Systems and methods for assisting users of respiratory therapy systems

Abstract

A method includes receiving first physiological data associated with a user. The method also includes determining a first emotional score associated with the user, at least in part, based on the first physiological data. The method further includes modifying one or more settings of a respiratory therapy system in response to determining that the first emotional score meets predetermined conditions.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 080,401, filed on September 18, 2020, which is incorporated herein by reference in its entirety. Technical Field

[0003] This disclosure generally relates to systems and methods for assisting users in using respiratory therapy systems, and more specifically to systems and methods for determining a mood score associated with a user and for communicating one or more prompts to the user to help modify the mood score. Background Technology

[0004] Many individuals suffer from sleep-related and / or breathing disorders, such as periodic limb movement disorder (PLMD), restless legs syndrome (RLS), and sleep-disordered breathing (SDB) such as obstructive sleep apnea (OSA), Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity-related hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disease (NMD), chest wall disorders, and insomnia. Many of these disorders can be treated with respiratory therapy systems, while others can be treated with different techniques. However, users may experience anxiety or stress when using respiratory therapy systems, for example, due to unfamiliarity (e.g., first-time use) or discomfort. This anxiety or stress can prevent users from falling asleep or cause them to abandon the use of the respiratory therapy system. The purpose of this disclosure is to address these and other issues. Summary of the Invention

[0005] According to some implementations of this disclosure, the method includes receiving first physiological data associated with a user. The method also includes determining a first emotion score associated with the user based at least in part on the first physiological data. The method further includes modifying one or more settings of the respiratory therapy system in response to determining that the first emotion score meets predetermined conditions.

[0006] According to some implementations of this disclosure, the system includes an electronic interface, a memory, and a control system. The electronic interface is configured to receive physiological data associated with a user. The memory stores machine-readable instructions. The control system includes one or more processors configured to execute the machine-readable instructions to determine an emotion score associated with the user, at least in part, based on the physiological data. The control system is also configured to modify one or more settings of the respiratory therapy system in response to determining that the emotion score meets predetermined conditions.

[0007] The above overview is not intended to represent every implementation or aspect of this disclosure. Additional features and benefits of this disclosure will become apparent from the detailed description and accompanying drawings listed below. Attached Figure Description

[0008] Figure 1 This is a functional block diagram of a system based on some implementation methods of this disclosure;

[0009] Figure 2 This is based on some implementation methods of this disclosure. Figure 1 A perspective view of at least a part of the system, the user, and the bed partner;

[0010] Figure 3A This is based on some implementation methods of this disclosure. Figure 1 A perspective view of the user interface of a respiratory therapy system;

[0011] Figure 3B This is based on some implementation methods of this disclosure. Figure 3A A perspective breakdown of the user interface;

[0012] Figure 4 The illustration shows an exemplary timeline of sleep periods according to some implementations of this disclosure;

[0013] Figure 5 The diagram illustrates some implementations of this disclosure. Figure 4 An exemplary sleep graph associated with sleep periods; and

[0014] Figure 6 This is a flowchart illustrating the process of methods used to assist users based on some implementations of this disclosure.

[0015] While this disclosure allows for various modifications and alternatives, specific implementations and embodiments have been shown by way of example in the accompanying drawings and will be described in detail herein. However, it should be understood that this disclosure is not intended to be limited to the specific forms disclosed. Rather, this disclosure will cover all modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure as defined by the appended claims. Detailed Implementation

[0016] Many individuals suffer from sleep-related and / or breathing disorders. Examples of sleep-related and / or breathing disorders include periodic limb movement disorder (PLMD), restless legs syndrome (RLS), sleep-disordered breathing (SDB) such as obstructive sleep apnea (OSA), central sleep apnea (CSA), other types of apnea such as mixed apnea and hypopnea, respiratory effort-related arousal (RERA), Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity-related hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disease (NMD), rapid eye movement (REM) behavior disorder (also known as RBD), dream-disordered behavior (DEB), hypertension, diabetes, stroke, insomnia, and chest wall disorders.

[0017] Obstructive sleep apnea (OSA) is a form of sleep-disordered breathing (SDB) characterized by events during sleep involving obstruction or blockage of the upper airway due to a combination of an abnormally small upper airway and loss of normal muscle tone in the areas of the tongue, soft palate, and posterior oropharyngeal walls. More generally, apnea refers to the cessation of breathing caused by air obstruction (obstructive sleep apnea) or cessation of respiratory function (often called central sleep apnea). Typically, during an obstructive sleep apnea event, an individual will stop breathing for approximately 15 to 30 seconds.

[0018] Other types of sleep apnea include hypoventilation, hyperventilation, and hypercapnia. Hypopnea is typically characterized by slow or shallow breathing caused by airway narrowing, rather than airway obstruction. Hyperventilation is typically characterized by increased depth and / or rate of breathing. Hypercapnia is typically characterized by elevated or excessive levels of carbon dioxide in the blood, usually caused by insufficient breathing.

[0019] Cheyne-Stokes respiration (CSR) is another form of sleep-disordered breathing. CSR is a disorder of the patient's respiratory controller, characterized by rhythmic alternations of waxing and waning ventilation known as the CSR cycle. CSR is characterized by repetitive hypoxia and reoxygenation of arterial blood.

[0020] Obesity hyperventilation syndrome (OHS) is defined as a combination of severe obesity and chronic hypercapnia at wakefulness, without other known causes of hypoventilation. Symptoms include dyspnea, morning headache, and excessive daytime sleepiness.

[0021] Chronic obstructive pulmonary disease (COPD) includes any of a group of lower airway diseases with certain common characteristics, such as increased resistance to air movement, prolonged expiratory phase of breathing, and loss of normal lung elasticity.

[0022] Neuromuscular diseases (NMDs) encompass a wide range of conditions and ailments that impair muscle function directly through intrinsic muscle pathology or indirectly through neuropathology. Chest wall disorders are a group of chest wall deformities that result in inefficient connection between the respiratory muscles and the thorax.

[0023] A respiratory effort-related awakening (RERA) event is typically characterized by an increased respiratory effort lasting ten seconds or longer, resulting in an awakening from sleep, and does not meet the criteria for an apnea or hypopnea event. RERA is defined as a respiratory sequence characterized by increased respiratory effort leading to a sleep awakening, but not meeting the criteria for apnea or hypopnea. These events must meet two criteria: (1) a pattern of progressively more negative esophageal pressure terminating with a sudden change in pressure to a lower negative level and the awakening, and (2) the event lasting ten seconds or longer. In some implementations, a nasal cannula / pressure transducer system is sufficient and reliable for detecting RERA. The RERA detector can be based on an actual flow signal derived from a respiratory therapy device. For example, a flow limitation measurement can be determined based on the flow signal. The awakening measurement can then be derived from the flow limitation measurement and the measurement of the sudden increase in ventilation. One such method is described in WO 2008 / 138040, assigned to ResMed Ltd., and U.S. Patent No. 9,358,353, the disclosure of each of which is incorporated herein by reference in its entirety.

[0024] These and other disorders are characterized by specific events that occur when an individual is sleeping (such as snoring, sleep apnea, hypopnea, restless legs, sleep disturbances, apnea, increased heart rate, difficulty breathing, asthma attacks, seizures, sudden attacks, or any combination thereof).

[0025] The Apnea-Hypopnea Index (AHI) is an index used to indicate the severity of sleep apnea during a sleep period. The AHI is calculated by dividing the number of apnea and / or hypopnea events experienced by the user during the sleep period by the total number of hours of sleep in that period. An event can be, for example, an apnea lasting at least 10 seconds. An AHI less than 5 is considered normal. An AHI greater than or equal to 5 but less than 15 is considered an indicator of light sleep apnea. An AHI greater than or equal to 15 but less than 30 is considered an indicator of moderate sleep apnea. An AHI greater than or equal to 30 is considered an indicator of severe sleep apnea. In children, an AHI greater than 1 is considered abnormal. When the AHI is normal, or when the AHI is normal or mild, sleep apnea can be considered “controlled.” The AHI can also be used in conjunction with oxygen desaturation levels to indicate the severity of obstructive sleep apnea.

[0026] Additionally, many individuals suffer from insomnia, which is typically characterized by dissatisfaction with the quality or duration of sleep (e.g., difficulty falling asleep, frequent or prolonged awakenings after initial sleep onset, and inability to fall back asleep after initial awakening). It is estimated that over 2.6 billion people worldwide experience some form of insomnia, and over 750 million have been diagnosed with insomnia disorder. In the United States, insomnia causes approximately $107.5 billion in total economic burden annually, accounting for 13.6% of all days of absence and 4.6% of injuries requiring medical care. Recent research also indicates that insomnia is the second most common mental disorder and a major risk factor for depression.

[0027] Nighttime insomnia symptoms typically include, for example, decreased sleep quality, shortened sleep duration, sleep-onset insomnia, sleep maintenance insomnia, late-night insomnia, mixed insomnia, and / or paradoxical insomnia. Sleep-onset insomnia is characterized by difficulty initiating sleep at bedtime. Sleep maintenance insomnia is characterized by frequent or prolonged awakenings during the night after the initial fall asleep. Late-night insomnia is characterized by early morning awakenings (e.g., before a target or desired wake-up time) and inability to fall back asleep. Comorbid insomnia refers to a type of insomnia where insomnia symptoms are at least partially caused by symptoms or comorbidities of another physical or mental condition (e.g., anxiety, depression, medical condition, and / or medication use). Mixed insomnia refers to a combination of attributes of other types of insomnia (e.g., a combination of symptoms of sleep-onset insomnia, sleep maintenance insomnia, and late-night insomnia). Paradoxical insomnia refers to a discontinuity or inconsistency between the user's perceived sleep quality and the user's actual sleep quality.

[0028] Daytime (e.g., during the day) insomnia symptoms include, for example, fatigue, decreased energy, impaired cognition (e.g., attention, concentration, and / or memory), difficulty functioning in academic or professional settings, and / or mood disturbances. These symptoms can lead to psychological complications such as reduced intellectual (and / or physical) performance, decreased reaction time, increased risk of depression, and / or increased risk of anxiety disorders. Insomnia symptoms can also lead to physical complications such as poor immune system function, high blood pressure, increased risk of heart disease, increased risk of diabetes, weight gain, and / or obesity.

