System and method for monitoring comorbidities

Abstract

A system includes a respiratory therapy system, a memory device, and a control system. The respiratory therapy system includes a respiratory therapy device supplying pressurized air and a user interface connected via a catheter to the respiratory therapy device to direct the pressurized air to the user's airway. The memory device stores machine-readable instructions. The control system includes a processor to execute the machine-readable instructions to: generate data associated with the user of the respiratory therapy system during a current sleep period; analyze the generated data to determine a value of a first indicator associated with sleep apnea (SDB); analyze the generated data to determine a value of a second indicator associated with a health condition other than SDB; and cause an action to be performed based at least in part on the determined value of the second indicator.

Description

[0001] Cross-reference of related applications

[0002] This application claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 080,344, filed on September 18, 2020, which is incorporated herein by reference. Technical Field

[0003] This disclosure generally relates to systems and methods for analyzing data generated during an individual's use of a respiratory therapy system, and more specifically to systems and methods for analyzing data generated during a user's use of a respiratory therapy system to determine a first indicator associated with sleep-disordered breathing and a second indicator associated with health conditions other than sleep-disordered breathing. Background Technology

[0004] Many individuals suffer from sleep-related and / or respiratory conditions, such as, for example, sleep-disordered breathing (SDB), which may include obstructive sleep apnea (OSA), central sleep apnea (CSA), other types of apnea such as mixed apnea and hypopnea, and respiratory effort-related microarousing (RERA). These individuals may also have other health conditions (which may be referred to as comorbidities), such as insomnia (characterized by, for example, difficulty falling asleep, frequent or prolonged awakenings after initial sleep onset and / or early awakenings with inability to fall back asleep), periodic limb tic disorder (PLMD), restless legs syndrome (RLS), Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity-related hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disease (NMD), rapid eye movement (REM) behavior disorder (also known as RBD), dream behavior evolution (DEB), hypertension, diabetes, stroke, and chest wall disorders. It can be difficult to accurately identify and monitor these other health conditions. In individuals using respiratory therapy systems to treat sleep-related conditions, the use of the respiratory therapy system can influence the severity of these health conditions. Therefore, it would be advantageous to be able to analyze data associated with an individual's use of a respiratory therapy system to determine the characteristics, severity, and / or progression of any other health condition. This disclosure relates to systems, devices, and methods that allow the use of data associated with an individual's use of a respiratory therapy system to identify and / or monitor health conditions. Summary of the Invention

[0005] According to some embodiments of this disclosure, a system for monitoring a user's sleep periods includes a respiratory therapy system, a memory device, 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 coupled to the respiratory therapy device via a conduit and configured to engage the user and assist in directing the supplied pressurized air into the user's airway. The memory device stores machine-readable instructions. The control system is coupled to the memory device and includes one or more processors configured to execute the machine-readable instructions to: generate user-associated data during a current sleep period; analyze the generated data to determine a value of a first indicator associated with sleep-disordered breathing (SDB); analyze the generated data to determine a value of a second indicator associated with a health condition other than SDB; and cause an action to be performed, at least in part, based on the determined value of the second indicator.

[0006] According to some implementations, one or more processors of the control system are further configured to execute machine-readable instructions to: track a second indicator over multiple sleep periods; determine a value of the second indicator for each of the multiple sleep periods; determine (i) the duration of use of the respiratory therapy system, (ii) the value of one or more settings of the respiratory therapy system, (iii) or both for each of the multiple sleep periods; and identify (i) the optimal duration of use of the respiratory therapy system, (ii) the optimal value of one or more settings of the respiratory therapy system, or (iii) both, to treat a health condition.

[0007] According to some implementations, one or more processors of the control system are further configured to execute machine-readable instructions to: receive historical data associated with one or more previous sleep periods of the user; analyze the historical data to determine a value of a second indicator for each of the one or more previous sleep periods; and compare the value of the second indicator determined for each of the one or more previous sleep periods with the value of the second indicator determined for the current sleep period.

[0008] According to some implementations, one or more processors of the control system are further configured to execute machine-readable instructions to: determine the severity of a health condition based at least in part on the value of a second indicator determined for the current sleep period; generate data during one or more subsequent sleep periods; determine the value of the second indicator for each of the one or more subsequent sleep periods; determine an updated severity of the health condition based at least in part on the value of the second indicator determined for each of the one or more subsequent sleep periods; and cause an action to be performed based at least in part on the updated severity of the health condition.

[0009] According to some implementations, one or more processors of the control system are further configured to execute machine-readable instructions to: receive additional data associated with the user when the user is awake; analyze the additional data to determine the value of a third indicator associated with the health status; and cause an action to be performed based at least in part on the determined value of the third indicator associated with the health status.

[0010] According to some embodiments of this disclosure, a method for monitoring a user's sleep periods includes generating data associated with an individual and a respiratory therapy system during a current sleep period. The method further includes analyzing the generated data to determine values ​​of a first indicator associated with sleep-disordered breathing (SDB). The method also includes analyzing the generated data to determine values ​​of a second indicator associated with health conditions other than SDB. The method further includes performing an action based at least in part on the determined value of the second indicator.

[0011] According to some implementations, the method further includes tracking a second indicator across multiple sleep periods. The method also includes determining a value for the second indicator for each of the multiple sleep periods. The method further includes determining (i) the duration of use of the respiratory therapy system, (ii) values ​​of one or more settings of the respiratory therapy system, or (iii) both for each of the multiple sleep periods. The method also includes identifying (i) the optimal duration of use of the respiratory therapy system, (ii) the optimal value of one or more settings of the respiratory therapy system, or (iii) both, to treat a health condition.

[0012] According to some implementations, the method further includes receiving historical data associated with one or more previous sleep periods of the user. The method also includes analyzing the historical data to determine a value for a second indicator for each of the one or more previous sleep periods. The method further includes comparing the value of the second indicator determined for each of the one or more previous sleep periods with a value of a second indicator determined for the current sleep period.

[0013] According to some implementations, the method further includes determining the severity of the health condition based at least in part on the value of a second indicator determined for the current sleep period. The method also includes generating data during one or more subsequent sleep periods. The method further includes determining the value of the second indicator for each of the one or more subsequent sleep periods. The method further includes determining an updated severity of the health condition based at least in part on the value of the second indicator determined for each of the one or more subsequent sleep periods. The method further includes causing an action to be performed based at least in part on the updated severity of the health condition.

[0014] According to some implementations, the method further includes receiving additional data associated with the user while awake. The method also includes analyzing the additional data to determine a value of a third indicator associated with health status. The method further includes performing an action based at least in part on the determined value of the third indicator associated with health status.

[0015] The above overview is not intended to represent every embodiment or aspect of this disclosure. Additional features and benefits of this disclosure will become apparent from the following detailed description and accompanying drawings. Attached Figure Description

[0016] Figure 1 This is a functional block diagram of a system for monitoring sleep periods according to some embodiments of the present disclosure;

[0017] Figure 2 This is based on some embodiments of the present disclosure. Figure 1 A perspective view of the system, the system's users, and the users' bed partners;

[0018] Figure 3 The illustration shows an exemplary timeline of sleep periods according to some embodiments of the present disclosure;

[0019] Figure 4 The illustrations show some embodiments of the present disclosure. Figure 3 An exemplary sleep graph associated with sleep periods;

[0020] Figure 5 This is a flowchart of a first method for monitoring an individual during sleep when a user is using a respiratory therapy system, according to some embodiments of the present disclosure;

[0021] Figure 6 This is a flowchart illustrating a second method for monitoring an individual during sleep periods when a user is using a respiratory therapy system, according to some embodiments of this disclosure; and

[0022] Figure 7 This is a flowchart of a third method for monitoring an individual during sleep when a user is using a respiratory therapy system, according to some embodiments of this disclosure.

[0023] While this disclosure allows for various modifications and alternatives, specific implementations and embodiments have been illustrated by example in the accompanying drawings and will be described in detail herein. However, it should be understood that this disclosure is not intended to be limited to the specific forms disclosed; rather, it will cover all modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure as defined by the appended claims. Detailed Implementation

[0024] This disclosure is described with reference to the accompanying drawings, in which the same reference numerals are used throughout the drawings to denote similar or equivalent elements. The drawings are not drawn to scale and are provided merely for illustration. Several aspects of this disclosure are described below with reference to exemplary applications for illustrative purposes.

[0025] Many individuals suffer from sleep-related and / or respiratory conditions such as periodic limb tic disorder (PLMD), restless legs syndrome (RLS), sleep-disordered breathing (SDB) such as obstructive sleep apnea (OSA), central sleep apnea (CSA) and other types of apnea, effort-related microarousing (RERA), Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity-related hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular diseases (NMD), and chest wall disorders. Obstructive sleep apnea (OSA), a form of sleep-disordered breathing (SDB), is characterized by events including: closure or obstruction of the upper airway during sleep caused by a combination of abnormally small loss of normal muscle tone in the upper airway and the areas of the tongue, soft palate, and posterior oropharyngeal walls. Central sleep apnea (CSA) is another form of sleep-disordered breathing. CSA occurs when the brain temporarily stops sending signals to the muscles that control breathing. Other types of apnea include hypoventilation, hyperventilation, and hypercapnia. Hypopnea is typically characterized by slow or shallow breathing caused by a narrowed airway, rather than airway obstruction. Hyperventilation is typically characterized by an increase in the depth and / or rate of breathing. Hypercapnia is typically characterized by an increase or excess of carbon dioxide in the bloodstream, usually caused by insufficient breathing. An effort-related microarousals (RERA) event is typically characterized by an increased respiratory effort lasting ten seconds or longer, resulting in a microarousal from sleep, and does not meet the criteria for apnea or hypopnea events. RERA is defined as a series of breaths characterized by increased respiratory effort resulting in a microarousal from sleep, but which does not meet the criteria for apnea or hypopnea. These events must simultaneously meet two of the following criteria: (1) a pattern of gradually increasing negative esophageal pressure terminating with a sudden change in pressure to a lower negative pressure level and microarousal, and (2) the event lasting 10 seconds or longer. In some implementations, nasal cannula / pressure transducer systems are satisfactory and reliable for detecting RERA. RERA detectors can be based on actual airflow signals derived from the respiratory therapy device. For example, airflow limitation measurements can be determined based on airflow signals. The micro-awakening measurement can then be derived from the airflow limitation measurement and the measurement of a sudden increase in ventilation. Such a method is described in WO 2008 / 138040, assigned to ResMed Ltd., and U.S. Patent No. 9,358,353, the disclosure of each of which is incorporated herein by reference in its entirety.

[0026] Cheyne-Stokes respiration (CSR) is another form of SDB. CSR is a condition in which a patient's respiratory controller exhibits alternating rhythmic cycles of increased and decreased ventilation, known as CSR cycles. CSR is characterized by repeated deoxygenation and reoxygenation of arterial blood. OHS is defined as a combination of severe obesity and chronic hypercapnia upon awakening, without other known causes of hypoventilation. Symptoms include dyspnea, morning headache, and excessive daytime sleepiness. COPD includes any of the lower airway diseases with certain common characteristics, such as increased resistance to air movement, prolonged expiratory phase of breathing, and loss of normal lung elasticity. NMD includes a wide range of diseases and conditions that impair muscle function directly through intrinsic muscular pathology or indirectly through neuropathy. Chest wall disorders are a group of chest wall deformities that result in inefficient connection between the respiratory muscles and the chest wall.

[0027] Many of these conditions are characterized by specific events that may occur when an individual is sleeping (e.g., snoring, sleep apnea, hypopnea, restless legs, sleep disturbances, suffocation, rapid heart rate, difficulty breathing, asthma attacks, seizures, convulsions, or any combination thereof). Various types of data can be used to monitor the health of individuals with any of the aforementioned types of sleep-related and / or respiratory (or other) conditions. However, it is often difficult to collect accurate data in a way that does not interrupt or interfere with the user's sleep or any treatment the user may undergo during sleep. Therefore, it is advantageous to utilize a treatment-specific system that includes various sensors to generate and collect data without interfering with the user, their sleep, or their treatment.

[0028] The Apnea-Hypopnea Index (AHI) is an index used to indicate the severity of sleep apnea during a sleep period. The AHI is calculated by dividing the number of apnea and / or hypopnea events a user experiences during a sleep period by the total number of hours of sleep in that period. An event can be, for example, an apnea lasting at least 10 seconds. An AHI less than 5 is considered normal. An AHI greater than or equal to 5 but less than 15 is considered a sign of mild sleep apnea. An AHI greater than or equal to 15 but less than 30 is considered a sign of moderate sleep apnea. An AHI greater than or equal to 30 is considered a sign of severe sleep apnea. In children, an AHI greater than 1 is considered abnormal. When the AHI is normal, or when the AHI is normal or mild, sleep apnea can be considered “controlled.” The AHI can also be used in conjunction with oxygen desaturation levels to indicate the severity of obstructive sleep apnea.

[0029] refer to Figure 1The illustration shows a system 100 according to some embodiments of the present disclosure. System 100 can be used to detect, identify, treat, and / or monitor respiratory diseases (and / or other diseases), such as before any external physical symptoms of these diseases manifest. 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 embodiments, system 100 also includes a respiratory therapy system 120, which includes a respiratory therapy device 122.

