TST) may be defined as total continuous sleep time (PTST). In such implementations, total continuous sleep time excludes a predetermined initial portion or period of the first non-REM phase (e.g., light sleep phase). For example, the predetermined initial portion may be between approximately 30 seconds and 20 minutes, between approximately 1 minute and 10 minutes, or between approximately 3 minutes and 5 minutes. Total continuous sleep time is a measure of continuous sleep and smooths the sleep-wake hypnogram. For example, when a user first falls asleep, the user may enter the first non-REM phase for a very short time (e.g., approximately 30 seconds), then return to the wakefulness phase for a short time (e.g., 1 minute), and then return to the first non-REM phase. In this example, total continuous sleep time excludes the first instance of the first non-REM phase (e.g., approximately 30 seconds).

[0089] In some implementations, the sleep session is defined by the time of going to bed (t bed It starts with ) and wake-up time (t rise A sleep session is defined as ending at t sleep ) begins, and the wake-up time (t wake It is defined as ending at ). In some implementations, a sleep session is defined as total sleep time (TST). In some implementations, a sleep session is defined as ending at the time of sleep onset (t GTS ) begins, and the wake-up time (t wake It is defined as ending at the time of sleep onset (t). In some implementations, a sleep session is defined as ending at the time of sleep onset (t). GTS It starts with ) and wake-up time (t rise It is defined as ending at bedtime (t). In some implementations, a sleep session is defined as ending at bedtime (t). bed ) begins, and the wake-up time (t wake It is defined as ending at the initial sleep time (t). In some implementations, a sleep session is defined as ending at the initial sleep time (t). sleep It starts with ) and wake-up time (t rise It is defined as ending in ).

[0090] Referring to Figure 4, exemplary hypnograms 350 corresponding to the time axis 301 (Figure 3) are shown for several implementations. As illustrated, the hypnogram 350 includes a sleep-wake signal 351, a wakefulness stage axis 360, a REM stage axis 370, a light sleep stage axis 380, and a deep sleep stage axis 390. The intersection of the sleep-wake signal 351 and one of axes 360-390 indicates the sleep stage at any given time during a sleep session.

[0091] A sleep-wake signal 351 can be generated (for example, by one or more sensors 130 described herein) based at least in part on physiological data related to the user. The sleep-wake signal may indicate one or more sleep stages, including wakefulness, relaxed wakefulness, micro-wakefulness, REM stages, first non-REM stages, second non-REM stages, third non-REM stages, or any combination thereof. In some implementations, one or more of the first non-REM stages, second non-REM stages, and third non-REM stages may be grouped together and classified as light sleep stages or deep sleep stages. For example, a light sleep stage may include the first non-REM stage, and a deep sleep stage may include the second and third non-REM stages. In Figure 4, the hypnogram 350 is shown to include a light sleep stage axis 380 and a deep sleep stage axis 390, but in some implementations, the hypnogram 350 may include axes for the first non-REM stage, the second non-REM stage, and the third non-REM stage, respectively. In other implementations, the sleep-wake signal can represent respiratory signals, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory / expiratory amplitude ratio, inspiratory / expiratory duration ratio, number of events per hour, event patterns, or any combination thereof. Information describing the sleep-wake signal can be stored in the memory device 114.

[0092] Using the Hypnogram 350, one or more sleep-related parameters can be determined, for example, sleep latency (SOL), wakefulness during the night (WASO), sleep efficiency (SE), sleep fragmentation index, sleep blocks, or any combination thereof.

[0093] Sleep latency (SOL) is the time it takes to fall asleep (t GTS ) from the initial sleep time (t sleep Sleep latency is defined as the time until the user first attempts to fall asleep. In other words, sleep latency indicates the time it takes for a user to actually fall asleep after they first attempt to do so. In some implementations, sleep latency is defined as sustained sleep latency (PSOL). Sustained sleep latency differs from sleep latency in that it is defined as the duration from the time of falling asleep to a predetermined amount of sustained sleep. In some implementations, a predetermined amount of sustained sleep may include, for example, a second non-REM phase, a third non-REM phase, and / or a REM phase including a state of wakefulness of 2 minutes or less, a first non-REM phase, and / or at least 10 minutes of sleep in the transition between them. In other words, sustained sleep latency may require, for example, a second non-REM phase, a third non-REM phase, and / or up to 8 minutes of sustained sleep in the REM phase. In other implementations, a predetermined amount of sustained sleep may include at least 10 minutes of sleep in a first non-REM phase, a second non-REM phase, a third non-REM phase, and / or a REM phase following the initial sleep time. In such implementations, the predetermined amount of sustained sleep may exclude any minute awakenings (for example, this 10 minutes may not be initiated by a 10-second minute awakening).

[0094] Nocturnal awakening (WASO) is related to the total duration of wakefulness a user experiences between the start of sleep and the wake-up time. Therefore, nocturnal awakening includes short, minute awakenings during a sleep session, whether conscious or unconscious (e.g., minute awakenings MA1 and MA2 shown in Figure 4). In some implementations, nocturnal awakening (WASO) is defined as persistent nocturnal awakening (PWASO), which includes only the total duration of wakefulness having a predetermined length (e.g., 10 seconds or more, 30 seconds or more, 60 seconds or more, approximately 5 minutes or more, approximately 10 minutes or more, etc.).

[0095] Sleep efficiency (SE) is determined as the ratio of total bedtime (TIB) to total sleep time (TST). For example, if total bedtime is 8 hours and total sleep time is 7.5 hours, the sleep efficiency for that sleep session is 93.75%. Sleep efficiency indicates a user's sleep hygiene. For example, if a user goes to bed and spends time on other activities (e.g., watching television) before falling asleep, sleep efficiency decreases (e.g., the user is penalized). In some implementations, sleep efficiency (SE) can be calculated based at least partially on total bedtime (TIB) and the total time the user is trying to fall asleep. In such implementations, the total time the user is trying to fall asleep is defined as the duration from the time of falling asleep (GTS) to the time of waking up as described herein. For example, in an implementation where total sleep time is 8 hours (e.g., from 11 p.m. to 7 a.m.), the time of falling asleep is 10:45 p.m., and the time of waking up is 7:15 a.m., the sleep efficiency parameter is calculated as approximately 94%.

