System and method for determining sleep scores based on images

Abstract

A method includes causing a user device to capture an image of a user via an application executing on the user device. The method also includes receiving, by the control system, an image of the user. The method further includes analyzing, by the control system, the image of the user based on a machine learning algorithm. The method further includes determining, by the control system, a sleep score for the user based on the analysis of the image of the user.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 369,155, filed on July 22, 2022, which is hereby incorporated by reference in its entirety. Technical Field

[0003] The present invention relates generally to systems and methods for determining a sleep score, and more particularly to systems and methods for determining a sleep score based on an image. Background Art

[0004] Many individuals suffer from sleep-related and / or breathing-related disorders, 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), respiratory effort-related micro-arousal (RERA) and snoring. In some cases, these disorders may appear or appear more obviously when the individual is in a specific lying / sleeping posture. These individuals may also suffer from other health conditions (which may be referred to as comorbidities), such as insomnia (e.g., difficulty falling asleep, frequent or long awakenings after initially falling asleep, and / or early awakening and inability to fall asleep again), periodic limb movement disorder (PLMD), restless legs syndrome (RLS), Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disease (NMD), rapid eye movement (REM) behavior disorder (also referred to as RBD), dream enactment behavior (DEB), hypertension, diabetes, stroke, chest wall disorders.

[0005] These disorders are often treated using respiratory therapy systems (e.g., continuous positive airway pressure (CPAP) systems), which deliver pressurized air to help prevent the individual's airway from narrowing or collapsing during sleep. However, some users find such systems uncomfortable, difficult to use, expensive, unsightly, and / or unable to perceive the benefits associated with using the systems. As a result, some users will choose not to use or cease using a respiratory therapy system without demonstrating the severity of their symptoms when not using respiratory therapy treatment, or without receiving encouragement or confirmation that the respiratory therapy system is improving their sleep quality and alleviating the symptoms of these disorders. The present invention is intended to address these and other problems. Summary of the invention

[0006] According to some embodiments of the present invention, a method includes causing a user device to capture an image of a user via an application executed on the user device. The method also includes receiving, by a control system, the image of the user. The method also includes analyzing, by the control system, the image of the user based on a machine learning algorithm. The method also includes determining, by the control system, a sleep score for the user based on the analysis of the image of the user.

[0007] According to some embodiments of the invention, a system includes an application executable on a user device, the application configured to cause the user device to capture an image of a user. The system also includes a control system communicatively coupled to the user device. The control system is configured to receive the image of the user from the user device. The control system is further configured to analyze the image of the user using a machine learning algorithm. The control system is further configured to determine a sleep score for the user based on the analysis of the image of the user.

[0008] The above summary of the invention is not intended to represent every embodiment or every aspect of the present invention. Additional features and benefits of the present invention will become apparent from the detailed description and drawings set forth below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a functional block diagram of a system according to some embodiments of the present invention;

[0010] Figure 2 According to some embodiments of the present invention Figure 1 a perspective view of at least a portion of a system, a user, and a bed partner;

[0011] Figure 3A According to some embodiments of the present invention Figure 1 A perspective view of a system of respiratory therapy equipment;

[0012] Figure 3B is a diagram illustrating the interior of a housing according to some embodiments of the present invention. Figure 3A A perspective view of a respiratory therapy device;

[0013] Figure 4A is a perspective view of a user interface according to some embodiments of the present invention;

[0014] Figure 4B According to some embodiments of the present invention Figure 4A An exploded view of the user interface of

[0015] Figure 5A is a perspective view of a user interface according to some embodiments of the present invention;

[0016] Figure 5B According to some embodiments of the present invention Figure 5A An exploded view of the user interface of

[0017] Fig. 6A is a perspective view of a user interface according to some embodiments of the present invention;

[0018] Figure 6B According to some embodiments of the present invention Fig. 6A An exploded view of the user interface of

[0019] Figure 7 illustrates an exemplary timeline of a sleep session according to some embodiments of the present invention;

[0020] Figure 8 The present invention is illustrated in some embodiments. Figure 7 An exemplary hypnogram associated with a sleep session of;

[0021] Fig. 9 is a perspective view of a user capturing an image of themselves according to some embodiments of the present invention;

[0022] FIG. 10A to FIG. 10C Depicting a user capturing an image of themselves with their face aligned according to some embodiments of the present invention;

[0023] Fig.11 depicts a user's face according to some embodiments of the present invention, including several exploded views;

[0024] Fig.12 depicts a user's face according to some embodiments of the present invention, including several exploded views;

[0025] Fig.13 is a block diagram of a system for determining a sleep score for a user according to some embodiments of the present invention; and

[0026] Fig.14 is a flow diagram depicting example operations for determining a sleep score for a user in accordance with some implementations.

[0027] Although the present invention is susceptible to various modifications and alternative forms, its specific implementation and embodiments have been shown by way of example in the drawings and will be described in detail herein. However, it should be understood that this is not intended to limit the invention to the specific forms disclosed, but on the contrary, the present invention will cover all modifications, equivalents and substitutes that fall within the spirit and scope of the invention as defined by the appended claims. DETAILED DESCRIPTION

[0028] Many individuals suffer from sleep-related and / or breathing disorders, such as sleep-disordered breathing (SDB), such as obstructive sleep apnea (OSA), central sleep apnea (CSA) and other types of apnea, respiratory effort-related arousals (RERA), snoring, Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), periodic limb movement disorder (PLMD), restless legs syndrome (RLS), neuromuscular diseases (NMDs), and chest wall disorders.

[0029] Obstructive sleep apnea (OSA), a form of sleep-disordered breathing (SDB), is characterized by events of occlusion or obstruction of the upper airway during sleep caused by a combination of an abnormally small upper airway and loss of normal muscle tone in the tongue, soft palate, and posterior oropharyngeal wall areas. More generally, apnea usually refers to respiratory arrest caused by air blockage (obstructive sleep apnea) or cessation of respiratory function (commonly known as central sleep apnea). CSA occurs when the brain temporarily stops sending signals to the muscles that control breathing. Typically, during an obstructive sleep apnea event, an individual will stop breathing for about 15 seconds to about 30 seconds.

[0030] Other types of apnea include hypopnea, hyperpnea, and hypercapnia. Hypopnea is usually characterized by slow or shallow breathing caused by narrow airways rather than airway obstruction. Hyperpnea is usually characterized by increased depth and / or rate of breathing. Hypercapnia is usually characterized by elevated or excessive carbon dioxide in the bloodstream, usually caused by inadequate breathing.

[0031] Respiratory effort-related arousals (RERA) events are typically characterized by increased respiratory effort lasting ten seconds or longer, resulting in arousals from sleep, and which do not meet the criteria for an apnea or hypopnea event. RERA is defined as a respiratory sequence characterized by increased respiratory effort, resulting in arousals from sleep, but which does not meet the criteria for an apnea or hypopnea event. These events meet the following criteria: (1) a pattern of gradually more negative esophageal pressures, terminated by an abrupt change in pressure to a lower negative level and arousal, and (2) the event lasts for 10 seconds or longer. In some embodiments, the nasal cannula / pressure transducer system is sufficient and reliable in the detection of RERA. The RERA detector can be based on an actual flow signal derived from a respiratory therapy device. For example, a flow limitation measure can be determined based on the flow signal. A microarousal measure can then be derived based on the flow limitation measure and the measure of the sudden increase in ventilation. One such method is described in WO 2008 / 138040 and US Pat. No. 9,358,353, assigned to ResMed Ltd., the disclosures of each of which are hereby incorporated by reference in their entirety.

[0032] Cheyne-Stokes respiration (CSR) is another form of sleep-disordered breathing. CSR is a disorder of the patient's respiratory controller in which there are rhythmic alternating cycles of boom-and-bust ventilation called CSR cycles. CSR is characterized by repeated deoxygenation and reoxygenation of arterial blood.

[0033] Obesity hyperventilation syndrome (OHS) is defined as the combination of severe obesity and chronic hypercapnia during wakefulness in the absence of other known causes of hypoventilation. Symptoms include dyspnea, morning headache, and excessive daytime sleepiness.

[0034] Chronic obstructive pulmonary disease (COPD) encompasses any of a group of lower airway diseases that have certain common features, such as increased resistance to the movement of air, prolonged expiratory phase of breathing, and loss of normal elasticity of the lungs. COPD encompasses a group of lower airway diseases that have certain common features, such as increased resistance to the movement of air, prolonged expiratory phase of breathing, and loss of normal elasticity of the lungs.

[0035] Neuromuscular diseases (NMDs) encompass a number of diseases and ailments that impair muscle function either directly through intrinsic muscle pathology or indirectly through neuropathology.Chest wall disorders are a group of thoracic deformities that result in inefficient coupling between the respiratory muscles and the thorax.

[0036] These and other disorders are characterized by specific events that occur while an individual is sleeping (e.g., snoring, apnea, hypopnea, restless legs, sleep disturbances, choking, increased heart rate, breathing difficulties, asthma attacks, seizures, convulsions, or any combination thereof).

[0037] The Apnea-Hypopnea Index (AHI) is an index used to indicate the severity of sleep apnea during a sleep session. The AHI is calculated by dividing the number of apnea and / or hypopnea events experienced by the user during a sleep session by the total number of hours of sleep in the sleep session. The event can be, for example, an apnea that lasts at least 10 seconds. An AHI of less than 5 is considered normal. An AHI greater than or equal to 5 but less than 15 is considered an indication of mild sleep apnea. An AHI greater than or equal to 15 but less than 30 is considered an indication of moderate sleep apnea. An AHI greater than or equal to 30 is considered an indication of severe sleep apnea. In children, an AHI greater than 1 is considered abnormal. Sleep apnea can be considered "controlled" when the AHI is normal, or when the AHI is normal or mild. The AHI can also be used in conjunction with the oxygen desaturation level to indicate the severity of obstructive sleep apnea.

[0038] refer to Figure 1, illustrates a system 10 according to some embodiments of the present invention. The system 10 includes a respiratory therapy system 100, a control system 200, one or more sensors 210, a user device 260, and an activity tracker 270.

[0039] The respiratory therapy system 100 includes a respiratory pressure therapy (RPT) device 110 (referred to herein as respiratory therapy device 110), a user interface 120 (also referred to as a mask or patient interface), a conduit 140 (also referred to as a tube or air circuit), a display device 150, and a humidifier 160. Respiratory pressure therapy refers to the application of air supplied to the entrance of a user's airway at a controlled target pressure that is nominally positive relative to atmosphere (e.g., as opposed to negative pressure therapy such as a canister ventilator or chest plate) throughout the user's breathing cycle. The respiratory therapy system 100 is typically used to treat individuals suffering from one or more sleep-related breathing disorders (e.g., obstructive sleep apnea, central sleep apnea, or mixed sleep apnea).

[0040] The respiratory therapy system 100 can be used as, for example, a ventilator or a positive airway pressure (PAP) system, such as a continuous positive airway pressure (CPAP) system, an automatic positive airway pressure system (APAP), a bi-level or variable positive airway pressure system (BPAP or VPAP), or any combination thereof. The CPAP system delivers a predetermined air pressure (e.g., determined by a sleep physician) to the user. The APAP system automatically changes the air pressure delivered to the user based on, for example, respiratory data associated with the user. The 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 (e.g., expiratory positive airway pressure or EPAP) that is lower than the first predetermined pressure.

[0041] like Figure 2 As shown, respiratory therapy system 100 can be used to treat user 20. In this example, user 20 of respiratory therapy system 100 and bed partner 30 are located on bed 40 and lying on mattress 42. User interface 120 can be worn by user 20 during a sleep session. Respiratory therapy system 100 generally helps increase air pressure in the throat of user 20 to help prevent airway closure and / or narrowing during sleep. Respiratory therapy device 110 can be positioned in direct proximity to a user such as Figure 2 The bed 40 is shown on a nightstand 44 , or more generally, positioned on any surface or structure generally adjacent to the bed 40 and / or the user 20 .

[0042] The respiratory therapy device 110 is typically used to generate pressurized air delivered to a user (e.g., using one or more motors driving one or more compressors). In some embodiments, the respiratory therapy device 110 generates a continuous constant air pressure delivered to the user. In other embodiments, the respiratory therapy device 110 generates two or more predetermined pressures (e.g., a first predetermined air pressure and a second predetermined air pressure). In other embodiments, the respiratory therapy device 110 generates various different air pressures within a predetermined range. For example, the respiratory therapy device 110 can deliver at least about 6cmH2O, at least about 10cmH2O, at least about 20cmH2O, about 6cmH2O to about 10cmH2O, about 7cmH2O to about 12cmH2O, etc. The respiratory therapy device 110 can also deliver pressurized air at a predetermined flow rate of, for example, about -20L / min to about 150L / min, while maintaining a positive pressure (relative to ambient pressure).