[0030] The control system 110 includes one or more processors 112 (hereinafter referred to as processor 112). The control system 110 is typically used to control (e.g., drive) various components of the system 100 and / or analyze data acquired and / or generated by the components of the system 100. The processor 112 may be a general-purpose or special-purpose processor or a microprocessor. Although in Figure 1 A processor 112 is shown, but the control system 110 may include any suitable number of processors (e.g., one processor, two processors, five processors, ten processors, etc.), which may be in a single housing or located remotely from each other. The control system 110 (or any other control system) or a portion thereof, such as processor 112 (or any other processor or a portion thereof), may be used to perform one or more steps of any of the methods described and / or claimed herein. The control system 110 may be coupled to, for example, the housing of user device 170 and / or the housing of one or more sensors among sensors 130 and / or housed therein. The control system 110 may be centralized (within one such housing) or distributed (within two or more physically distinct such housings). In such embodiments including two or more housings containing the control system 110, such housings may be adjacent to and / or located remotely from each other.

[0031] Memory device 114 stores machine-readable instructions executable by processor 112 of control system 110. Memory device 114 can be any suitable computer-readable storage device or medium, such as, for example, random or serial access memory devices, hard disk drives, solid-state drives, flash memory devices, etc. Although Figure 1A memory device 114 is shown, but system 100 may include any suitable number of memory devices 114 (e.g., one memory device, two memory devices, five memory devices, ten memory devices, etc.). The memory device 114 may be coupled to or housed within 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 among the sensors 130, or any combination thereof. Similar to control system 110, the memory device 114 may be centralized (within one such housing) or distributed (within two or more physically different such housings).

[0032] In some embodiments, memory device 114 stores a user profile associated with a user. The user profile may include, for example, user-associated demographic information, user-associated biostatistical information, user-associated medical information, self-reported user feedback, user-associated sleep parameters (e.g., sleep-related parameters recorded from one or more earlier sleep periods) or any combination thereof. Demographic information may include, for example, information indicating the user's age, gender, ethnicity, family medical history (such as a 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 associated with the user, medication use, or both. Medical information data may also include user-associated fall risk assessments (e.g., a fall risk score using the Morse Fall Scale), multiple sleep latency test (MSLT) results or scores, and / or Pittsburgh Sleep Quality Index (PSQI) scores or values. Self-reported user feedback may include prompts for the following information: self-reported subjective sleep rating (e.g., poor, average, excellent), user's self-reported subjective stress level, user's self-reported subjective fatigue level, user's self-reported subjective health status, user's recent life events, or any combination thereof.

[0033] Electronic interface 119 is configured to receive data (e.g., physiological data and / or acoustic data) from one or more sensors 130, such that the data can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. Electronic interface 119 can communicate with one or more sensors 130 using wired or wireless connections (e.g., using RF communication protocols, WiFi communication protocols, Bluetooth communication protocols, IR communication protocols, via cellular networks, via any other optical communication protocols, etc.). 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. Electronic interface 119 may also include one or more processors and / or one or more memory devices that are the same as or similar to processor 112 and memory device 114 described herein. In some embodiments, electronic interface 119 is coupled to or integrated therein with user device 170. In other embodiments, electronic interface 119 is coupled to or integrated therewith (e.g., in a housing) with control system 110 and / or memory device 114.

[0034] As described above, in some embodiments, system 100 may optionally include a respiratory therapy system 120 (also referred to as a respiratory pressure therapy system). The respiratory therapy system 120 may include a respiratory therapy device 122 (also referred to as a respiratory pressure device), a user interface 124 (also referred to as a mask or patient interface), a catheter 126 (also referred to as a tube or air circuit), a display device 128, a humidifier canister 129, or any combination thereof. In some embodiments, one or more of the control system 110, memory device 114, display device 128, sensor 130, and humidifier canister 129 are part of the respiratory therapy device 122. Respiratory pressure therapy refers to applying a controlled target pressure of air to the inlet of the user's airway throughout the user's respiratory cycle, which is nominally positive relative to atmosphere (e.g., opposite to negative pressure therapy such as a canister ventilator or a chest tube). The respiratory therapy system 120 is typically used to treat individuals with one or more sleep-related respiratory conditions (e.g., obstructive sleep apnea, central sleep apnea, or mixed sleep apnea), other respiratory conditions such as COPD, or other conditions that cause respiratory insufficiency that may manifest during sleep or wakefulness.

[0035] The respiratory therapy device 122 is typically used to generate pressurized air to be delivered to a user (e.g., using one or more electric motors (such as blower motors) that drive one or more compressors). In some embodiments, the respiratory therapy device 122 generates a continuous, constant air pressure to be delivered to the user. In other embodiments, 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 many other embodiments, the respiratory therapy device 122 is configured to generate a variety of different air pressures within a predetermined range. For example, the respiratory therapy device 122 may deliver at least about 6 cm H2O, at least about 10 cm H2O, at least about 20 cm H2O, about 6 cm H2O to about 10 cm H2O, about 7 cm H2O to about 12 cm H2O, etc. The respiratory therapy device 122 may also deliver pressurized air at predetermined flow rates, for example, between about -20 L / min and about 150 L / min, while maintaining positive pressure (relative to ambient pressure). In some embodiments, the control system 110, memory device 114, electronic interface 119, or any combination thereof may be coupled to and / or housed within the housing of the respiratory therapy device 122.

[0036] User interface 124 engages with a portion of the user's face and delivers pressurized air from respiratory therapy device 122 to the user's airway to help prevent airway narrowing and / or collapse during sleep. This can also increase the user's oxygen uptake during sleep. Depending on the treatment to be applied, user interface 124 may, for example, form a seal with an area or portion of the user's face to facilitate gas delivery for treatment at a pressure sufficiently different from ambient pressure, for example, at a positive pressure of about 10 cm H2O relative to ambient pressure. For other forms of treatment, such as oxygen delivery, the user interface may not include a seal sufficient to facilitate the delivery of gas supply to the airway at a positive pressure of about 10 cm H2O.

[0037] In some implementations, the user interface 124 is or includes a mask that covers the user's nose and mouth (e.g., as shown in the image). Figure 2(As shown). Alternatively, user interface 124 is or includes a nasal mask that supplies air to the user's nose or a nasal pillow that delivers air directly to the user's nostrils. User interface 124 may include a retaining clip assembly and a conformal cushion (e.g., silicone, plastic, foam, etc.), wherein the retaining clip assembly has multiple retaining clips (e.g., including hook and loop fasteners) for positioning and / or stabilizing user interface 124 on a portion of user interface 124 in a desired position (e.g., face) for the user, and the conformal cushion helps to provide an airtight seal between user interface 124 and the user. In some embodiments, user interface 124 may include a connector 127 and one or more vents 125. One or more vents 125 may be used to allow the user's exhaled carbon dioxide and other gases to escape. In other embodiments, user interface 124 includes a mouthpiece (e.g., a night-protective mouthpiece molded to conform to the user's teeth, a jaw repositioning device, etc.). In some embodiments, connector 127 is different from user interface 124 (and / or conduit 126), but may be coupled to user interface 124 (and / or conduit 126). Connector 127 is configured to connect user interface 124 and fluidly connect to conduit 126.

[0038] The conduit 126 allows air to flow between two components of the respiratory therapy system 120, such as the respiratory therapy device 122 and the user interface 124. In some embodiments, there may be separate conduit branches for inhalation and exhalation. In other embodiments, a single branch conduit is used for both inhalation and exhalation. Typically, the respiratory therapy system 120 forms an air passage extending between the motor of the respiratory therapy device 122 and the user and / or user airway. Therefore, the air passage typically includes at least the motor of the respiratory therapy device 122, the user interface 124, and the conduit 126.

[0039] One or more of the respiratory therapy device 122, user interface 124, catheter 126, display device 128, and humidifier 129 may include one or more sensors (e.g., pressure sensors, flow sensors, or more generally any of the other sensors 130 described herein). These one or more sensors may be used, for example, to measure the air pressure and / or flow rate of the pressurized air supplied by the respiratory therapy device 122.

[0040] Display device 128 is typically used to display images, including still images, video images, or both, and / or information about the respiratory therapy device 122. For example, display device 128 may provide information about the status of the respiratory therapy device 122 (e.g., whether the respiratory therapy device 122 is on / off, the pressure of the air delivered by the respiratory therapy device 122, the temperature of the air delivered by the respiratory therapy device 122, etc.) and / or other information (e.g., sleep scores or treatment scores such as sleep ratings). The rating, as described in WO 2016 / 061629 and US 2017 / 0311879 (each of which is incorporated herein by reference in its entirety), the current date / time, the user's personal information, a questionnaire for the user, etc. In some embodiments, the display device 128 acts as a human-machine interface (HMI) including a graphical user interface (GUI) configured to display images as an input interface. The display device 128 may be an LED display, an OLED display, an LCD display, etc. The input interface may be, for example, a touch screen or touch-sensitive substrate, a mouse, a keyboard, or any sensor system configured to sense input made by a human user interacting with the respiratory therapy device 122.

[0041] The humidifier canister 129 is coupled to or integrated into the respiratory therapy device 122 and includes a water reservoir for humidifying pressurized air delivered from the respiratory therapy device 122. The respiratory therapy device 122 may include a heater for heating the water in the humidifier canister 129 to humidify the pressurized air supplied to the user. Additionally, in some embodiments, the conduit 126 may also include a heating element (e.g., coupled to and / or embedded therein) that heats the pressurized air delivered to the user. The humidifier canister 129 may be fluidly coupled to a water vapor inlet of an air passage and deliver water vapor into the air passage via the water vapor inlet, or it may be formed linearly with the air passage as part of the air passage itself. In other embodiments, the respiratory therapy device 122 or the conduit 126 may include a waterless humidifier. The waterless humidifier may be integrated with sensors connected to other sensors located elsewhere in the system 100.

[0042] The respiratory therapy system 120 can be used, for example, as 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 to the user (e.g., determined by a sleep physician). An APAP system automatically changes the air pressure delivered to the user based at least in part on, for example, respiratory data associated with 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 below the first predetermined pressure (e.g., expiratory positive airway pressure or EPAP).

[0043] refer to Figure 2 The illustration shows a system 100 according to some embodiments. Figure 1As part of the respiratory therapy system 120, the user 210 and bed partner 220 are located in bed 230 and lie on mattress 232. A user interface 124 (e.g., a full-face mask) can be worn by the user 210 during sleep periods. The user interface 124 is fluidly connected and / or connected to the respiratory therapy device 122 via conduit 126. The respiratory therapy device 122, in turn, delivers pressurized air to the user 210 via conduit 126 and user interface 124 to increase air pressure in the user 210's throat to help prevent airway closure and / or narrowing during sleep periods. 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 also include a humidifier tank 129 for storing water for humidifying the pressurized air. The respiratory therapy device 122 can be positioned as follows: Figure 2 The device is placed on a bedside table 240 directly adjacent to the bed 230, or more typically on any surface or structure usually 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.

[0044] Return to reference Figure 1 The system 100 includes one or more sensors 130, such as 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 photoplethysmography (PPG) sensor 154, an electrocardiogram (ECG) sensor 156, an electroencephalogram (EEG) sensor 158, a capacitive sensor 160, a force sensor 162, a strain gauge sensor 164, an electromyography (EMG) sensor 166, an oxygen sensor 168, an analyte sensor 174, a humidity sensor 176, a light detection and ranging (LiDAR) sensor 178, or any combination thereof. Typically, each of the one or more sensors 130 is configured to output sensor data received and stored in a memory device 114 or one or more other memory devices. Sensor 130 may also include an electrooculogram (EOG) sensor, a peripheral oxygen saturation (SpO2) sensor, a skin conductance response (GSR) sensor, a carbon dioxide (CO2) sensor, or any combination thereof.

[0045] While 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, capacitive sensor 160, force sensor 162, strain gauge sensor 164, EMG sensor 166, oxygen sensor 168, analyte sensor 174, humidity sensor 176, and LiDAR sensor 178, more generally, one or more sensors 130 may include any combination and any number of each of the sensors described and / or shown herein.

[0046] One or more sensors 130 can be used to generate, for example, physiological data, acoustic data, or both, which are communicated with the user of the respiratory therapy system 120 (such as...). Figure 2 The user 210), the respiratory therapy system 120, and both the user and the respiratory therapy system 120, or other entities, objects, activities, etc., are associated. Physiological data generated by one or more sensors in the sensor 130 can be used by the control system 110 to determine sleep-wake signals and one or more sleep-related parameters associated with the user during sleep periods. Sleep-wake signals may indicate one or more sleep stages (sometimes referred to as sleep states), including sleep, wakefulness, relaxation, wakefulness, micro-awakeness, or different sleep stages such as rapid eye movement (REM) stages (which may include both typical and atypical REM stages), a first non-REM stage (commonly referred to as "N1"), a second non-REM stage (commonly referred to as "N2"), a third non-REM stage (commonly 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 in, for example, WO 2014 / 047310, US 10,492,720, US 10,660,563, US 2020 / 0337634, WO 2017 / 132726, WO2019 / 122413, US 2021 / 0150873, WO 2019 / 122414, and US 2020 / 0383580, each of which is incorporated herein by reference in its entirety.

[0047] The sleep-wake signal can also be timestamped to indicate the time the user enters bed, the time the user leaves bed, the time the user attempts to fall asleep, etc. The sleep-wake signal can be measured during the sleep period by one or more sensors in sensor 130 at a predetermined sampling rate, such as, for example, one sample per second, one sample every 30 seconds, one sample per minute, etc. Examples of one or more sleep-related parameters that can be determined for the user based at least in part on the sleep-wake signal during the sleep period include total time in bed, total sleep time, total wake time, sleep onset latency, wake-up parameters after sleep onset, sleep efficiency, fragmentation index, amount of time to fall asleep, consistency of breathing rate, time to fall asleep, wake-up time, sleep disturbance rate, number of movements, or any combination thereof.