[0096] The fragmentation index is determined at least partially based on the number of awakenings during a sleep session. For example, if a user had two minor awakenings (e.g., minor awakenings MA1 and MA2 shown in Figure 4), the fragmentation index could be represented as 2. In some implementations, the fragmentation index is scaled within a given range of integers (e.g., between 0 and 10).

[0097] Sleep blocks relate to the transition between any sleep stage (e.g., the first non-REM stage, the second non-REM stage, the third non-REM stage, and / or REM) and the wakefulness stage. For example, sleep blocks can be calculated with a resolution of 30 seconds.

[0098] In some implementations, the systems and methods described herein generate or analyze a hypnogram containing sleep-wake signals and determine the time of bedtime (t) based at least partially on the sleep-wake signals of the hypnogram. bed ), sleep onset time (t GTS ), initial sleep time (t sleep), one or more first minute awakenings (e.g., MA1 and MA2), wake time (t wake ), wake-up time (t rise ) or any combination thereof may include determining or identifying.

[0099] In other implementations, one or more sensors 130 are used to determine the time of going to bed (t bed ), sleep onset time (t GTS ), initial sleep time (t sleep ), one or more first minute awakenings (e.g., MA1 and MA2), wake time (t wake ), wake-up time (t rise A sleep session can be defined by determining or specifying ) or any combination thereof. For example, bedtime t bed The time to fall asleep can be determined, for example, based at least in part on data generated by a motion sensor 138, a microphone 140, a camera 150, or any combination thereof. For example, the time to fall asleep can be determined based at least in part on data from the motion sensor 138 (e.g., data indicating that the user is not moving), data from the camera 150 (e.g., data indicating that the user is not moving and / or data indicating that the user has turned off the lights), data from the microphone 140 (e.g., data indicating that the user has turned off the television), data from the user device 170 (e.g., data indicating that the user has stopped using the user device 170), data from the pressure sensor 132 and / or the flow sensor 134 (e.g., data indicating that the user has turned on the respiratory therapy device 122, data indicating that the user has put on the user interface 124, etc.), or any combination thereof.

[0100] Figure 5 shows a schematic diagram of the airway 300 of user 210. More specifically, the airway 300 includes the mouth 302, throat 304 (also called the oropharynx), pharyngolaryngeal 306, larynx 308, trachea 310, main bronchi 312A and 312B, lungs 314A and 314B, lobar bronchi 316A and 316B, and alveoli 318. The airway 300 forms a series of branching tubes, which become narrower, shorter, and more numerous as they penetrate deeper into the lungs 314A and 314B of user 210. The primary function of the lungs is gas exchange, moving oxygen from inhaled air into the venous blood and carbon dioxide in the opposite direction. The trachea 310 divides into the main bronchi 312A and 312B, which in turn divide into the lobar bronchi 316A and 316B located in the lungs 314A and 314B. The lobar bronchi 316A and 316B can also branch into higher-order bronchi. The bronchi constitute the guiding airways and are not involved in gas exchange. Further division of the airway 300 leads to the respiratory bronchioles, which eventually become the alveoli 318. The alveolar regions of the lungs are where gas exchange takes place and are also called the respiratory regions. The pharynx and larynx 306, larynx 308, and vocal cords are generally located in the neck region 320 of the user 210. The trachea 310, main bronchi 312A and 312B, lungs 314A and 314B, lobar bronchi 316A and 316B, and alveoli 318 are generally located in the thoracic cavity 322 of user 210.

[0101] To measure the airway 300 of user 210, one or more pressure vibrations can be transmitted to the airway 300 using various components of system 100. The acoustic signal is reflected by various parts of user 210's airway 300 and / or any obstacles within the airway 300. This reflection can be measured and used to determine the values ​​of various parameters related to user 210's airway 300. These parameters can indicate the presence, identification, severity, etc., of various different health conditions. As further described herein, an acoustic signal can be generated by a transducer located somewhere in system 100, including the respiratory therapy device 122, user interface 124, conduit 126, or other locations (e.g., a motor such as the blower motor of the respiratory therapy system 122, a speaker, etc.). A transducer (such as a microphone) can detect the reflection of the acoustic signal and subsequently generate acoustic data representing the reflection.

[0102] The term “acoustic signal,” as used herein, refers to these pressure vibrations. In some implementations, the acoustic signal is an alternating current signal with varying amplitude and may have any number of frequencies. In some implementations, the frequency of the acoustic signal is low enough that the acoustic signal is not audible to user 210 or any other individual. However, the term “acoustic signal,” as used herein, refers to any pressure vibration transmitted to user 210’s airway 300, regardless of whether the acoustic signal is audible to user 210.

[0103] Figure 6A is a cepstrum showing an acoustic signal 400 whose acoustic amplitude changes along the Y-axis as the acoustic signal progresses along the X-axis. The acoustic signal 400 has an acoustic amplitude that changes based on the physical obstacles it typically encounters. The cepstrum of the acoustic signal 400 is obtained using one or more signal processing methods.

[0104] The movement path along the X-axis includes a mask portion X1 that indicates the distance traveled by the acoustic signal 400 within the mask worn by the user. The mask is at position M1. When describing the acoustic signal, the term “mask” is used to refer to the user interface currently being used by user 210. However, those skilled in the art will understand that this description generally applies equally to other types of user interfaces. In implementations where the transducer is not located within the mask (e.g., the transducer is located within the respiratory therapy device 122 or conduit 126), the acoustic signal 400 includes a pre-airway portion that indicates the movement of the acoustic signal 400 before it reaches the mask at mask position M1.

[0105] At mask position M1, the acoustic signal 400 has a first amplitude Y1 that represents at least a portion of the first acoustic reflection 402 caused by the mask at mask position M1. Mask position M1 ends at mouth position M2. The distance between mask position M1 and mouth position M2 is denoted as X1. After encountering mouth position M2, the acoustic signal 400 travels further into the airway 300 through a mouth portion X2 that represents the distance the acoustic signal 400 travels within the mouth 302 of user 210. Here, the acoustic signal 400 encounters a physical obstacle P. At physical obstacle P, the acoustic signal has a second amplitude Y2 that represents at least a portion of the second acoustic reflection 404 (also called “acoustic reflection 404”) caused by the physical obstacle P located within the throat 304 of user 210. The physical obstacle P extends into the airway 300 by a third distance X3 after the second distance X2. Therefore, Cepstrum identifies distances (e.g., a first distance X1, a second distance X2, and / or a third distance X3) associated with the first acoustic reflection 402 and the second acoustic reflection 404, where these distances indicate the location of the physical obstacle P within the user 210's airway 300.