[0029] Comorbid Insomnia and Sleep Apnea (COMISA) refers to a subject experiencing both insomnia and obstructive sleep apnea (OSA). OSA can be measured based on the apnea-hypopnea index (AHI) and / or oxygen desaturation level. AHI is calculated by dividing the number of apnea and / or hypopnea events experienced by the user during a sleep period by the total number of hours of sleep in that period. An event can be, for example, an apnea lasting at least 10 seconds. An AHI less than 5 is considered normal. An AHI greater than or equal to 5 but less than 15 is considered an indicator of mild OSA. An AHI greater than or equal to 15 but less than 30 is considered an indicator of moderate OSA. An AHI greater than or equal to 30 is considered an indicator of severe OSA. In children, an AHI greater than 1 is considered abnormal.

[0030] Insomnia can also be classified based on its duration. For example, if insomnia symptoms have lasted for less than 3 months, it is considered acute or transient. Conversely, if insomnia symptoms have lasted for 3 months or longer, it is considered chronic or persistent. Persistent / chronic insomnia symptoms usually require a different treatment pathway than acute / transient insomnia symptoms.

[0031] Known risk factors for insomnia include sex (e.g., insomnia is more common in women than in men), family history, and stress exposure (e.g., severe and chronic life events). Age is a potential risk factor for insomnia. For example, sleep-onset insomnia is more common in younger people, while sleep maintenance insomnia is more common in middle-aged and older adults. Other potential risk factors for insomnia include race, geography (e.g., living in a geographic area with long winters), altitude, and / or other sociodemographic factors (e.g., socioeconomic status, employment, education level, self-reported health, etc.).

[0032] The mechanisms of insomnia include precipitating factors, triggering factors, and persistent factors. Precipitating factors include hyperarousal, characterized by increased physiological arousal during both sleep and insomnia. Measures of hyperarousal include, for example, increased cortisol levels, increased activity of the autonomic nervous system (e.g., as indicated by increased resting heart rate and / or changes in heart rate), increased brain activity (e.g., increased EEG frequency during sleep and / or increased number of awakenings during REM sleep), increased metabolic rate, increased body temperature, and / or increased activity of the pituitary-adrenal axis. Triggering factors include stressful life events (e.g., those related to employment or education, interpersonal relationships, etc.). Persistent factors include excessive worry about sleep deprivation and its consequences; insomnia symptoms may persist even after the precipitating factors are eliminated.

[0033] Diagnosing or screening for insomnia typically involves a series of steps, including identifying the type of insomnia and / or specific symptoms. The screening process usually begins with the patient's subjective complaint (e.g., their inability to fall asleep or maintain sleep).

[0034] Next, clinicians use a checklist that includes insomnia symptoms, factors influencing those symptoms, health factors, and social factors to assess subjective complaints. Insomnia symptoms may include, for example, age of onset, sudden event, time of onset, current symptoms (e.g., sleep-onset insomnia, sleep-maintenance insomnia, and late-onset insomnia), symptom frequency (e.g., every night, occasional, specific night, specific situation, or seasonal variation), duration of illness since symptom onset (e.g., changes in severity and / or relative occurrence of symptoms), and / or perceived consequences during the day. Factors influencing insomnia symptoms include, for example, past and current treatments (including their effectiveness), factors that improve or enhance symptoms, factors that worsen insomnia (e.g., stress or changes in schedule), and factors that maintain insomnia, including behavioral factors (e.g., going to bed too early, sleeping more on weekends, alcohol consumption, etc.) and cognitive factors (e.g., unhelpful beliefs about sleep, worries about the consequences of insomnia, worries about poor sleep quality, etc.). Health factors include medical barriers and symptoms, sleep-interfering conditions (e.g., pain, discomfort, treatment), and pharmacological considerations (e.g., warnings and sedative effects of medications). Social factors include work schedules that are incompatible with sleep, arriving home late and having no time to relax, nighttime family and social responsibilities (e.g., caring for children or the elderly), stressful life events (e.g., past stressful events may be triggering factors, while current stressful events may be perpetuating factors), and / or sleeping with pets.

[0035] After clinicians complete checklists and assess insomnia symptoms, influencing factors, health factors, and / or social factors, patients are typically instructed to create a daily sleep diary and / or complete questionnaires (e.g., the Insomnia Severity Index or the Pittsburgh Sleep Quality Index). Therefore, this routine approach to insomnia screening and diagnosis is susceptible to error because it relies on subjective complaints rather than objective sleep assessments. Due to misunderstandings of sleep status (ambivalent insomnia), there may be a disconnect between the patient's subjective complaints and actual sleep patterns.

[0036] Furthermore, standard methods used for diagnosing insomnia do not exclude other sleep-related disorders, such as periodic limb movement disorder (PLMD), restless legs syndrome (RLS), sleep-disordered breathing (SDB), obstructive sleep apnea (OSA), Cheyne-Stokes respiration (CSR), respiratory insufficiency, obesity-related hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disease (NMD), and chest wall disorders. These other disorders are characterized by specific events that occur during an individual's sleep (e.g., snoring, apnea, hypopnea, restless legs, sleep disturbances, apnea, increased heart rate, dyspnea, asthma attacks, seizures, sudden onset, or any combination thereof). While these other sleep-related disorders may present with symptoms similar to insomnia, differentiating them from insomnia helps in tailoring an effective treatment plan, distinguishing features that may require different treatments. For example, fatigue is often characteristic of insomnia, while excessive daytime sleepiness is a characteristic feature of other disorders (e.g., PLMD) and reflects a physiological tendency to fall asleep unconsciously. Insomnia can also be related to mood (e.g., anxiety-induced insomnia), so tracking a patient's mood (or anxiety) can provide insights into managing or treating insomnia.

[0037] Once diagnosed, insomnia can be managed or treated using a variety of techniques or by providing advice to the patient. Generally, patients can be encouraged or advised to develop healthy sleep habits (e.g., plenty of exercise and daytime activity, regular sleep schedules, avoiding daytime naps, eating dinner early, relaxing before bed, avoiding caffeine in the afternoon, avoiding alcohol, making the bedroom comfortable, eliminating bedroom distractions, getting out of bed when not sleepy, and waking up at the same time every day regardless of bedtime) or discouraged from developing certain habits (e.g., not working in bed, not going to bed early, not going to bed unless tired). Patients can use sleep medications and medical therapies, such as prescription sleep aids, over-the-counter sleep aids, and / or home remedies, as supplementary or alternative treatments.

[0038] Patients may also be treated with cognitive behavioral therapy (CBT) or cognitive behavioral therapy for insomnia (CBT-I), which typically includes sleep hygiene education, relaxation therapy, stimulus control, sleep restriction, and sleep management tools and devices. Sleep restriction is a method designed to limit time spent in bed (the sleep window or duration) to actual sleep, thereby enhancing homeostatic sleep drive. The sleep window can be gradually increased over a period of days or weeks until the patient reaches their optimal sleep duration. Stimulus control involves providing the patient with a set of instructions designed to strengthen the association between the bed and bedroom and sleep, and to re-establish a consistent sleep-wake schedule (e.g., going to bed only when sleepy, getting out of bed when unable to sleep, using the bed only for sleeping (e.g., not reading or watching TV), waking up at the same time every morning, not napping, etc.). Relaxation training includes clinical procedures designed to reduce autonomic arousal, muscle tension, and intrusive thoughts that interfere with sleep (e.g., using progressive muscle relaxation). Cognitive therapy is a psychological approach designed to reduce excessive worry about sleep and to reconstruct unhelpful beliefs about insomnia and its daytime consequences (e.g., using Socratic questions, behavioral experiences, and paradoxical intentions techniques). Sleep hygiene generally refers to an individual's practices (e.g., death, exercise, substance use, bedtime, pre-sleep activities, bedtime activities, etc.) and / or environmental parameters (e.g., ambient light, ambient noise, ambient temperature, etc.). In at least some cases, individuals can improve their sleep hygiene by going to bed at a certain time each night, sleeping for a certain amount of time, waking up at a certain time, modifying environmental parameters, or any combination thereof. Sleep hygiene education includes general guidelines about health practices (e.g., diet, exercise, substance use) and environmental factors (e.g., light, noise, excessive temperature) that may interfere with sleep. Mindfulness-based interventions may include, for example, meditation.

[0039] Reference Figure 1 The figure illustrates a system 100 according to some implementations of the present disclosure. System 100 includes a control system 110, a memory device 114, an electronic interface 119, a respiratory therapy system 120, one or more sensors 130, one or more user devices 170, a light source 180, and an activity tracker 190.

[0040] The control system 110 includes one or more processors 112 (hereinafter referred to as processor 112). The control system 110 is typically used to control (e.g., drive) various components of the system 100 and / or analyze data acquired and / or generated by the components of the system 100. The processor 112 may be a general-purpose or special-purpose processor or a microprocessor. Although in Figure 1A processor 112 is shown, but the control system 110 may include any suitable number of processors (e.g., one processor, two processors, five processors, ten processors, etc.), which may be located in a single housing or positioned remotely from each other. The control system 110 may be coupled to and / or located within the housing of, for example, the housing of user equipment 170, a portion of respiratory therapy system 120 (e.g., a housing), and / or one or more of sensors 130. The control system 110 may be centralized (within one such housing) or distributed (within two or more physically different such housings). In such implementations including two or more housings containing the control system 110, such housings may be positioned close to and / or far from each other.

[0041] Memory device 114 stores machine-readable instructions executable by processor 112 of control system 110. Memory device 114 can be any suitable computer-readable storage device or medium, such as random or serial access memory devices, hard disk drives, solid-state drives, flash memory devices, etc. Although Figure 1 A memory device 114 is shown, but system 100 may include any suitable number of memory devices 114 (e.g., one memory device, two memory devices, five memory devices, ten memory devices, etc.). Memory devices 114 may be coupled to and / or located within the housing of respiratory therapy device 122, the housing of user device 170, the housing of activity tracker 190, the housing of one or more sensors 130, or any combination thereof. Similar to control system 110, memory devices 114 may be centralized (within one such housing) or distributed (within two or more physically different such housings).

[0042] In some implementations, memory device 114 ( Figure 1This system stores user profiles associated with users. User profiles may include, for example, user-associated demographic information, user-associated biostatistics, user-associated medical information, self-reported user feedback, user-associated sleep parameters (e.g., sleep-related parameters recorded from one or more earlier sleep periods), or any combination thereof. Demographic information may include, for example, information indicating the user's age, gender, ethnicity, geographic location, relationship status, family history of insomnia, employment status, education status, socioeconomic status, or any combination thereof. Medical information may include, for example, information indicating one or more medical conditions associated with the user, medication use, or both. Medical information data may also include Multisleep Latency Test (MSLT) results or scores and / or Pittsburgh Sleep Quality Index (PSQI) scores or values. Medical information data may include results from one or more of the following: Polysomnography (PSG) tests, CPAP titration, or Home Sleep Testing (HST); respiratory therapy system settings from one or more sleep periods; sleep-related respiratory events from one or more sleep periods, or any combination thereof. Self-reported user feedback may include information indicating self-reported subjective sleep scores (e.g., poor, average, excellent), users' self-reported subjective stress levels, users' self-reported subjective fatigue levels, users' self-reported subjective health status, information about recent life events experienced by users, or any combination thereof.