[0043] Respiratory therapy device 110 includes housing 112, blower motor 114, air inlet 116, and air outlet 118 ( Figure 1 ). refer to Figure 3A and Figure 3B , the blower motor 114 is at least partially disposed or integrated within the housing 112. The blower motor 114 draws air from outside the housing 112 (e.g., the atmosphere) via the air inlet 116 and causes the pressurized air to flow through the humidifier 160 and through the air outlet 118. In some embodiments, the air inlet 116 and / or the air outlet 118 include a cover that is movable between a closed position and an open position (e.g., to prevent or inhibit air from flowing through the air inlet 116 or the air outlet 118). Figure 3A and Figure 3B As shown, housing 112 may include vent 113 to allow air to pass through housing 112 to air inlet 116. Conduit 140 is coupled to air outlet 118 of respiratory therapy device 110 as described below.

[0044] Return to reference Figure 1, the user interface 120 engages a portion of the user's face, and pressurized air is delivered from the respiratory therapy device 110 to the user's airway to help prevent the airway from narrowing and / or collapsing during sleep. This can also increase the user's oxygen intake during sleep. Generally, the user interface 120 engages the user's face so that pressurized air is delivered to the user's airway via the user's mouth, the user's nose, or the user's mouth and nose. The respiratory therapy device 110, the user interface 120, and the conduit 140 together form an air passage coupled with the user's airway fluid. Pressurized air also increases the user's oxygen intake during sleep. Depending on the therapy to be applied, the user interface 120 can, for example, form a seal with an area or part of the user's face, so that gas is delivered to achieve therapy at a pressure that is sufficiently different from the ambient pressure (e.g., at a positive pressure of about 10cmH2O relative to the ambient pressure) to achieve therapy. For other forms of therapy, such as the delivery of oxygen, the user interface may not include a seal that is sufficient to facilitate the delivery of gas supply to the airway at a positive pressure of about 10cmH2O.

[0045] The user interface 120 may include, for example, a cushion 122, a frame 124, a head cover 126, a connector 128, and one or more vents 130. The cushion 122 and the frame 124 define the volume of the space around the user's mouth and / or nose. When the respiratory therapy system 100 is in use, the volume space (e.g., via the conduit 140 from the respiratory therapy device 110) receives pressurized air to enter the user's airway. The head cover 126 is generally used to help position and / or stabilize the user interface 120 on a part of the user (e.g., face), and together with the cushion 122 (which may, for example, include silicone, plastic, foam, etc.), help provide a substantially airtight seal between the user interface 120 and the user 20. In some embodiments, the head cover 126 includes one or more straps (e.g., including hook-and-loop fasteners). The connector 128 is generally used to couple (e.g., connect and fluidly couple) the conduit 140 to the cushion 122 and / or frame 124. Alternatively, conduit 140 may be coupled directly to cushion 122 and / or frame 124 without connector 128. Vent 130 may be used to allow carbon dioxide and other gases exhaled by user 20 to escape. User interface 120 may generally include any suitable number of vents (e.g., one, two, five, ten, etc.).

[0046] like Figure 2As shown, in some embodiments, the user interface 120 is a mask (e.g., a full face mask) that covers at least a portion of the nose and mouth of the user 20. Alternatively, the user interface 120 may be a nasal mask that provides air to the user's nose or a nasal pillow mask that delivers air directly to the nostrils of the user 20. In other embodiments, the user interface 120 includes a mouthpiece (e.g., a night guard mouthpiece molded to conform to the user's teeth, a jaw repositioning device, etc.).

[0047] refer to Figure 4A and Figure 4B , illustrating a method for interacting with a user interface 120 ( Figure 1 ) The user interface 400 is the same or similar to the user interface 400. The user interface 400 generally includes a cushion 430 and a frame 450, which define the volume of the space around the user's mouth and / or nose. When in use, the volume of the space receives pressurized air to enter the user's airway. In some embodiments, the cushion 430 and the frame 450 of the user interface 400 form an integral part of the user interface. The user interface 400 may also include a head cover 410, which generally includes a belt assembly and optionally includes a connector 470. The head cover 410 is configured to be positioned approximately around at least a portion of the user's head when the user wears the user interface 400. The head cover 410 can be coupled to the frame 450 and positioned on the user's head so that the user's head is positioned between the head cover 410 and the frame 450. The cushion 430 is positioned between the user's face and the frame 450 to form a seal on the user's face. The connector 470 is configured to be coupled to the frame 450 and / or the cushion 430 at one end and coupled to a conduit (not shown) of the respiratory therapy device. Pressurized air can flow directly from the conduit of the respiratory therapy system through connector 470 into the volume of the space defined by cushion 430 (or cushion 430 and frame 450) of user interface 400. Pressurized air passes from user interface 400 through the user's mouth, nose, or both to the user's airway. Alternatively, where user interface 400 does not include connector 470, the conduit of the respiratory therapy system can be directly connected to cushion 430 and / or frame 450.

[0048] In some embodiments, the connector 470 may include one or more vents 472 (e.g., multiple vents) located on the body of the connector 470 itself and / or one or more vents 476 ("diffuser vents") near the frame 450 for allowing carbon dioxide (CO2) and other gases exhaled by the user to escape. In some embodiments, one or more vents (such as vents 472 and / or 476) may be located in the user interface 400 (such as in the frame 450) and / or in the conduit 140. In some embodiments, the frame 450 includes at least one anti-asphyxia valve (AAV) 474 that allows CO2 and other gases exhaled by the user to escape in the event that the vent (e.g., vent 472 or 476) fails when the respiratory therapy device is activated. Typically, an AAV (e.g., AAV 474) is present with full face masks (e.g., as a safety feature); however, both diffuser vents and vents located on the mask or connector (typically an array of holes in the mask material itself or a mesh made of some fabric, which is replaceable in many cases) are not necessarily present at the same time (e.g., some masks may have only diffuser vents, such as multiple vents 476, while other masks may have multiple vents 472 only on the connector itself).

[0049] refer to Figure 5A and Figure 5B , illustrating a method for interacting with a user interface 120 ( Figure 1 ) is the same or similar user interface 500. The user interface 500 is the same as or similar to the user interface 400 ( Figure 4A and Figure 4B ) in that user interface 500 is an indirect user interface, whereas user interface 400 is a direct user interface. Interface 500 includes headgear 510 (e.g., as a belt assembly), cushion 530, frame 550, connector 570, and user interface conduit 590 (commonly referred to as a mini tube or flexible tube). User interface 500 is an indirectly connected user interface because pressurized air is delivered to cushion 530 and / or frame 550 from conduit 140 of the respiratory therapy system through user interface conduit 590 rather than directly from conduit 140 of the respiratory therapy system.

[0050] In some embodiments, the cushion 530 and the frame 550 form an integral part of the user interface 500. Generally, the user interface conduit 590 is larger than the conduit 140 ( Figure 1 ) is more flexible and / or has a smaller diameter than the diameter of the conduit 140. The user interface conduit 590 is typically shorter than the conduit 140. A headgear 310 ( FIG. 3A to FIG. 3B), the headgear 510 of the user interface 500 is configured to be positioned generally around at least a portion of the user's head when the user wears the user interface 500. The headgear 510 can be coupled to the frame 550 and positioned on the user's head so that the user's head is positioned between the headgear 510 and the frame 550. The cushion 530 is positioned between the user's face and the frame 550 to form a seal on the user's face. The connector 570 is configured to be coupled to the frame 550 and / or the cushion 530 at one end and to the conduit 590 of the user interface 500 at the other end. In other embodiments, the conduit 590 can be directly connected to the frame 550 and / or the cushion 530. The conduit 590 is configured to be connected to the conduit 140 at the opposite end relative to the frame 550 and the cushion 530. Pressurized air may flow from the conduit 140 of the respiratory therapy system, through the user interface conduit 590 and connector 570, and into the volume of space defined by the cushion 530 (or cushion 530 and frame 550) of the user interface 500 against the user's face. From this volume of space, the pressurized air passes through the user's mouth, nose, or both to the user's airway.

[0051] In some embodiments, connector 570 includes multiple vents 572, which are used to allow carbon dioxide (CO2) and other gases exhaled by the user to escape when the respiratory therapy device is activated. In such embodiments, each vent in multiple vents 572 is an opening, and the opening can be angled relative to the thickness of the connector wall forming the opening. The angled opening can reduce the noise of CO2 and other gases escaping into the atmosphere. Due to the reduced noise, the acoustic signal associated with multiple vents 572 may be more obvious for an internal microphone rather than an external microphone. Therefore, the internal microphone can be located in a respiratory therapy system or otherwise physically integrated with a respiratory therapy system, and is acoustically communicated with an air stream, which is generated by a flow generator of a respiratory therapy device and reaches the user interface 500 through a conduit in operation.

[0052] In some embodiments, connector 570 optionally includes at least one valve 574 for allowing CO2 and other gases exhaled by the user to escape when the respiratory therapy device is inactive. In some embodiments, valve 574 (an example of an anti-asphyxia valve) includes a silicone (or other suitable material) flap that is a fail-safe component that allows CO2 and other gases exhaled by the user to escape in the event that vent 572 fails when the respiratory therapy device is activated. In such embodiments, when the silicone flap is open, the valve opening is much larger than each vent opening and is therefore less likely to become blocked by obstructive material.

[0053] refer to Fig. 6A and Figure 6B, illustrating a method for interacting with a user interface 120 ( Figure 1 ) is the same or similar user interface 600. User interface 600 is similar to user interface 500 in that it is an indirect user interface. Indirect headgear user interface 600 includes headgear 610, cushion 630, and connector 670. Headgear 610 includes strap 610a and headgear conduit 610b. Similar to user interface 400 ( FIG. 4A to FIG. 4B ) and user interface 500( FIG. 5A to FIG. 5B ), the headgear 610 is configured to be positioned generally around at least a portion of the user's head when the user wears the user interface 600. The headgear 610 includes a band 610a that can be coupled to a headgear conduit 610b and positioned on the user's head so that the user's head is positioned between the band 610a and the headgear conduit 610b. The cushion 630 is positioned between the user's face and the headgear conduit 610b to form a seal on the user's face.

[0054] The connector 670 is configured to couple to the headgear 610 at one end and to a conduit of a respiratory therapy system (e.g., conduit 140) at another end. In other embodiments, the connector 670 is not included and the headgear 610 may instead be directly connected to the conduit of the respiratory therapy system. The headgear conduit 610b may be configured to deliver pressurized air from the conduit of the respiratory therapy system to the cushion 630, or more specifically, to the volume of space surrounding the mouth and / or nose of the user and enclosed by the user cushion. The headgear conduit 610b is hollow to provide a passage for pressurized air. Both sides of the headgear conduit 610b may be hollow to provide two passages for pressurized air. Alternatively, only one side of the headgear conduit 610b may be hollow to provide a single passage. In Fig. 6A and Figure 6B In the illustrated embodiment, the headgear conduit 610b includes two channels that are positioned on either side of the user's head / face in use. Alternatively, only one channel of the headgear conduit 610b can be hollow to provide a single channel. Pressurized air can flow from the conduit of the respiratory therapy system through the connector 670 and the headgear conduit 610b and into the volume of space between the cushion 630 and the user's face. The pressurized air reaches the user's airway from the volume of space between the cushion 630 and the user's face through the user's mouth, nose, or both.

[0055] In some embodiments, the cushion 630 includes a plurality of vents 672 on the cushion 630 itself. Additionally or alternatively, in some embodiments, the connector 670 includes a plurality of vents 676 ("diffuser vents") proximate the headgear 610 for allowing the user's exhaled carbon dioxide (CO2) and other gases to escape when the respiratory therapy device is activated. In some embodiments, the headgear 610 may include at least one additional anti-asphyxia valve (AAV) 674 proximate the cushion 630 to allow the user's exhaled CO2 and other gases to escape in the event that the vent (e.g., vent 672 or 676) fails when the respiratory therapy device is activated.

[0056] Return to reference Figure 1 , conduit 140 (also referred to as an air circuit or tube) allows air to flow between components of respiratory therapy system 100, such as between respiratory therapy device 110 and user interface 120. In some embodiments, there may be separate branches of conduits for inhalation and exhalation. In other embodiments, a single branch conduit is used for both inhalation and exhalation.