[0048] Physiological and / or acoustic data generated by one or more sensors 130 can also be used to determine respiratory signals associated with the user during sleep periods. Respiratory signals typically indicate the user's respiration / breathing during sleep periods. Respiratory signals may indicate, for example, respiratory rate, respiratory rate variability, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory amplitude ratio, inspiratory-expiratory duration ratio, number of events per hour, event pattern, pressure setting of the respiratory therapy device 122, or any combination thereof. Events may include snoring, sleep apnea, central sleep apnea, obstructive sleep apnea, mixed sleep apnea, hypoventilation, RERA, airflow limitation (e.g., an event indicating increased effort despite increased intrathoracic negative pressure without increased airflow), mask leakage (e.g., from user interface 124), restless legs, sleep disturbance, apnea, tachycardia, heart rate variability, dyspnea, asthma attack, seizure, convulsion, fever, cough, sneezing, snoring, wheezing, presence of illness such as the common cold or influenza, increased stress levels, etc. The event can be detected by any means known in the art, such as those described in, for example, US 5,245,995, US 6,502,572, WO 2018 / 050913, WO 2020 / 104465, each of which is incorporated herein by reference in its entirety.

[0049] Pressure sensor 132 outputs pressure data that can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. In some embodiments, pressure sensor 132 is an air pressure sensor (e.g., an atmospheric pressure sensor) that generates sensor data indicating the user's breathing (e.g., inhalation and / or exhalation) and / or ambient pressure of respiratory therapy system 120. In such embodiments, pressure sensor 132 can be coupled to or integrated into respiratory therapy device 122. Pressure sensor 132 can be, for example, a capacitive sensor, an electromagnetic sensor, an inductive sensor, a resistive sensor, a piezoelectric sensor, a strain gauge sensor, an optical sensor, a potentiometric sensor, or any combination thereof. In one example, pressure sensor 132 can be used to determine a user's blood pressure.

[0050] The flow sensor 134 outputs flow data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. In some embodiments, 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 embodiments, the flow sensor 134 may be coupled to or integrated into 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, for example, a rotary flow meter (e.g., a Hall effect flow meter), a turbine flow meter, an orifice plate flow meter, an ultrasonic flow meter, a hot wire sensor, an eddy current sensor, a membrane sensor, or any combination thereof.

[0051] Temperature sensor 136 outputs temperature data that can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. In some embodiments, temperature sensor 136 generates temperature data indicating the following: user's core body temperature, user 210's skin temperature, the temperature of air flowing from respiratory therapy device 122 and / or through conduit 126, temperature in user interface 124, ambient temperature, or any combination thereof. Temperature sensor 136 can 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.

[0052] Motion sensor 138 outputs motion data that can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. Motion sensor 138 can be used to detect user movement during sleep and / or movement of any component of respiratory therapy system 120 (such as respiratory therapy device 122, user interface 124, or catheter 126). Motion sensor 138 may include one or more inertial sensors, such as accelerometers, gyroscopes, and magnetometers. Motion sensor 138 can be used to detect motion or acceleration associated with an arterial pulse, such as a pulse in or around the user's face and near user interface 124, and is configured to detect characteristics of the pulse shape, velocity, amplitude, or volume. In some embodiments, motion sensor 138 alternatively or additionally generates one or more signals representing the user's body movement, from which signals representing the user's sleep state can be obtained, for example, via the user's respiratory movements.

[0053] The output of microphone 140 may be acoustic data stored in memory device 114 and / or analyzed by processor 112 of control system 110. The acoustic data generated by microphone 140 can be reproduced as one or more sounds (e.g., sounds from the user) during a sleep period to determine (e.g., using control system 110) one or more sleep-related parameters, as further described herein. The acoustic data from microphone 140 can also be used to identify (e.g., using control system 110) events experienced by the user during a sleep period, as further described herein. In other embodiments, the acoustic data from microphone 140 represents noise associated with respiratory therapy system 120. In some embodiments, system 100 includes a plurality of microphones (e.g., two or more microphones and / or a microphone array with beamforming) such that sound data generated by each of the plurality of microphones can be used to distinguish sound data generated by another of the plurality of microphones. Microphone 140 can generally be coupled to or integrated into respiratory therapy system 120 (or system 100) in any configuration. For example, microphone 140 may be disposed inside respiratory therapy device 122, user interface 124, conduit 126, or other components. Microphone 140 may also be disposed adjacent to or connected to the exterior of respiratory therapy device 122, user interface 124, conduit 126, or any other component. Microphone 140 may also be a component of user device 170 (e.g., microphone 140 is a microphone for a smartphone). Microphone 140 may be integrated into user interface 124, conduit 126, respiratory therapy device 122, or any combination thereof. Typically, microphone 140 may be located at any point within or adjacent to the air passage of respiratory therapy system 120, which includes at least the motor of respiratory therapy device 122, user interface 124, and conduit 126. Therefore, the air passage may also be referred to as an acoustic passage.

[0054] Speaker 142 outputs sound waves that are normally audible to the user. In one or more embodiments, the sound waves may be audible to the user of system 100 or inaudible to the user of the system (e.g., ultrasound). Speaker 142 may be used, for example, as an alarm clock or to play alarms or messages to the user (e.g., in response to an event). In some embodiments, speaker 142 may be used to transmit acoustic data generated by microphone 140 to the user. Speaker 142 may be coupled to or integrated into respiratory therapy device 122, user interface 124, catheter 126, or user device 170.

[0055] Microphone 140 and speaker 142 can be used as separate devices. In some embodiments, microphone 140 and speaker 142 can be combined into an acoustic sensor 141 (e.g., a SONAR sensor), as described, for example, in WO 2018 / 050913 and WO2020 / 104465, each of which is incorporated herein by reference in its entirety. In such embodiments, speaker 142 generates or emits sound waves at predetermined intervals and / or frequencies, and microphone 140 detects reflections of the emitted sound waves from speaker 142. The sound waves generated or emitted by speaker 142 have frequencies inaudible to the human ear (e.g., below 20 Hz or above about 18 kHz) so as not to disturb the user or the user's bed partner (such as...). Figure 2 The sleep of the bed partner (220) is monitored. Based at least in part on data from microphone 140 and / or speaker 142, control system 110 can determine the user's position and / or one or more sleep-related parameters described herein, such as, for example, respiratory signal, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, number of events per hour, event pattern, sleep stage, pressure setting of respiratory therapy device 122, mouth leakage, or any combination thereof. In this context, a SONAR sensor can be understood to involve active acoustic sensing such as generating / transmitting ultrasound or low-frequency ultrasound sensing signals through the air (e.g., in the frequency range of about 17 to 23 kHz, 18 to 22 kHz, or 17 to 18 kHz). Such a system can be considered to be related to WO 2018 / 050913 and WO2020 / 104465 described above. In some embodiments, speaker 142 is a bone conduction speaker. In some embodiments, one or more sensors 130 include (i) a first microphone that is the same as or similar to microphone 140 and is integrated into acoustic sensor 141; and (ii) a second microphone that is the same as or similar to microphone 140 but is separate from and different from the first microphone integrated into acoustic sensor 141.

[0056] RF transmitter 148 generates and / or transmits radio waves having a predetermined frequency and / or predetermined amplitude (e.g., in the high-frequency band, in the low-frequency band, long-wave signal, short-wave signal, etc.). RF receiver 146 detects the reflection of the radio waves emitted from RF transmitter 148, and this data can be analyzed by control system 110 to determine the user's location and / or one or more sleep-related parameters described herein. RF receivers (RF receiver 146 and RF transmitter 148 or another RF pair) can also be used for wireless communication between control system 110, respiratory therapy device 122, one or more sensors 130, user device 170, or any combination thereof. Although RF receiver 146 and RF transmitter 148 are in... Figure 1While shown as separate and distinct components, in some embodiments, the RF receiver 146 and RF transmitter 148 are combined as part of the RF sensor 147 (e.g., a RADAR sensor). In some such embodiments, the RF sensor 147 includes control circuitry. The specific format of the RF communication may be WiFi, Bluetooth, etc.

[0057] In some implementations, 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, network routers, and network gateways, each of which may be mobile / movable or fixed. In such implementations, the WiFi mesh system includes WiFi routers and / or WiFi controllers and one or more satellites (e.g., access points), each of which includes the same or similar RF sensor as RF sensor 147. The WiFi routers and satellites communicate with each other continuously using WiFi signals. The WiFi mesh system can be used to generate motion data based at least in part on changes in WiFi signals (e.g., differences in received signal strength) caused by partial signal obstruction between the routers and satellites due to moving objects or people. Motion data may indicate movement, breathing, heart rate, gait, falls, behavior, etc., or any combination thereof.

[0058] Camera 150 outputs image data that can be reproduced as one or more images (e.g., still images, video images, thermal images, or combinations thereof) that can be stored in memory device 114. Image data from camera 150 can be used by 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 identify the user's location, determine when the user enters the user's bed (such as...). Figure 2 The camera 150 can also be used to track the time the user is in bed 230 and to determine when the user leaves bed 230. The 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. The camera 150 can also be used to track the user's position, which can affect the duration and / or severity of apnea episodes in users with postural obstructive sleep apnea.

[0059] The IR sensor 152 outputs infrared image data that can be reproduced as one or more infrared images (e.g., still images, video images, or both) that can be stored in the memory device 114. The infrared data from the IR sensor 152 can be used to determine one or more sleep-related parameters during a sleep period, including the user's temperature and / or the user's movement. The IR sensor 152 can also be used in conjunction with the camera 150 when measuring the user's presence, location, and / or movement. The IR sensor 152 can detect, for example, infrared light with wavelengths between about 700 nm and about 1 mm, while the camera 150 can detect visible light with wavelengths between about 380 nm and about 740 nm.

[0060] The IR sensor 152 outputs infrared image data that can be reproduced as one or more infrared images (e.g., still images, video images, or both) that can be stored in the memory device 114. The infrared data from the IR sensor 152 can be used to determine one or more sleep-related parameters during a sleep period, including the user's temperature and / or the user's movement. The IR sensor 152 can also be used in conjunction with the camera 150 when measuring the user's presence, location, and / or movement. The IR sensor 152 can detect, for example, infrared light with wavelengths between about 700 nm and about 1 mm, while the camera 150 can detect visible light with wavelengths between about 380 nm and about 740 nm.

[0061] PPG sensor 154 outputs physiological data associated with the user, which can be used to determine one or more sleep-related parameters, such as, for example, heart rate, heart rate pattern, heart rate variability, cardiac cycle, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, estimated blood pressure parameters, or any combination thereof. PPG sensor 154 may be worn by the user, embedded in clothing and / or fabric worn by the user, embedded in and / or connected to the user interface 124 and / or its associated headgear (e.g., a fixation clip, etc.).

[0062] ECG sensor 156 outputs physiological data associated with the electrical activity of the user's heart. In some embodiments, ECG sensor 156 includes one or more electrodes that are placed on or around a portion of the user during sleep periods. The physiological data from ECG sensor 156 can be used, for example, to determine one or more sleep-related parameters as described herein.

[0063] EEG sensor 158 outputs physiological data related to the electrical activity of the user's brain. In some embodiments, EEG sensor 158 includes one or more electrodes that are positioned on or around the user's scalp during sleep periods. The physiological data from EEG sensor 158 can be used, for example, to determine the user's sleep stage at any given time during a sleep period. In some embodiments, EEG sensor 158 may be integrated into user interface 124 and / or an associated headgear (e.g., a fixation splint, etc.).

[0064] Capacitive sensor 160, force sensor 162, and strain gauge sensor 164 output data, which may be stored in memory device 114 and used by control system 110 to determine one or more sleep-related parameters among those described herein. EMG sensor 166 outputs physiological data associated with electrical activity generated by one or more muscles. Oxygen sensor 168 outputs oxygen data indicating the oxygen concentration of a gas (e.g., in conduit 126 or at user interface 124). 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 embodiments, one or more sensors 130 further include a skin conductance response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a blood pressure sensor, a blood oxygenation sensor, or any combination thereof.

[0065] Analyte sensor 174 can be used to detect the presence of analytes in a user's exhaled breath. Data output from analyte sensor 174 can be stored in memory device 114 and used by control system 110 to determine the characteristics and concentration of any analytes in the user's breath. In some embodiments, analyte sensor 174 is positioned near the user's mouth to detect analytes in the user's exhaled breath. For example, when user interface 124 is a mask covering the user's nose and mouth, analyte sensor 174 can be positioned inside the mask to monitor the user's mouth breathing. In other embodiments, such as when user interface 124 is a nasal mask or nasal pillow mask, analyte sensor 174 can be positioned near the user's nose to detect analytes in the user's exhaled breath through the user's nose. In many other embodiments, when user interface 124 is a nasal mask or nasal pillow mask, analyte sensor 174 can be positioned near the user's mouth. In this embodiment, analyte sensor 174 can be used to detect any unintentional air leakage from the user's mouth. In some embodiments, the analyte sensor 174 is a volatile organic compound (VOC) sensor, which can be used to detect carbon-based chemicals or compounds, such as carbon dioxide. In some embodiments, the analyte sensor 174 can also be used to detect whether the user is breathing through their nose or mouth. For example, if the presence of an analyte is detected by data output from the analyte sensor 174, which is located near the user's mouth or inside a mask (in embodiments where the user interface 124 is a mask), the control system 110 can use that data as an indication that the user is breathing through their mouth.