[0043] Electronic interface 119 is configured to receive data (e.g., physiological data and / or audio data) from one or more sensors 130, such that the data can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. The received data, such as physiological data, flow rate data, pressure data, motion data, acoustic data, etc., can be used to determine and / or calculate physiological parameters. Electronic interface 119 can communicate with one or more sensors 130 using wired or wireless connections (e.g., using RF communication protocols, Wi-Fi communication protocols, Bluetooth communication protocols, IR communication protocols, via cellular networks, via any other optical communication protocols, etc.). Electronic interface 119 may include an antenna, a receiver (e.g., an RF receiver), a transmitter (e.g., an RF transmitter), a transceiver, or any combination thereof. Electronic interface 119 may also include one or more processors and / or one or more memory devices that are the same as or similar to processor 112 and memory device 114 described herein. In some implementations, electronic interface 119 is coupled to or integrated into user equipment 170. In other implementations, the electronic interface 119 is coupled to or integrated with the control system 110 and / or the memory device 114 (e.g., in a housing).

[0044] As described above, in some implementations, system 100 may optionally include a respiratory therapy system 120. The respiratory therapy system 120 may include a respiratory pressure therapy (RPT) device 122 (referred to herein as respiratory therapy device 122), a user interface 124, a catheter 126 (also referred to as a tube or air circuit), a display device 128, a humidifier canister 129, or any combination thereof. In some implementations, one or more of the control system 110, memory device 114, display device 128, sensor 130, and humidifier canister 129 are part of the respiratory therapy device 122. Respiratory pressure therapy refers to the application of supplying air to the user's airway inlet at a controlled target pressure nominally positive relative to the atmosphere (e.g., as opposed to negative pressure therapy such as a canister respirator or chest brace) throughout the user's respiratory cycle. The respiratory therapy system 120 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).

[0045] The respiratory therapy device 122 is typically used to generate pressurized air for delivery to a user (e.g., using one or more motors driving one or more compressors). In some implementations, the respiratory therapy device 122 generates a continuous, constant air pressure delivered to the user. In other implementations, the respiratory therapy device 122 generates two or more predetermined pressures (e.g., a first predetermined air pressure and a second predetermined air pressure). In still other implementations, the respiratory therapy device 122 is configured to generate a variety of different air pressures within a predetermined range. For example, the respiratory therapy device 122 may deliver pressurized air at pressures of at least about 6 cm H2O, at least about 10 cm H2O, at least about 20 cm H2O, between about 6 cm H2O and about 10 cm H2O, between about 7 cm H2O and about 12 cm H2O, etc. The respiratory therapy device 122 may also deliver pressurized air at predetermined flow rates, for example, between about -20 L / min and about 150 L / min, while maintaining positive pressure (relative to ambient pressure).

[0046] User interface 124 engages with a portion of the user's face and delivers pressurized air from respiratory therapy device 122 to the user's airway to help prevent airway narrowing and / or collapse during sleep. This also increases the user's oxygen intake during sleep. Typically, user interface 124 engages with the user's face such that pressurized air is delivered to the user's airway via the user's mouth, the user's nose, or both the user's mouth and nose. Respiratory therapy device 122, user interface 124, and conduit 126 together form an air passage fluidly connected to the user's airway. Pressurized air also increases the user's oxygen intake during sleep.

[0047] Depending on the treatment to be applied, the user interface 124 may, for example, form a seal with an area or portion of the user's face to facilitate the delivery of gas to achieve the treatment under a pressure sufficiently varied relative to ambient pressure, for example, at a positive pressure of about 10 cm H2O relative to ambient pressure. For other forms of treatment, such as oxygen delivery, the user interface may not include a seal sufficient to facilitate the delivery of gas supply to the airway at a positive pressure of about 10 cm H2O.

[0048] like Figure 2 As shown, in some implementations, user interface 124 is or includes a face mask (e.g., a full-face mask) that covers the user's nose and mouth. Alternatively, in some implementations, user interface 124 is a nasal mask that delivers air to the user's nose or a nasal pillow mask that delivers air directly to the user's nostrils. User interface 124 may include multiple straps (e.g., including hook-and-loop fasteners) for positioning and / or stabilizing the interface on a portion of the user (e.g., the face), and conformal cushioning pads (e.g., silicone, plastic, foam, etc.) to help provide an airtight seal between user interface 124 and the user. In some instances, user interface 124 may be a tubular mask, wherein the straps of the mask are configured to act as conduits for delivering pressurized air to the face mask or nasal mask. User interface 124 may also include one or more vents for allowing carbon dioxide and other gases exhaled by user 210 to escape. In other implementations, user interface 124 includes a mouthpiece (e.g., a night-use protective mouthpiece molded to conform to the user's teeth, a jaw repositioning device, etc.).

[0049] The conduit 126 (also referred to as an air circuit or tube) allows air to flow between two components of the respiratory therapy system 120, such as the respiratory therapy device 122 and the user interface 124. In some implementations, there may be separate branches of the conduit for inhalation and exhalation. In other implementations, a single-branch conduit is used for both inhalation and exhalation.

[0050] One or more of the respiratory therapy device 122, user interface 124, catheter 126, display device 128, and humidifier 129 may contain one or more sensors (e.g., pressure sensor, flow sensor, humidity sensor, temperature sensor, or any other sensor 130 more commonly described herein). These one or more sensors can be used, for example, to measure the air pressure and / or flow rate of the pressurized air supplied by the respiratory therapy device 122.

[0051] Display device 128 is typically used to display images including still images, video images, or both, and / or information about respiratory therapy device 122. For example, display device 128 may provide information about the status of respiratory therapy device 122 (e.g., whether respiratory therapy device 122 is on / off, the pressure of the air delivered by respiratory therapy device 122, the temperature of the air delivered by respiratory therapy device 122, etc.) and / or other information (e.g., sleep score and / or treatment score (such as myAir™ score, as described in WO 2016 / 061629, which is incorporated herein by reference in its entirety), current date / time, personal information of user 210, etc.). In some implementations, display device 128 acts as a human-machine interface (HMI) including a graphical user interface (GUI) configured to display images as an input interface. Display device 128 may be an LED display, OLED display, LCD display, etc. The input interface may be, for example, a touchscreen 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 122.

[0052] The humidifier canister 129 is coupled to or integrated into the respiratory therapy device 122. The humidifier canister 129 includes a water reservoir for humidifying pressurized air supplied from the respiratory therapy device 122. The respiratory therapy device 122 may include a heater for heating the water in the humidifier canister 129 to humidify the pressurized air supplied to the user. Additionally, in some implementations, the conduit 126 may also include a heating element (e.g., coupled to and / or embedded in the conduit 126) that heats the pressurized air supplied to the user. The humidifier canister 129 may be fluidly coupled to a water vapor inlet of an air passage and deliver water vapor into the air passage via the water vapor inlet, or it may be linearly integrated into the air passage itself. In other implementations, the respiratory therapy device 122 or the conduit 126 may include a waterless humidifier. The waterless humidifier may be incorporated into a sensor that engages with other sensors located elsewhere in the system 100.

[0053] The respiratory therapy system 120 can be used, for example, as a ventilator or positive airway pressure (PAP) system, such as a continuous positive airway pressure (CPAP) system, an automated positive airway pressure (APAP) system, a bilevel or variable positive airway pressure (BPAP or VPAP) system, a high-flow therapy (HFT) system, or any combination thereof. A CPAP system delivers a predetermined air pressure (e.g., determined by a sleep physician) to the user. An APAP system automatically changes the air pressure delivered to the user based on, for example, respiratory data associated with the user. A BPAP or VPAP system is configured to deliver a first predetermined pressure (e.g., inspiratory positive airway pressure or IPAP) and a second predetermined pressure below the first predetermined pressure (e.g., expiratory positive airway pressure or EPAP). An HFT system typically delivers a continuous, heated, humidified flow of air to the airway inlet through an unsealed or open patient interface at a “therapeutic flow rate” that remains substantially constant throughout the respiratory cycle. This therapeutic flow rate is nominally set to exceed the patient’s peak inspiratory flow rate.

[0054] refer to Figure 2 The diagram illustrates system 100 according to some implementation methods. Figure 1 The user 210 and bed partner 220 of the respiratory therapy system 120 are located on bed 230 and lying on mattress 232. User interface 124 is a face mask (e.g., a full-face mask) covering the nose and mouth of user 210. Alternatively, user interface 124 may be a nasal mask that delivers air to the nose of user 210 or a nasal pillow mask that delivers air directly to the nostrils of user 210. User interface 124 may include multiple straps (e.g., including hook and loop fasteners) for positioning and / or stabilizing the interface on a portion of user 210 (e.g., face), and conformal cushioning pads (e.g., silicone, plastic, foam, etc.) to help provide an airtight seal between user interface 124 and user 210. User interface 124 may also include one or more vents for allowing carbon dioxide and other gases exhaled by user 210 to escape. In other implementations, user interface 124 is a mouthpiece for directing pressurized air into the mouth of user 210 (e.g., a night-time protective mouthpiece molded to conform to the user's teeth, a jaw repositioning device, etc.).

[0055] User interface 124 is fluidly connected and / or connected to respiratory therapy device 122 via conduit 126. Respiratory therapy device 122, in turn, delivers pressurized air to user 210 via conduit 126 and user interface 124 to increase air pressure in user 210's larynx, thereby helping to prevent airway closure and / or narrowing during sleep. Respiratory therapy device 122 can be positioned such as... Figure 2 On the bedside table 240 located directly adjacent to the bed 230, or more generally, on any surface or structure located generally adjacent to the bed 230 and / or the user 210.

[0056] Typically, compared to those who do not use the respiratory therapy system 120 (especially when the user has sleep apnea or other sleep-related disorders), users designated to use the respiratory therapy system 120 tend to experience higher quality sleep and less fatigue throughout the day following use of the respiratory therapy system 120 during sleep. For example, user 210 may have obstructive sleep apnea and rely on user interface 124 (e.g., a full-face mask) to deliver pressurized air from respiratory therapy device 122 via catheter 126. Respiratory therapy device 122 may be a continuous positive airway pressure (CPAP) machine used to increase air pressure in user 210's throat to prevent airway closure and / or narrowing during sleep. For individuals with sleep apnea, their airways may narrow or collapse during sleep, a condition that reduces oxygen intake and forces them to wake up and / or otherwise disrupts their sleep. CPAP machines prevent airway narrowing or collapse, thereby minimizing awakenings or disturbances due to reduced oxygen intake. Although the respiratory therapy device 122 strives to maintain one or more medically prescribed air pressures during sleep, the user may experience sleep discomfort due to the treatment.