[0057] refer to Figure 3A , the conduit 140 includes a first end 142 that is coupled to the air outlet 118 of the respiratory therapy device 110. The first end 142 can be coupled to the air outlet 118 of the respiratory therapy device 110 using various techniques (e.g., a press fit connection, a snap fit connection, a threaded connection, etc.). In some embodiments, the conduit 140 includes one or more heating elements that heat the pressurized air flowing through the conduit 140 (e.g., heating the air to a predetermined temperature or within a predetermined temperature range). Such heating elements can be coupled to the conduit 140 and / or embedded in the conduit. In such embodiments, the first end 142 can include electrical contacts that are electrically coupled to the respiratory therapy device 110 to power the one or more heating elements of the conduit 140. For example, the electrical contacts can be electrically coupled to electrical contacts of the air outlet 118 of the respiratory therapy device 110. In this example, the electrical contacts of the conduit 140 can be male connectors, and the electrical contacts of the air outlet 118 can be female connectors, or alternatively, the opposite configuration can be used.

[0058] Display device 150 is generally used to display images including still images, video images, or both, and / or information about respiratory therapy device 110. For example, display device 150 may provide information about the status of respiratory therapy device 110 (e.g., whether respiratory therapy device 110 is on / off, the pressure of air delivered by respiratory therapy device 110, the temperature of air delivered by respiratory therapy device 110, etc.) and / or other information (e.g., sleep score and / or therapy score (also referred to as myAir TMscores, such as described in WO 2016 / 061629 and U.S. Patent Publication No. 2017 / 0311879, which are hereby incorporated by reference in their entirety), current date / time, personal information of user 20, etc. In some embodiments, display device 150 acts as a human-machine interface (HMI) that includes a graphical user interface (GUI) configured to display an image as an input interface. Display device 150 can be an LED display, an OLED display, an LCD display, etc. The input interface can 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 respiratory therapy device 110.

[0059] The humidifier 160 is coupled to or integrated in the respiratory therapy device 110 and includes a reservoir 162 for storing water that can be used to humidify the pressurized air delivered from the respiratory therapy device 110. The humidifier 160 includes one or more heating elements 164 to heat the water in the reservoir to generate water vapor. The humidifier 160 can be fluidly coupled to a water vapor inlet of an air passage between the blower motor 114 and the air outlet 118, or can be formed in line with the air passage between the blower motor 114 and the air outlet 118. For example, as shown in FIG. 3, air flows from the air inlet 116 through the blower motor 114 and then through the humidifier 160 before leaving the respiratory therapy device 110 via the air outlet 118.

[0060] Although the respiratory therapy system 100 has been described herein as including each of the respiratory therapy device 110, the user interface 120, the conduit 140, the display device 150, and the humidifier 160, more or fewer components may be included in the respiratory therapy system according to embodiments of the present invention. For example, a first alternative respiratory therapy system includes the respiratory therapy device 110, the user interface 120, and the conduit 140. As another example, a second alternative system includes the respiratory therapy device 110, the user interface 120, the conduit 140, and the display device 150. Thus, various respiratory therapy systems may be formed using any one or more portions of the components shown and described herein and / or in combination with one or more other components.

[0061] The control system 200 includes one or more processors 202 (hereinafter referred to as processors 202). The control system 200 is generally used to control (e.g., actuate) various components of the system 10 and / or analyze data obtained and / or generated by the components of the system 10. The processor 202 can be a general-purpose processor or a special-purpose processor or a microprocessor. Figure 1, but the control system 200 may include any number of processors (e.g., one processor, two processors, five processors, ten processors, etc.), which may be located in a single housing or remotely from each other. The control system 200 (or any other control system) or a portion of the control system 200 (such as the processor 202 (or any other processor or one or more portions of any other control system)) may be used to perform one or more steps of any of the methods described and / or claimed herein. The control system 200 may be coupled to the housing of the user device 260 and / or located, for example, within the housing of the user device, within a portion of the respiratory therapy system 100 (e.g., the respiratory therapy device 110), and / or within the housing of one or more sensors in the sensor 210. The control system 200 may be centralized (within one such housing) or decentralized (within two or more such housings that are physically distinct). In such embodiments including two or more housings containing the control system 200, the housings may be located close to and / or remotely from each other.

[0062] The memory device 204 stores machine-readable instructions that are executable by the processor 202 of the control system 200. The memory device 204 may be any suitable computer-readable storage device or medium, such as, for example, a random or serial access memory device, a hard drive, a solid-state drive, a flash memory device, etc. Figure 1 2 , but system 10 may include any suitable number of memory devices 204 (e.g., one memory device, two memory devices, five memory devices, ten memory devices, etc.). Memory device 204 may be coupled to and / or located within a housing of respiratory therapy device 110 of respiratory therapy system 100, within a housing of user device 260, within a housing of one or more of sensors 210, or any combination thereof. Similar to control system 200, memory device 204 may be centralized (within one such housing) or distributed (within two or more such housings that are physically distinct).

[0063] In some embodiments, the memory device 204 stores a user profile associated with the user. The user profile may include, for example, demographic information associated with the user, biometric information associated with the user, medical information associated with the user, self-reported user feedback, sleep parameters associated with the user (e.g., sleep-related parameters recorded from one or more earlier sleep sessions), or any combination thereof. The demographic information may include, for example, information indicating the user's age, the user's gender, the user's race, the user's geographic location, the relationship status, the family history of insomnia or sleep apnea, the user's employment status, the user's educational status, the user's socioeconomic status, or any combination thereof. The medical information may include, for example, information indicating one or more medical conditions associated with the user, the user's medication use, or both. The medical information data may also include a multiple sleep latency test (MSLT) result or score and / or a Pittsburgh Sleep Quality Index (PSQI) score or value. The self-reported user feedback may include information indicating a self-reported subjective sleep score (e.g., poor, average, excellent), the user's self-reported subjective stress level, the user's self-reported subjective fatigue level, the user's self-reported subjective health status, the user's recent life events, or any combination thereof.

[0064] As described herein, the processor 202 and / or the memory device 204 can receive data (e.g., physiological data and / or audio data) from one or more sensors 210, so that the data is stored in the memory device 204 and / or analyzed by the processor 202. The processor 202 and / or the memory device 204 can communicate with the one or more sensors 210 using a wired connection or a wireless connection (e.g., using an RF communication protocol, a Wi-Fi communication protocol, a Bluetooth communication protocol, via a cellular network, etc.). In some embodiments, the system 10 may include an antenna, a receiver (e.g., an RF receiver), a transmitter (e.g., an RF transmitter), a transceiver, or any combination thereof. Such components can be coupled to or integrated into a housing of the control system 200 (e.g., in the same housing as the processor 202 and / or the memory device 204) or the user device 260.

[0065] Return to reference Figure 1, the one or more sensors 210 include a pressure sensor 212, a flow sensor 214, a temperature sensor 216, a motion sensor 218, a microphone 220, a speaker 222, a radio frequency (RF) receiver 226, an RF transmitter 228, a camera 232, an infrared sensor 234, a photoplethysmography (PPG) sensor 236, an electrocardiogram (ECG) sensor 238, an electroencephalogram (EEG) sensor 240, a capacitive sensor 242, a force sensor 244, a strain gauge sensor 246, an electromyogram (EMG) sensor 248, an oxygen sensor 250, an analyte sensor 252, a humidity sensor 254, a LiDAR sensor 256, or any combination thereof. In general, each of the one or more sensors 210 is configured to output sensor data, which is received and stored in the memory device 204 or one or more other memory devices.

[0066] Although the one or more sensors 210 are shown and described as including each of the pressure sensor 212, the flow sensor 214, the temperature sensor 216, the motion sensor 218, the microphone 220, the speaker 222, the RF receiver 226, the RF transmitter 228, the camera 232, the infrared sensor 234, the photoplethysmography (PPG) sensor 236, the electrocardiogram (ECG) sensor 238, the electroencephalogram (EEG) sensor 240, the capacitive sensor 242, the force sensor 244, the strain gauge sensor 246, the electromyogram (EMG) sensor 248, the oxygen sensor 250, the analyte sensor 252, the humidity sensor 254, and the LiDAR sensor 256, more generally, the one or more sensors 210 may include any combination and any number of each of the sensors described and / or shown herein.

[0067] As described herein, the system 10 may generally be used to generate physiological data associated with a user (e.g., a user of the respiratory therapy system 100) during a sleep session. The physiological data may be analyzed to generate one or more sleep-related parameters, which may include any parameters, measurements, etc. associated with the user during the sleep session. The one or more sleep-related parameters that may be determined for the user 20 during the sleep session include, for example, an apnea-hypopnea index (AHI) score, a sleep score, a flow signal, a breathing signal, a breathing rate, an inspiratory amplitude, an expiratory amplitude, an inspiratory-expiratory ratio, a number of events per hour, an event pattern, a stage, a pressure setting of the respiratory therapy device 110, a heart rate, a heart rate variability, movement of the user 20, a temperature, an EEG activity, an EMG activity, micro-arousals, snoring, choking, coughing, whistling, gasping, or any combination thereof.

[0068] The one or more sensors 210 may be used to generate, for example, physiological data, audio data, or both. The control system 200 may use the physiological data generated by one or more of the sensors 210 to determine whether the user 20 ( Figure 2 ) and one or more sleep-related parameters associated with the sleep-wake signal. The sleep-wake signal can indicate one or more sleep states, including wakefulness, relaxed wakefulness, micro-awakening, or different sleep stages, such as, for example, a rapid eye movement (REM) stage, 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 states and / or sleep stages based on physiological data generated by one or more sensors (such as one or more sensors 210) are described in, for example, WO 2014 / 047310, U.S. Patent Publication No. 2014 / 0088373, WO 2017 / 132726, WO 2019 / 122413, WO 2019 / 122414, and U.S. Patent Publication No. 2020 / 0383580, each of which is hereby incorporated by reference in its entirety.

[0069] In some embodiments, the sleep-wake signal described herein may be time stamped to indicate the time when the user entered the bed, the time when the user left the bed, the time when the user attempted to fall asleep, etc. The sleep-wake signal may be measured by one or more sensors 210 during a sleep session at a predetermined sampling rate, such as, for example, one sample per second, one sample per 30 seconds, one sample per minute, etc. In some embodiments, the sleep-wake signal may also indicate a respiratory signal, a respiratory rate, an inspiratory amplitude, an expiratory amplitude, an inspiratory-expiratory ratio, a number of events per hour, a pattern of events, a pressure setting of the respiratory therapy device 110, or any combination thereof during a sleep session. Events may include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, mask leak (e.g., from the user interface 120), restless legs, sleep disturbance, choking, increased heart rate, difficulty breathing, asthma attack, epileptic seizure, convulsion, or any combination thereof. One or more sleep-related parameters that can be determined for a user based on the sleep-wake signal during a sleep session include, for example, total time in bed, total sleep time, sleep onset latency, wake parameters after sleep onset, sleep efficiency, segmentation index, or any combination thereof. As described in further detail herein, physiological data and / or sleep-related parameters can be analyzed to determine one or more sleep-related scores.

[0070] The physiological data and / or audio data generated by one or more sensors 210 can also be used to determine a breathing signal associated with the user during a sleep session. The breathing signal generally indicates the user's breathing (respiration / breathing) during a sleep session. The breathing signal can indicate and / or be analyzed to determine (e.g., using the control system 200) one or more sleep-related parameters, such as, for example, respiratory rate, respiratory rate variability, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, the occurrence of one or more events, the number of events per hour, event patterns, sleep states, SLEET stages, apnea-hypopnea index (AHI), pressure settings of the respiratory therapy device 110, or any combination thereof. One or more events can include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, mask leak (e.g., from the user interface 120), coughing, restless legs, sleep disorders, suffocation, increased heart rate, dyspnea, asthma attack, epileptic seizure, convulsion, increased blood pressure, or any combination thereof. Many of the sleep-related parameters are physiological parameters, although some of the sleep-related parameters can be considered non-physiological parameters. Other types of physiological parameters and / or non-physiological parameters may also be determined based on data from one or more sensors 210 or based on other types of data.

[0071] The pressure sensor 212 outputs pressure data that can be stored in the memory device 204 and / or analyzed by the processor 202 of the control system 200. In some embodiments, the pressure sensor 212 is an air pressure sensor (e.g., an atmospheric pressure sensor) that generates sensor data indicative of the respiration (e.g., inhalation and / or exhalation) of the user of the respiratory therapy system 100 and / or ambient pressure. In such embodiments, the pressure sensor 212 can be coupled to or integrated in the respiratory therapy device 110. The pressure sensor 212 can be, for example, a capacitive sensor, an electromagnetic sensor, a piezoelectric sensor, a strain gauge sensor, an optical sensor, a potentiometric sensor, or any combination thereof.