[0106] The first acoustic reflection 402 has a specific signal pattern that is different from the signal pattern of the second acoustic reflection 404. For example, the amplitude Y1 of the first reflection is greater than the amplitude Y2 of the second reflection. In another example, the shape of the first acoustic reflection 402 is different from the shape of the second acoustic reflection 404. According to some examples, the signal pattern includes the acoustic shape of the acoustic wave. According to some implementations of this disclosure, one or more physical properties of a physical obstacle P can be estimated based on one or more signal patterns of the first acoustic reflection 402 and the second acoustic reflection 404.

[0107] Figure 6B shows an implementation where the user interface worn by user 210 is a full-face mask 424, and the transducer that generates the acoustic signal 400 is located inside the mask 424. The mask 424 covers both the mouth and nose of user 210. The mask 424 is connected to a conduit 126 via an elbow connector 125. The other end of the conduit 126 can be connected to a respiratory therapy device 122. The conduit 126, elbow connector 125, and mask 524 together form an airway that fluidly connects the respiratory therapy device 122 to the airway 300 of user 210.

[0108] The mask 524 includes a speaker 426 and a microphone 428. The speaker 426 is a transducer that generates an acoustic signal, and the microphone 428 is a transducer that generates acoustic data representing reflections of the acoustic signal. The speaker 426 may be speaker 142 of system 100, or an additional or alternative speaker. Similarly, the microphone 428 may be microphone 140 of system 100, or an additional or alternative microphone. The speaker 426 is configured to generate an acoustic signal 400 that is transmitted to the airway 300 of user 210. The microphone 428 is configured to generate acoustic data representing any reflection of the acoustic signal 400 caused by (i) a portion of the individual's airway, (ii) an obstruction in the individual's airway, or (iii) both of (i) and (ii).

[0109] In the shown implementation, the speaker 426 and microphone 428 are housed in separate enclosures. In other implementations, the speaker 426 and microphone 428 may be housed in a single enclosure forming an acoustic device or sensor. In some implementations, the speaker 426 and microphone 428 are embedded in openings defined in the mask 424. In other implementations, the speaker 426 and microphone 428 are formed integrally with the mask 424.

[0110] In some implementations, the speaker 426 generates the acoustic signal 400 in the form of sound, which is one or more of the following: standard sounds (e.g., original unmodified sounds from commercial sound applications), custom sounds, inaudible frequencies, audible frequencies, white noise, broadband impulses, continuous tones, pulse tones, sine waves, square waves, sawtooth waves, frequency-modulated sine waves (e.g., chirps), continuous wave (CW) sounds, and ultra-wideband (UWB) sounds (e.g., white noise generated by a motor (e.g., a blower motor), impulses generated by a speaker, spread spectrum generated by a speaker). Other techniques such as adaptive frequency range gating, adaptive frequency range hopping, frequency shift modulation, and phase shift modulation may also be used to adjust the acoustic signal 400. In some implementations, as described herein, the acoustic signal 400 can be calibrated, for example, based on the type of user interface worn by the user or other characteristics related to the user and / or system 100.

[0111] In general, not only unmodulated signals but also any type of frequency-modulated or amplitude-modulated signal (such as a frequency-modulated continuous wave) can be used. The acoustic signal 400 may have a spread spectrum of frequencies, a pseudo-random spectrum of frequencies, or other forms. According to some other implementations, the acoustic signal 400 is one or more forms of audible sound or ultrasound. In general, the having of any properties of the acoustic signal 400 ensures that the acoustic signal 400 can propagate to a desired location in the user's airway and that the reflection of the acoustic signal 400 can be measured based on any number of internal factors (e.g., the user's physical characteristics) and external factors (e.g., the type of user interface the user is wearing).

[0112] The speaker 426 and microphone 428 can be connected to a control system and a storage device (such as a control system 110 and a storage device 114). The control system is configured to operate both the speaker 426 and the microphone 428. The control system causes the speaker 426 to emit an acoustic signal 400 and the microphone 428 to generate acoustic data representing the reflection of the acoustic signal 400. The acoustic data can then be stored in the storage device.

[0113] As shown in Figure 6B, the acoustic signal 400 (represented by a dashed line connecting a series of arrows) is directed by the speaker 426 into the user 210's airway 300. Specifically, the acoustic signal 400 is directed through the user 210's mouth 302 towards the back of the user 210's throat 304. When the acoustic signal 400 reaches a physical obstruction P located deep in the user 210's throat 304, a reflex 404 is directed back towards the mask 424, where the reflex 404 is detected by the microphone 428, generating acoustic data representing the reflex 404. The physical obstruction P can be any physical obstruction, such as airway collapse during an apnea or hypopnea event, or an obstruction caused by other respiratory conditions (e.g., mucus buildup due to a respiratory infection). Figure 6B shows an acoustic signal 400 that is generally directed to the mouth 302 of user 210, but in additional or alternative implementations, the acoustic signal 400 may be directed towards the nose of user 210.

[0114] Acoustic data associated with the acoustic reflection 404 can be analyzed to characterize the physical obstacle P. The physical obstacle P is characterized based at least in part on the analyzed acoustic data. According to some implementations of this disclosure, it is characterized based solely on the analyzed acoustic data. The physical obstacle P may indicate an apnea event or a hypopnea event of the user 210. According to some implementations of this disclosure, the acoustic data includes at least one physical measurement from the mouth region, nasal region, and throat region of the user 210.

[0115] Characterizing a physical obstacle P includes, for example, determining the location of the physical obstacle P within the user 210's airway 300. As shown in Figure 6B, the physical obstacle P is located at the point where the acoustic signal enters the user's airway 300, for example, at a second distance X2 from the user 210's mouth 302. In other examples, characterization further includes determining the part size, part shape and / or other physical characteristics of the physical obstacle P.