[0057] Return to reference Figure 1 The system 100 includes one or more sensors 130, such as a pressure sensor 132, a flow sensor 134, a temperature sensor 136, a motion sensor 138, a microphone 140, a speaker 142, a radio frequency (RF) receiver 146, an RF transmitter 148, a camera 150, an infrared sensor 152, a photoplethysmography (PPG) sensor 154, an electrocardiogram (ECG) sensor 156, an electroencephalogram (EEG) sensor 158, a capacitance sensor 160, a force sensor 162, a strain gauge sensor 164, an electromyography (EMG) sensor 166, an oxygen sensor 168, an analyte sensor 174, a humidity sensor 176, a light detection and ranging (LiDAR) sensor 178, a skin conductance sensor, an accelerometer, an electrooculogram (EOG) sensor, a light sensor, a humidity sensor, an air quality sensor, or any combination thereof. Typically, each of the one or more sensors 130 is configured to output sensor data received and stored in a memory device 114 or one or more other memory devices.

[0058] Although one or more sensors 130 are shown and described as including each of the following: pressure sensor 132, flow sensor 134, temperature sensor 136, motion sensor 138, microphone 140, speaker 142, RF receiver 146, RF transmitter 148, camera 150, infrared sensor 152, photoplethysmography (PPG) sensor 154, electrocardiogram (ECG) sensor 156, electroencephalogram (EEG) sensor 158, capacitance sensor 160, force sensor 162, strain gauge sensor 164, electromyography (EMG) sensor 166, oxygen sensor 168, analyte sensor 174, humidity sensor 176, and LiDAR sensor 178, more generally, one or more sensors 130 may include any combination and any number of each of the sensors described and / or shown herein.

[0059] As described herein, system 100 can typically be used to generate information with the user before, during, and / or after sleep periods (e.g., Figure 2 Data associated with the user of the illustrated respiratory therapy system 120 (e.g., physiological data, flow rate data, pressure data, motion data, acoustic data, etc.) can be analyzed to generate one or more physiological parameters (e.g., before, during, and / or after sleep periods) and / or sleep-related parameters (e.g., during sleep periods). These parameters can include any user-related parameters, measurements, etc. Examples of one or more physiological parameters include breathing pattern, respiratory rate, inspiratory amplitude, expiratory amplitude, heart rate, heart rate variability, length of time between breaths, maximum inspiratory time, maximum expiratory time, forced breathing parameters (e.g., distinguishing between release breaths and forced exhalations), respiratory variability, respiratory morphology (e.g., the shape of one or more breaths), user 210's motion, temperature, EEG activity, EMG activity, ECG data, sympathetic response parameters, parasympathetic response parameters, etc. One or more sleep-related parameters that can be determined for user 210 during sleep periods include, for example, apnea-hypopnea index (AHI) score, sleep score, treatment score, flow signal, pressure signal, respiratory signal, breathing pattern, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, number of events per hour (e.g., apnea events), event pattern, sleep state and / or sleep stage, heart rate, heart rate variability, user 210's movement, temperature, EEG activity, EMG activity, arousal, snoring, choking, coughing, whistling, wheezing, or any combination thereof.

[0060] One or more sensors 130 may be used to generate, for example, physiological data, audio data, or both. The control system 110 may use the physiological data generated by one or more of the sensors 130 to determine the sleep duration and sleep quality of the user 210. Examples include sleep-wake signals and one or more sleep-related parameters associated with the user 210 during sleep periods. Sleep-wake signals may indicate one or more sleep states, including sleep, sleeplessness, relaxed sleeplessness, micro-arousal, or different sleep stages such as rapid eye movement (REM) stage, first non-REM stage (commonly referred to as "N1"), second non-REM stage (commonly referred to as "N2"), third non-REM stage (commonly referred to as "N3"), or any combination thereof. For example, methods for determining sleep state and / or sleep stage based on physiological data generated by one or more sensors (such as sensor 130) are described in WO 2014 / 047310, US 2014 / 0088373, WO 2017 / 132726, WO 2019 / 122413 and WO 2019 / 122414, each of which is incorporated herein by reference in its entirety.

[0061] The sleep-wake signal can also be timestamped to determine the time the user goes to bed, the time the user gets out of bed, the time the user attempts to fall asleep, etc. The sleep-wake signal can be measured by one or more sensors 130 during the sleep period at a predetermined sampling rate (e.g., one sample per second, one sample every 30 seconds, one sample per minute, etc.). In some implementations, the sleep-wake signal can also indicate respiratory signals, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, number of events per hour, event pattern, pressure setting of the respiratory therapy device 122, or any combination thereof during the sleep period.

[0062] Events can include snoring, sleep apnea, central sleep apnea, obstructive sleep apnea, mixed sleep apnea, hypopnea, oral leakage, mask leakage (e.g., from user interface 124), kinesthetic leg movement, sleep disturbance, choking, increased heart rate, heart rate variability, difficulty breathing, asthma attack, seizure, sudden onset, fever, cough, sneezing, snoring, wheezing, the presence of an illness such as the common cold or influenza, or any combination thereof. In some implementations, oral leakage can include continuous oral leakage or valve-type oral leakage (i.e., varying in duration of breathing), where the user's lips (typically using a nose / nose occipital mask) suddenly open during exhalation. Oral leakage can cause dry mouth, halitosis, and is sometimes colloquially known as "sandpaper mouth."

[0063] One or more sleep-related parameters can be determined for a user based on sleep-wake signals during sleep periods, including, for example, sleep quality indicators such as total bedtime, total sleep time, sleep onset wait time, wake-up start parameters after sleep, sleep efficiency, fragmentation index, or any combination thereof.

[0064] Data generated by one or more sensors 130 (e.g., physiological data, flow rate data, pressure data, motion data, acoustic data, etc.) can also be used to determine respiratory signals. Respiratory signals typically indicate a user's breathing or respiratory status. Respiratory signals can indicate a breathing pattern, which may include, for example, respiratory rate, respiratory rate variability, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, and other respiratory-related parameters, and any combination thereof. In some cases, during sleep periods, respiratory signals may include the number of events per hour (e.g., during sleep), event patterns, pressure settings of the respiratory therapy device 122, or any combination thereof. Events may include snoring, sleep apnea (e.g., central sleep apnea, obstructive sleep apnea, mixed sleep apnea, and hypopnea), oral leakage, mask leakage (e.g., from user interface 124), restless legs, sleep disturbances, apnea, increased heart rate, dyspnea, asthma attacks, seizures, sudden attacks, or any combination thereof.

[0065] Typically, a sleep period includes any point in time after the user 210 has already lay down or sat in bed 230 (or another area or object where they intend to sleep), and / or has turned on the breathing therapy device 122 and / or put on the user interface 124. A sleep period can therefore include time periods (i) when the user 210 is using the CPAP system but before attempting to fall asleep (e.g., when the user 210 is lying in bed 230 reading); (ii) when the user 210 begins to attempt to fall asleep but is still awake; (iii) when the user 210 is in light sleep (also known as stages 1 and 2 of non-rapid eye movement (NREM) sleep); (iv) when the user 210 is in deep sleep (also known as slow-wave sleep, SWS, or stage 3 of NREM sleep); (v) when the user 210 is in rapid eye movement (REM) sleep; (vi) when the user 210 periodically wakes up between light sleep, deep sleep, or REM sleep; or (vii) when the user 210 wakes up and does not fall asleep again.

[0066] A sleep period is typically defined as ending once user 210 removes user interface 124, shuts off respiratory therapy device 122, and / or leaves bed 230. In some implementations, a sleep period may include additional time periods, or may be limited to only some of the aforementioned time periods. For example, a sleep period may be defined as a time period that begins when respiratory therapy device 122 begins supplying pressurized air to the airway or user 210, ends when respiratory therapy device 122 stops supplying pressurized air to the airway of user 210, and includes some or all of the time points between when user 210 is asleep or awake.

[0067] In some cases, a pre-sleep period can be defined as the time period before a user falls asleep (e.g., before the user enters light sleep, deep sleep, or REM sleep), which may include the time before and / or after the user lies or sits in bed 230 (or another area or object where they intend to sleep). In some cases, personalized clips as disclosed herein may be used during this pre-sleep period, although this is not always the case. In some cases, for example, personalized clips may be used during a sleep period (e.g., when the user is asleep or when the user periodically wakes up between light sleep, deep sleep, or REM sleep) and / or after a sleep period (e.g., after the user has woken up and decided to stay awake). In some cases, personalized clips as disclosed herein may be used during the pre-sleep period, continue to be used during the sleep period (e.g., in the same or modified form), and / or be used after the end of the sleep period (e.g., in the same or modified form).

[0068] Pressure sensor 132 outputs pressure data that can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. In some implementations, pressure sensor 132 is an air pressure sensor (e.g., an atmospheric pressure sensor) that generates sensor data indicating the breathing (e.g., inhalation and / or exhalation) and / or ambient pressure of the user of respiratory therapy system 120. In such implementations, pressure sensor 132 can be coupled to, or integrated into, respiratory therapy device 122, user interface 124, or conduit 126. Pressure sensor 132 can be used to determine air pressure in respiratory therapy device 122, air pressure in conduit 126, air pressure in user interface 124, or any combination thereof. Pressure sensor 132 can be, for example, a capacitive sensor, electromagnetic sensor, inductive sensor, resistive sensor, piezoelectric sensor, strain gauge sensor, optical sensor, potentiometric sensor, or any combination thereof. In one example, pressure sensor 132 can be used to determine the user's blood pressure.

[0069] The flow sensor 134 outputs flow rate data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. In some implementations, the flow sensor 134 is used to determine the airflow rate from the respiratory therapy device 122, the airflow rate through the conduit 126, the airflow rate through the user interface 124, or any combination thereof. In such implementations, the flow sensor 134 can be coupled to, or integrated into, the respiratory therapy device 122, the user interface 124, or the conduit 126. The flow sensor 134 can be a mass flow sensor, such as a rotary flow meter (e.g., a Hall effect flow meter), a turbine flow meter, an orifice flow meter, an ultrasonic flow meter, a hot-wire sensor, an eddy current sensor, a membrane sensor, or any combination thereof.