[0072] The flow sensor 214 outputs flow data, which can be stored in the memory device 204 and / or analyzed by the processor 202 of the control system 200. Examples of flow sensors (such as, for example, flow sensors 214) are described in International Publication No. WO 2012 / 012835 and U.S. Patent No. 10,328,219, both of which are incorporated herein by reference in their entirety. In some embodiments, the flow sensor 214 is used to determine the air flow from the respiratory therapy device 110, the air flow through the conduit 140, the air flow through the user interface 120, or any combination thereof. In such embodiments, the flow sensor 214 can be coupled to the respiratory therapy device 110, the user interface 120, or the conduit 140 or integrated in the respiratory therapy device, the user interface, or the conduit. The flow sensor 214 can 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 flow meter, an ultrasonic flow meter, a hot wire sensor, a vortex sensor, a membrane sensor, or any combination thereof. In some embodiments, the flow sensor 214 is configured to measure ventilation flow (e.g., intentional "leak"), unintentional leak (e.g., mouth leak and / or mask leak), patient flow (e.g., air entering and / or leaving the lungs), or any combination thereof. In some embodiments, the flow data can be analyzed to determine the user's cardiogenic oscillations. In some examples, the pressure sensor 212 can be used to determine the user's blood pressure.

[0073] The temperature sensor 216 outputs temperature data that can be stored in the memory device 204 and / or analyzed by the processor 202 of the control system 200. In some embodiments, the temperature sensor 216 generates a temperature data indicating that the user 20 ( Figure 2 ), the core body temperature of user 20, the skin temperature of user 20, the temperature of air flowing out of respiratory therapy device 110 and / or through conduit 140, the temperature in user interface 120, the ambient temperature, or any combination thereof. Temperature sensor 216 may be, for example, a thermocouple sensor, a thermistor sensor, a silicon bandgap temperature sensor or a semiconductor-based sensor, a resistance temperature detector, or any combination thereof.

[0074] The motion sensor 218 outputs motion data that can be stored in the memory device 204 and / or analyzed by the processor 202 of the control system 200. The motion sensor 218 can be used to detect movement of the user 20 during a sleep session, and / or detect movement of any of the components of the respiratory therapy system 100 (such as the respiratory therapy device 110, the user interface 120, or the catheter 140). The motion sensor 218 may include one or more inertial sensors, such as an accelerometer, a gyroscope, and a magnetometer. In some embodiments, the motion sensor 218 alternatively or additionally generates one or more signals representing the user's body movement, from which a signal representing the user's sleep state can be obtained; for example, via the user's breathing movement. In some embodiments, the motion data from the motion sensor 218 can be used in combination with additional data from another sensor in the sensor 210 to determine the user's sleep state.

[0075] The microphone 220 outputs sounds and / or audio data that can be stored in the memory device 204 and / or analyzed by the processor 202 of the control system 200. The audio data generated by the microphone 220 can be reproduced as one or more sounds (e.g., sounds from the user 20) during the sleep session. The audio data from the microphone 220 can also be used to identify (e.g., using the control system 200) events experienced by the user during the sleep session, as described in further detail herein. The microphone 220 can be coupled to the respiratory therapy device 110, the user interface 120, the catheter 140, or the user device 260 or integrated in the respiratory therapy device, the user interface, the catheter, or the user device. In some embodiments, the system 10 includes multiple microphones (e.g., two or more microphones and / or a microphone array with beamforming) so that the sound data generated by each of the multiple microphones can be used to distinguish the sound data generated by another microphone in the multiple microphones.

[0076] Speaker 222 outputs information to the user of system 10 (e.g., Figure 2 The speaker 222 may be used, for example, as an alarm clock or to play an alarm or message to the user 20 (e.g., in response to an event). In some embodiments, the speaker 222 may be used to communicate audio data generated by the microphone 220 to the user. The speaker 222 may be coupled to or integrated into the respiratory therapy device 110, the user interface 120, the catheter 140, or the user device 260.

[0077] Microphone 220 and speaker 222 can be used as separate devices. In some embodiments, microphone 220 and speaker 222 can be combined into an acoustic sensor 224 (e.g., a SONAR sensor), as described in, for example, WO 2018 / 050913, WO2020 / 104465, U.S. Patent Application Publication No. 2022 / 0007965, each of which is hereby incorporated by reference in its entirety. In such embodiments, speaker 222 generates or emits sound waves at predetermined intervals, and microphone 220 detects reflections of the emitted sound waves from speaker 222. The sound waves generated or emitted by speaker 222 have a frequency that is inaudible to the human ear (e.g., below 20 Hz or above about 18 kHz) so as not to interfere with user 20 or bed partner 30 ( Figure 2 )'s sleep. Based at least in part on the data from the microphone 220 and / or the speaker 222, the control system 200 may determine that the user 20 ( Figure 2 ) and / or one or more of the sleep-related parameters described herein, such as, for example, a respiratory signal, a respiratory rate, an inspiratory amplitude, an expiratory amplitude, an inspiratory-expiratory ratio, a number of events per hour, an event pattern, a sleep state, a sleep stage, a pressure setting of the respiratory therapy device 110, or any combination thereof. In such a context, a sonar sensor may be understood to involve active acoustic sensing such as generating and / or transmitting ultrasound and / or low-frequency ultrasound sensing signals (e.g., in a frequency range of, for example, about 17-23 kHz, 18-22 kHz, or 17-18 kHz) through air.

[0078] In some embodiments, the sensor 210 includes: (i) a first microphone that is the same as or similar to the microphone 220 and is integrated into the acoustic sensor 224; and (ii) a second microphone that is the same as or similar to the microphone 220, but is separate and different from the first microphone integrated into the acoustic sensor 224.

[0079] The RF transmitter 228 generates and / or transmits radio waves having a predetermined frequency and / or a predetermined amplitude (e.g., within a high frequency band, within a low frequency band, a long wave signal, a short wave signal, etc.). The RF receiver 226 detects reflections of the radio waves transmitted from the RF transmitter 228, and this data can be analyzed by the control system 200 to determine the user's position and / or one or more of the sleep-related parameters described herein. The RF receiver (RF receiver 226 and RF transmitter 228 or another RF pair) can also be used for wireless communication between the control system 200, the respiratory therapy device 110, one or more sensors 210, the user device 260, or any combination thereof. Although the RF receiver 226 and the RF transmitter 228 are in Figure 12 and 3. Although shown as separate and distinct elements, in some embodiments, the RF receiver 226 and the RF transmitter 228 are combined as part of the RF sensor 230 (e.g., a RADAR sensor). In some such embodiments, the RF sensor 230 includes a control circuit. The format of the RF communication can be Wi-Fi, Bluetooth, etc.

[0080] In some embodiments, the RF sensor 230 is part of a mesh system. An example of a mesh system is a Wi-Fi mesh system, which may include mesh nodes, mesh routers, and mesh gateways, each of which may be mobile / removable or fixed. In such embodiments, the Wi-Fi mesh system includes a Wi-Fi router and / or a Wi-Fi controller and one or more satellites (e.g., access points), each of which includes an RF sensor that is the same or similar to the RF sensor 230. The Wi-Fi router and the satellites communicate continuously with each other using Wi-Fi signals. The Wi-Fi mesh system can be used to generate motion data based on changes in Wi-Fi signals (e.g., differences in received signal strength) between the router and the satellite due to partial obstruction of the signal by a moving object or person. The motion data may indicate movement, breathing, heart rate, gait, falls, behavior, etc., or any combination thereof.

[0081] The camera 232 outputs image data that can be reproduced as one or more images (e.g., still images, video images, thermal images, or any combination thereof) that can be stored in the memory device 204. The image data from the camera 232 can be used by the control system 200 to determine one or more of the sleep-related parameters described herein, such as, for example, one or more events (e.g., periodic limb movements or restless legs syndrome), a breathing signal, a breathing rate, an inspiratory amplitude, an expiratory amplitude, an inspiratory-expiratory ratio, a number of events per hour, an event pattern, a sleep state, a sleep stage, or any combination thereof. In addition, the image data from the camera 232 can be used to, for example, identify the user's position, determine the user's chest movement ( Figure 2 ), determine the air flow around the user's mouth and / or nose, determine when the user enters the bed ( Figure 2 ) and determining when the user leaves the bed. In some embodiments, the camera 232 includes a wide-angle lens or a fisheye lens.

[0082] Infrared (IR) sensor 234 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 memory device 204. Infrared data from IR sensor 234 can be used to determine one or more sleep-related parameters during a sleep session, including the temperature of user 20 and / or the movement of user 20. IR sensor 234 can also be used in conjunction with camera 232 when measuring the presence, position, and / or movement of user 20. For example, IR sensor 234 can detect infrared light having a wavelength between about 700 nm and about 1 mm, while camera 232 can detect visible light having a wavelength between about 380 nm and about 740 nm.

[0083] The PPG sensor 236 outputs the same signal as the user 20 ( Figure 2 ) that can be used to determine one or more sleep-related parameters, such as, for example, heart rate, heart rate variability, cardiac cycle, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, estimated blood pressure parameters, or any combination thereof. The PPG sensor 236 can be worn by the user 20, embedded in clothing and / or fabric worn by the user 20, embedded in the user interface 120 and / or its associated headgear (e.g., a band, etc.), and / or coupled to the user interface and / or its associated headgear (e.g., a band, etc.), etc.

[0084] ECG sensor 238 outputs physiological data associated with the electrical activity of the heart of user 20. In some embodiments, ECG sensor 238 includes one or more electrodes positioned on or around a portion of user 20 during a sleep session. Physiological data from ECG sensor 238 can be used, for example, to determine one or more of the sleep-related parameters described herein.

[0085] The EEG sensor 240 outputs physiological data associated with the electrical activity of the brain of the user 20. In some embodiments, the EEG sensor 240 includes one or more electrodes positioned on or around the scalp of the user 20 during a sleep session. The physiological data from the EEG sensor 240 can be used, for example, to determine the sleep state and / or sleep stage of the user 20 at any given time during the sleep session. In some embodiments, the EEG sensor 240 can be integrated into the user interface 120 and / or associated headgear (e.g., a band, etc.).

[0086] Capacitive sensor 242, force sensor 244, and strain gauge sensor 246 output data that can be stored in memory device 204 and used / analyzed by control system 200 to determine, for example, one or more of the sleep-related parameters described herein. EMG sensor 248 outputs physiological data associated with electrical activity generated by one or more muscles. Oxygen sensor 250 outputs oxygen data indicating the oxygen concentration of a gas (e.g., in conduit 140 or at user interface 120). Oxygen sensor 250 can be, for example, an ultrasonic oxygen sensor, an electrical oxygen sensor, a chemical oxygen sensor, an optical oxygen sensor, a pulse oximeter (e.g., an SpO2 sensor), or any combination thereof.

[0087] The analyte sensor 252 can be used to detect the presence of an analyte in the exhaled breath of the user 20. The data output by the analyte sensor 252 can be stored in the memory device 204 and used by the control system 200 to determine the identity and concentration of any analyte in the user's breath. In some embodiments, the analyte sensor 174 is positioned near the user's mouth to detect analytes in the breath exhaled from the user's mouth. For example, when the user interface 120 is a mask covering the user's nose and mouth, the analyte sensor 252 can be positioned in the mask to monitor the user's mouth breathing. In other embodiments, such as when the user interface 120 is a nasal mask or a nasal pillow mask, the analyte sensor 252 can be positioned near the user's nose to detect analytes in the breath exhaled through the user's nose. In other embodiments, when the user interface 120 is a nasal mask or a nasal pillow mask, the analyte sensor 252 can be positioned near the user's mouth. In this embodiment, the analyte sensor 252 can be used to detect whether any air leaks unintentionally from the user's mouth and / or the user interface 120. In some embodiments, the analyte sensor 252 is a volatile organic compound (VOC) sensor that can be used to detect carbon-based chemicals or compounds. 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 data output by the analyte sensor 252 positioned near the user's mouth or positioned within the mask (e.g., in embodiments where the user interface 120 is a mask) detects the presence of an analyte, the control system 200 can use the data as an indication that the user is breathing through their mouth.

[0088] The humidity sensor 254 outputs data that can be stored in the memory device 204 and used by the control system 200. The humidity sensor 254 can be used to detect humidity in various areas surrounding the user (e.g., within the conduit 140 or the user interface 120, near the user's face, near the connection between the conduit 140 and the user interface 120, near the connection between the conduit 140 and the respiratory therapy device 110, etc.). Therefore, in some embodiments, the humidity sensor 254 can be coupled to the user interface 120 or the conduit 140 or integrated in the user interface or in the conduit to monitor the humidity of the pressurized air from the respiratory therapy device 110. In other embodiments, the humidity sensor 254 is placed near any area where the humidity level needs to be monitored. The humidity sensor 254 can also be used to monitor the humidity of the surrounding environment surrounding the user, such as the air in a bedroom.