[0066] The humidity sensor 176 outputs data that can be stored in the memory device 114 and used by the control system 110. The humidity sensor 176 can be used to detect moisture in various areas around 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 user interface 124, near the connection between the conduit 126 and the respiratory therapy device 122, etc.). Therefore, in some embodiments, the humidity sensor 176 can be coupled to or integrated into the user interface 124 or conduit 126 to monitor the humidity of pressurized air from the respiratory therapy device 122. In other embodiments, the humidity sensor 176 is placed near any area where moisture content needs to be monitored. The humidity sensor 176 can also be used to monitor the humidity of the surrounding environment around the user, for example, the humidity of the air inside the user's bedroom. The humidity sensor 176 can also be used to track the user's biometric responses to environmental changes.

[0067] One or more LiDAR sensors 178 can be used for depth sensing. This type of optical sensor (e.g., a laser sensor) can be used to detect objects and construct a three-dimensional (3D) map of the surrounding environment, such as a living space. LiDAR typically utilizes pulsed lasers for time-of-flight measurements. LiDAR is also known as 3D laser scanning. In examples of such sensor use, a fixed or mobile device (such as a smartphone) with LiDAR sensor 178 can measure and map an area extending 5 meters or more from the sensor. For example, LiDAR data can be fused with point cloud data estimated by an electromagnetic RADAR sensor. LiDAR sensor 178 can also use artificial intelligence (AI) to automatically geofence the RADAR system by detecting and classifying features in the space that may cause problems for the RADAR system, such as glass windows (which can be highly reflective of RADAR). For example, LiDAR can also be used to provide an estimate of a person's height, and how that height changes when the person sits down or falls. LiDAR can be used to form a 3D mesh representation of the environment. In further applications, LiDAR can reflect radio waves away from solid surfaces (e.g., semi-transparent materials), allowing for the classification of different types of obstacles.

[0068] Although Figure 1 While shown separately, any combination of one or more sensors 130 may be integrated into and / or coupled to any one or more components of the system 100, including the respiratory therapy device 122, user interface 124, conduit 126, humidifier 129, control system 110, user device 170, or any combination thereof. For example, acoustic sensor 141 and / or RF sensor 147 may be integrated into and / or coupled to the user device 170. In such embodiments, according to some aspects of this disclosure, user device 170 may be considered as an auxiliary device for generating additional or auxiliary data for use by the system 100 (e.g., control system 110). In some embodiments, pressure sensor 132 and / or flow sensor 134 are integrated into and / or coupled to the respiratory therapy device 122. In some embodiments, at least one of the one or more sensors 130 is not coupled to the respiratory therapy device 122, the control system 110, or the user device 170, and is typically positioned near the user during sleep periods (e.g., placed on or in contact with a part of the user, worn by the user, coupled to or placed on a bedside table, coupled to a mattress, coupled to a ceiling, etc.). More typically, the one or more sensors 130 may be positioned relative to the user in any suitable location such that the one or more sensors 130 can generate physiological data associated with the user and / or bed partner 220 during one or more sleep periods.

[0069] Data from one or more sensors 130 can be analyzed to determine one or more sleep-related parameters, which may include respiratory signals, respiratory rate, respiratory pattern, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, occurrence of one or more events, number of events per hour, event pattern, average duration of events, range of event durations, ratio between different event numbers, sleep stage, 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 air leakage, unintentional user interface air leakage, mouth air leakage, coughing, restless legs, sleep disturbance, apnea, tachycardia, dyspnea, asthma attack, seizure, convulsion, elevated blood pressure, hyperventilation, or any combination thereof. Many of these sleep-related parameters are physiological parameters, although some may be considered non-physiological parameters. Other types of physiological and non-physiological parameters may also be determined based on data from one or more sensors 130 or based on other types of data.

[0070] User device 170 includes display device 172. User device 170 may be, for example, a mobile device such as a smartphone, tablet, laptop, game console, or smartwatch. Alternatively, 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 a Google smart speaker). Google Amazon Amazon Echo (Enabling devices, etc.). In some embodiments, user device 170 is a wearable device (e.g., a smartwatch). Display device 172 is typically used to display images including still images, video images, or both. In some embodiments, display device 172 acts as a human-machine interface (HMI), which includes a graphical user interface (GUI) configured to display images and an input interface. Display device 172 may be an LED display, an OLED display, an LCD display, etc. Input interface may be, for example, a touchscreen or touch-sensitive substrate, a mouse, a keyboard, or any sensor system configured to sense input from a human user interacting with user device 170. In some embodiments, one or more user devices 170 may be used by system 100 and / or included in the system.

[0071] Blood pressure device 180 is typically used to help generate physiological data for determining one or more blood pressure measurements associated with a user. Blood pressure device 180 may include at least one of one or more sensors 130 for measuring, for example, systolic blood pressure components and / or diastolic blood pressure components.

[0072] In some embodiments, the blood pressure device 180 is a blood pressure monitor that includes an inflatable cuff that can be worn by a user and a pressure sensor (e.g., pressure sensor 132 as described herein). For example, as Figure 2 As illustrated in the examples, the blood pressure device 180 can be worn on a user's upper arm. In such embodiments 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 light bulb) for inflating the cuff. In some embodiments, the blood pressure device 180 is coupled to a respiratory therapy device 122 of a respiratory therapy system 120, which in turn delivers pressurized air to inflate the cuff. More generally, the blood pressure device 180 may be communicatively coupled to and / or physically integrated (e.g., within a housing) with a control system 110, a memory device 114, a respiratory therapy system 120, a user device 170, and / or an activity tracker 190.

[0073] Activity tracker 190 is typically used to help generate physiological data for determining activity measurements associated with a user. Activity measurements may include, for example, steps, distance traveled, steps climbed, duration of physical activity, type of physical activity, intensity of physical activity, time spent standing, respiratory rate, average respiratory rate, resting respiratory rate, maximum respiratory rate, respiratory rate variability, heart rate, average heart rate, resting heart rate, maximum heart rate, heart rate variability, calories burned, blood oxygen saturation, electrical skin activity (also known as skin conductance or skin response), or any combination thereof. Activity tracker 190 includes one or more sensors of the sensors 130 described herein, such as, for example, motion sensor 138 (e.g., one or more accelerometers and / or gyroscopes), PPG sensor 154, and / or ECG sensor 156.

[0074] In some implementations, the activity tracker 190 is a wearable device that can be worn by a user, such as a smartwatch, wristband, ring, or patch. For example, see reference... Figure 2The activity tracker 190 is worn on the user's wrist. The activity tracker 190 can also be attached to or integrated into clothing or garments worn by the user. Alternatively, the activity tracker 190 can also be attached to or integrated into the user device 170 (e.g., within the same housing). More typically, the activity tracker 190 can be communicatively attached to or physically integrated into (e.g., within a housing) the control system 110, memory device 114, respiratory therapy system 120, user device 170, and / or blood pressure device 180.

[0075] Although the control system 110 and the memory device 114 are in Figure 1 While described and shown as separate and distinct components of system 100, in some embodiments, the control system 110 and / or memory device 114 are integrated into user device 170 and / or respiratory therapy device 122. Alternatively, in some embodiments, the control system 110 or a portion thereof (e.g., processor 112) may reside in the cloud (e.g., integrated into a server, integrated into an Internet of Things (IoT) device, connected to the cloud, subjected to edge cloud processing, etc.) or in one or more servers (e.g., remote servers, local servers, etc., or any combination thereof).

[0076] While system 100 is shown as including all of the components described above, according to embodiments of this disclosure, a system for identifying the user interface used by a user may include more or fewer components. For example, a first alternative system includes a control system 110, a memory device 114, and at least one of one or more sensors 130. As another example, a second alternative system includes a control system 110, a memory device 114, at least one of one or more sensors 130, and a user device 170. As yet another example, a third alternative system includes a control system 110, a memory device 114, a respiratory therapy system 120, at least one of one or more sensors 130, and a user device 170. As a further example, a fourth alternative system includes a control system 110, a memory device 114, a respiratory therapy system 120, at least one of one or more sensors 130, a user device 170, and a blood pressure device 180 and / or an activity tracker 190. Therefore, various systems for modifying pressure settings can be formed using any one or more portions of the components shown and described herein and / or combinations with one or more other components.

[0077] Refer again Figure 2In some embodiments, any sensor or combination thereof from the control system 110, memory device 114, one or more sensors 130 may be located on and / or therein on any surface and / or structure generally adjacent to the bed 230 and / or user 210. For example, in some embodiments, at least one of the one or more sensors 130 may be located at a first location on and / or therein 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 coupled to the respiratory therapy system 120, user interface 124, catheter 126, display device 128, humidifier 129, or a combination thereof.

[0078] Alternatively or additionally, at least one of the one or more sensors 130 may be located on and / or in a second location on the bed 230 (e.g., one or more sensors 130 are coupled to and / or integrated therein). Further, alternatively or additionally, at least one of the one or more sensors 130 may be located on the mattress 232 and / or in a third location on the mattress adjacent to the bed 230 and / or the user 210 (e.g., one or more sensors 130 are coupled to and / or integrated therein). Alternatively or additionally, at least one of the one or more sensors 130 may be located on a pillow and / or in a fourth location on the pillow, typically adjacent to the bed 230 and / or the user 210.

[0079] Alternatively or additionally, at least one of the one or more sensors 130 may be located on the bedside table 240 and / or in a fifth position within the bedside table, typically adjacent to the bed 230 and / or the user 210. Alternatively or additionally, at least one of the one or more sensors 130 may be located in a sixth position, such that at least one of the one or more sensors 130 is coupled to and / or placed on the user 210 (e.g., the one or more sensors 130 are embedded in or coupled to fabric, clothing, and / or a smart device worn by the user 210). More generally, at least one of the one or more sensors 130 may be positioned relative to the user 210 in any suitable location, such that the one or more sensors 130 can generate sensor data associated with the user 210.

[0080] In some implementations, a primary sensor, such as microphone 140, is configured to generate acoustic data associated with user 210 during sleep periods. For example, one or more microphones (with...) Figure 1The microphone 140 (which is the same as or similar to the microphone 140) may be integrated into (i) the circuit board of the respiratory therapy device 122, (ii) the catheter 126, (iii) the connector between the components of the respiratory therapy system 120, (iv) the user interface 124, (v) the headgear (e.g., a fixing clip) associated with the user interface, or (vi) a combination thereof and / or connected to (i), (ii), (iii), (iv), (v) or (vi).

[0081] In some implementations, in addition to the primary sensor, one or more auxiliary sensors may be used to generate additional data. In some such implementations, one or more auxiliary 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-type sensor (VAF), a hot-wire sensor (MAF), a cold-wire sensor, a laminar flow sensor, an ultrasonic sensor, an inertial sensor, or a combination thereof.

[0082] Additional or alternative, one or more microphones (with) Figure 1 The microphone 140 (same as or similar to the microphone) can be integrated into and / or connected to the corresponding smart device, such as user device 170, television, watch (e.g., mechanical watch or another smart device worn by the user), pendant, mattress 232, bed 230, bedding placed on bed 230, pillow, speaker (e.g., Figure 1 The smart device may include a speaker 142), a radio, a flat panel device, a waterless humidifier, or a combination thereof. The co-located smart device can be any smart device within the range for detecting sounds emitted by the user, the respiratory therapy system 120, and / or any part of the system 100. In some embodiments, the co-located smart device is a smart device that is in the same room as the user during sleep periods.

[0083] Additionally or alternatively, in some implementations, one or more microphones (with) Figure 1 The microphone 140 (same or similar) can be located away from system 100. Figure 1 ) and / or User 210 ( Figure 2 This applies as long as there is an air passage that allows acoustic signals to propagate to one or more microphones. For example, one or more microphones may be in a different room than the room containing system 100.

[0084] As used herein, a sleep period can be defined, at least in part, based on, for example, an initial start time and an end time, in various ways. In some implementations, a sleep period is the duration for which a user is asleep, i.e., a sleep period has a start time and an end time, and during the sleep period, the user does not wake up until the end time. That is, any period during which the user is awake is not included in a sleep period. According to this first definition of a sleep period, if a user wakes up and falls asleep multiple times in the same night, each of the sleep intervals separated by wakefulness intervals is a sleep period.

[0085] Alternatively, in some implementations, the sleep period has a start time and an end time, and during the sleep period, the user can wake up as long as the continuous duration of wakefulness is less than a wakefulness duration threshold, without the sleep period ending. The wakefulness duration threshold can be defined as a percentage of the sleep period. The wakefulness duration threshold can be, for example, about 20 percent of the sleep period, about 15 percent of the sleep period, about 10 percent of the sleep period, about 5 percent of the sleep period, about 2 percent of the sleep period, or any other threshold percentage. In some implementations, the wakefulness duration threshold is defined as a fixed amount of time, such as, for example, about one hour, about thirty minutes, about fifteen minutes, about ten minutes, about five minutes, about two minutes, or any other amount of time.

[0086] In some implementations, a sleep period is defined as the entire time between the time a user first enters bed at night and the time the user last leaves bed the following morning. In other words, a sleep period can be defined as a time period that begins on the first date (e.g., Monday, January 6, 2020) at the first time the user enters bed intending to sleep (e.g., if the user intends to watch TV or use a smartphone before sleeping), and ends on the second date (e.g., Tuesday, January 7, 2020) at the second time the user leaves bed intending not to continue sleeping the following morning, which can be referred to as the second time of the following morning (e.g., 7:00 AM).

[0087] In some implementations, the user can manually define the start and / or end of a sleep period. For example, the user can select (e.g., by clicking or tapping) on ​​the user device 170 ( Figure 1 One or more user-selectable elements are displayed on the display device 172 to manually initiate or terminate a sleep period.

[0088] refer to Figure 3 The diagram illustrates an exemplary timeline 300 for a sleep period. Timeline 300 includes bedtime (t... 入床 ), sleep time (t)GTS ), initial sleep time (t) 睡眠 First micro-awakening MA1, second micro-awakening MA2, awakening A, awakening time (t) wake ) and wake-up time (t 起床 ).