[0116] According to some implementations of this disclosure, one or more physical properties of a physical obstacle P are estimated based on changes in acoustic impedance, as shown by the analyzed acoustic data. According to some implementations of this disclosure, one or more physical properties of a physical obstacle P are estimated based on an analysis of acoustic reflections 404 originating from the physical obstacle P within the airway 300 of user 210.

[0117] According to some implementations of this disclosure, one or more physical properties of a physical obstacle P are estimated based on an analysis of (a) one or more acoustic waves reflected at mouth position M2 (before entering the user 210's airway 300) and (b) one or more acoustic waves reflected at the physical obstacle P (after entering the user 210's airway 300). According to some other implementations of this disclosure, one or more physical properties of the physical obstacle P are estimated based on a second distance X2 over which the acoustic signal travels through mouth position M2 into the user 210's airway 300. According to some examples, the point of entry into the airway 300 is the user 210's mouth 302 (e.g., mouth position M2) or nose.

[0118] According to some implementations of this disclosure, one or more physical properties of the physical obstacle P are estimated based on one or more properties of user 210, such as age, biological sex, weight, mouth size, neck size, or the type of mask user 210 is currently wearing.

[0119] Referring now to Figures 7A and 7B, the acoustic signal emitted by speaker 426 can be used to characterize and / or measure portions of the airway 300 beyond the throat 304 of user 210, including the pharynx 306, larynx 308, trachea 310, various bronchi, and lungs 314A, 314B. Figure 7A is a cepstrum showing an acoustic signal 500 directed toward the airway 300 of user 210. The acoustic signal 500 is generally identical or similar to the acoustic signal 400, with its amplitude changing along the Y-axis as the acoustic signal travels along the X-axis. The cepstrum includes a mask portion starting at mask position M1, one or more reflections 502 within the mask (similar to reflections 402), and a mouth portion starting at mouth position M2. However, as shown in Figure 7B, there are no physical obstacles P to which the acoustic signal 500 is reflected, and the acoustic signal 500 continues to travel through the airway 300. The acoustic signal 500 can cause one or more reflections 504 by traveling from the back of the mouth 302 at position M3 to the back of the throat 304 at position M4.

[0120] Subsequently, the acoustic signal 500 can continue to propagate through the airway 300. The acoustic signal 500 travels through the pharynx and larynx 306 from position M4 at the back of the throat 304 to position M5 at the starting point of the larynx 308. One or more reflections 506 can be produced by the reflection of a portion of the acoustic signal 500 by a portion of the pharynx and larynx 306.

[0121] Next, the acoustic signal 500 travels through the larynx 308 from position M5 to position M6, the starting point of the trachea 310. One or more reflexes 508 can be produced by the reflection of a portion of the acoustic signal 500 by a portion of the larynx 308. Next, the acoustic signal 500 travels through the trachea 310 from position M6, the apex of the trachea 310, to position M7, the base of the trachea 310, where the trachea 310 divides into main bronchi 312A and 312B. One or more reflexes 510 can be produced by the reflection of a portion of the acoustic signal 500 by a portion of the trachea 310. Finally, the acoustic signal 500 can travel through the main bronchi 312A and 312B from position M7 to position M8, the lungs 314A and 314B. One or more reflexes 512 can be produced by the reflection of a portion of the acoustic signal 500 by a portion of the main bronchi 312A and 312B.

[0122] Reflections 502-512 can propagate back to the microphone 428 through the user 210's airway 300. Acoustic data representing reflections 502-512 is generated by the microphone 428 and can be stored in a memory device (such as the memory device 114 of the system 100). The acoustic data can then be analyzed to determine various parameters of the airway 300, such as acoustic impedance, resonant frequency, and the location and size of any physical obstacles.

[0123] Figure 7A shows the cepstrum of an acoustic signal with specific reflexes, and Figure 7B shows a specific path that an acoustic signal can follow through user 210's airway 300. However, those skilled in the art will understand that, as long as the acoustic signal is guided into the airway 300, it can travel along a variety of different paths. Different users' airways have different physical characteristics, so a variety of acoustic data can be obtained. For example, in one user, an acoustic signal may generate reflexes at multiple points in the pharynx and larynx, while in another user, an acoustic signal may generate a reflex at only a single point in the pharynx and larynx. However, for both users, it is possible to generate acoustic data that exhibits these reflexes and various characteristics of the user's airway.

[0124] Figure 8 shows a method 600 for monitoring a user. Method 600 can be used to identify a user's respiratory illness, for example, before the appearance of externally identifiable physical symptoms. For example, Method 600 can be implemented using a system (such as System 100) that includes a respiratory therapy system (such as Respiratory Therapy System 120) having a respiratory therapy device (such as Respiratory Therapy Device 122) configured to supply pressurized air, and a user interface (such as User Interface 124) connected to the respiratory therapy device via a conduit (such as Conduit 126). The user interface is configured to engage with the user and help guide the pressurized air into the user's airway. Implementations of Method 600 may also use a control system that includes a memory (such as Memory Device 114) for storing machine-readable instructions, and one or more processors (such as Control System 110 and Processor 112) for executing machine-readable instructions and performing the steps of Method 600.

[0125] Step 602 of Method 600 includes directing an acoustic signal into the user's airway. The acoustic signal can be generated by a transducer, such as a speaker 426, located in the user interface (e.g., inside a face mask). The acoustic signal can be directed into the user's airway by aligning the output of the transducer with the user's airway. In other implementations, the user interface may include various physical structures that help direct the acoustic signal, when radiated by the speaker 426, into the user's airway.

[0126] The acoustic signal may have various different shapes, including a variable amplitude repeating at a given frequency. The frequency of the acoustic signal may be between approximately 0 and 100 Hz, between approximately 0 and 50 Hz, between approximately 0 and 25 Hz, or in other ranges. In some implementations, the frequency is between approximately 0 Hz and less than approximately 4 Hz, or in other ranges. Generally, low-frequency acoustic signals (between approximately 0 and 5 Hz) can propagate to the periphery of the lungs (such as the higher bronchi), while high-frequency acoustic signals (around 20 Hz) can only propagate to the main bronchi.