[0089] Light detection and ranging (LiDAR) sensor 256 can be used for depth sensing. This type of optical sensor (e.g., laser sensor) can be used to detect objects and build a three-dimensional (3D) map of the surrounding environment (such as living space). LiDAR can usually use pulsed lasers to measure time of flight. LiDAR is also called 3D laser scanning. In an example using such a sensor, a fixed or mobile device (such as a smart phone) with a LiDAR sensor 256 can measure and map an area extending 5 meters or more away from the sensor. For example, LiDAR data can be fused with point cloud data estimated by an electromagnetic RADAR sensor. LiDAR sensor 256 can also use artificial intelligence (AI) to automatically make the RADAR system enter the geo-fence 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 to the RADAR). For example, LiDAR can also be used to provide an estimate of a person's height, as well as changes in height when a person sits down or falls. LiDAR can be used to form a 3D grid representation of the environment. In a further use, for solid surfaces through which radio waves pass (e.g., radio translucent materials), LiDAR can reflect off such surfaces, allowing classification of different types of obstacles.

[0090] In some embodiments, one or more sensors 210 also include a galvanic skin response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a sphygmomanometer sensor, an oximeter sensor, a sonar sensor, a RADAR sensor, a blood glucose sensor, a color sensor, a pH sensor, an air quality sensor, a tilt sensor, a rain sensor, a soil moisture sensor, a water flow sensor, an alcohol sensor, or any combination thereof.

[0091] Although in Figure 110, but any combination of one or more sensors 210 may be integrated into and / or coupled to any one or more of the components of system 100, including respiratory therapy device 110, user interface 120, conduit 140, humidifier 160, control system 200, user device 260, activity tracker 270, or any combination thereof. For example, microphone 220 and speaker 222 may be integrated into and / or coupled to user device 260, and pressure sensor 212 and / or flow sensor 132 may be integrated into and / or coupled to respiratory therapy device 110. In some embodiments, at least one of the one or more sensors 210 is not coupled to respiratory therapy device 110, control system 200, or user device 260, and is generally positioned adjacent to user 20 during a sleep session (e.g., positioned on or in contact with a portion of user 20, worn by user 20, coupled to or positioned on a nightstand, coupled to a mattress, coupled to a ceiling, etc.).

[0092] One or more of respiratory therapy device 110, user interface 120, conduit 140, display device 150, and humidifier 160 may include one or more sensors (e.g., a pressure sensor, a flow sensor, a microphone, or more generally any of other sensors 210 described herein). These one or more sensors may be used, for example, to measure the air pressure and / or flow of pressurized air supplied by respiratory therapy device 110.

[0093] Data from one or more sensors 210 may be analyzed (e.g., by the control system 200) to determine one or more sleep-related parameters, which may include a respiratory signal, a respiratory rate, a respiratory pattern, an inspiratory amplitude, an expiratory amplitude, an inspiratory-expiratory ratio, the occurrence of one or more events, the number of events per hour, an event pattern, a sleep state, an apnea-hypopnea index (AHI), or any combination thereof. One or more events may include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, mask leak, cough, restless legs, sleep disorder, choking, increased heart rate, dyspnea, asthma attack, epileptic seizure, convulsion, increased blood pressure, or any combination thereof. Many of these sleep-related parameters are physiological parameters, although some of the sleep-related parameters may be considered non-physiological parameters. Other types of physiological parameters and non-physiological parameters may also be determined based on data from one or more sensors 210 or based on other types of data.

[0094] User equipment 260 ( Figure 1) includes a display device 262. User device 260 can be, for example, a mobile device such as a smart phone, a tablet, a game console, a smart watch, a laptop, etc. Alternatively, user device 260 can be an external sensing system, a television (e.g., a smart TV) or another smart home device (e.g., a smart speaker such as Google Home, Amazon Echo, Alexa, etc.). In some embodiments, the user device is a wearable device (e.g., a smart watch). Display device 262 is generally used to display images including still images, video images, or both. In some embodiments, display device 262 acts as a human-machine interface (HMI), which includes a graphical user interface (GUI) and an input interface configured to display images. Display device 262 can be an LED display, an OLED display, an LCD display, etc. The input interface can be, for example, a touch screen or a touch-sensitive substrate, a mouse, a keyboard, or any sensor system configured to sense input made by a human user interacting with user device 260. In some embodiments, system 10 can use and / or include one or more user devices.

[0095] In some embodiments, the system 100 also includes an activity tracker 270. The activity tracker 270 is generally used to help generate physiological data associated with the user. The activity tracker 270 may include one or more of the sensors 210 described herein, such as, for example, a motion sensor 138 (e.g., one or more accelerometers and / or gyroscopes), a PPG sensor 154, and / or an ECG sensor 156. The physiological data from the activity tracker 270 can be used to determine, for example, the number of steps, the distance traveled, the number of steps climbed, the duration of physical activity, the type of physical activity, the intensity of physical activity, the time spent standing, the breathing rate, the average breathing rate, the resting breathing rate, the maximum breathing rate, the breathing rate variability, the heart rate, the average heart rate, the resting heart rate, the maximum heart rate, the heart rate variability, the number of calories burned, the blood oxygen saturation, the skin electrode activity (also known as skin conductance or skin electrode response), or any combination thereof. In some embodiments, the activity tracker 270 is coupled to the user device 260 (e.g., electronically or physically).

[0096] In some embodiments, the activity tracker 270 is a wearable device that can be worn by a user, such as a smart watch, wristband, ring, or patch. Figure 2, activity tracker 270 is worn on the wrist of user 20. Activity tracker 270 may also be coupled to or integrated into a garment or clothing worn by the user. Still alternatively, activity tracker 270 may also be coupled to or integrated into user device 260 (e.g., within the same housing). More generally, activity tracker 270 may be communicatively coupled to or physically integrated into (e.g., within a housing) control system 200, memory device 204, respiratory therapy system 100, and / or user device 260.

[0097] In some embodiments, the system 100 also includes a blood pressure device 280. The blood pressure device 280 is generally used to assist in generating cardiovascular data to determine one or more blood pressure measurements associated with the user 20. The blood pressure device 280 may include at least one of the one or more sensors 210 to measure, for example, a systolic blood pressure component and / or a diastolic blood pressure component.

[0098] In some embodiments, blood pressure device 280 is a sphygmomanometer that includes an inflatable cuff and a pressure sensor (e.g., pressure sensor 212 described herein) that can be worn by user 20. For example, in Figure 2 In the example of , the blood pressure device 280 can be worn on the upper arm of the user 20. In such embodiments where the blood pressure device 280 is a sphygmomanometer, the blood pressure device 280 also includes a pump (e.g., a manually operated bulb) for inflating the cuff. In some embodiments, the blood pressure device 280 is coupled to the respiratory therapy device 110 of the respiratory therapy system 100, which in turn delivers pressurized air to inflate the cuff. More generally, the blood pressure device 280 can be communicatively coupled to and / or physically integrated into (e.g., within a housing) the control system 200, the memory device 204, the respiratory therapy system 100, the user device 260, and / or the activity tracker 270.

[0099] In other embodiments, the blood pressure device 280 is a mobile blood pressure monitor communicatively coupled to the respiratory therapy system 100. The mobile blood pressure monitor includes a portable recording device attached to a band or belt worn by the user 20 and an inflatable cuff attached to the portable recording device and worn around the arm of the user 20. The mobile blood pressure monitor is configured to measure blood pressure about every 15 minutes to about 30 minutes over a 24-hour or 48-hour period. The mobile blood pressure monitor can simultaneously measure the heart rate of the user 20. These multiple readings are averaged over a 24-hour period. The mobile blood pressure monitor determines any changes in the blood pressure and heart rate of the user 20 measured during the sleep time period and the wake time period of the user 20, as well as any distribution and / or trend patterns of the blood pressure and heart rate data. The measured data and statistics can then be communicated to the respiratory therapy system 100.

[0100] The blood pressure device 280 can be positioned external to the respiratory therapy system 100, coupled directly or indirectly to the user interface 120, coupled directly or indirectly to a headgear associated with the user interface 120, or inflatably coupled to a portion of or around the user 20. The blood pressure device 280 is generally used to help generate physiological data to determine one or more blood pressure measurements associated with the user, such as a systolic blood pressure component and / or a diastolic blood pressure component. In some embodiments, the blood pressure device 280 is a sphygmomanometer that includes an inflatable cuff that can be worn by the user and a pressure sensor (e.g., the pressure sensor 212 described herein).

[0101] In some embodiments, the blood pressure device 280 is an invasive device that can continuously monitor the arterial blood pressure of the user 20 and collect arterial blood samples as needed to analyze the gas of the arterial blood. In some other embodiments, the blood pressure device 280 is a continuous blood pressure monitor that uses a radio frequency sensor and can measure the blood pressure of the user 20 only once every few seconds (e.g., every 3 seconds, every 5 seconds, every 7 seconds, etc.). The radio frequency sensor can use continuous wave, frequency modulated continuous wave (FMCW with ramp linear frequency modulation wave, triangle wave, sine wave), other schemes such as PSK, FSK, etc., pulse continuous wave, and / or extension in ultra-wideband range (which can include extension, PRN code or pulse system).

[0102] Although the control system 200 and the memory device 204 are Figure 1 100, but in some embodiments, the control system 200 and / or the memory device 204 are integrated into the user device 260 and / or the respiratory therapy device 110. Alternatively, in some embodiments, the control system 200 or a portion thereof (e.g., the processor 202) can be located in the cloud (e.g., integrated in a server, integrated in an Internet of Things (IoT) device, connected to the cloud, subject to edge cloud processing, etc.), located in one or more servers (e.g., a remote server, a local server, etc.), or any combination thereof.

[0103] Although system 100 is shown as including all of the above components, more or fewer components may be included in systems according to embodiments of the present invention. For example, a first alternative system includes control system 200, memory device 204, and at least one of one or more sensors 210, and does not include respiratory therapy system 100. As another example, a second alternative system includes control system 200, memory device 204, at least one of one or more sensors 210, and user device 260. As yet another example, a third alternative system includes control system 200, memory device 204, respiratory therapy system 100, at least one of one or more sensors 210, and user device 260. Thus, various systems may be formed using any one or more portions of the components shown and described herein and / or in combination with one or more other components.

[0104] As used herein, a sleep session may be defined in a variety of ways. For example, a sleep session may be defined by an initial start time and an end time. In some embodiments, a sleep session is a duration of time that a user sleeps, i.e., a sleep session has a start time and an end time, and during the sleep session, the user does not wake up until the end time. That is, any period of time that the user is awake is not included in a sleep session. According to this first definition of a sleep session, if a user wakes up and falls asleep multiple times in the same night, each of the sleep intervals separated by the awake intervals is a sleep session.

[0105] Alternatively, in some embodiments, a sleep session has a start time and an end time, and during a sleep session, as long as the user is awake for a continuous duration below an awake duration threshold, the user can wake up without the sleep session ending. The awake duration threshold can be defined as a percentage of the sleep session. The awake duration threshold can be, for example, about 20% of the sleep session, about 15% of the sleep session duration, about 10% of the sleep session duration, about 5% of the sleep session duration, about 2% of the sleep session duration, etc., or any other threshold percentage. In some embodiments, the awake 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, etc., or any other amount of time.

[0106] In some embodiments, a sleep session is defined as the entire time between the time the user first goes to bed in the evening and the time the user last leaves the bed the next morning. In other words, a sleep session can be defined as a period of time that begins on a first date (e.g., Monday, January 6, 2020) at a first time (e.g., 10:00 p.m.) when the user first goes to bed intending to fall asleep (e.g., this is not the case if the user intends to first watch TV or use a smartphone before falling asleep, etc.), which can be referred to as the current evening, and ends on a second date (e.g., Tuesday, January 7, 2020) at a second time (e.g., 7:00 a.m.) when the user first leaves the bed and does not intend to fall asleep again the next morning.

[0107] In some embodiments, a user can manually define the start of a sleep session and / or manually terminate a sleep session. For example, a user can select (e.g., by clicking or tapping) a sleep session on user device 260 ( Figure 1 ) to manually initiate or terminate a sleep session by using one or more user-selectable elements displayed on the display device 262 of the display device.