[0089] Time to enter bed t 入床 Before the user falls asleep (e.g., when the user lies down or sits on the bed), they initially enter the bed (e.g., Figure 2 The time of bed entry (230) is related to the time of entry into bed. 入床 Bed entry time can be identified, at least in part, based on bed threshold duration to distinguish between the time a user enters the bed to sleep and the time a user enters the bed for other reasons (e.g., watching TV). For example, bed threshold duration could be at least approximately 10 minutes, at least approximately 20 minutes, at least approximately 30 minutes, at least approximately 45 minutes, at least approximately 1 hour, at least approximately 2 hours, etc. While the term t in this document refers to the bed itself, bed entry time is used to describe the process. 入床 But more often, the time to enter the bed is t 入床 This can refer to the time when a user initially enters any location intended for sleeping (e.g., a sleeping chair, chair, sleeping bag, etc.).

[0090] Sleep time (GTS) and the time it takes for a user to initially attempt to fall asleep after getting into bed (t) 入床 This is related to the initial sleep time (t). For example, after getting into bed, a user can engage in one or more activities to relax before attempting sleep (e.g., reading, watching TV, listening to music, using user device 170, etc.). 睡眠 ) is the time when a user initially falls asleep. For example, initial sleep time (t 睡眠 This could be the time when the user initially enters the first non-REM sleep stage.

[0091] Awakening Time t 觉醒 This is the time associated with when a user wakes up and no longer goes back to sleep (e.g., the opposite of a user waking up in the middle of the night and going back to sleep). A user may experience one or more unconscious micro-awakenings (e.g., micro-awakenings MA1 and MA2) of short duration (e.g., 5 seconds, 10 seconds, 30 seconds, 1 minute, etc.) after initially falling asleep. This is related to the wakefulness time t. 觉醒 Conversely, the user continues to sleep after each of the micro-awake events MA1 and MA2. Similarly, the user may have one or more conscious awakenings (e.g., awakening A) after initial sleep onset (e.g., waking up to use the bathroom, caring for a child or pet, sleepwalking, etc.). However, the user continues to sleep after awakening A. Therefore, the wakefulness time t 觉醒It can be defined, for example, at least in part, based on arousal threshold duration (e.g., the user has been awake for at least 15 minutes, at least 20 minutes, at least 30 minutes, at least 1 hour, etc.).

[0092] Similarly, wake-up time t 起床 This is associated with the time a user leaves the bed and remains outside the bed, intending to end their sleep (e.g., the opposite of a user getting up at night to go to the bathroom, care for a child or pet, or sleepwalking). In other words, wake-up time t 起床 This is the time when a user last leaves bed and does not return before the next sleep period (e.g., the following night). Therefore, wake-up time t 起床 This can be defined, for example, at least in part, based on a wake-up threshold duration (e.g., the user has been out of bed for at least 15 minutes, at least 20 minutes, at least 30 minutes, at least 1 hour, etc.). The bed-entry time t for the second subsequent sleep period... 入床 It can also be defined, at least in part, based on wake-up threshold duration (e.g., the user has been out of bed for at least 4 hours, at least 6 hours, at least 8 hours, at least 12 hours, etc.).

[0093] As mentioned above, the user may initially t 入床 and finally t 起床 Waking up and getting up again during the night between sleep hours. In some implementations, the final wake-up time t 觉醒 and / or final wake-up time t 起床 It is identified or determined, at least in part, based on a predetermined threshold duration following the 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 then wakes up and gets out of bed in the morning, any time period between approximately 12 and approximately 18 hours (the time after the user wakes up) can be used. 觉醒 ) or get up (t 起床 ) and users going to bed (t 入床 ), sleep (t) GTS ) or fall asleep (t 睡眠 For users who spend longer periods of time in bed, shorter threshold periods can be used (e.g., between approximately 8 hours and approximately 14 hours). The threshold period can be initially selected and / or adjusted later, at least in part, based on the system's monitoring of the user's sleep behavior.

[0094] Total time in bed (TIB) is the time to enter bed t 入床 and wake-up time t 起床The duration between sleep and wake times. Total sleep time (TST) is the duration between initial sleep time and wake time, excluding any conscious or unconscious wakefulness and / or micro-awakeness in between. Typically, total sleep time (TST) will be shorter than total time in bed (TIB) (e.g., one minute shorter, ten minutes shorter, one hour shorter, etc.). For example, refer to... Figure 3 Timeline 300, Total Sleep Time (TST) spans from initial sleep time t 睡眠 and awakening time t 觉醒 The duration of this period does not include the durations of the first micro-awake (MA1), the second micro-awake (MA2), and awakening A. As shown in the figure, in this example, the total sleep time (TST) is shorter than the total time in bed (TIB).

[0095] In some implementations, total sleep time (TST) can be defined as total sustained sleep time (PTST). In such implementations, total sustained sleep time excludes a predetermined initial portion or period of the first non-REM stage (e.g., a light sleep stage). For example, the predetermined initial portion could be between about 30 seconds and about 20 minutes, between about 1 minute and about 10 minutes, between about 3 minutes and about 5 minutes, etc. Total sustained sleep time is a measure of sustained sleep and smooths the sleep-wake sleep graph. For example, when a user initially falls asleep, the user may be in the first non-REM stage for a very short time (e.g., about 30 seconds), then return to the wakeful stage for a short time (e.g., one minute), and then return to the first non-REM stage. In this example, total sustained sleep time excludes the first instance of the first non-REM stage (e.g., about 30 seconds).

[0096] In some implementations, the sleep period is defined as the time from bedtime (t... 入床 Start at wake-up time (t) 起床 The sleep period ends, meaning the sleep period is defined as the total time in bed (TIB). In some implementations, the sleep period is defined as the time from the initial sleep time (t...). 睡眠 ) begins and at the awakening time (t) 觉醒 End. In some implementations, a sleep period is defined as total sleep time (TST). In some implementations, a sleep period is defined as the time spent sleeping (t). GTS ) begins and at the awakening time (t) 觉醒 The sleep period ends. In some implementations, the sleep period is defined as the time during which sleep begins (t). GTS Start at wake-up time (t) 起床 The sleep period ends at bedtime. In some implementations, the sleep period is defined as the time from bedtime to bedtime (t...). 入床 ) begins and at the awakening time (t) 觉醒 The sleep period ends at the initial sleep time (t). In some implementations, the sleep period is defined as the period from the initial sleep time (t) to the end.睡眠 Start at wake-up time (t) 起床 )Finish.

[0097] refer to Figure 4 The illustration shows the timeline 300 according to some implementation methods. Figure 3 An exemplary sleep graph 400 is shown. As illustrated, sleep graph 400 includes a sleep-wake signal 401, a wakefulness stage axis 410, a REM stage axis 420, a light sleep stage axis 430, and a deep sleep stage axis 440. The intersection of the sleep-wake signal 401 with one of the axes 410 to 440 indicates the sleep stage at a given time during a sleep period.

[0098] The sleep-wake signal 401 may be generated at least in part based on physiological data associated with the user (e.g., generated by one or more sensors in the sensor 130 described herein). The sleep-wake signal may indicate one or more sleep stages, including wakefulness, relaxed wakefulness, micro-awakeness, REM sleep, a first non-REM sleep stage, a second non-REM sleep stage, a third non-REM sleep stage, or any combination thereof. In some embodiments, one or more of the first non-REM sleep stage, the second non-REM sleep stage, and the third non-REM sleep stage may be grouped together and categorized as light sleep stages or deep sleep stages. For example, light sleep stages may include the first non-REM sleep stage, while deep sleep stages may include the second and third non-REM sleep stages. Although in Figure 4 The sleep graph 400 shown includes a light sleep stage axis 430 and a deep sleep stage axis 440, but in some embodiments, the sleep graph 400 may include axes for each of the first non-REM stage, the second non-REM stage, and the third non-REM stage. In other embodiments, sleep-wake signals may also indicate respiratory signals, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory amplitude ratio, inspiratory-expiratory time ratio, number of events per hour, event pattern, or any combination thereof. Information describing sleep-wake signals may be stored in memory device 114.

[0099] Sleep graph 400 can be used to determine one or more sleep-related parameters, such as sleep onset latency (SOL), wakefulness after sleep onset (WASO), sleep efficiency (SE), sleep fragmentation index, sleep blocks, or any combination thereof.

[0100] Sleep onset latency (SOL) is defined as the duration of sleep (t). GTS ) and initial sleep time (t 睡眠The sleep onset latency is the time between the initial attempt to fall asleep and the actual time it takes for the user to fall asleep. In some implementations, the sleep onset latency is defined as the continuous sleep onset latency (PSOL). The difference between continuous sleep onset latency and sleep onset latency is that continuous sleep onset latency is defined as the duration between the sleep time and a predetermined amount of continuous sleep. In some implementations, the predetermined amount of continuous sleep may include, for example, at least 10 minutes of sleep within the second non-REM stage, the third non-REM stage, and / or the REM stage, without more than 2 minutes of wakefulness, movement during the first non-REM stage, and / or in between. In other words, the continuous sleep onset latency requires, for example, up to 8 minutes of continuous sleep within the second non-REM stage, the third non-REM stage, and / or the REM stage. In other implementations, the predetermined amount of continuous sleep may include at least 10 minutes of sleep within the first non-REM stage, the second non-REM stage, the third non-REM stage, and / or the REM stage after the initial sleep time. In such implementations, the predetermined amount of continuous sleep may not include any micro-awakenings (e.g., a ten-second micro-awakening does not restart the 10-minute period).

[0101] Waking after sleep onset (WASO) is associated with the total duration of a user's wakefulness between the initial sleep time and wakefulness time. Therefore, WASO includes brief awakenings and micro-awakenings during the sleep period (e.g., Figure 4 The micro-awakes (MA1 and MA2) shown can be either conscious or unconscious. In some implementations, sleep onset wakefulness (WASO) is defined as continuous sleep onset wakefulness (PWASO) that includes only the total duration of wakefulness with a predetermined length (e.g., greater than 10 seconds, greater than 30 seconds, greater than 60 seconds, greater than about 5 minutes, greater than about 10 minutes, etc.).

[0102] Sleep efficiency (SE) is defined as the ratio of total time in bed (TIB) to total sleep time (TST). For example, if the total time in bed is 8 hours and the total sleep time is 7.5 hours, the sleep efficiency for that sleep period is 93.75%. Sleep efficiency is a measure of a user's sleep hygiene. For example, if a user goes to bed before sleep and spends time engaging in other activities (e.g., watching television), sleep efficiency is reduced (e.g., the user is punished). In some implementations, sleep efficiency (SE) may be calculated at least in part based on the total time in bed (TIB) and the total time the user attempts to sleep. In such implementations, the total time the user attempts to sleep is defined as the duration between the sleep time (GTS) and the wake-up time described herein. For example, if the total sleep time is 8 hours (e.g., between 11 p.m. and 7 a.m.), the sleep time is 10:45 p.m., and the wake-up time is 7:15 a.m., in such implementations, the sleep efficiency parameter is calculated to be approximately 94%.

[0103] The fragmentation index is determined at least in part based on the number of awakenings during a sleep period. For example, if a user has two micro-awakenings (e.g., Figure 4 If micro-awakening MA1 and micro-awakening MA2 are shown, then the fragmentation index can be expressed as 2. In some implementations, the fragmentation index is scaled between a predetermined range of integers (e.g., between 0 and 10).

[0104] Sleep blocks are associated with the transition between any sleep stage (e.g., first non-REM stage, second non-REM stage, third non-REM stage, and / or REM stage) and the wakefulness stage. Sleep blocks can be calculated at a resolution of, for example, 30 seconds.

[0105] In some embodiments, the systems and methods described herein may include generating or analyzing a sleep map including sleep-wake signals to determine or identify bedtime based at least in part on the sleep-wake signals of the sleep map. 入床 ), sleep time (t) GTS ), initial sleep time (t) 睡眠 ), one or more first micro-awakenings (e.g., MA1 and MA2), awakening time (t) 觉醒 ), wake-up time (t) 起床 (or any combination thereof).

[0106] In other embodiments, one or more of the sensors in sensor 130 may be used to determine or identify the bed entry time (t). 入床 ), sleep time (t) GTS ), initial sleep time (t) 睡眠 ), one or more first micro-awakenings (e.g., MA1 and MA2), awakening time (t) 觉醒), wake-up time (t) 起床 (or any combination thereof), which in turn defines sleep periods. For example, bedtime t 入床 Sleep time can be determined at least in part based on, for example, data generated by motion sensor 138, microphone 140, camera 150, or any combination thereof. Sleep time can be determined at least in part based on, for example, data from motion sensor 138 (e.g., data indicating the user is not moving), data from camera 150 (e.g., data indicating the user is not moving and / or the user has turned off the lights), data from microphone 140 (e.g., data indicating the user is turning off the TV), data from user device 170 (e.g., data indicating the user is no longer using user device 170), data from pressure sensor 132 and / or flow sensor 134 (e.g., data indicating the user is turning on the breathing therapy device 122, data indicating the user is putting on the user interface 124, etc.) or any combination thereof.