[0070] Flow sensor 134 can be used to generate data with user 210 of breathing therapy device 122 during sleep periods. Figure 2 The flow rate data is associated with the flow sensor. Examples of flow sensors (such as flow sensor 134) are described in WO 2012 / 012835, which is incorporated herein by reference in its entirety. In some implementations, flow sensor 134 is configured to measure ventilation flow (e.g., intentional “leakage”), unintentional leakage (e.g., oral leak and / or mask leak), patient flow (e.g., air entering and / or leaving the lungs), or any combination thereof. In some implementations, the flow rate data can be analyzed to determine the user’s cardiogenic oscillations.

[0071] Temperature sensor 136 outputs temperature data that can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. In some implementations, temperature sensor 136 generates instructions for user 210 ( Figure 2 Temperature data including core body temperature, user 210 skin temperature, temperature of air flowing from respiratory therapy device 122 and / or through conduit 126, temperature of air in user interface 124, ambient temperature, or any combination thereof. Temperature sensor 136 may be, for example, a thermocouple sensor, a thermistor sensor, a silicon bandgap temperature sensor or a semiconductor-based sensor, a resistance temperature detector, or any combination thereof.

[0072] Motion sensor 138 outputs motion data that can be stored in memory device 114 and / or analyzed by processor 112 of control system 110. Motion sensor 138 can be used to detect movement of user 210 during sleep periods, and / or to detect movement of any component of respiratory therapy system 120 (such as respiratory therapy device 122, user interface 124, or catheter 126). Motion sensor 138 may include one or more inertial sensors, such as accelerometers, gyroscopes, and magnetometers. In some implementations, motion sensor 138 alternatively or additionally generates one or more signals representing the user's body movements, from which signals representing the user's sleep state or sleep stage can be obtained; for example, via the user's breathing movements. In some implementations, motion data from motion sensor 138 can be combined with additional data from another sensor 130 to determine the user's sleep state or sleep stage. In some implementations, motion data can be used to determine the user's position, body position, and / or changes in body position.

[0073] The output of microphone 140 may be stored in memory device 114 and / or analyzed by processor 112 of control system 110. The audio data generated by microphone 140 can be reproduced as one or more sounds (e.g., sounds from user 210) during sleep periods. The audio data from microphone 140 can also be used to identify (e.g., using control system 110) events experienced by the user during sleep periods, as described further in detail herein. Microphone 140 may be coupled to, or integrated into, respiratory therapy device 122, user interface 124, catheter 126, or user device 170. In some implementations, system 100 includes multiple microphones (e.g., two or more microphones and / or a microphone array with beamforming) such that sound data generated by each of the multiple microphones can be used to distinguish sound data generated by another of the multiple microphones.

[0074] Speaker 142 outputs sound waves. In one or more implementations, the sound waves can be audible to the user of system 100 (e.g., Figure 2 The speaker 142 can be used as, for example, an alarm clock or to play alarms or messages to the user 210 (e.g., in response to an identified body position and / or a change in body position). In some implementations, the speaker 142 can be used to convey audio data generated by the microphone 140 to the user. The speaker 142 can be coupled to, or integrated into, a respiratory therapy device 122, a user interface 124, a catheter 126, or a user device 170.

[0075] Microphone 140 and speaker 142 can be used as separate devices. In some implementations, microphone 140 and speaker 142 can be combined into acoustic sensor 141 (e.g., a SONAR sensor), as described in, for example, WO 2018 / 050913 and WO2020 / 104465, each of which is incorporated herein by reference in its entirety. In such implementations, speaker 142 generates or emits sound waves at predetermined intervals and / or frequencies, and microphone 140 detects reflections of the emitted sound waves from speaker 142. In one or more implementations, the sound waves generated or emitted by speaker 142 may have frequencies inaudible to the human ear (e.g., below 20 Hz or above about 18 kHz) so as not to disturb user 210 or bed partner 220. Figure 2 The control system 110 can determine the sleep of user 210, based at least in part on data from microphone 140 and / or speaker 142. Figure 2 The location and / or one or more of the sleep-related parameters (e.g., the identified body position and / or changes in body position) and / or the respiratory-related parameters described herein, such as breathing patterns, respiratory signals (e.g., respiratory morphology that can be determined from the respiratory signals), respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, number of events per hour, event pattern, sleep state, sleep stage, or any combination thereof. In this context, a sonar sensor can be understood to involve active acoustic sensing, such as by generating / transmitting ultrasonic or low-frequency ultrasonic sensing signals (e.g., in the frequency range of about 17 to 23 kHz, 18 to 22 kHz, or 17 to 18 kHz) through the air. Such systems can be considered relative to WO2018 / 050913 and WO 2020 / 104465 above.

[0076] In some cases, microphone 140 and / or speaker 142 may be incorporated into a separate device, such as a wearable device, such as one or more headphones or headsets. In some cases, such a device may include other sensors among one or more sensors 130.

[0077] In some implementations, sensor 130 includes (i) a first microphone that is the same as or similar to microphone 140 and is integrated in acoustic sensor 141; and (ii) a second microphone that is the same as or similar to microphone 140, but is separate from and different from the first microphone integrated in acoustic sensor 141.

[0078] RF transmitter 148 generates and / or transmits radio waves with a predetermined frequency and / or predetermined amplitude (e.g., in the high-frequency band, in the low-frequency band, long-wave signal, short-wave signal, etc.). RF receiver 146 detects the reflection of the radio waves transmitted from RF transmitter 148, and this data can be analyzed by control system 110 to determine the user 210 (…). Figure 2 The location and / or body position and / or one or more sleep-related parameters described herein. RF receivers (RF receiver 146 and RF transmitter 148 or another RF pair) may also be used for wireless communication between control system 110, respiratory therapy device 122, one or more sensors 130, user equipment 170, or any combination thereof. Although RF receiver 146 and RF transmitter 148 are in... Figure 1 While shown as separate and distinct components, in some implementations, the RF receiver 146 and RF transmitter 148 are combined as part of the RF sensor 147 (e.g., a RADAR sensor). In some such implementations, the RF sensor 147 includes control circuitry. The specific format of the RF communication may be Wi-Fi, Bluetooth, etc.

[0079] In some implementations, RF sensor 147 is part of a mesh system. An example of a mesh system is a Wi-Fi mesh system, which may include mesh nodes, one or more mesh routers, and one or more mesh gateways, each of which may be mobile / movable or fixed. In such implementations, the Wi-Fi mesh system includes Wi-Fi routers and / or Wi-Fi controllers, and one or more satellites (e.g., access points), each of which includes the same or similar RF sensor as RF sensor 147. The Wi-Fi routers and 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 the Wi-Fi signals between the routers and satellites (e.g., differences in received signal strength) caused by a moving object or person partially blocking the signal. The motion data may indicate movement, breathing, heart rate, gait, falls, behavior, etc., or any combination thereof.

[0080] Camera 150 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 memory device 114. Image data from camera 150 can be used by control system 110 to determine one or more of the sleep-related parameters described herein, such as one or more events (e.g., periodic limb movements or restless legs syndrome), respiratory signals, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, number of events per hour, event pattern, sleep state, sleep stage, or any combination thereof. Furthermore, image data from camera 150 can be used to identify the user's location and / or body position, determine the user 210's chest movements, determine the user 210's mouth and / or nose airflow, determine the time the user 210 got into bed 230, and determine the time the user 210 got out of bed 230. Camera 150 can also be used to track eye movements, pupil dilation (assuming one or both of the user 210's eyes are open), blink rate, or any changes during REM sleep.

[0081] Infrared (IR) sensor 152 outputs infrared image data that can be reproduced as one or more infrared images (e.g., still images, video images, or both) that can be stored in memory device 114. The infrared data from IR sensor 152 can be used to determine one or more sleep-related parameters during a sleep period, including the user 210's temperature and / or the user 210's movement. IR sensor 152 can also be used in conjunction with camera 150 when measuring the presence, location, and / or movement of user 210. For example, IR sensor 152 can detect infrared light with wavelengths between about 700 nm and about 1 mm, while camera 150 can detect visible light with wavelengths between about 380 nm and about 740 nm.

[0082] PPG sensor 154 output and user 210 ( Figure 2The PPG sensor 154 can be associated with physiological data that can be used to determine one or more sleep-related parameters, such as heart rate, heart rate pattern, heart rate variability, cardiac cycle, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, estimated blood pressure parameters, or any combination thereof. The PPG sensor 154 can be worn by the user 210, embedded in clothing and / or fabric worn by the user 210, embedded in and / or connected to the user interface 124 and / or its associated headband (e.g., a strap, etc.). In some cases, the PPG sensor 154 can be a non-contact PPG sensor capable of performing PPG at a distance. In some cases, the PPG sensor 154 can be used to determine the pulse arrival time (PAT). PAT can be the determination of the time interval required for a pulse wave to travel from the heart to a distal location on the body (e.g., a finger or other location). In other words, PAT can be determined by measuring the time interval between the R wave of the ECG and the peak of the PPG. In some cases, baseline changes in the PPG signal can be used to derive the respiratory signal and thus respiratory information, such as respiratory rate. In some cases, PPG signals can provide SpO2 data, which can be used to detect sleep-related disorders such as OSA.

[0083] ECG sensor 156 outputs physiological data associated with the electrical activity of the heart of user 210. In some implementations, ECG sensor 156 includes one or more electrodes positioned on or around a portion of user 210 during sleep periods. Physiological data from ECG sensor 156 can be used, for example, to determine one or more of the sleep-related parameters described herein. In some cases, amplitude and / or morphological changes in the ECG traces can be used to identify respiratory curves and thus respiratory information, such as respiratory rate.

[0084] In some cases, ECG and / or PPG signals can be used in conjunction with secondary estimates innervated by the parasympathetic and / or sympathetic nervous systems, such as via a ground-skin response (GSR) sensor. Such signals can be used to identify the actual respiratory curve that occurs and whether it has a positive, neutral, or negative effect on an individual's stress level.

[0085] EEG sensor 158 outputs physiological data associated with the electrical activity of the user 210's brain. In some implementations, EEG sensor 158 includes one or more electrodes positioned on or around the user 210's scalp during sleep periods. The physiological data from EEG sensor 158 can be used, for example, to determine the user 210's sleep state or sleep stage at any given time during a sleep period. In some implementations, EEG sensor 158 may be integrated into user interface 124 and / or an associated headband (e.g., a strap, etc.).