[0108] Generally, a sleep session includes any point in time after the user 20 has been lying or sitting in the bed 40 (or another area or object where they intend to sleep), and has turned on the respiratory therapy device 110 and put on the user interface 120. A sleep session may therefore include the following time periods: (i) when the user 20 is using the respiratory therapy system 100, but before the user 20 attempts to fall asleep (e.g., when the user 20 is lying in the bed 40 reading a book); (ii) when the user 20 begins to try to fall asleep but is still awake; (iii) when the user 20 is in light sleep (also known as stage 1 and stage 2 of non-rapid eye movement (NREM) sleep); (iv) when the user 20 is in deep sleep (also known as slow wave sleep SWS or stage 3 of NREM sleep); (v) when the user 20 is in rapid eye movement (REM sleep); (vi) when the user 20 is awake periodically between light sleep, deep sleep, or REM sleep; or (vii) when the user 20 wakes up and does not fall back asleep.

[0109] A sleep session is generally defined as ending once user 20 removes user interface 120, turns off respiratory therapy device 110, and leaves bed 40. In some embodiments, a sleep session may include additional time periods, or may be limited to only some of the time periods disclosed above. For example, a sleep session may be defined as a time period that begins when respiratory therapy device 110 begins supplying pressurized air to the airway or user 20, ends when respiratory therapy device 110 stops supplying pressurized air to the airway of user 20, and includes some or all time points in between when user 20 falls asleep or wakes up.

[0110] refer to Figure 7 Timeline 700 in the figure, bed entry time t 床 The user initially enters the bed (e.g., before falling asleep) (e.g., when the user lies down or sits in bed) Figure 2 The bed entry time t can be identified based on the bed threshold duration 床 , to distinguish between the time when the user enters the bed for sleeping and the time when the user enters the bed for other reasons (e.g., watching TV). For example, the bed threshold duration can be at least about 10 minutes, at least about 20 minutes, at least about 30 minutes, at least about 45 minutes, at least about 1 hour, at least about 2 hours, etc. Although the bed entry time t is described herein with reference to the bed, 床 , but more generally, the bed entry time t 床 May refer to the time when a user initially enters any position (eg, sofa, chair, sleeping bag, etc.) for the purpose of sleeping.

[0111] Going to sleep time (GTS) and the time it takes for the user to enter the bed (t 床 ) is associated with the time of an initial attempt to fall asleep after entering the bed. For example, after entering the bed, the user may engage in one or more activities to relax before attempting to fall asleep (e.g., reading, watching television, listening to music, using user device 260, etc.). The initial sleep time (t 睡眠 ) is the time when the user initially falls asleep. For example, the initial sleep time (t 睡眠 ) may be the time when the user initially enters the first non-REM sleep stage.

[0112] Wake up time 觉醒 is the time associated with the time when the user wakes up and does not fall asleep again (e.g., as opposed to the user waking up in the middle of the night and falling asleep again). The user may experience one of a number of unconscious micro-awakenings (e.g., micro-awakenings MA1 and MA2) with short durations (e.g., 5 seconds, 10 seconds, 30 seconds, 1 minute, etc.) after initially falling asleep. 觉醒 Instead, the user falls asleep again after each of the micro-awakenings MA1 and MA2. Similarly, the user may have one or more conscious awakenings (e.g., awakening A) after initially falling asleep (e.g., getting up to go to the bathroom, taking care of a child or pet, sleepwalking, etc.). However, the user falls asleep again after awakening A. Therefore, the wake-up time t 觉醒 It can be defined, for example, based on a wakefulness threshold duration (e.g., the user is awake for at least 15 minutes, at least 20 minutes, at least 30 minutes, at least 1 hour, etc.).

[0113] Similarly, the standing time t 起身is associated with the time when the user leaves the bed and moves away from the bed with the intention of ending the sleep session (e.g., as opposed to the user getting up during the night to go to the bathroom, take care of children or pets, sleepwalk, etc.). In other words, the time to get up t 起身 is the time when the user last left the bed and did not return to the bed until the next sleep session (e.g., the next night). Therefore, the rise time t 起身 The bed entry time t of the second subsequent sleep session may be defined, for example, based on a get-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 of the second subsequent sleep session may also be defined based on a get-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.). 床 time.

[0114] As mentioned above, at the initial t 床 With the final t 起身 During the night between t and t, the user may wake up and get out of bed more than once. In some embodiments, the final wake-up time t is identified or determined based on a predetermined threshold duration after an event (e.g., falling asleep or getting out of bed). 觉醒 and / or final standing time t 起身 Such a threshold duration may be customized for the user. For a typical user who goes to bed at night and then wakes up and gets out of bed in the morning, any time period of about 12 hours to about 18 hours may be used (at the time the user wakes up (t 觉醒 ) or stand up (t 起身 ) and the user goes to bed (t 床 ), enter sleep (t GTS ) or fall asleep (t 睡眠 )). For users who spend longer periods of time in bed, a shorter threshold time period (e.g., about 8 hours to about 14 hours) may be used. The threshold time period may be initially selected and / or later adjusted based on a system that monitors the user's sleep behavior.

[0115] Total time in bed (TIB) is the time spent in bed 床 and the time to stand up 起身 The total sleep time (TST) is associated with the duration between the initial sleep time and the wake time, excluding any conscious or unconscious arousals and / or micro-awakenings in between. Generally, the total sleep time (TST) will be shorter than the total time in bed (TIB) (e.g., one minute shorter, ten minutes shorter, one hour shorter, etc.). For example, refer to Figure 7 Timeline 700, total sleep time (TST) at initial sleep time t 睡眠 and wake-up time t 觉醒, but does not include the duration of the first micro-awakening MA1 , the second micro-awakening 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).

[0116] In some embodiments, total sleep time (TST) can be defined as continuous total sleep time (PTST). In such embodiments, continuous total sleep time does not include a predetermined initial portion or time period of the first non-REM stage (e.g., a light sleep stage). For example, the predetermined initial portion may 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. Continuous total sleep time is a measure of continuous sleep and smoothes the sleep-wake hypnogram. 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 wake stage for a very short period (e.g., one minute), and then return to the first non-REM stage. In this example, continuous total sleep time does not include a first instance of the first non-REM stage (e.g., about 30 seconds).

[0117] In some embodiments, a sleep session is defined as the time between bed entry (t 床 ) and at the time of getting up (t 起身 ) ends, i.e., the sleep session is defined as total time in bed (TIB). In some embodiments, a sleep session is defined as the total time in bed (TIB) during the initial sleep time (t 睡眠 ) and starts at the wake-up time (t 觉醒 ) ends. In some embodiments, a sleep session is defined as total sleep time (TST). In some embodiments, a sleep session is defined as the time between sleep onset time (t GTS ) and starts at the wake-up time (t 觉醒 ) ends. In some embodiments, a sleep session is defined as a sleep session starting at sleep entry time (t GTS ) and at the time of getting up (t 起身 ) ends. In some embodiments, a sleep session is defined as the time at which a person enters the bed (t 床 ) and starts at the wake-up time (t 觉醒 ) ends. In some embodiments, a sleep session is defined as a sleep session at an initial sleep time (t 睡眠 ) and at the time of getting up (t 起身 )Finish.

[0118] refer to Figure 8 , illustrating a timeline 700 ( Figure 7). As shown, hypnogram 800 includes a sleep-wake signal 801, a wake stage axis 810, a REM stage axis 820, a light sleep stage axis 830, and a deep sleep stage axis 840. The intersection between the sleep-wake signal 801 and one of the axes 810 to 840 indicates the sleep stage at any given time during a sleep session.

[0119] The sleep-wake signal 801 can be generated based on physiological data associated with the user (e.g., generated by one or more of the sensors 210 described herein). The sleep-wake signal can indicate one or more sleep states, including wakefulness, relaxed wakefulness, micro-arousal, REM stage, first non-REM stage, second non-REM stage, third non-REM stage, or any combination thereof. In some embodiments, one or more of the first non-REM stage, the second non-REM stage, and the third non-REM stage can be grouped together and classified as a light sleep stage or a deep sleep stage. For example, the light sleep stage may include the first non-REM stage, and the deep sleep stage may include the second non-REM stage and the third non-REM stage. Although the sleep graph 800 is Figure 8 800 as including a light sleep stage axis 830 and a deep sleep stage axis 840, but in some embodiments, the hypnogram 800 may include an axis for each of the first non-REM stage, the second non-REM stage, and the third non-REM stage. In other embodiments, the sleep-wake signal may also indicate a breathing signal, a breathing rate, an inspiratory amplitude, an expiratory amplitude, an inspiratory-expiratory ratio, a number of events per hour, an event pattern, or any combination thereof. Information describing the sleep-wake signal may be stored in the memory device 204.

[0120] The hypnogram 800 may be used to determine one or more sleep-related parameters, such as, for example, sleep onset latency (SOL), wake after sleep onset (WASO), sleep efficiency (SE), sleep segmentation index, sleep blocks, or any combination thereof.

[0121] Sleep onset latency (SOL) is defined as the time to enter sleep (t GTS ) and initial sleep time (t 睡眠). In other words, the sleep onset latency indicates the time it takes for the user to actually fall asleep after the initial attempt to fall asleep. In some embodiments, the sleep onset latency is defined as the sustained sleep onset latency (PSOL). The difference between the sustained sleep onset latency and the sleep onset latency is that the sustained sleep onset latency is defined as the duration between the time of entering sleep and the predetermined amount of sustained sleep. In some embodiments, the predetermined amount of sustained sleep may include, for example, at least 10 minutes of sleep in the second non-REM stage, the third non-REM stage and / or the REM stage with no more than 2 minutes of awakening, the first non-REM stage and / or the movement therebetween. In other words, the sustained sleep onset latency requires sustained sleep for up to, for example, 8 minutes in the second non-REM stage, the third non-REM stage and / or the REM stage. In other embodiments, the predetermined amount of sustained sleep may include at least 10 minutes of sleep in 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 embodiments, the predetermined amount of sustained sleep may not include any micro-awakening (e.g., a ten-second micro-awakening does not restart a 10-minute time period).

[0122] Awakes after sleep onset (WASO) is associated with the total duration of time the user is awake between the initial sleep time and the wake time. Thus, Awakes after sleep onset includes brief awakenings and micro-awakenings during a sleep session (e.g., Figure 7 In some embodiments, a wakefulness after sleep onset (WASO) is defined as a persistent wakefulness after sleep onset (PWASO) that includes only wakefulness with a total duration of 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.).

[0123] Sleep efficiency (SE) is determined 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 of the sleep session is 93.75%. Sleep efficiency indicates the sleep hygiene of the user. For example, if the user enters the bed before going to bed and spends time participating in other activities (e.g., watching TV), the sleep efficiency will be reduced (e.g., the user is punished). In some embodiments, the sleep efficiency (SE) can be calculated based on the total time in bed (TIB) and the total time the user attempts to sleep. In such embodiments, the total time the user attempts to sleep is defined as the duration between the time to go to sleep (GTS) and the time to get up described herein. For example, if the total sleep time is 8 hours (e.g., 11 pm to 7 am), the time to go to sleep is 10:45 pm, and the time to get up is 7:15 am, then in such embodiments, the sleep efficiency parameter is calculated to be about 94%.

[0124] The segment index is determined based at least in part on the number of awakenings during the sleep session. For example, if a user has two micro-awakenings (e.g., Figure 7 If the segment index is 2, the segment index can be expressed as 2. In some embodiments, the segment index is scaled between a predetermined range of integers (eg, between 0 and 10).

[0125] A sleep block is associated with a transition between any sleep stage (eg, first non-REM stage, second non-REM stage, third non-REM stage, and / or REM) and a wake stage. A sleep block may be calculated at a resolution of, for example, 30 seconds.

[0126] In some embodiments, the systems and methods described herein may include generating or analyzing a hypnogram including a sleep-wake signal to determine or identify a bed entry time (t 床 ), sleep time (t GTS )、initial sleep time (t 睡眠 ), one or more first micro-awakenings (e.g., MA1 and MA2), wake-up time (t 觉醒 ), getting up time (t 起身 ) or any combination thereof.

[0127] In other embodiments, one or more of the sensors 210 may be used to determine or identify a bed entry time (t 床 ), sleep time (t GTS )、initial sleep time (t 睡眠 ), one or more first micro-awakenings (e.g., MA1 and MA2), wake-up time (t 觉醒), getting up time (t 起身 ) or any combination thereof. For example, the bed entry time t may be determined based on data generated, for example, by the motion sensor 218, the microphone 220, the camera 232, or any combination thereof. 床 The time to go to sleep may be determined based on, for example, data from motion sensor 218 (e.g., data indicating that the user is not moving), data from camera 232 (e.g., data indicating that the user is not moving and / or the user has turned off the lights), data from microphone 220 (e.g., data indicating that the user has turned off the TV), data from user device 260 (e.g., data indicating that the user is no longer using user device 260), data from pressure sensor 212 and / or flow sensor 214 (e.g., data indicating that the user has turned on respiratory therapy device 110, data indicating that the user has put on user interface 120, etc.), or any combination thereof.