[0107] refer to Figure 5 The illustration depicts a method 500 for monitoring a user during sleep periods when using a respiratory therapy system (such as respiratory therapy system 12). Typically, a control system (such as control system 110 of system 100) is configured to perform the various steps of method 500. A memory device (such as memory device 114 of system 100) can be used to store any type of data utilized in the steps of method 500 (or other methods). Typically, a user with SDB may have additional health conditions (also known as comorbidities) accompanying their SDB. The use of a respiratory therapy system (e.g., as a CPAP system) can generate data that can be analyzed to identify and / or monitor these additional health conditions. The use of a respiratory therapy system can also, in some cases, treat the additional health conditions as well as SDB. By analyzing the data generated during the use of the respiratory therapy system and, in some cases, the additional data, various indicators related to the additional health conditions can be determined, and more effective treatment options for the additional health conditions can be identified.

[0108] Step 502 of method 500 includes generating data during a current sleep period associated with a user of the respiratory therapy system. The data can be generated from any suitable source, including multiple different sensors (such as sensor 130). The sensors can be located inside or outside the housing of a respiratory therapy device (such as respiratory therapy device 122) used with the respiratory therapy system. The data can also be generated from multiple different devices such as smartwatches, activity trackers, mobile phones, any number of external medical measurement devices, etc. The respiratory therapy system may include a respiratory therapy device that supplies pressurized air to a user's airway via, for example, a catheter and a user interface. The generated data may include information indicating the pressure, flow rate, and other properties of the pressurized air. The user interface may include a full-face mask, nasal mask, or other type of user interface covering the user's mouth and nose.

[0109] Step 504 of method 500 includes analyzing the generated data to determine the value of a first indicator associated with sleep apnea (SDB). Step 506 of method 500 includes analyzing the generated data to determine the value of a second indicator associated with the user's health status other than SDB. The first indicator may include indicators used to analyze the user's sleep periods. For example, if the respiratory therapy system is used as a CPAP system, the first indicator may be associated with using the CPAP system to minimize events such as sleep apnea events.

[0110] The first indicator (and in some embodiments, the second indicator) may include respiratory signals, respiratory rate, respiratory pattern, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, occurrence of one or more events, number of events per hour, event pattern, average duration of events, range of event durations, ratio between the number of different events, sleep stage, time spent in each of multiple sleep stages, sleep stage pattern, apnea-hypopnea index (AHI), sleep score, treatment score, total sleep time, total time in bed, wake time, wake-up time, sleep graph, total light sleep time, total deep sleep time, total REM sleep time, total sleep time during treatment, total sleep time after treatment, number of awakenings, sleep onset latency, stress level, or any combination thereof.

[0111] In some implementations, the first indicator is associated only with SDB, while the second indicator is associated only with health status. In some implementations, the first indicator is associated with both SDB and health status, while the second indicator is associated only with health status. In some implementations, the first indicator is associated only with SDB, while the second indicator is associated with both health status and SDB. In some implementations, the first indicator is associated with both SDB and health status. In some implementations, the second indicator is associated with both health status and SDB.

[0112] In some implementations, the second indicator is associated with the presence of heart disease. For example, the second indicator may be associated with heart failure, heart murmur, tachycardia, heart attack, atrial fibrillation, arrhythmia, myocarditis, cardiac autonomic neuropathy, chronic inflammatory diseases such as atherosclerosis (repeated nocturnal drops in blood oxygen levels caused by SDB can lead to intermittent hypoxia, which has been shown to be associated with systemic inflammation). The second indicator may include heart rate variability (a lack of decrease in heart rate variability during sleep may suggest cardiac stress and an inadequate response to sleep); standard deviation of the beat-to-beat interval (also known as SDNN, which can be correlated with cardiac resilience); root mean square of the continuous difference between adjacent beats (also known as RMSSD, which can be correlated with cardiac resilience); cardiac output (a decrease in cardiac output (e.g., less blood pumped per time interval) may indicate hypertension and / or heart failure); atrial cavity structure (modified structure may indicate atrial fibrillation risk); tidal volume (tidal volume instability may indicate heart failure); apnea duration, expiratory duration, expiratory gradient, envelope of the flow signal (which can show the stability level of the user's breathing), respiratory rate, etc.

[0113] In some implementations, the second indicator is associated with the user's clinical stress level or sympathetic nervous activity. For example, the second indicator may include heart rate, heart rate variability, skin conductance (e.g., skin conductance response), arterial pulse velocity, arterial pulse shape, arterial pulse volume, arterial pulse amplitude, or any combination thereof. Further, one or more of these measurements may be used to quantify the user's stress level, such that the second indicator itself includes a quantifiable measure of the user's stress level. The second indicator may also be an indicator of the user's stress response to various types of apnea events. For example, a second indicator for a single user may indicate that the user experiences elevated stress levels only in response to prolonged apnea events and / or apnea events with a significant reduction in inspiratory volume (which can be measured using heart rate, heart rate variability, skin conductance, arterial pulse characteristics, etc.). However, a second indicator for a different user may indicate that the user experiences elevated stress levels in response to shorter apnea events and / or apnea events with a slight reduction in inspiratory volume, as well as longer apnea events and / or apnea events with a significant reduction in inspiratory volume. The second metric can also indicate the amount by which a user's stress level increases with the severity of the apnea event. Therefore, in some implementations, the second metric may include the relationship between a user's stress response and various types of apnea events, the percentage of different types of apnea events leading to different stress responses, etc.

[0114] In a further embodiment, the respiratory therapy system can be configured to detect the association between a second indicator and the respiratory therapy system treatment (e.g., CPAP pressure). In yet another embodiment, the respiratory therapy level (e.g., CPAP pressure level) can be altered to enhance the detection of the association between the treatment and the second indicator, and in still further embodiments, the treatment level can be adjusted to control the second indicator (e.g., CPAP pressure can be increased or decreased to reduce indicators associated with stress or sympathetic nervous system activity).

[0115] In some implementations, the second indicator is associated with the user's breathing during sleep. For example, the second indicator may include the rhythm of the user's breathing (e.g., the speed of the user's breathing, and / or whether there are any beginnings and stops in the user's breathing), the amplitude of the user's breathing (e.g., the amount of air the user inhales and / or exhales), the time constant of exhalation (e.g., the time constant of the exponential decay of lung volume during exhalation), the shape of exhalation (e.g., the shape of a curve showing the change of lung volume over time during exhalation), the magnitude of exhalation (e.g., the amount or force of exhalation), the rate of exhalation (e.g., the rate at which lung volume decreases during exhalation), the time constant of inhalation (e.g., the time constant of the exponential increase of lung volume during inhalation), the shape of inhalation (e.g., the shape of a curve showing the change of lung volume over time during inhalation), the magnitude of inhalation (e.g., the amount and / or force of inhalation), the rate of inhalation (e.g., the rate at which lung volume increases during inhalation), tidal volume, respiratory rate, or other respiratory indicators (e.g., respiratory-associated indicators).

[0116] These respiratory indicators can be associated with any number of different health conditions. For example, a user's breathing rhythm and / or tidal volume can be associated with obesity, COPD, pneumonia, asthma, and other conditions. A user with shortness of breath (e.g., a rapid breathing rhythm and / or shallow tidal volume) can indicate that the user is obese or has COPD, pneumonia, asthma, etc. In another instance, the shape of inhalation and / or exhalation can suggest an obstruction in the user's airway. In a further instance, tidal volume can be associated with heart failure. Instability in tidal volume (e.g., different volumes for different breaths) can indicate the presence of heart failure or a risk of heart failure. In a further instance, any one or more of (i) breathing rhythm, (ii) the shape, rate, and size of inhalation, and (iii) the shape, rate, and size of exhalation can indicate the presence of Cheyne-Stokes respiration.

[0117] In another example, the second indicator can be correlated with the time a user is awake or asleep during a sleep period, and can include the amount of time spent falling asleep, the total amount of time spent awake, the total amount of time spent asleep, the time the user falls asleep, the time the user wakes up, the consistency of the user's breathing rate, etc. These indicators can indicate that the user's awake time is longer than expected, the time spent asleep is shorter than expected, the user's breathing does not slow down and only becomes consistent later than expected during the sleep period (indicating that the user has fallen asleep), etc., all of which can indicate that the user has insomnia. Information related to sleep staging, such as sleep graphs (e.g., Figure 3 Sleep graphs (400) can also be used to help determine if a user suffers from insomnia.

[0118] These or other indicators can also suggest the presence of other neurological disorders such as anxiety, claustrophobia, and stress. Typically, the second indicator can be associated with heart disease, respiratory disease, neurological disorders, and other types of illnesses. Typically, indicators associated with neurological disorders may include heart rate (high heart rate may indicate anxiety); blood pressure (high blood pressure may indicate anxiety); sleep onset latency (low sleep onset latency may indicate anxiety); microarousal threshold (e.g., ease with which a user wakes up – a low microarousal threshold may indicate anxiety); amount of physical activity during sleep (e.g., uncontrolled leg movements may indicate restless legs syndrome); indicators related to wakefulness during sleep (unstable sleep-wake patterns may indicate circadian rhythm disruption and can lead to morning depression, and may also indicate nocturnal epilepsy); interface leakage rate (a high leakage rate from user interfaces such as user interface 124 may indicate that the user interface is being worn looser due to claustrophobia); the number of times the user interface is removed during sleep (a high number may indicate claustrophobia); and various indicators related to user responses to questionnaires, which are discussed in more detail below.

[0119] Step 508 of method 500 includes performing an action based at least in part on the value of the determined second indicator. In some implementations, the second indicator indicates the characteristics, presence, and / or severity of the user's health condition and can therefore be used to determine the characteristics, presence, and / or severity of the user's health condition. Many different actions can then be taken.

[0120] In some implementations, one or more settings of the respiratory therapy system can be adjusted, at least in part, based on the value of a determined second indicator. In one instance, the respiratory therapy system initially operates as a positive airway pressure ventilation system such as a CPAP system. In response to the value of a second indicator indicating the presence of or an increased risk of developing heart disease (such as heart failure), one or more settings of the respiratory therapy device can be adjusted (manually or automatically by the control system) such that the respiratory therapy system operates as an adaptive servo ventilation system. Heart disease (such as heart failure) often leads to apnea that cannot be treated with a CPAP system, and the use of a CPAP system often exacerbates the occurrence and / or severity of these apneas. When the respiratory therapy system operates as an adaptive servo ventilation system, it can monitor the user's breathing and increase the user's expiratory volume to ensure tidal volume stability, and reduce the occurrence and / or severity of these apneas.

[0121] In another example, settings related to the supply of pressurized air can be modified, such as air pressure, air flow rate, pressurization ramp time (e.g., the time it takes for the air pressure to increase to the desired pressure (e.g., the desired therapeutic pressure) from the start of use of the respiratory therapy system), and humidity of the pressurized air. Medications or other substances can also be supplied via pressurized air and / or injected into the user's airway. Medications can be used to help the user fall asleep. This substance could be a scent used to calm the user and help them fall asleep. In one example, the volume of the respiratory therapy system operating at high pressure can affect a user's insomnia and, in some cases, worsen it. If a second indicator suggests the user has insomnia, the ramp time can be increased, giving the user more time to fall asleep until the respiratory therapy system reaches the desired pressure. In a further instance, if the second indicator indicates the presence of insomnia, the treatment response sensitivity ramp time can be increased, and / or the air pressure can be maintained at a relatively low level (e.g., less than the desired treatment, which can be increased more quickly in the presence of milder events such as snoring or airflow limitation) until the respiratory therapy system detects that the user has fallen asleep (e.g., at least in part based on sleep-wake signals).

[0122] In another instance, for users suffering from COPD, asthma, allergies, sinus infections, rhinitis, or other respiratory-related conditions, the humidity of the pressurized air may be increased. In a further instance, if a second indicator indicates that a user is suffering from a condition treatable by inhaled medication, the medication may be supplied and / or injected into the user's airway. In some of these embodiments, the value of the first indicator associated with SDB may influence how the settings of the respiratory therapy system are adjusted. In many other embodiments, adjusting the settings may include changing the type of user interface currently being used. Microphone 140 and / or speaker 142 may be used to characterize the user interface, for example, by directing an acoustic signal toward the user interface and then analyzing acoustic data associated with the reflection of the acoustic signal. Once the type of user interface currently being used is determined, a recommendation to change the type of user interface can be generated, at least in part, based on the determined value of the second indicator. Typically, the settings of the respiratory therapy system have an expected therapeutic effect. The settings of the respiratory therapy system may be adjusted as needed to improve the expected therapeutic effect.

[0123] In a further example, adjusting the settings of a respiratory therapy system may include adjusting the pressure of the pressurized air to take into account the CO2 level around the interface. If the user's interface is leaking and / or if the user's ventilation rate is low, the pressurized air pressure can be reduced.

[0124] In some implementations, notifications and / or reports may be generated and sent to the user and / or a third party. Third parties may include friends, family members, spouses, other significant persons, caregivers, healthcare providers, etc. Notifications and / or reports may identify detected illnesses and / or the severity of detected illnesses. Notifications and / or reports may also recommend future treatments to help manage the illness. For example, in the event that a second indicator indicates the presence of insomnia, the notification and / or report may suggest cognitive behavioral therapy. Notifications and / or reports may be displayed to the user on an electronic display device, such as display device 172 of user device 170.

[0125] In some embodiments, the techniques of method 500 can be used to monitor the efficacy of a respiratory therapy system in treating a health condition. In these embodiments, a second indicator is tracked over multiple sleep periods, and a value for the second indicator is determined for each sleep period. The settings of the respiratory therapy system for each sleep period and the duration of use of the respiratory therapy system for each sleep period can be determined. The settings and duration of use of the respiratory therapy system may be related to any changes in the presence and / or severity of the health condition. The optimal settings and / or duration of use for treating the health condition can then be determined.