[0127] If necessary, the amplitude and / or frequency of the acoustic signal can be modulated. In some implementations, the frequency of the acoustic signal delivered to the user's airway is increased and / or decreased in steps. For example, the acoustic signal may initially be emitted at a frequency of about 0.1 Hz and increase in increments from about 0.1 Hz to about 2 Hz over a period of about 10 seconds. Alternatively, the frequency of the acoustic signal can be increased continuously. More generally, the acoustic signal may have any desired characteristics. In some implementations, the characteristics of the acoustic signal (frequency, amplitude, waveform, etc.) may be manually selected by the individual. In other implementations, the characteristics of the acoustic signal may be automatically selected by machine-executable instructions executed by a control system (e.g., control system 110).

[0128] In some implementations, the characteristics of the acoustic signal depend on the type of user interface worn by the user. As described herein, a user may wear various different types of user interfaces, including face masks, nose masks, and nose pillow masks. Different types of user interfaces can affect the acoustic signal in different ways. For example, a face mask may attenuate the acoustic signal more than a nose mask or nose pillow mask. Therefore, when using a given acoustic signal, reflection of the acoustic signal may result in acoustic data with a signal-to-noise ratio that is too low to accurately measure the parameter being measured, depending on the type of user interface worn by the user. Accordingly, step 606 may include determining the type of user interface worn by the user before directing the acoustic signal into the user's airway.

[0129] In some implementations, a system implementing method 600 (such as system 100) can receive input from the user indicating the type of user interface the user is wearing. In other implementations, a system implementing method 600 can determine the type of user interface the user is wearing without receiving input from the user. For example, the system may include an image sensor (such as camera 150) that generates image data of the user wearing the user interface. A control system can analyze the image data to determine the type of user interface the user is wearing. In another example, the system can direct a preliminary acoustic signal into the user's airway. Based on the reflection of the acoustic signal, the system can determine the type of user interface the user is wearing and then determine the characteristics of the acoustic signal used in step 602. Further implementations may also sweep the frequency of the acoustic signal over a wide range of frequency, amplitude, waveform, or any combination thereof to ensure that at least a portion of the reflections of the acoustic signal generate acoustic data with a sufficiently large signal-to-noise ratio so that respiratory parameters can be accurately measured.

[0130] As noted, in some implementations, the transducer emitting the acoustic signal may be a speaker 426 located in the user interface. In these implementations, the user interface is generally a full-face mask covering the user's mouth and nose, but other user interfaces may be used. In other implementations, the transducer may be located in another usable part of the system (which may be system 100). The transducer may be located in the respiratory therapy device, conduit, or other suitable location. In implementations where the transducer is located within the respiratory therapy device, the transducer may be located within the housing of the respiratory therapy device, alongside the motor used to generate pressurized air. In some implementations, as noted, the transducer is a speaker. However, in other implementations, the transducer may be a motor, such as the motor of the respiratory therapy device that generates pressurized air. In this implementation, the motor noise when the motor is operating is used as an acoustic signal and directed to the user's airway through the conduit of the respiratory therapy system. In yet another implementation, the conduit, elbow connector, or user interface may include a separate device that can be driven by pressurized air from the motor of the respiratory therapy device. When driven by pressurized air, the device generates the necessary acoustic signals and directs them into the user's airway.

[0131] Step 604 of Method 600 includes generating acoustic data representing one or more reflections of an acoustic signal. As an acoustic signal propagates through the user's airway as described herein, the acoustic signal may be reflected by parts of the user's airway and / or by obstacles within the user's airway. Reflections can be detected by a transducer that generates acoustic data representing the reflections. In some implementations, the transducer is a microphone and may be located in the user interface (e.g., microphone 428 located in the mask). The microphone may be located in other locations in the system, such as within a conduit, a respiratory therapy device, or a connector between the user interface and the conduit (e.g., an elbow connector). The acoustic data generated by the transducer generally represents the characteristics of the reflections necessary to analyze the user's airway. For example, the acoustic data may represent the amplitude of the reflections, the physical distance between reflections, the temporal length between reflections, the frequency of a series of reflections, and so on.

[0132] Step 606 of Method 600 involves analyzing the generated acoustic data to determine the values ​​of parameters related to the user's airway. The data analysis can be performed by a control system. The parameters are any parameters that can be used to characterize the user's airway. For example, the parameters may be the impedance of the user's airway (a combination of airway resistance and airway reactance, both of which may be measurable parameters), the resonant frequency of the user's airway, the location of physical obstructions within the user's airway, the size of physical obstructions within the user's airway, or other parameters of interest. In some implementations, various signal processing techniques can be applied to obtain the data of interest. Time-spectrograms or frequency-spectrograms can be obtained from the acoustic data and used for user analysis.

[0133] Generally, the parameter values ​​indicate whether or not the user has any type of respiratory illness or disease. For example, respiratory impedance is a combination of both the energy required for an acoustic signal to propagate through the user's airway (respiratory resistance) and the amount of rebound produced by the tissue in response to the acoustic signal (respiratory reactance). These properties of the user's airway can change in the presence of respiratory disease. By measuring respiratory impedance, changes in the user's airway due to the presence of respiratory disease can often be detected before external physical symptoms appear. Therefore, early detection of respiratory disease can increase treatment options. Possible respiratory diseases that can be detected include obstruction, pneumonia, inflammation, allergies, lung cancer, bacterial infections, viral infections, the common cold, asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis, congestive heart failure, pneumothorax (lung collapse), and SARS-CoV-2. Some of these respiratory diseases can increase the resistance of the bronchioles in the lungs, thus reducing the amount of air inhaled with each breath and subsequently reducing the amount of oxygen that reaches the pulmonary artery. Therefore, by measuring this deficiency using method 600, it is possible to provide users with early signs of respiratory disease.

[0134] In some implementations, acoustic data can be windowed to remove unwanted acoustic data. For example, depending on where the transducer is positioned and thus where the acoustic signal is generated, some of the acoustic signal reflections may not be related to any part of the user's airway. Instead, these reflections may be the result of acoustic signals interacting with the conduit and / or user interface, and therefore cannot be used to measure parameters related to the user's airway. Thus, these parts of the acoustic data can be discarded before determining the parameter values.

[0135] As noted herein, the type of user interface worn by the user may affect the acoustic data. If the type of user interface being used is known, the acoustic data can be adjusted to eliminate these variations and obtain accurate parameter values. Sensors (such as sensor 130) can be used to help determine the type of user interface worn by the user. These sensors may include acoustic sensors and / or microphones (such as acoustic sensor 141 and microphone 140), cameras (such as camera 150), and other sensors.