[0128] Although Figures 1 to 8 The discussion provides details about sleep scoring and respiratory therapy devices, but Figures 9 to 14 The discussion of provides additional details regarding determining a sleep score for a user based on one or more images of the user.

[0129] Fig. 9 is a perspective view of a user 902 capturing an image 908 of themselves according to some embodiments of the present invention. Fig. 9 As depicted, user 902 captures their own images via user device 904. User device 904 includes display device 906 and image capture device 910. Display device 906 can be of any suitable type. For example, display device 906 can be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, etc. In some embodiments, display device 906 is a touch screen and serves as both display device 906 and user input device. Image capture device 910 can be of any suitable type. For example, image capture device 910 can be a digital camera capable of capturing still images and / or video images. In addition, user device 904 can include more than one image capture device 910. For example, user device 904 can include a first image capture device 910 on the front side of user device 904 and one or more additional image capture devices 910 on the back side of user device 904.

[0130] Image 908 is used to determine a sleep score for user 902. The sleep score may be any suitable sleep-related score contemplated by the present invention as described herein or known in the art. When user 902 is using their respiratory therapy device, a sleep score may be calculated for user 902 based on data collected by their respiratory therapy device. However, when the user is not using their respiratory therapy device, there is no rich data set from which to calculate a sleep score for user 902. Instead of relying on data from the respiratory therapy device, or in combination with data from the respiratory therapy device, a sleep score may be calculated for user 902 based on image 908. For example, and with respect to Fig.11 and 12 Described in more detail, the features of user 902 (e.g., the face of user 902) can indicate how well rested user 902 is. Therefore, these features can be used to determine the sleep score of user 902.

[0131] In one embodiment, images 908 of user 902 are analyzed by a machine learning algorithm to determine a sleep score. The machine learning algorithm may be trained based on any suitable training set, and in some embodiments, the machine learning algorithm is continuously or periodically updated to include additional user-generated images. As an example, the training set may include images of the user and a sleep score associated with each of the images. The sleep score associated with the image may be generated based on external data, such as, for example, data generated by a respiratory therapy device. In some embodiments, the machine learning algorithm is specific to user 902 and is updated based on images captured by user 902. In one form, the machine learning algorithm may compare a user's current image with a past or baseline image of the user to determine the user's sleep score.

[0132] In some embodiments, the sleep score of user 902 is determined by comparing image 908 of user 902 to past or baseline images of user 902. For example, the system may use past images of user 902 (such as images captured by user 902 within a time period (e.g., the last week, two weeks, month, etc.) to form an average for the user. Image 908 may then be compared to the average to determine whether image 908 of user 902 indicates that the user's rest level is above or below the average for user 902. For example, if the user's rest level is above or below the average for user 902, the system may determine whether the user's rest level is above or below the average for user 902. Fig.11 and 12 As discussed in more detail, the system may determine average or baseline values ​​for different features of the face of user 902. For example, the system may determine an average or baseline value for the color of the eyes of user 902. The averages may be used to help determine a sleep score for user 902 and / or provide a quick metric to the user indicating whether user 902 appears to be better or worse rested than their average.

[0133] Although Fig. 9 The discussion of FIG. 10 provides background information regarding determining a sleep score for a user based on an image of the user, but the discussion of FIG. 10 provides additional details regarding capturing an image of a user to determine a sleep score for the user.

[0134] FIG. 10A to FIG. 10C A user 1004 is depicted capturing an image of themselves aligned with their face 1010 in accordance with some embodiments of the present invention. In some embodiments, an application executed on the user device 1002 is used to facilitate capturing an image of the user 1004. The application may be, for example, a dedicated sleep-related application (e.g., an application associated with a sleep, health, respiratory therapy device, etc.) or a general purpose application (e.g., a web browser) that works in conjunction with one or more backend systems.

[0135] In one embodiment, to help facilitate capturing images that may be used to determine a sleep score for user 1004 , user device 1002 may present a guide to user 1004 . FIG. 10A to FIG. 10C An example of such a guide is depicted in FIG. 10A to FIG. 10C As depicted, the guide helps the user 1004 align their face relative to the image capture device 1014. Such a guide can help the user 1004 position their face 1010 within the frame and ensure that the user 1004 is neither too far away from the image capture device 1014 nor too close to the image capture device.

[0136] exist Fig. 10A In the first step of the example tutorial depicted, the user 1004 is asked to center their face 1010 within the first marker 1006. Thus, the first marker 1006 may be any suitable size and / or shape. Fig. 10AIn the depicted example, the first marker 1006 is an oval. The user 1004 may be prompted to center their face 1010 within the first marker 1006 and position the user device 1002 so that their entire face is within the first marker 1006 and fills or approximately fills the first marker 1006. In one embodiment, the user device 1002 (or a back-end device, such as a control system) may pre-process (i.e., process) an image feed (or image) from the image capture device 1014. In such embodiments, the user device 1002 (or back-end system) pre-processes the image feed to determine whether the face 1010 of the user 1004 is within the first marker 1006. For example, the user device 1002 (or back-end system) may use image analysis to detect the face 1010 of the user 1004 and determine whether the face 1010 of the user 1004 is properly aligned with the first marker 1006. In such embodiments, the user device 1002 (or the backend system) may present an indicator to the user 1004 indicating whether the face 1010 of the user 1004 is correctly aligned with the first marker 1006. For example, the user device 1002 may present a dialog to the user 1004 indicating that the face 1010 of the user 1004 is correctly aligned with the first marker 1006, cause the first marker 1006 to change color when the face 1010 of the user 1004 is correctly aligned with the first marker 1006, and so on.

[0137] Then, if Fig. 10B As shown, the user 1004 is prompted to position the user device 1002 so that their eye 1012 is aligned with the second marker 1008. Fig. 10BIn the depicted example, the second mark 1008 includes two circles. The user 1004 may be prompted to center their eyes 1012 within the second mark 1008 and position the user device 1002 so that their eyes 1012 are within the second mark 1008 and fill or approximately fill the second mark 1008. In one embodiment, the user device 1002 (or a back-end device, such as a control system) may pre-process (i.e., process) an image feed (or image) from the image capture device 1014. In such embodiments, the user device 1002 (or back-end system) pre-processes the image feed to determine whether the eyes 1012 of the user 1004 are within the second mark 1008. For example, the user device 1002 (or back-end system) may use image analysis to detect the eyes 1012 of the user 1004 and determine whether the eyes 1012 of the user 1004 are properly aligned with the second mark 1008. In such embodiments, the user device 1002 (or the backend system) may present an indicator to the user 1004 indicating whether the eye 1012 of the user 1004 is properly aligned with the second mark 1008. For example, the user device 1002 may present a dialog to the user 1004 indicating that the eye 1012 of the user 1004 is properly aligned with the second mark 1008, cause the second mark 1008 to change color when the eye 1012 of the user 1004 is properly aligned with the first mark 1006, and so on.

[0138] When the user 1004 has properly aligned their face 1010 and / or eyes 1012 relative to the first marker 1006 and / or the second marker 1008, the user 1004 can capture an image of themselves. Fig. 10C As depicted, once the user 1004 has correctly positioned the user device 1002 relative to themselves, the user device 1002 presents the user 1004 with a “capture image” button 1016. The user 1004 may select the “capture image” button 1016 to capture an image of themselves. In some embodiments, the “capture image” button 1016 may only appear or be selectable when the user 1004 has correctly positioned the user device 1002.

[0139] Although FIG. 10A to FIG. 10C The depicted example shows the first mark 1006 and the second mark 1008 as ovals / circles, but this is not required. That is, the first mark 1006 and the second mark 1008 can be in any suitable form. For example, the first mark 1006 and / or the second mark 1008 can include crosshairs, polygons, lines, images, etc. Additionally, although FIG. 10A to FIG. 10CThe example guide depicted depicts the user 1004 aligning both their face 1010 and eyes 1012, but this is not required. The user 1004 may be prompted to align fewer than two features or more features with the marker. For example, the user 1004 may be prompted to align only their face 1010 or their eyes 1012, or any other suitable feature (e.g., their nose, chin, ears, mouth, neck, etc.).

[0140] In addition to pre-processing (i.e., processing) the image feed (or images) to ensure that the user device 1002 is properly aligned with the user 1004, in some embodiments, the user device 1002 (or the backend system) may pre-process (i.e., process) the image feed (or images) to determine whether the resulting image is suitable for sleep score determination. For example, the user device 1002 (or the backend system) may analyze lighting, blurriness, size, resolution, content (e.g., whether the eyes 1012 of the user 1004 are open), etc. to determine whether the image (or the image generated by the image feed) is suitable for determining the sleep score of the user 1004. If the image (or the image generated by the image feed) is not suitable for determining the sleep score of the user 1004, the user device 1002 may prompt the user to realign the user device 1002 and / or capture another image.

[0141] Although the discussion of FIG. 10 provides additional details regarding capturing an image of a user to determine a sleep score for the user, Fig.11 and Fig.12 The discussion of provides additional details regarding analyzing a user's images to determine the user's sleep score.

[0142] Fig.11 A user 1102 is depicted, including several exploded views, according to some embodiments of the present invention. As previously discussed, features of the user 1102 (e.g., the face of the user 1102) may indicate how well rested the user 1102 is. Thus, these features may be used to calculate a sleep score for the user 1102. The features of the user 1102 may include, for example, the color of the eyes 1104 of the user 1102, the sclera of the eyes 1104 of the user 1102, the degree to which the eyes 1104 of the user 1102 are open, blood oxygen, pupil size, breathing rate, pulse rate, muscle tone of the face of the user 1102, markings on the face of the user 1102, alertness of the user 1102, stress cues in the face of the user 1102, anxiety cues in the face of the user 1102, and the like. Thus, analysis of the face of the user 1102 may be used to determine a sleep score for the user 1102.

[0143] exist Fig.11 In the depicted image, user 1102 is well rested (with Fig.12 compared to the image depicted). Fig.11 11. Three example features are depicted in the exploded views of FIG. A first exploded view 1110 depicts one of the eyes 1104 of the user 1102, a second exploded view 1112 depicts an area of ​​the user's 1102 face below the user's eye 1104, and a third exploded view 1114 depicts a portion of the user's 1102 mouth 1108.

[0144] In the first exploded view 1110, the eyes 1104 of the user 1102 do not have bloodshot or other discoloration, indicating that the user 1102 is well rested. In addition, the eyes 1004 of the user 1002 appear to be fully open and alert, indicating that the user 1102 is well rested. Additionally, if Fig.11 If the depicted image includes a video and / or multiple frames, features such as breathing rate, pulse rate, etc. can be determined from the image. In the second exploded view 1112, the user 1102 does not have dark circles or "eye bags" under their eyes 1104, indicating that the user is well rested. Discoloration and / or swelling under the eyes 1104 of the user 1102 may indicate that the user 1102 is not well rested. In the third exploded view 1114, the mouth 1108 of the user 1102 is slightly smiling 1116, indicating that the user 1102 is well rested.

[0145] Although Fig.11 The discussion describes the characteristics of users when they are well rested, but Fig.12 The discussion describes the characteristics of users when they are not well rested.

[0146] Fig.12 Depicts the face of a user according to some embodiments of the present invention, including several exploded views. Fig.11 Same, Fig.12 Three exploded views are included. A first exploded view 1210 depicts one of the eyes 1204 of the user 1202, a second exploded view 1212 depicts an area of ​​the user's 1202 face below the user's eye 1204, and a third exploded view 1214 depicts a portion of the user's 1202 mouth 1206. Fig.11 When compared to the depicted image, the user's 1202 eyes 1204 appear bloodshot, the user 1202 appears to have discoloration 1218 below their eyes 1204, and the user's mouth 1208 is slightly turned down 1216. Each of these factors indicates that the user 1202 is Fig.11 The user in the depicted image is more rested. Fig.12 The image in the image is determined by the user 1202 Fig.111202. In some embodiments, the system can recommend actions to the user based on the sleep score. For example, if the user's sleep score is low and the user is busy in the afternoon (e.g., based on accessing the user's calendar), the system can suggest that the user take a nap, go to bed earlier at night, etc.

[0147] Although Fig.11 and Fig.12 The discussion of provides additional details about analyzing a user's images to determine the user's sleep score, but Fig.13 The discussion of provides additional details regarding a system for determining a user's sleep score.