[0126] In some implementations, the second metric is related to the user's stress level, as discussed above. In these implementations, the action may include adjusting various settings of the respiratory therapy system based on the determined user stress level. In one instance, the user stress level is used to adjust how the respiratory therapy system responds to apnea events in real time. The respiratory therapy system may operate as a positive airway pressure (CPAP) system, which supplies pressurized air to the user's airway at a constant pressure (CPAP system) or at two different constant pressures for the user's inspiration and expiration (BiPAP system or VPAP system). If the user is experiencing elevated stress levels, the respiratory therapy system may increase the pressure of the supplied air when a severe apnea event is detected. Increasing the air pressure can help end a severe apnea event more quickly and / or minimize the reduction in inspiration that occurs during a severe apnea event. Increasing the pressure may have negative side effects, such as drying out the user's airway and potentially causing discomfort, and is therefore generally not done. However, if a user experiences elevated stress levels during sleep (especially during a severe apnea event), the benefit of ending the apnea event more quickly by increasing air pressure may outweigh any disadvantages of the increased pressure. Therefore, the respiratory therapy system in these embodiments can only increase air pressure in response to a severe apnea event if the user's stress level is elevated. If the user's stress level is not elevated, the respiratory therapy system can maintain the same pressure level even during a severe apnea event.

[0127] In some implementations, if the user typically experiences elevated stress levels during sleep, the pressure increases in response to a severe apnea event. Once the severe apnea event ends, the pressure can decrease back to its standard level. In other implementations, if the user experiences elevated stress levels during a severe apnea event, the pressure increases in response to the event. Once the severe apnea event ends and / or the user's stress levels return to normal, the pressure can decrease back to its standard level. In further implementations, this pressure increase may occur during mild apnea events, not just severe apnea events. Therefore, in some implementations, the respiratory therapy system may increase the pressure of the air delivered to the user's airway in response to an apnea event (severe or mild), provided that a second indicator indicates an increase in the user's stress level. If the second indicator does not indicate an increase in the user's stress level during the apnea event, the respiratory therapy system may continue to operate at its standard pressure.

[0128] refer to Figure 6The illustration depicts a method 600 for monitoring a user during sleep when the user is using a respiratory therapy system (such as respiratory therapy system 12). Typically, a control system (such as control system 110 of system 100) is configured to perform the various steps of method 600. A memory device (such as memory device 114 of system 100) can be used to store any type of data utilized in the steps of method 600 (or other methods).

[0129] Step 602 of method 600 includes generating data during a current sleep period associated with a user of the respiratory therapy system. Step 602 of method 600 is the same as or similar to step 502 of method 500. Step 604 includes receiving historical data associated with one or more previous sleep periods. Typically, the historical data can be of the same type as the data generated during the current sleep period, except that the historical data is associated with one or more previous sleep periods of the user.

[0130] Step 606 of method 600 includes analyzing the generated data to determine values ​​of an indicator associated with the user's health status, excluding SDB. Step 606 of method 600 is the same as or similar to step 506 of method 500. Therefore, the indicator whose value is determined may be a second indicator determined in step 506. Step 608 of method 600 includes analyzing historical data to determine the value of the indicator for each of one or more previous sleep periods. Step 610 of method 600 includes comparing the value of the indicator determined for one or more previous sleep periods with the value of the indicator determined for the current sleep period. This comparison may reveal whether the severity of the user's disease has increased or decreased over time.

[0131] Finally, step 612 of method 600 includes performing an action at least in part based on a comparison. If the comparison in step 610 indicates an increase in the severity of the health condition, various different actions can be taken. In some embodiments, a notification may be sent to the user or a third party (such as a friend, family member, spouse, partner, caregiver, or healthcare provider). The notification may provide information about the increased severity of the health condition. The notification may be displayed to the user on an electronic display device such as user device 170. In another embodiment, one or more settings of the respiratory therapy system may be modified to better treat the health condition.

[0132] In another implementation, future treatment recommendations can be sent to the user. These recommendations may include advice to see a doctor or dentist, recommendations to accept a medication or medical treatment plan, recommendations to modify the settings of a respiratory therapy system, recommendations to use a separate device (such as a portable oxygen concentrator) to treat a health condition, or recommendations to use a separate device to confirm an increase in the severity of a health condition.

[0133] The individual device can be any device that can be used to confirm the increased severity. For example, the device can be a medical measurement device that a user can use to measure a characteristic or parameter that indicates the severity of a health condition. Individual devices can include: a pulse oximeter configured to measure a user's oxygen saturation; a blood pressure monitor configured to monitor a user's blood pressure; a heart rate monitor configured to measure a user's heart rate; a blood glucose meter configured to measure a user's blood glucose level; an electroencephalogram (EEG) device configured to measure brain activity (to monitor central micro-arousals and / or sleep stages during sleep periods); an electrooculogram (EOG) device configured to detect eye movements during sleep periods; a wearable device to detect movement during sleep periods; a mattress sensor or other device for detecting movement during sleep periods.

[0134] In many other implementations, comparisons between data from the current sleep period and past sleep periods can indicate whether the severity of the health condition has increased, decreased, remained unchanged, or decreased. If the severity of the health condition has increased, the action may include recommending that the user adjust the settings and / or use of the respiratory therapy system to improve the expected therapeutic effect of the respiratory therapy system commensurate with the increased severity of the health condition. If the severity of the health condition has decreased or remained unchanged, the action may include recommending that the user continue using the respiratory therapy system with the current settings or adjusting the settings and / or use of the respiratory therapy system to reduce the expected therapeutic effect of the respiratory therapy system commensurate with the unchanged or decreased severity of the health condition. Other types of actions may also be taken.

[0135] In an additional implementation, data from previous sleep periods can be analyzed to predict future conditions for various health conditions. This may include predicting the appropriate timing for any future changes to intervention or treatment, and sending notifications and / or reports to the user or third parties regarding the predicted future intervention or treatment changes. The predictions can also be continuously updated as more data is obtained from each sleep period.

[0136] In some implementations, historical data from one or more previous sleep periods are analyzed to track the user's stress level over time, and a second metric includes a measurement of the user's stress level during the current sleep period. If a comparison indicates that the user's stress level has not decreased during the sleep period, the settings of the respiratory therapy system can be adjusted to help reduce the user's stress level. For example, the settings of the respiratory therapy system can be adjusted to increase the ramp-up time of pressurized air delivered to the user's airway or to decrease the pressure of pressurized air delivered to the user's airway. Typically, when a user initially begins using the respiratory therapy system at the start of a sleep period, the system ramps up the pressure of the air supplied to the user's airway from a low initial pressure to a higher operating pressure over a first time period (which could be 5 minutes, 10 minutes, 30 minutes, 1 hour, etc.). The time taken for the pressure to increase from the initial pressure to the operating pressure can be referred to as the ramp-up time. If the user's stress level increases (e.g., in response to initially wearing the user interface), this action can include increasing the ramp-up time of the respiratory therapy system such that the pressure of the air supplied to the user increases from the initial pressure to the operating pressure over a second time period greater than the first time period. This action may additionally or alternatively include reducing the operating pressure of the respiratory therapy system. In these embodiments, the operating pressure may be modified to a lower than the original operating pressure.

[0137] In some implementations, historical data may be used to determine a user's baseline stress level during different types of apnea events, and a second indicator may include a measurement of the user's stress level during the current sleep period. If the second indicator indicates that the user is experiencing elevated stress levels (compared to baseline) during certain apnea events, the pressure of the pressurized air delivered to the user's airway may be increased to help reduce the duration and / or severity of the apnea events, even if such prolonged and / or severe apnea events would typically be treated with increased pressure. Similarly, if the second indicator indicates that the user is not experiencing elevated stress levels during certain apnea events, the pressure of the pressurized air delivered to the user's airway may be kept constant, even if such prolonged and / or severe apnea events would typically be treated with increased pressure.

[0138] While Method 600 generally refers to comparing data from the current sleep period with data from previous sleep periods, it is typically applicable to any comparison between different datasets generated during different sleep periods. Therefore, data generated during the current sleep period can also be compared with data generated during subsequent sleep periods to determine the value of a second indicator for both the current and subsequent sleep periods, and to take an action, at least in part, based on that comparison.

[0139] refer to Figure 7The illustration depicts a method 700 for monitoring a user during a sleep period when the user is using a respiratory therapy system (such as respiratory therapy system 12). Typically, a control system (such as control system 110 of system 100) is configured to perform the various steps of method 700. A memory device (such as memory device 114 of system 100) can be used to store any type of data utilized in the steps of method 700 (or other methods).

[0140] Step 702 of method 700 includes generating data during the current sleep period associated with the user of the respiratory therapy system. Step 702 of method 700 is generally the same as or similar to step 602 of method 600 and / or step 502 of method 500. Step 704 of method 700 includes analyzing the generated data to determine the value of a first indicator associated with sleep apnea (SDB). Step 704 of method 700 is generally the same as or similar to step 504 of method 500. Step 706 of method 700 includes analyzing the generated data to determine the value of a second indicator associated with a health condition other than SDB. Step 706 of method 700 is generally the same as or similar to step 506 of method 500 and step 606 of method 600.

[0141] Step 708 of method 700 includes receiving additional data associated with the user while the user is awake. Typically, the additional data is associated with the user but not with the user's use of the respiratory therapy system. This data may include demographic information such as the user's age, gender, social gender, geographic location, height, weight, neck size, and occupation; medical information associated with the user, such as smoking status; audio data associated with the user, such as the user's answers to questionnaires or other data related to the user's speech; and other types of additional data.

[0142] Questionnaires may include questions designed to elicit further information from users about themselves. These questions may relate to the quality and / or amount of sleep, the user's health, recent activities, physical activity / exercise, stress levels, physical health, mental health, other data, or any combination thereof. Data associated with a user's responses to the questionnaire may include the content of the user's answers.

[0143] However, in some implementations, the data may also include how the user actually answers the questions. Attributes including the pitch of the user's voice, the rhythm of the user's voice, the structure of the provided answer (e.g., complete sentences versus single words), the speed and accuracy of the user's answers can provide insight into various disorders, including neurological disorders such as anxiety and depression. For example, a faster pace, monotonous / limited pitch, a high ratio of breathing sounds to speech during the answer, large intervals between words, and / or any tremor in the user's voice may indicate the presence of neurological disorders such as anxiety and / or depression.

[0144] In some implementations, the questions may be displayed to the user via the display device 128 of the respiratory therapy system 120 and / or the display device 172 of the user device 170. In other implementations, the questions may be transmitted to the user via the speaker 142 (e.g., played aloud). The user's answers to the questionnaire may be entered manually (e.g., via the display device 128 of the respiratory therapy system 128 or the user device 170). However, the user may also speak their answers aloud, and sensors (such as the microphone 140) may generate audio data prompting the user's answers. The audio data represents attributes or characteristics of the user's health status in their answers.

[0145] Additional data may include audio data, not just user responses to questionnaires. For example, a user could be recorded during the day (e.g., using a microphone 142 or other device). Audio data associated with the user's voice and other sounds the user makes (e.g., coughing, wheezing, etc.) can indicate a variety of illnesses, including respiratory illnesses (e.g., asthma, pneumonia, allergies, respiratory infections, etc.) and neurological illnesses (depression, anxiety, bipolar disorder, etc.).

[0146] Step 710 of method 700 includes analyzing the received additional data (data associated with the user during wakefulness) to determine the value of a third indicator associated with health status. Step 712 of method 700 includes performing an action based at least in part on the determined value of the third indicator.

[0147] Typically, a third indicator associated with health status differs from the second indicator. By determining the value of the third indicator based on additional data associated with the user during wakefulness, a more accurate representation of health status can be obtained, and actions can be taken.

[0148] In some implementations, the value of the second indicator may be adjusted at least in part based on the value of the third indicator. In these implementations, the accuracy of the determined value of the second indicator may be limited when based at least in part on data associated solely with the use of the respiratory therapy system. However, the value of the second indicator can be determined more precisely by taking into account data associated with the user during wakefulness and / or the value of the third indicator.

[0149] In other implementations, the value of the second indicator may indicate that the user may have multiple different health conditions. However, based at least in part on the value of the second indicator, it may be impossible to determine which of the multiple health conditions the user actually suffers from. The value of the third indicator can provide more detail, making it possible to determine which of the multiple health conditions the user is suffering from. In other implementations, the situation may be exactly the opposite. The value of the third indicator may indicate the probability that the user is suffering from multiple different health conditions, and then the value of the second indicator can be used to determine which of the multiple health conditions the user is suffering from.

[0150] In many other implementations, the characteristics of the health condition the user is experiencing can only be determined based on a second (or third) indicator. The severity of the health condition can then be determined using the value of the third (or second) indicator.

[0151] Typically, any of methods 500, 600, and 700 can be implemented using a system having a control system and a memory device, the control system having one or more processors, and the memory device storing machine-readable instructions. The control system can be coupled to the memory device, and methods 500, 600, and 700 can be implemented when the machine-readable instructions are executed by at least one of the processors of the control system. Methods 500, 600, and 700 can also be implemented using a computer program product (such as a non-transitory computer-readable medium) including instructions that, when executed by a computer, cause the computer to perform the steps of methods 500, 600, and 700.

[0152] One or more elements, aspects, or steps or any part thereof from any one or more of claims 1 to 125 may be combined with one or more elements, aspects, or steps or any part thereof from any other claim 1 to 125 to form one or more additional embodiments and / or claims of this disclosure.

[0153] 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 changes can be made thereto without departing from the spirit and scope of this disclosure. Each of these implementations, and its obvious variations, is considered to fall within the spirit and scope of this disclosure. It is also contemplated that additional implementations according to various aspects of this disclosure may combine any number of features from any of the implementations described herein.