[0136] Step 608 of Method 600 performs an action based on the determined value of the parameter. In some implementations, the action may include comparing the parameter value to a baseline value of the parameter to help determine whether the user has a respiratory illness or whether the user's respiratory illness is worsening. Additional actions may then be performed. In some examples, the baseline value is an expected value based on various characteristics of the user, including age, biological sex, social gender role, ethnicity, location, known medical conditions, height, weight, neck circumference, etc. The expected value may be a predetermined value of the parameter from individuals who share one or more of the user's characteristics. The expected value may also be a value based on the average of one or more different individuals who share different characteristics with the user. In some implementations, a parameter value that deviates by a certain amount from the baseline value indicates that the user has a particular respiratory illness. In other implementations, a parameter value that deviates by a certain amount from the baseline value indicates that the user has an unknown respiratory illness and that further follow-up is needed to determine the identity of the respiratory illness.

[0137] Reference values ​​can also be predetermined from individuals diagnosed with specific respiratory diseases. By comparing the user's determined parameter values ​​with predetermined parameter values ​​from individuals diagnosed with specific respiratory diseases, it is possible to determine whether the user currently suffers from the same specific respiratory disease. Furthermore, by comparing the user's parameter values ​​with predetermined parameter values ​​from multiple different individuals known to suffer from different respiratory diseases, the identity of the user's respiratory disease can be determined.

[0138] In other implementations, the baseline value of a parameter is a predetermined value for the same user. By monitoring the user's parameter values ​​over a period of time, the progression of respiratory disease can be tracked, and appropriate interventions can be triggered as needed. Parameter values ​​can be monitored over a day, a week, a month, a year, or other appropriate period. Therefore, the baseline value of the user's parameters can be determined at a first time point, and the current value of the parameters can be determined at a second time point after the first time point. This analytical technique allows for long-term monitoring of parameters to determine long-term trends. If a trend indicates a worsening of a particular medical condition, it can be flagged for the user or an appropriate third party, such as a spouse or healthcare provider.

[0139] In some implementations, the time difference between the current value of a parameter and its baseline value is selected based on which parameter is being measured and / or which respiratory illness is being monitored. For example, to monitor a user's allergies, the parameter value determined in spring (e.g., the first season of the year) can be compared to the parameter value measured in the previous autumn or winter (e.g., the second season of the year) to determine whether the user has an allergy or is likely to develop one in the spring. The parameter value can also be measured over consecutive spring seasons to determine whether the user's allergy is worsening over time.

[0140] The operation may also include combining the determined value of the parameter with other data sources to help determine whether a user has a respiratory illness or is at risk of developing one. For example, if a user's medical record indicates that the user has been previously diagnosed with a respiratory illness, a given value of the parameter may more strongly suggest the current presence of that respiratory illness or another respiratory illness compared to a user who has never been previously diagnosed with one. Other data such as age, biological sex, social gender role, ethnicity, location, known medical conditions, height, weight, and neck circumference may also be used to help determine whether the determined value of the parameter indicates the presence of a respiratory illness. This data can be obtained from the user's medical record, but additionally or alternatively, it can be obtained directly from the user. For example, a user may complete a questionnaire and provide certain data that would otherwise help determine and identify the presence of a potential respiratory illness.

[0141] Additionally, data from other sources may be used. For example, data from any sensor (such as sensor 130) can be used to help evaluate acoustic data. For instance, data from sensors can be used to measure the user's respiratory rate and determine whether the user is breathing abnormally. This determination can be combined with parameter values ​​to provide more insight into whether the user has a respiratory illness. Additional data can be obtained from smart devices such as smartwatches or other wearables, smart speakers, and smart inhalers. This data may include pulse oximetry data and / or heart rate data obtained from smartwatches or other wearables. In yet another implementation, the additional data may include data related to the user of medications. For example, a user with asthma could use a smart inhaler that can track the user's inhaler and the use of various medications (e.g., corticosteroids, bronchodilators). Data representing these uses can be used to help determine the presence, identification, severity, etc., of any potential respiratory illnesses. Further implementations may include additional data generated by medical measurement devices such as pulse oximeters, blood pressure monitors (e.g., blood pressure cuffs), thermometers, heart rate monitors, and sample measurement devices (e.g., blood glucose meters).

[0142] In some implementations, the operation may include activating specific functions of the respiratory therapy system. For example, if a parameter value indicates that the user has a respiratory illness, a drug designed for inhalation may be injected into the airway along with pressurized air to deliver the drug to the user's airway. The drug may be a bronchodilator or another drug designed to help the user recover from a respiratory illness.

[0143] In some implementations, operation may include adjusting various settings of the respiratory therapy system. The respiratory therapy system may typically be used as a positive airway pressure system. Based on measured parameter values, the pressure and / or flow rate of the pressurized air supplied by the respiratory therapy system can be changed. For example, if the measured parameter values ​​indicate that the user's respiratory impedance is higher than expected, the pressurized air pressure can be increased. In another example, the pressurized air supplied to the user's airway can be humidified (e.g., with steam).

[0144] In some implementations, the respiratory therapy system can be configured to operate in different ways. For example, the respiratory therapy system may initially operate as a CPAP system, but then be modified to operate as a BPAP system. The respiratory therapy system may also be modified to operate as an oxygen concentrator or a ventilator.

[0145] These implementations can also be used to monitor the effectiveness of the respiratory therapy system itself. For example, parameter values ​​may be determined when the respiratory therapy system is first used as a CPAP system with specific pressure and flow settings. After a predetermined period (e.g., one hour, one week), the parameter values ​​can be determined again to check whether the user's respiratory condition has been alleviated by using the CPAP system. If not, the settings of the respiratory therapy system can be changed. Thus, in some implementations, the system is a closed-loop system that can analyze data related to its own performance and adjust its settings accordingly.

[0146] In related implementations, the respiratory therapy system can also be used to monitor the user's recovery from respiratory disease, in addition or alternatively, to monitor the progression of the respiratory disease. In these implementations, parameter values ​​may be determined periodically during or after treatment of the respiratory disease (e.g., during medication planning, after inhaler use, etc.). Thus, the effectiveness of the treatment can be monitored using the techniques disclosed herein, which can provide early indication of whether the treatment is working or whether another treatment should be tried.