[0086] Capacitive sensor 160, force sensor 162, and strain gauge sensor 164 output data that can be stored in memory device 114 and used by control system 110 to determine one or more of the sleep-related parameters described herein. EMG sensor 166 outputs physiological data associated with electrical activity generated by one or more muscles. Oxygen sensor 168 outputs oxygen data indicating the oxygen concentration of a gas (e.g., in conduit 126 or at user interface 124). Oxygen sensor 168 may be, for example, an ultrasonic oxygen sensor, an electro-oxygen sensor, a chemical oxygen sensor, an optical oxygen sensor, or any combination thereof. In some implementations, one or more sensors 130 may also include a ground-skin response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a blood pressure sensor, a blood oxygenation sensor, or any combination thereof.

[0087] Analyte sensor 174 can be used to detect the presence of analytes in the exhaled breath of user 210. Data output from analyte sensor 174 can be stored in memory device 114 and used by control system 110 to determine the identity and concentration of any analytes in user 210's breath. In some implementations, analyte sensor 174 is positioned near user 210's mouth to detect analytes in the breath exhaled from user 210's mouth. For example, when user interface 124 is a mask covering user 210's nose and mouth, analyte sensor 174 can be positioned inside the mask to monitor user 210's mouth breathing. In other implementations, such as when user interface 124 is a nasal mask or nasal bolus mask, analyte sensor 174 can be positioned near user 210's nose to detect analytes in the breath exhaled through user's nose. In other implementations, when user interface 124 is a nasal mask or nasal bolus mask, analyte sensor 174 can be positioned near user 210's mouth. In this implementation, the analyte sensor 174 can be used to detect whether any air is unintentionally leaking from the mouth of user 210. In some implementations, the analyte sensor 174 is a volatile organic compound (VOC) sensor that can be used to detect carbon-based chemicals or compounds. In some implementations, the analyte sensor 174 can also be used to detect whether user 210 is breathing through their nose or mouth. For example, if the presence of an analyte is detected by data output from the analyte sensor 174 located near the mouth of user 210 or inside a mask (in the implementation where user interface 124 is a mask), the control system 110 can use that data as an indication that user 210 is breathing through their mouth.

[0088] The humidity sensor 176 outputs data that can be stored in the memory device 114 and used by the control system 110. The humidity sensor 176 can be used to detect humidity in various areas surrounding the user (e.g., within the conduit 126 or user interface 124, near the user 210's face, near the connection between the conduit 126 and user interface 124, near the connection between the conduit 126 and the respiratory therapy device 122, etc.). Therefore, in some implementations, the humidity sensor 176 may be positioned in the user interface 124 or the conduit 126 to monitor the humidity of pressurized air from the respiratory therapy device 122. In other implementations, the humidity sensor 176 is placed near any area where the humidity level needs to be monitored. The humidity sensor 176 can also be used to monitor the humidity of the environment surrounding the user 210, such as the air in the user 210's bedroom. The humidity sensor 176 can also be used to track the user 210's biometric response to environmental changes.

[0089] One or more Light Detection and Ranging (LiDAR) sensors 178 can be used for depth sensing. This type of optical sensor (e.g., a laser sensor) can be used to detect a subject and construct a three-dimensional (3D) map of the surrounding environment (such as a living space). LiDAR typically utilizes pulsed lasers for time-of-flight measurements. LiDAR is also known as 3D laser scanning. In instances using such sensors, a fixed or mobile device (such as a smartphone) with LiDAR sensor 178 can measure and map an area extending 5 meters or more from the sensor. For example, LiDAR data can be fused with point cloud data estimated by an electromagnetic RADAR sensor. LiDAR sensor 178 can also use artificial intelligence (AI) to automatically geofence the RADAR system by detecting and classifying features in the space that may cause problems for the RADAR system, such as glass windows (which may be highly reflective of the RADAR). For example, LiDAR can also be used to provide an estimate of a person's height, and how that height changes when the person sits down or falls. LiDAR can be used to form a 3D mesh representation of the environment. In further applications, LiDAR can reflect radio waves off solid surfaces (e.g., transmissive materials), allowing for the classification of different types of obstacles.

[0090] In some implementations, one or more sensors 130 may also include a skin conductance response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a blood pressure sensor, a blood oxygen measurement 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 orientation sensor, a rain sensor, a soil moisture sensor, a water flow sensor, an alcohol sensor, or any combination thereof.

[0091] Although Figure 1 While shown separately, any combination of one or more sensors 130 may be coupled to and / or integrated into any one or more components of system 100, including respiratory therapy device 122, user interface 124, catheter 126, humidifier 129, control system 110, user device 170, or any combination thereof. For example, microphone 140 and speaker 142 are coupled to and / or integrated into user device 170, and pressure sensor 130 and / or flow sensor 132 are integrated into and / or coupled to respiratory therapy device 122. In some implementations, at least one of the one or more sensors 130 is not coupled to respiratory therapy device 122, control system 110, or user device 170, and is positioned substantially adjacent to user 210 during sleep periods (e.g., positioned on or in contact with a portion of user 210, worn by user 210, coupled to or positioned on a bedside table, coupled to a mattress, coupled to a ceiling, etc.).

[0092] Data from one or more sensors 130 can be analyzed to determine one or more physiological parameters, which may include respiratory signals, respiratory rate, respiratory pattern or morphology, respiratory rate variability, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, duration between breaths, maximum inspiratory time, maximum expiratory time, forced breathing parameters (e.g., distinguishing between release breaths and forced exhalations), occurrence of one or more events, number of events per hour, event patterns, sleep state, sleep stage, apnea-hypopnea index (AHI), heart rate, heart rate variability, user 210 movement, temperature, EEG activity, EMG activity, ECG data, sympathetic response parameters, parasympathetic response parameters, or any combination thereof. One or more events may include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, intentional mask leak, unintentional mask leak, oral leak, cough, leg movement, sleep disturbance, apnea, increased heart rate, dyspnea, asthma attack, seizure, sudden onset, increased blood pressure, or any combination thereof. Many of these physiological parameters are sleep-related, although in some cases data from one or more sensors 130 can be analyzed to determine one or more non-physiological parameters, such as non-physiological sleep-related parameters. Non-physiological parameters may also include operating parameters of the respiratory therapy system, including flow rate, pressure, humidity of the pressurized air, motor speed, etc. Other types of physiological and non-physiological parameters can also be determined based on data from one or more sensors 130 or based on other types of data.

[0093] User equipment 170 ( Figure 1The system includes a display device 172. User device 170 can be a mobile device such as a smartphone, tablet, game console, smartwatch, laptop, etc. Alternatively, user device 170 can be an external sensing system, a television (e.g., a smart TV), or another smart home device (e.g., a smart speaker, optionally with a display, such as Google Home™, Google Nest™, Amazon Echo™, Amazon Echo Show™, Alexa™-enabled devices, etc.). In some implementations, the user device is a wearable device (e.g., a smartwatch). Display device 172 is typically used to display images including still images, video images, or both. In some implementations, display device 172 acts as a human-machine interface (HMI) including a graphical user interface (GUI) configured to display images and an input interface. Display device 172 can be an LED display, OLED display, LCD display, etc. The input interface can be, for example, a touchscreen or touch-sensitive substrate, a mouse, keyboard, or any sensor system configured to sense input from a human user interacting with user device 170. In some implementations, system 100 may use and / or include one or more user devices.

[0094] Light source 180 is typically used to emit light having intensity and wavelength (e.g., color). For example, light source 180 may emit light having wavelengths between about 380 nm and about 700 nm (e.g., wavelengths in the visible spectrum). Light source 180 may include, for example, one or more light-emitting diodes (LEDs), one or more organic light-emitting diodes (OLEDs), light bulbs, lamps, incandescent light bulbs, CFL bulbs, halogen bulbs, or any combination thereof. In some implementations, the intensity and / or wavelength (e.g., color) of the light emitted from light source 180 may be modified by control system 110. Light source 180 may also emit light in predetermined emission modes, such as continuous emission, pulsed emission, periodic emission of varying intensities (e.g., including a light emission cycle that gradually increases in intensity followed by a decrease in intensity), or any combination thereof. The light emitted from light source 180 may be directly viewed by a user, or alternatively, may be reflected or refracted before reaching the user. In some implementations, light source 180 includes one or more light tubes.

[0095] In some implementations, the light source 180 is physically coupled to or integrated into the respiratory therapy system 120. For example, the light source 180 may be physically coupled to or integrated into the respiratory therapy device 122, user interface 124, catheter 126, display device 128, or any combination thereof. In some implementations, the light source 180 is physically coupled to or integrated into the user device 170 or activity tracker 190. In other implementations, the light source 180 is separate from and distinct from each of the respiratory therapy system 120, user device 170, and activity tracker 190. In such implementations, the light source 180 may be located, for example, to user 210 (…). Figure 2 ), bedside table 240, bed 230, other furniture, walls, ceiling, etc.

[0096] Activity tracker 190 is typically used to help generate physiological data for determining activity measurements associated with a user. Activity measurements may include, for example, steps, distance traveled, steps climbed, duration of physical activity, type of physical activity, intensity of physical activity, time spent standing, respiratory rate, average respiratory rate, resting respiratory rate, maximum respiratory rate, respiratory rate variability, heart rate, average heart rate, resting heart rate, maximum heart rate, heart rate variability, calories burned, blood oxygen saturation level (SpO2), skin conductance (also known as skin conductance or skin response), user location, user posture, or any combination thereof. Activity tracker 190 includes one or more sensors 130 described herein, such as motion sensors 138 (e.g., one or more accelerometers and / or gyroscopes), PPG sensors 154, and / or ECG sensors 156.

[0097] In some implementations, the activity tracker 190 is a wearable device that can be worn by the user, such as a smartwatch, wristband, ring, or patch. For example, see reference... Figure 2 The activity tracker 190 is worn on the wrist of user 210. The activity tracker 190 can also be attached to or integrated into clothing or garments worn by the user. Alternatively, the activity tracker 190 can also be attached to or integrated into user device 170 (e.g., within the same housing). More typically, the activity tracker 190 can communicate with or be physically integrated into control system 110, memory device 114, respiratory therapy system 120, and / or user device 170 (e.g., within a housing).

[0098] Although the control system 110 and the memory device 114 are in Figure 1While described and shown as separate and distinct components of system 100, in some implementations, control system 110 and / or memory device 114 are integrated into user equipment 170 and / or respiratory therapy device 122. Alternatively, in some implementations, control system 110 or a portion thereof (e.g., processor 112) may reside in the cloud (e.g., integrated into a server, integrated into an Internet of Things (IoT) device, connected to the cloud, subjected to edge cloud processing, etc.), reside in one or more servers (e.g., remote server, local server, etc.), or any combination thereof.