Claims

1. A system for monitoring a user's sleep periods, the system comprising: A respiratory therapy system, the respiratory therapy system comprising: A respiratory therapy device, configured to supply pressurized air; and A user interface, connected to the respiratory therapy device via a conduit, is configured to engage the user and assist in directing the supplied pressurized air into the user's airway; A memory device storing machine-readable instructions; and A control system, coupled to the memory device, includes one or more processors configured to execute the machine-readable instructions to: One or more sensors associated with the respiratory therapy device are used to generate data acquired during sleep periods; The generated data was analyzed to determine the value of the primary indicator associated with sleep-disordered breathing. The generated data is analyzed to determine the value of a second indicator associated with a health condition other than the aforementioned sleep-disordered breathing, wherein the health condition includes insomnia or heart disease; and An action is performed, at least in part, based on a comparison of the value of the determined second indicator with a predetermined value of the second indicator. The action includes treating the user's health condition, adjusting one or more settings of the respiratory therapy system, presenting a notification or suggestion, or any combination thereof.

2. The system of claim 1, wherein the value of the second indicator indicates the presence of the health condition, the severity of the health condition, or both.

3. The system of claim 1 or claim 2, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to determine the characteristics of the health condition, the severity of the health condition, or both, based at least in part on the value of the determined second indicator.

4. The system according to any one of claims 1 to 2, wherein the first indicator is associated only with sleep-disordered breathing and the second indicator is associated only with the health condition.

5. The system according to any one of claims 1 to 2, wherein the first indicator includes respiratory signal, respiratory rate, respiratory pattern, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, occurrence of one or more events, number of events per hour, event pattern, average duration of events, range of event duration, ratio between different numbers of events, sleep stage, time spent in each of multiple sleep stages, sleep stage pattern, apnea-hypopnea index (AHI), sleep score, treatment score, total sleep time, total time in bed, wake-up time, wake-up time, sleep graph, sleep disturbance index, total light sleep time, total deep sleep time, total REM sleep time, total sleep time during treatment, total sleep time after treatment, number of awakenings, sleep onset latency, or any combination thereof.

6. The system according to any one of claims 1 to 2, wherein at least a first portion of the data is generated by one or more sensors disposed within the housing of the respiratory therapy device.

7. The system of claim 6, wherein at least a second portion of the data is generated by one or more sensors disposed outside the respiratory therapy device.

8. The system according to any one of claims 1 to 2, wherein the second indicator is associated with the user's breathing during the sleep period.

9. The system of claim 8, wherein the second indicator includes the rhythm of the breathing, the amplitude of the user's breathing, the time constant of exhalation, the shape of exhalation, the size of exhalation, the speed of exhalation, the time constant of inhalation, the shape of inhalation, the size of inhalation, the speed of inhalation, tidal volume, the rate of breathing, or any combination thereof.

10. The system of claim 9, wherein the second indicator includes the rhythm of breathing, and the health condition further includes obesity, chronic obstructive pulmonary disease (COPD), pneumonia, asthma, Cheyne-Stokes respiration, heart failure, or any combination thereof.

11. The system of claim 10, wherein the rhythm of the breathing indicates shortness of breath and is associated with the presence of obesity.

12. The system of claim 9, wherein the second indicator includes the shape of exhalation, and wherein the health condition further includes the presence of obstruction in the user's airway.

13. The system of claim 9, wherein the second indicator includes tidal volume, and wherein instability in the tidal volume indicates the presence of heart failure or the risk of developing heart failure.

14. The system of claim 13, wherein the respiratory therapy system initially operates as a positive airway pressure ventilation system, and wherein, in response to the second indicator indicating the presence of heart failure or the risk of heart failure, the action includes adjusting one or more settings of the respiratory therapy system to operate as an adaptive servo ventilation system.

15. The system of claim 1, wherein the health condition is insomnia, and wherein the second indicator includes total time in bed, total sleep time, total wake time, sleep onset latency, wake-up parameters after sleep onset, sleep efficiency, fragmentation index, time to fall asleep, consistency of respiratory rate, time to fall asleep, wake-up time, sleep disturbance rate, number of movements, or any combination thereof.

16. The system of claim 15, wherein in response to the second indicator indicating the presence of insomnia, the action includes (i) adjusting one or more settings of the respiratory therapy system, (ii) sending future treatment suggestions to the user or to a third party, (iii) or both.

17. The system of claim 16, wherein the future treatment includes cognitive behavioral therapy.

18. The system of claim 16, wherein adjusting one or more settings of the respiratory therapy system includes reducing the pressure of the pressurized air supplied to the user's airway.

19. The system of claim 1, wherein the health condition is a heart condition, and wherein the second indicator comprises heart rate variability, standard deviation of the interval between the user's heartbeats, root mean square of the difference between consecutive beats of the user's heart, cardiac output, atrial cavity structure of the user's heart, tidal volume, duration of apnea, duration of expiration, expiratory gradient, envelope of flow signal, respiratory rate, or any combination thereof.

20. The system of claim 19, wherein the respiratory therapy system initially operates as a positive airway pressure ventilation system, and in response to the second indicator indicating the presence of the heart disease, the action includes adjusting one or more settings of the respiratory therapy system to operate as an adaptive servo ventilation system.

21. The system of claim 19, wherein the cardiac disease includes heart failure, heart murmur, tachycardia, heart attack, atrial fibrillation, arrhythmia, myocarditis, cardiac autonomic neuropathy, chronic inflammation, or any combination thereof.

22. The system of claim 1, wherein the generated data includes data indicating the pressure of the pressurized air, the flow rate of the pressurized air, or both.

23. The system of claim 22, wherein the action comprises modifying the pressure of the pressurized air, modifying the flow rate of the pressurized air, modifying the ramp time of the pressurized air, modifying the humidity of the pressurized air, supplying the agent into the user's airway via the pressurized air, or any combination thereof.

24. The system of claim 23, wherein in response to a determined value of a second index indicating the presence of insomnia, anxiety, claustrophobia, or any combination thereof, the action comprises increasing the ramp time of the pressurized air.

25. The system of claim 23, wherein in response to a determined value of a second indicator indicating the presence of COPD, asthma, allergy, sinus infection, rhinitis, or any combination thereof, the action comprises increasing the humidity of the pressurized air, supplying the medication into the user's airway, or both.

26. The system of claim 1, wherein the actions include sending a notification to the user or a third party, displaying the notification on an electronic display device, changing one or more settings of the respiratory therapy system, sending treatment suggestions to the user or the third party, or any combination thereof.

27. The system of claim 1, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: The second metric was tracked across multiple sleep periods; The value of the second indicator is determined for each of the plurality of sleep periods; For each of the plurality of sleep periods, determine (i) the duration of use of the respiratory therapy system, (ii) the value of one or more settings of the respiratory therapy system, or (iii) both; and Identify (i) the optimal duration of use of the respiratory therapy system, (ii) the optimal value of one or more settings of the respiratory therapy system, or (iii) both, to treat the health condition.

28. The system of claim 1, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: Receive historical data associated with one or more previous sleep periods of the user; Analyze the historical data to determine the value of the second indicator for each of the one or more previous sleep periods; as well as The value of the second indicator determined for each of the one or more previous sleep periods is compared with the value of the second indicator determined for the sleep period.

29. The system of claim 28, wherein the one or more processors of the control system are configured to execute the machine-readable instructions to cause the action to be performed in response to the comparison indicating that the severity of the health condition has increased.

30. The system of claim 29, wherein the actions include sending a notification to the user or a third party, displaying the notification on an electronic display device, adjusting one or more settings of the respiratory therapy system, sending treatment suggestions to the user or the third party, or any combination thereof.

31. The system of claim 30, wherein the treatment recommendations include recommendations to see a doctor, recommendations to see a dentist, recommendations to use a separate device to perform measurements indicating the presence of the health condition or the severity of the health condition, recommendations to use a portable oxygen concentrator, or any combination thereof.

32. The system of claim 31, wherein the individual device is a pulse oximeter configured to measure the user's oxygen saturation, a blood pressure monitor configured to monitor the user's blood pressure, a heart rate monitor configured to measure the user's heart rate, a blood glucose meter configured to monitor the user's blood glucose level, an electroencephalogram (EEG) device configured to monitor brain activity, an electrooculogram (EOG) device configured to monitor eye movements, a wearable device configured to measure the user's physical motion, a mattress sensor configured to measure the user's physical motion, or any combination thereof.

33. The system of claim 28, wherein the health condition includes the user's stress level, and wherein in response to the comparison indicating that the user's stress level has increased, the action includes reducing the pressure of the pressurized air delivered to the user by the respiratory therapy system.

34. The system of claim 1, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: The severity of the health condition is determined at least in part based on the value of a second indicator specific to the sleep period. Data is generated during one or more subsequent sleep periods; The value of the second indicator is determined for each of the one or more subsequent sleep periods; The severity of the updated health condition is determined at least in part based on the value of a second indicator determined for each of the one or more subsequent sleep periods. as well as The action is performed based at least in part on the severity of the updated health condition.

35. The system of claim 34, wherein the action includes sending future treatment recommendations to the user based at least in part on the severity of the updated health condition.

36. The system of claim 34, wherein in response to a value of a second indicator determined for each of the one or more subsequent sleep periods indicating an increase in the severity of the health condition, the action includes adjusting one or more settings of the respiratory therapy system to improve the intended therapeutic effect of the respiratory therapy system.

37. The system of claim 34, wherein in response to a value of a second indicator determined for each of the one or more subsequent sleep periods indicating an increase in the severity of the health condition, the action includes sending a treatment recommendation to the user or to a third party.

38. The system of claim 34, wherein in response to a value of a second indicator determined for each of the one or more subsequent sleep periods indicating that the severity of the health condition has decreased, the action includes continuing to use the respiratory therapy system with the current settings, or adjusting one or more settings of the respiratory therapy system to reduce the expected therapeutic effect of the respiratory therapy system.

39. The system of claim 1, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: Receive additional data associated with the user when the user is awake; Analyze the additional data to determine the value of a third indicator associated with the health condition; and The action is performed based at least in part on the value of the third indicator, which is determined to be associated with the health condition.

40. The system of claim 39, wherein the additional data includes the user's age, the user's gender, the user's social gender, the user's geographic location, the user's height, the user's weight, the user's neck size, medical information associated with the user, the user's smoking status, the user's occupation, the user's responses to a questionnaire, the manner in which the user provided responses to the questionnaire, or any combination thereof.

41. The system of claim 39, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: The value of the determined second indicator is modified, at least in part, based on the value of the determined third indicator; and The action is performed based at least in part on the value of the modified second indicator.

42. The system of claim 39, wherein the value of the second indicator is associated with multiple health conditions, and wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to determine, at least in part, a characteristic of the user's health condition from the multiple health conditions based on the determined value of the third indicator.

43. The system of claim 39, wherein the value of the third indicator is associated with multiple health conditions, and wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to determine, at least in part, a characteristic of the user's health condition from the multiple health conditions based on the determined value of the second indicator.

44. The system of claim 39, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: The characteristics of the user's health status are determined at least in part based on the value of the determined second indicator; and The severity of the user's health condition is determined at least in part based on the value of the identified third indicator.

45. The system of claim 39, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to: The characteristics of the user's health status are determined at least in part based on the value of the determined third indicator; and The severity of the user's health condition is determined at least in part based on the value of the determined second indicator.

46. ​​The system of claim 1, wherein the one or more processors of the control system are further configured to execute the machine-readable instructions to determine, at least in part, the characteristics of the health condition, the severity of the health condition, or both, based on (i) the value of the determined second indicator and (ii) additional data.

47. The system of claim 46, wherein the additional data includes demographic information associated with the user, medical information associated with the user, audio data associated with the user, or any combination thereof.

48. The system of claim 47, wherein the demographic information includes the user's age, the user's gender, the user's social gender, the user's geographic location, the user's height, the user's weight, the user's neck size, the user's occupation, or any combination thereof.

49. The system of claim 47, wherein the user's medical information is obtained from the user's medical history.

50. The system of claim 47, wherein the audio data associated with the user includes the user's answers to a questionnaire.

51. The system of claim 1, wherein the second indicator indicates the user's stress level and includes heart rate, heart rate variability, skin conductance, arterial pulse velocity, arterial pulse shape, arterial pulse volume, arterial pulse amplitude, or any combination thereof.

52. The system of claim 51, wherein in response to the second indicator indicating an increase in the user's stress level during a sleep apnea event, the action includes increasing the pressure of the pressurized air.

53. The system of claim 1, wherein the value of the determined second indicator indicates an increase in the user's stress level.

54. The system of claim 53, wherein the action includes increasing the pressure of the pressurized air in response to the user experiencing a sleep apnea event.

55. The system of claim 54, wherein the action further includes reducing the pressure of the pressurized air in response to the end of the apnea event.

56. The system of claim 53, wherein during operation of the respiratory therapy system, the respiratory therapy system is configured to increase the pressure of the pressurized air from an initial pressure to a working pressure within a first time period.

57. The system of claim 56, wherein the action includes increasing the ramp-up time of the pressurized air supplied to the user through the airway, such that the pressure of the pressurized air increases from the initial pressure to the operating pressure during a second time period greater than the first time period.

58. The system of claim 56, wherein the action includes modifying the working pressure to a modified working pressure less than the working pressure.

59. The system of claim 1, wherein the value of the determined second index indicates that the user is suffering from a respiratory-related illness, and wherein the action includes increasing the humidity of the pressurized air supplied to the user's airway.

60. The system of claim 59, wherein the respiratory-related disease includes chronic obstructive pulmonary disease (COPD), asthma, allergies, sinus infections, rhinitis, or any combination thereof.

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