[0147] In some implementations, the operation may include generating notifications and / or reports, and sending notifications and / or reports to the user or a third party. If the parameter value indicates that the user has or appears to have developed a respiratory illness, this fact may be notified to the user via text message, telephone, email, or text displayed on an electronic display device that can communicate with the respiratory treatment system and other related components, such as sensors. In some implementations, the notification is simply an instruction indicating that the user has developed or is developing a respiratory illness. In other implementations, a complete report containing various information related to the respiratory illness is sent to the user. Third parties to whom notifications and / or reports are sent may include the user's spouse or partner, family, friends, caregivers, healthcare providers, etc. In some implementations, any data related to Method 600 (including acoustic data and other data used) may be stored as part of the user's medical record. In other implementations, therapeutic recommendations may be sent to the user or a third party. Therapeutic recommendations may include recommendations to adjust respiratory therapy device settings to help treat the disease, recommendations to take medications, recommendations to schedule appointments with a healthcare provider (for example, to conduct a more thorough examination of the user's airway), and other recommendations.

[0148] In some implementations, commands can be provided to the user before the start of Method 600, for example, through the system's user interface (user interface 124). For example, determining parameter values ​​may be easier or more accurate for a particular user when the user is in a specific posture or position. The system can instruct the user to move into a specified posture or position, such as standing, sitting, inclined, or lying down. One or more sensors (motion sensor 138 and / or camera 150, for example) can determine the time the user has moved into the specified posture or position. The system can then begin directing an acoustic signal into the user's airway. In another example, these commands can instruct the user to breathe according to a specified pattern for part or all of the execution of Method 600. The commands can instruct the user to hold their breath, breathe slowly, breathe quickly, breathe deeply, breathe shallowly, or breathe in other patterns. In some implementations, the user may also be instructed to force inhale or exhale. The resulting airflow can be measured (for example, using either the microphone 428 and / or sensor 130) to provide additional data related to the user's respiratory condition.

[0149] As noted herein, Method 600 can be implemented using a respiratory therapy system that the user may already be using while sleeping at night, such as a CPAP system. Since the user is already wearing the user interface at night, providing the user interface with a speaker 426 and a microphone 428 is a simple and efficient update that allows for the measurement of parameters on a consistent schedule and enables early detection of respiratory disorders. In some implementations, Method 600 can be performed at the start of a sleep session (e.g., at night when the user goes to sleep) when the user first wears the user interface. When this occurs, the system can instruct the user to breathe normally and direct acoustic signals into the user's airway to determine the parameter values ​​for that sleep session.

[0150] In additional or alternative implementations, method 600 can be performed at the end of every sleep session (e.g., in the morning when the user wakes up) to determine the parameter values. In yet another implementation, method 600 can be performed at both the beginning and end of one or more sleep sessions. In yet another implementation, method 600 can be performed in the middle of a sleep session to measure the parameter values. The performance of method 600 in the middle of a sleep session may be random or based on data related to the user's use of the respiratory therapy system during the sleep session.

[0151] In yet another implementation, Method 600 can be performed to temporarily interrupt the standard operation of the respiratory therapy system. For example, the respiratory therapy system can operate normally as a CPAP system (e.g., during a sleep session). The operation of the motor that supplies positive pressure to the user's airway can be temporarily stopped to direct an acoustic signal into the user's airway and measure parameters. Once the reflection of the acoustic signal is received, the motor can resume normal operation. This timing may include implementations that use a separate speaker to generate the acoustic signal, and implementations that use the motor itself to generate the acoustic signal.

[0152] Method 600 may also include directing acoustic signals separately into the user's airway through both the user's mouth and the user's nose. The acoustic data can be analyzed to separate the two measurements. In some of these implementations, the airflow through either the mouth or the nose can be temporarily blocked (e.g., via a smart mask) to measure the other.

[0153] The duration of Method 600 can also be limited so as not to overly confuse or annoy the user. For example, in some implementations, the operation of the transducer for generating the acoustic signal (whether the transducer is a speaker in the user interface, a motor in a respiratory therapy device, or another transducer) may be relatively noisy, so the transducer may operate for only a short enough period to generate the required amount of acoustic data.

[0154] In some implementations, various steps of Method 600 can also be implemented using respiratory therapy systems other than typical respiratory therapy systems used by users with SDB, such as CPAP systems or BIPAP systems. For example, some users may use specific daytime respiratory support systems such as supplemental oxygen, high-flow nasal oxygen (HFO), or heated, humidified, high-flow oxygen (HHHF). These systems often include some type of user interface worn by the user and a conduit that delivers air between the user interface and the user. These systems can be used to direct acoustic signals into the user's airway and measure the resulting reflexes in order to determine the values ​​of various parameters.

[0155] In some implementations, method 600 includes determining whether the obstruction is an upper airway obstruction or a lower airway obstruction. Lower airway obstructions may indicate infection and / or inflammation, such as pneumonia or asthma. Often, it is difficult to detect and treat lower airway obstructions using conventional devices. Potential lower airway obstructions can be detected by guiding an acoustic signal that can propagate into the user's airway. Furthermore, because these techniques can be used in various respiratory therapy systems, users can treat both upper and lower airway obstructions and detect and treat other respiratory diseases.

[0156] In some implementations, Method 600 can be used as a diagnostic / screening tool. If Method 600 indicates the presence (or potential future presence) of a respiratory disease, the user can decide to visit a healthcare provider for follow-up care. In these implementations, regardless of how Method 600 is implemented, it can be administered to the user at any desired time. For example, even if Method 600 is implemented using a respiratory therapy system that normally operates at night during a sleep session, the user can still utilize the respiratory therapy system to implement Method 600 during the day. In other implementations, Method 600 can be used as part of a treatment routine. For example, as described herein, the administration of a drug (or other therapies used to treat respiratory diseases, such as humidifiers or bronchodilators) can be automatically triggered in response to a measurement parameter indicating the presence (or potential future presence) of a respiratory disease.