[0148] Fig.13 1 is a block diagram of a system 1300 for determining a sleep score for a user according to some embodiments of the present invention. System 1300 includes a control system 1302, a network 1308, and a user device 1310. In one embodiment, user device 1310 is communicatively coupled to control system 1302 via network 1308. Network 1308 can be of any suitable type (e.g., a local area network and / or a wide area network, such as the Internet). Thus, network 1308 can include wired links and / or wireless links. Although control system 1302 is depicted as a separate device, in some embodiments, the control system can reside on user device 1310. In such embodiments, user device 1310 may not need to connect to network 1308 or send data via the network.

[0149] The control system 1302 may include a fixed-purpose hardwired hardware platform (including, but not limited to, an application-specific integrated circuit (ASIC) (which is a custom integrated circuit designed for a specific purpose rather than intended for general-purpose use), a field programmable gate array (FPGA), etc.), or may include a partially or fully programmable hardware platform (including, but not limited to, a microcontroller, a microprocessor, etc.). These architectural choices for such structures are well known and understood in the art and do not require further description here. The control system 1302 is configured to perform one or more of the steps, actions, and / or functions described herein (e.g., by using corresponding programming well known to those skilled in the art).

[0150] By one optional approach, the control system 1302 is operably coupled to a memory. The memory may be integrated into the control system 1302, or may be physically separate (in whole or in part) from the control system 1302 as desired. The memory may also be local to the control system 1302 (where, for example, the two share a common circuit board, chassis, power supply, and / or housing), or may be partially or fully remote to the control system 1302 (where, for example, the memory is physically located in another facility, metropolitan area, or even country compared to the control system 1302).

[0151] The memory may be used, for example, to non-transitory store computer instructions that, when executed by the control system 1302, cause the control system 1302 to operate as described herein. As used herein, such references to "non-transitory" will be understood to refer to the non-transitory state of the stored contents (and thus excluding the case where the stored contents merely constitute a signal or wave), rather than the volatility of the storage medium itself, and thus include non-volatile memory (such as read-only memory (ROM)) as well as volatile memory (such as erasable programmable read-only memory (EPROM)).

[0152] The control system 1302 typically analyzes the image and determines a sleep score based on the image. For example, the control system 1302 may receive an image of a user and analyze the image. Fig.11 and Fig.12 As discussed, multiple features can be analyzed with respect to an image. For example, the control system 1302 can use image processing to detect one or more features associated with the image. The control system 1302 determines a sleep score for the user based on these features. In some embodiments, the control system 1302 determines the sleep score for the user based on a machine learning algorithm. In such embodiments, the machine learning algorithm can be pre-trained by the control system 1302 or another device. Additionally, or alternatively, the control system 1302 or another device can continuously train and / or update the machine learning algorithm based on images received from the user device 1310 as well as other user devices.

[0153] The user device 1310 typically captures an image of the user and sends the image to the control system 1302 for analysis. Therefore, the user device 1302 can be of any suitable type. For example, the user device can be a smart phone, a smart watch, a laptop or desktop computer, a personal digital assistant (PDA), a tablet computer, a car infotainment system, a smart mirror, a television, etc. In some embodiments, the user device 1310 includes an image capture device 1312, a display device 1314, a user input device 1316, and a communication radio device 1318. The image capture device 1312 can be of any suitable type (e.g., a digital camera) and is configured to capture still images and / or video images. The display device 1314 can be of any suitable type (e.g., an LED display, an LCD, etc.) and is configured to present information (e.g., instructions, a graphical user interface (GUI), images, etc.) to the user. The user input device 1316 can be of any suitable type (e.g., a keyboard, a mouse, a touch screen, a joystick, a touch pad, a microphone, etc.) and is configured to receive user input from the user. It should be noted that in some embodiments, the display device 1314 and the user input device 1316 can be combined into a single device, such as a touch screen. The communication radio device 1318 can be of any suitable type (e.g., a near field communication (NFC) radio device, a wireless wide area network (WWAN) radio device, a Wi-Fi radio device, etc.) and is configured to send data from the user device 1310 and receive data for the user device.

[0154] Although Fig.13 The discussion of provides additional details about the system for determining a user's sleep score, but Fig.14 The discussion of describes example operations of such a system.

[0155] Fig.14 is a flow chart depicting example operations for determining a sleep score for a user according to some implementations. The flow begins at block 1402 .

[0156] In box 1402, a user device is caused to capture an image of a user. For example, an application executed on a user device may cause the user device to capture an image of a user. The application may be a general-purpose application (e.g., a web browser) and / or a dedicated application (e.g., an application dedicated to determining a sleep score, associated with a respiratory therapy device, associated with the user's health, etc.). In some embodiments, the user device prompts the user to capture an image. For example, the user device may present a GUI comprising one or more buttons. The user may select one or more of the buttons to cause the user device to capture an image. The user device may capture an image via an image capture device. The image may be a single image, a series of images (frames), and / or a video. The process continues at box 1404.

[0157] At block 1404, an image of the user is received. For example, the image of the user may be received by the control system. The control system may be separate from or integrated with the user device. In embodiments where the control system is separate from the user device, the user device may send the image of the user to the control system via a network. In embodiments where the control system is integrated with the user device, the control system may receive the image of the user by accessing a memory location on the user device (or remote from the user device) where the image of the user is stored. The process continues at block 1406.

[0158] At block 1406, the image of the user is analyzed. For example, the control system may analyze the image of the user. The control system analyzes the image of the user based on any suitable technology, such as image recognition, color analysis, image comparison, etc. In some embodiments, the control system analyzes the image based on a machine learning algorithm. The control system analyzes the image of the user to determine features associated with the image. The features indicate how well the user is rested. The control system may analyze the image based on any suitable features, such as the color of the user's eyes, the degree to which the user's eyes are open, blood oxygen, pupil size, breathing rate, pulse rate, muscle tension of the user's face, marks on the user's face, alertness of the user, etc. As previously discussed, in some embodiments, the control system is separate (i.e., remote) from the user device. In such embodiments, the control system may operate in the "cloud". In other embodiments, the control system may be integrated with the user device. In such embodiments, the user device may store the machine learning algorithm locally in a memory. In such embodiments, the image of the user does not need to leave the user device. In order to minimize the storage requirements of the user device, in embodiments where the machine learning algorithm is stored locally on a memory device, a "light" or less complex version of the machine learning algorithm may be stored locally on the user device. The process continues at block 1408.

[0159] At block 1408, a sleep score for the user is determined. For example, the control system can determine a sleep score for the user. The control system determines the sleep score for the user based on an analysis of the image of the user.

[0160] One or more elements or aspects or steps or any parts thereof from one or more claims of any one of the following claims 1 to 28 may be combined with one or more elements or aspects or steps or any parts thereof from one or more other claims 1 to 28, or a combination thereof, to form one or more additional embodiments and / or claims of the present invention.

[0161] Although the present invention has been described with reference to one or more specific embodiments or implementations, it will be appreciated by those skilled in the art that many changes may be made thereto without departing from the spirit and scope of the present invention. Each of the embodiments and their obvious variations are contemplated as falling within the spirit and scope of the present invention. It is also contemplated that additional embodiments according to various aspects of the present invention may combine any number of features from any of the embodiments described herein.

Claims

1. A method for determining a sleep score of a user, the method comprising: causing the user device to capture an image of a user via an application executed on the user device; receiving, by a control system, the image of the user; analyzing, by the control system, the image of the user based on a machine learning algorithm; as well as The sleep score of the user is determined, by the control system, based on the analysis of the images of the user.

2. The method of claim 1, wherein the machine learning algorithm is trained based on images of a plurality of users.

3. A method according to claim 1 or claim 2, wherein the sleep score of the user is based on one or more of the color of the user's eyes, the degree of openness of the user's eyes, blood oxygen, pupil size, breathing rate, pulse rate, muscle tension in the user's face, markings on the user's face, alertness of the user, stress cues in the user's face, and anxiety cues in the user's face.

4. The method of any one of claims 1 to 3, wherein the sleep score of the user is based on the sclera of the user. 5 . The method according to claim 1 , wherein the image of the user comprises one or both of a plurality of images of the user and a video of the user.

6. The method according to any one of claims 1 to 5, further comprising: processing, by the application, the image of the user before sending the image of the user to the control system; as well as In response to determining that the image of the user is acceptable, the image of the user is sent to the control system.

7. The method according to any one of claims 1 to 5, further comprising: processing, by the application, the image of the user before sending the image of the user to the control system; as well as In response to determining that the image of the user is unacceptable, causing the user device to capture a second image of the user.

8. A method according to claim 5 or claim 7, wherein the application processes the image of the user based on one or more of the resolution of the image of the user, the clarity of the image of the user, the presence of a portion of the user in the image of the user, the openness of the user's eyes in the image of the user, and the lighting of the image of the user.

9. The method according to any one of claims 1 to 8, wherein the control system is remote from the user equipment.

10. The method according to any one of claims 1 to 9, further comprising: The application is caused to present the sleep score of the user on a display device of the user device.

11. The method according to claim 10, further comprising: determining, by the application, an average sleep score of the user; as well as The application is caused to present, on the display device of the user device, a comparison of the average sleep score of the user and the sleep score of the user.

12. The method according to any one of claims 1 to 11, further comprising: determining that the user was not using respiratory therapy prior to capturing the image of the user; determining a deviation between the sleep score of the user and a sleep score of the user when the user uses respiratory therapy; as well as The application is caused to present the sleep score and the indication of the deviation on a display device of the user device.

13. The method of any one of claims 1 to 12, wherein the user device is one or more of a smart phone, a smart watch, a laptop computer, a desktop computer, a personal digital assistant (PDA), a tablet computer, a car infotainment system, a smart mirror, and a television.

14. The method according to any one of claims 1 to 13, further comprising: determining, by the control circuit, an action of the user based on the sleep score of the user; as well as The control circuit is caused to send the action of the user to the user device.

15. A system, comprising: a control system comprising one or more processors; as well as a memory having machine-readable instructions stored thereon; Wherein the control system is coupled to the memory, and when the machine executable instructions in the memory are executed by at least one of the one or more processors of the control system, the method according to any one of claims 1 to 14 is implemented.

16. A system for determining a sleep score, the system comprising: an application executable on a user device, the application configured to cause the user device to capture an image of a user; a control system communicatively coupled to the user device, wherein the control system is configured to: receiving the image of the user from the user device; analyzing the image of the user using a machine learning algorithm; and The sleep score of the user is determined based on the analysis of the images of the user.

17. The system of claim 16, wherein the machine learning algorithm is trained based on images of a plurality of users.

18. A system according to claim 16 or claim 17, wherein the sleep score of the user is based on one or more of the color of the user's eyes, the degree of openness of the user's eyes, blood oxygen, pupil size, breathing rate, pulse rate, muscle tone of the user's face, markings on the user's face, alertness of the user, stress cues in the user's face, and anxiety cues in the user's face.

19. The system of any one of claims 16 to 18, wherein the image of the user comprises one or both of a plurality of images of the user and a video of the user.

20. The system according to any one of claims 16 to 19, wherein the application is further configured to: processing the image of the user before sending the image of the user to the control system; and In response to determining that the image of the user is acceptable, the image of the user is sent to the control system.

21. The system according to any one of claims 16 to 20, wherein the application is further configured to: processing the image of the user before sending the image of the user to the control system; and In response to determining that the image of the user is unacceptable, causing the user device to capture a second image of the user.

22. A system according to claim 20 or 21, wherein the application processes the image of the user based on one or more of the resolution of the image of the user, the clarity of the image of the user, the presence of a portion of the user in the image of the user, the openness of the user's eyes in the image of the user, and the lighting of the image of the user.

23. A system according to any one of claims 16 to 22, wherein the control system is remote from the user device.

24. The system according to any one of claims 16 to 23, wherein the application is further configured to: The sleep score of the user is caused to be presented on a display device of the user device.

25. The system of claim 24, wherein the application is further configured to: determining an average sleep score for the user; and A comparison of the average sleep score of the user and the sleep score of the user is caused to be presented on the display device of the user device.

26. The system of any one of claims 16 to 25, wherein the application is further configured to: determining that the user was not using respiratory therapy prior to capturing the image of the user; determining a deviation between the sleep score for the user and a sleep score for the user when the user uses respiratory therapy; and The sleep score and the indication of the deviation are caused to be presented on a display device of the user device.

27. The system of any one of claims 16 to 26, wherein the user device is one or more of a smart phone, a smart watch, a laptop computer, a desktop computer, a personal digital assistant (PDA), a tablet computer, a car infotainment system, a smart mirror, and a television.

28. The system of any one of claims 16 to 27, wherein the control system is further configured to: determining a motion of the user based on the sleep score of the user; and The action of the user is sent to the user device.

Images