[0099] While system 100 is shown as including all of the components described above, according to implementations of this disclosure, systems for generating physiological data and determining suggested notifications or actions for a user may include more or fewer components. For example, a first alternative system includes a control system 110, a memory device 114, and at least one of one or more sensors 130. As another example, a second alternative system includes a control system 110, a memory device 114, at least one of one or more sensors 130, and a user device 170. As yet another example, a third alternative system includes a control system 110, a memory device 114, a respiratory therapy system 120, at least one of one or more sensors 130, and a user device 170. Therefore, various systems can be formed using any part or multiple parts of the components shown and described herein and / or in combination with one or more other components.

[0100] Reference Figure 3A and Figure 3B The diagram illustrates a user interface 300 according to some implementations of this disclosure. User interface 300 can be used with user interface 124 ( Figure 1 and Figure 2 The user interface 300 is identical or similar to, and can be used with, the system 100 described herein. The user interface 300 includes a strap assembly 310, a cushioning pad 330, a frame 350, and a connector 370. The strap assembly 310 is configured to be positioned generally around at least a portion of the user's head when the user wears the user interface 300. The strap assembly 310 is attachable to the frame 350 and positioned on the user's head such that the user's head is positioned between the strap assembly 310 and the frame 350.

[0101] In some implementations, the cushioning pad 330 is positioned between the user's face and the frame 350 to form a seal on the user's face. A first end portion 372A of the connector 370 is coupled to the frame 350, while a second end portion 372B of the connector 370 may be coupled to a conduit (e.g., Figure 1 and Figure 2(See conduit 126). The conduit can also be connected to the air outlet of a respiratory therapy device (e.g., respiratory therapy device 122 described herein). A blower motor in the respiratory therapy device is operable to cause pressurized air to flow from the air outlet, thereby providing pressurized air to the user. The pressurized air can flow from the respiratory therapy device through the conduit, connector 370, frame 350, and cushion 330 until the air reaches the user's airway through the user's mouth, nose, or both.

[0102] The band assembly 310 is formed by a rear portion 312, a pair of upper bands 314A and 314B, and a pair of lower bands 316A and 316B. When a user wears the user interface 300, the rear portion 312 of the band assembly is typically positioned behind the user's head. The upper bands 314A, 314B and the lower bands 316A, 316B extend from the rear portion 312 toward the front of the user's face. In the illustrated implementation, the rear portion 312 has a circular shape. However, the rear portion 312 may also have other shapes. The rear portion 312, the upper bands 314A, 314B, and the lower bands 316A, 316B may be formed or woven from generally stretchable or elastic materials, such as fabric, elastic materials, rubber, or any combination of materials. In some implementations, the band assembly 310 has a hollow interior or channel through which wires or traces may extend, as discussed in further detail below.

[0103] The upper straps 314A and 314B and the lower straps 316A and 316B each have a first end starting from the rear portion 312 and a second end connected to the frame 350. When the user wears the user interface 300, the tension provided by the strap assembly 310 holds the frame 350 to the user's face, thereby securing the user interface 300 to the user's head.

[0104] In some implementations, the tension sensor can be embedded in one of the strips of the strip assembly. For example, Figure 3BThe diagram illustrates a tension sensor 313 embedded in the upper band 314A. The tension sensor 313 is configured to measure the tension in the band of the user interface 124. As discussed, the user interface 124 is typically fastened to the head of the user 210 using a band that can be tightened using hook-and-loop fasteners. The tension sensor 313 can sense the tension in the band, which can then be used to notify and / or indicate to the user 210 regarding the correct fit of the user interface 124. The tension sensor 313 can be integrated into yarn, fiber, wire, carbon fiber, warp, mesh, etc. When the tension in the band increases or decreases, the sensor element of the tension sensor 313 deflects, causing a change in the voltage of the output signal. The tension sensor 313 can have high elasticity and low resistance, as well as be washable. In some implementations, the tension sensor 313 measures the diameter of the inflatable body using the principle of breath-sensing plethysmography. The tension sensor 313 can also be an impedance plethysmography sensor, a magnetometer, a strain gauge sensor, or made of a piezoresistive material displacement sensor.

[0105] The frame 350 is typically formed by a body 352 defining a first surface 354A and a second opposing surface 354B. When a user wears the user interface 300, the first surface 354A faces away from the user's face, while the second surface 354B faces the user's face. The frame also defines an annular hole 356 into which a cushioning pad 330 and a connector 370 can be inserted, thereby physically connecting the cushioning pad 330 and the connector 370 to the frame 350.

[0106] The cushioning pad 330 can be attached to the interior of the frame 350 at a location adjacent to the second surface 354B, such that the cushioning pad 330 is positioned between the user's face and the frame 350. The cushioning pad 330 can be made of the same or similar material as the cushioning pad of the user interface 124, for example, a conformal material that helps form an airtight seal with the user's face. The cushioning pad 330 defines an opening 336 and includes an annular protrusion 338 extending from the cushioning pad 330 around the opening 336. The annular protrusion 338 is inserted into the annular opening 356 of the frame 350 such that the annular opening 336 of the cushioning pad 330 overlaps with the annular opening 356 of the frame 350. In some implementations, the annular protrusion 338 of the cushioning pad 330 is releasably secured to the body 352 of the frame 350 by a frictional engagement between the annular protrusion 338 and the body 352 surrounding the annular opening 356.

[0107] In other implementations, the annular protrusion 338 and the frame 350 may have mating features that engage with each other to secure the cushioning pad 330 to the frame 350. For example, the annular protrusion 338 of the cushioning pad 330 may include an outwardly extending peripheral flange, and the body 352 of the frame 350 may include a corresponding inwardly extending peripheral flange surrounding the annular hole 356. When the annular protrusion 338 of the cushioning pad 330 is inserted into the annular hole 356 of the frame 350, the peripheral flanges may slide or snap against each other, thereby securing the cushioning pad 330 to the frame 350. In an additional implementation, the cushioning pad 330 is held in place by tension provided by the belt assembly 310 and is not physically coupled to the frame 350. In other implementations, the cushioning pad 330 and the frame 350 may be formed as a single integral piece.

[0108] Connector 370 can be coupled to the opposite side of frame 350 in a similar manner to cushioning pad 330. The first end portion 372A of connector 370 has a generally cylindrical shape and can be inserted into an annular hole 356 of frame 350 such that the hollow interior 376 of the first end portion 372A overlaps with the annular hole 356 and the hole 336 of cushioning pad 330. The opposite second end portion 372B of connector 370 is then coupled to a conduit, allowing the user's face (including the user's mouth and / or nose) to be in fluid communication with the conduit through cushioning pad 330, frame 350, and connector 370.

[0109] The first end portion 372A of the connector 370 is generally annular and fits into the annular hole 356 of the frame 350. The frame 350 also includes an annular protrusion 358 extending from the second surface 354B of the frame 350 and forming around the annular hole 356. When the first end portion 372A is inserted into the annular hole 356 of the frame 350, the inner surface of the annular protrusion 358 overlaps with the outer surface of the first end portion 372A of the connector 370.

[0110] In some implementations, a frictional engagement between the annular protrusion 358 and the first end portion 372A secures the connector 370 to the frame 350. In other implementations, the connector 370 may include fasteners configured to secure the connector 370 to the frame 350 (e.g., via a threaded connection). In one example, the annular protrusion 358 has an outwardly extending peripheral flange, and the fastener is one or more deflectable latches formed on the first end portion 372A of the connector 370. When the first end portion 372A slides into the annular protrusion 358, the deflectable latch slides on the peripheral flange such that the deflectable latch is locked outside the annular protrusion 358. As the deflectable latch passes the peripheral flange, the peripheral flange pushes the deflectable latch away from the annular protrusion 358. The deflectable latch then returns to its initial position such that the connector 370 cannot be removed from the frame 350 without manually deflecting the deflectable latch away from the annular protrusion 358.

[0111] The frame 350 includes a T-shaped extension band 360 extending upward from the upper end 351A of the body 352. In some implementations, the extension band 360 is integrally formed with the body 352. In other implementations, the extension band 360 is a separate component attached to the body 352. When a user wears the user interface 300, the extension band 360 typically extends upward to the user's forehead. In some implementations, the extension band 360 includes a cooling portion or mechanism that contacts and cools the user's forehead, which can help a user with insomnia fall asleep.

[0112] Lower straps 316A and 316B extend from the rear portion 312 of the strap assembly 310 toward the frame 350 and are coupled to the opposite side of the lower end 351B of the body 352. Upper straps 314A and 314B extend from the rear portion 312 of the strap assembly 310 toward the frame 350 and are coupled to the opposite side of the upper end 361 of the extension strap 360 (e.g., a generally horizontal "cross" of a T). The frame 350 may include various strap attachment points for coupling with the upper straps 314A and 314B and the lower straps 316A and 316B.

[0113] One type of belt attachment point is shown in the extension belt 360. The upper end 361 of the extension belt 360 includes two holes 362A and 362B. These holes may be integrally formed in the extension belt 360 itself, or they may be formed as part of a separate component or part attached to the extension belt 360. The holes 362A and 362B are shaped to allow the ends 315A and 315B of the upper belts 314A and 314B to be inserted through the holes 362A and 362B. The ends 315A and 315B are then looped back and secured to the remainder of the upper belts 314A and 314B by any suitable mechanism such as hook and loop fasteners, adhesives, etc. The upper belts 314A and 314B are thus secured to the extension belt 360 of the frame 350.

[0114] The frame 350 and various types of strap attachment points for attaching lower straps 316A, 316B to the frame 350 are shown together. The frame 350 includes two lateral straps 364A, 364B extending from opposite ends of the lower end 351B of the body 352. A first end of each lateral strap 364A, 364B is attached to the body 352, and corresponding magnets 366A, 366B are disposed at the second end of each lateral strap 364A, 364B. Magnet 318A is attached to end 317A of the lower strap 316A, and magnet 318B is attached to end 317B of the lower strap 316B. Magnet 318A can be secured to magnet 366A by magnetic attraction, and magnet 318B can be secured to magnet 366B by magnetic attraction, thereby attaching the lower straps 316A, 316B to the body 352 of the frame 350.

[0115] In some implementations, frame 350 does not include extension band 360, and upper bands 314A and 314B are instead attached to the frame above lateral bands 364A and 364B. In these implementations, upper bands 314A and 314B extend past the temporal region of user 210 and around to the back of user 210's head. Frame 350 may include upper lateral bands to which upper bands 314A and 314B are attached.