[0157] Generally, Method 600 can be implemented using a system that includes a control system having one or more processors and a memory for storing machine-readable instructions. The control system is contigible to the memory, and Method 600 can be executed when the machine-readable instructions are executed by at least one of the processors of the control system. Method 600 can also be implemented using a computer program product (such as a non-temporary computer-readable medium) that contains instructions causing the computer to execute the steps of Method 600 when executed by a computer.

[0158] One or more further implementations and / or claims of the present disclosure can be formed by combining one or more elements, aspects, steps or parts thereof from any one or more of the following claims 1 to 76 with one or more elements, aspects, steps or parts thereof from any one or more of the other claims 1 to 76 or a combination thereof.

[0159] While this disclosure has been described with reference to one or more specific embodiments or implementations, those skilled in the art will recognize that many modifications are possible without departing from the spirit and scope of this disclosure. These implementations and their explicit modifications are each considered to be within the spirit and scope of this disclosure. Additional implementations according to aspects of this disclosure may also be constructed by combining any number of features from any of the implementations described herein.

Claims

1. It is a system that monitors an individual's airway. A control system including one or more processors, Includes memory that stores machine-readable instructions, The control system is connected to the memory, and at least one of the one or more processors executes the machine-readable instructions. The acoustic signal is directed to the airway of the person. (i) a portion of the airway of the individual, (ii) an obstruction within the airway of the individual, or (iii) both of (i) and (ii) generate acoustic data representing one or more reflections of the acoustic signal. By analyzing the aforementioned acoustic data, the values ​​of the parameters related to the airway of the individual are determined. Receiving additional data related to the individual other than the aforementioned acoustic data, The value of the parameter is changed based on the additional data, The operation is performed based on the changed parameter values ​​and the additional data. A system that is configured in a certain way.

2. A computer program that includes instructions, and when such instructions are executed by a computer, causes the computer to perform each of the steps described in claim 1.

3. The computer program according to claim 2, stored in a non-temporary computer-readable medium.

4. It is a system that monitors an individual's airway. A breathing apparatus configured to supply pressurized air, and A breathing system including a user interface connected to the breathing apparatus via a conduit, which engages with the individual and is configured to help guide the supplied pressurized air into the individual's airway, Memory for storing machine-readable instructions, A control system including one or more processors, wherein the processors execute the machine-readable instructions. The acoustic signal is guided to the individual's airway via the conduit and the user interface. (i) a portion of the airway of the individual, (ii) an obstruction within the airway of the individual, or (iii) both of (i) and (ii) generate acoustic data representing one or more reflections of the acoustic signal. By analyzing the aforementioned acoustic data, the values ​​of the parameters related to the airway of the individual are determined. Receiving additional data related to the individual other than the aforementioned acoustic data, The value of the parameter is changed based on the additional data, A system configured to perform an action based on the changed parameter value and the additional data.

5. The system according to claim 4, wherein the parameters are the impedance of the airway of the individual, the resonant frequency of the airway of the individual, the location of the obstruction, the size of the obstruction, or any combination thereof.

6. The system according to claim 4 or 5, wherein the operation includes injecting a drug into the airway.

7. The system according to any one of claims 4 to 6, wherein the operation includes sending or displaying a notification or report to the individual or a third party, generating a therapeutic recommendation, or any combination thereof.

8. The system according to any one of claims 4 to 7, wherein the operation includes adjusting the pressure, flow rate, or both of the pressurized air supplied to the airway of the individual.

9. The system according to claim 8, wherein the pressurized air is supplied to the airway of the individual at a first pressure, and the operation includes supplying the pressurized air to the airway of the individual at a second pressure greater than the first pressure by the breathing apparatus.

10. The respiratory system according to any one of claims 4 to 9, wherein the respiratory system initially operates as a positive airway pressure system, and the operation includes adjusting the respiratory system to operate as an oxygen concentrator, a ventilator, or both.

11. The system according to any one of claims 4 to 10, wherein the control system is configured to execute the machine-readable command and compare the determined value of the parameter with a previously acquired reference value of the parameter.

12. The system according to claim 11, wherein the operation is based on a comparison between the determined value of the parameter and the predetermined reference value of the parameter.

13. The system according to claim 11 or 12, wherein the reference value of the parameter is obtained in advance from the individual at a first time, and the control system is configured to execute the machine-readable command to determine the value of the parameter at a second time after the first time.

14. The system according to any one of claims 11 to 13, wherein the reference value of the parameter is obtained in advance from another individual who shares one or more characteristics with the individual.

15. The system according to any one of claims 4 to 14, wherein the value of the parameter indicates whether or not the individual is suffering from a respiratory-related illness or disease.

16. The system according to any one of claims 4 to 15, wherein the breathing apparatus includes a motor, and the acoustic signal is generated by the operation of the motor.

17. The system according to any one of claims 4 to 16, further comprising a speaker configured to generate the aforementioned acoustic signal.

18. The system according to any one of claims 4 to 17, wherein the control system is configured to execute the machine-readable command to modulate the frequency of the acoustic signal, the amplitude of the acoustic signal, or both.

19. The system according to any one of claims 4 to 18, further comprising a microphone configured to detect the reflection of the acoustic signal and generate audio data.

20. The control system executes the machine-readable instruction, The person is instructed to move to assume a designated position, The system according to any one of claims 4 to 19, configured to direct the acoustic signal into the airway of the individual in response to determining that the individual has moved to the designated position.

21. The control system executes the machine-readable instruction, The person is instructed to breathe according to a specified breathing pattern, The system according to any one of claims 4 to 20, configured to direct the acoustic signal to the airway of the individual in response to determining that the individual is breathing according to the specified breathing pattern.

22. The control system executes the machine-readable instruction, Having determined that the aforementioned individual is currently in the first position, The aforementioned individual is instructed to move to a second position, In response to determining that the individual has moved from the first posture to the second posture, the acoustic signal is directed into the airway of the individual, and The system according to any one of claims 4 to 21, configured to analyze the acoustic data and determine the value of the parameter when the individual is in the second posture.

23. The control system executes the machine-readable instruction, The individual has decided to breathe according to the first breathing pattern, The person is instructed to begin breathing according to the second breathing pattern, In response to determining that the individual has begun breathing according to the second breathing pattern, the acoustic signal is directed to the airway of the individual, and The system according to any one of claims 4 to 22, configured to analyze the acoustic data and determine the value of the parameter when the individual breathes according to the second breathing pattern.

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