[0116] The user interface 300 may also include one or more sensors 390. Although Figure 3B Typically, only a single sensor is shown, but any number of sensors can be coupled to the band assembly 310. In some implementations, one or more sensors 390 are coupled to the band assembly 310 and configured to adjoin a target area of ​​the user when the user interface 300 is worn. The target area could be the user's forehead, temples, throat, neck, ears, etc. In other implementations, one or more sensors 390 are not coupled to the band assembly 310, but are located elsewhere within the user interface 300, such as within the connector 370. Sensors 390 can be any of the types described herein. Figure 1 Any one or more of the sensors 130 may be included, and other types of sensors may be additionally or alternatively included.

[0117] In some implementations, one or more sensors 390 include one or more contact sensors that contact a target area of ​​the user. For example, one or more sensors 390 may include an electroencephalogram (EEG) sensor, an electrocardiogram (ECG) sensor, an electromyogram (EMG) sensor, an electrooculogram (EOG) sensor, an acoustic sensor, a peripheral oxygen saturation (SpO2) sensor, a skin conductance response (GSR) sensor, or any combination thereof.

[0118] In some implementations, the one or more sensors 390 additionally or alternatively include one or more non-contact sensors, which may include a carbon dioxide (CO2) sensor (to measure CO2 concentration), an oxygen (O2) sensor (to measure O2 concentration), a pressure sensor, a temperature sensor, a motion sensor, a microphone, an acoustic sensor, a flow sensor, a tension sensor, or any combination thereof.

[0119] In a further implementation, one or more sensors 390 include one or more contact sensors configured to contact a target area of ​​the user, and one or more non-contact sensors. In some of these implementations, the non-contact sensors are not coupled to the tape assembly 310, but are instead disposed in the cushioning pad 330, frame 350, or connector 370. Furthermore, the user interface 300 may include multiple non-contact sensors disposed in any combination of these locations.

[0120] Typically, one or more sensors 390 of the user interface 300 need to be electrically connected to the control system and memory devices of the respiratory therapy system (such as the control system 110 and memory device 114 of system 100) in order to transmit data to the control system and memory devices. This data can be used to modify the operation of the ventilator device and may also be used for other purposes. To transmit data from one or more sensors 390 to the control system and memory devices, one or more sensors 390 may be electrically connected to various parts of the user interface 300, including the frame 350 and connector 370. The electrical connection between one or more sensors 390, the frame 350, and the connector 370 can be used to transmit data from one or more sensors 390. Therefore, regardless of where the one or more sensors 390 are located within the user interface 300, the one or more sensors 390 need to be able to be electrically connected to the control system and memory devices.

[0121] As used in this article, sleep periods can be defined in several ways based on, for example, initial start and end times. (Reference) Figure 4 The diagram illustrates an exemplary timeline 400 for a sleep period. Timeline 400 includes bedtime (t... 入床 ), sleep onset time (t) GTS ), initial sleep time (t) 睡眠 ), First micro-awakening MA1, Second micro-awakening MA2, Awakening time (t) 觉醒 ), and wake-up time (t 起床 ).

[0122] In some implementations, a sleep period is the duration a user is asleep. In such implementations, a sleep period has a start time and an end time, and the user does not wake up until the end time during the sleep period. That is, any period of the user's wakefulness is not included in a sleep period. According to this first definition of a sleep period, if a user wakes up and falls asleep multiple times in the same night, each sleep interval separated by wakefulness intervals is a sleep period.

[0123] Alternatively, in some implementations, a sleep period has a start time and an end time, and during the sleep period, the user can wake up as long as the continuous duration of wakefulness is less than a wakefulness duration threshold, without the sleep period ending. The wakefulness duration threshold can be defined as a percentage of the sleep period. The wakefulness duration threshold can be, for example, approximately 20% of the sleep period, approximately 15% of the sleep period duration, approximately 10% of the sleep period duration, approximately 5% of the sleep period duration, approximately 2% of the sleep period duration, etc., or any other threshold percentage. In some implementations, the wakefulness duration threshold is defined as a fixed amount of time, such as approximately one hour, approximately thirty minutes, approximately fifteen minutes, approximately ten minutes, approximately five minutes, approximately two minutes, etc., or any other amount of time.

[0124] In some implementations, a sleep period is defined as the entire time between the time a user first goes to bed at night and the time the user last gets up the following morning. In other words, a sleep period can be defined as a time period that begins on the first date (e.g., Monday, January 6, 2020) when the user first goes to bed intending to fall asleep (e.g., assuming the user doesn't intend to watch TV or use their smartphone before falling asleep), which can be called the first time of the current night (e.g., 10:00 PM), and ends on the second date (e.g., Tuesday, January 7, 2020) when the user first gets out of bed the following morning and does not fall asleep again, which can be called the second time of the following morning (e.g., 7:00 AM).

[0125] In some implementations, users can manually define the start and / or end of a sleep period. For example, a user can select (e.g., by clicking or tapping) on ​​the user device 170 ( Figure 1 The user-selectable elements displayed on the display device 172 allow for manual initiation or termination of sleep periods.

[0126] Bedtime t 入床 The user initially goes to bed before falling asleep (e.g., when the user lies down or sits on the bed). Figure 2 The time of bed admission (230) is associated with the bed's time. Bed admission time t can be identified based on the bed threshold duration. 入床This distinguishes between when a user goes to bed for sleep and when a user goes to bed for other reasons (e.g., watching television). For example, the bed threshold duration could be at least approximately 10 minutes, at least approximately 20 minutes, at least approximately 30 minutes, at least approximately 45 minutes, at least approximately 1 hour, at least approximately 2 hours, etc. While this document refers to bed as the time to enter the bed (t), the threshold duration is used to describe the time to enter the bed. 入床 But more generally, bedtime t 入床 This can refer to the time when a user initially enters any location intended for sleeping (e.g., sofa, chair, sleeping bag, etc.).

[0127] Sleep onset time (GTS) and the time it takes for a user to initially attempt to fall asleep after going to bed (t) 入床 This is related to the initial sleep time (t). For example, after going to bed, a user can engage in one or more activities to relax before attempting to sleep (e.g., reading, watching TV, listening to music, using user device 170, etc.). 睡眠 ) is the time when a user initially falls asleep. For example, initial sleep time (t) 睡眠 This could be the time when the user initially enters the first non-REM sleep stage.

[0128] Awakening Time t 觉醒 This is the time associated with when a user wakes up but does not fall back asleep (e.g., the opposite of a user waking up in the middle of the night and falling back asleep). After initially falling asleep, a user may experience one or more unconscious micro-awakenings (e.g., micro-awakenings MA1 and MA2) of short duration (e.g., 4 seconds, 10 seconds, 30 seconds, 1 minute, etc.). This is related to the wakefulness time t. 觉醒 Conversely, the user falls asleep again after each of the micro-awakenings MA1 and MA2. Similarly, the user may experience one or more conscious awakenings after initially falling asleep (e.g., awakening A), such as getting up to go to the bathroom, caring for a child or pet, sleepwalking, etc. However, the user falls asleep again after awakening A. Therefore, the awakening time t 觉醒 It can be defined, for example, based on the duration of arousal threshold (e.g., the user is aroused for at least 15 minutes, at least 20 minutes, at least 30 minutes, at least 1 hour, etc.).

[0129] Similarly, wake-up time t 起床 This is associated with the time a user gets out of bed and intends to end their sleep period (as opposed to when a user gets up at night to go to the bathroom, care for a child or pet, or sleepwalks). In other words, wake-up time t 起床 This is the time a user last leaves bed and does not return until the next sleep period (e.g., the following night). Therefore, wake-up time t 起床This can be defined, for example, based on the duration of the wake-up threshold (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 bedtime t for the second subsequent sleep period... 入床 It can also be defined based on the duration of wake-up thresholds (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.).

[0130] As mentioned above, in the initial t 入床 And the last t 起床 During the night, a user may wake up and get out of bed more than once. In some implementations, the final wake-up time t is identified or determined based on a predetermined threshold duration following the event (e.g., falling asleep or getting out of bed). 觉醒 and / or final wake-up time t 起床 The duration of this threshold can be customized for the user. For a standard user who goes to bed at night and then wakes up and gets out of bed in the morning, any time period between approximately 12 and approximately 18 hours can be used (when the user wakes up (t...)). 觉醒 ) or get up (t 起床 ) and users going to bed (t 入床 ), sleep (t) GTS ) or fall asleep (t 睡眠 For users who spend longer periods of time in bed, shorter threshold periods can be used (e.g., between approximately 8 hours and approximately 14 hours). The threshold period can be initially selected and / or later adjusted based on the system's monitoring of the user's sleep behavior.

[0131] Total time in bed (TIB) is the time from bed entry to bed. 入床 and wake-up time t 起床 The duration between the initial sleep time and wake time. Total sleep time (TST) is the duration between the initial sleep time and wake time, excluding any conscious or unconscious awakenings and / or micro-awakenings in between. Typically, total sleep time (TST) will be shorter than total time in bed (TIB) (e.g., one minute shorter, ten minutes shorter, one hour shorter, etc.). For example, refer to... Figure 4 Timeline 401, Total Sleep Time (TST) at initial sleep time t 睡眠 and awakening time t 觉醒 The duration spans between these periods, but does not include the durations of the first micro-awake (MA1), the second micro-awake (MA2), and awakening A. As shown in the figure, in this example, the total sleep time (TST) is shorter than the total time in bed (TIB).

[0132] In some implementations, Total Sleep Time (TST) can be defined as Continuous Total Sleep Time (PTST). In such implementations, PTST excludes a predetermined initial portion or period of the first non-REM stage (e.g., a light sleep stage). For example, the predetermined initial portion could be between approximately 30 seconds and approximately 20 minutes, between approximately 1 minute and approximately 10 minutes, between approximately 3 minutes and approximately 5 minutes, etc. PTST is a measure of continuous sleep and smooths the sleep-wake sleep graph. For example, when a user initially falls asleep, the user may be in the first non-REM stage for a very short time (e.g., approximately 30 seconds), then return to the non-REM stage for a very short time (e.g., one minute), and then return to the first non-REM stage. In this instance, PTST excludes the first instance of the first non-REM stage (e.g., approximately 30 seconds).

[0133] In some implementations, the sleep period is defined as the time from bedtime (t... 入床 Start at wake-up time (t) 起床 The sleep period ends at the beginning of the sleep cycle, meaning the sleep period is defined as the total time spent in bed (TIB). In some implementations, the sleep period is defined as the time from the beginning of the sleep cycle (t...). 睡眠 ) begins and at the awakening time (t) 觉醒 End. In some implementations, the sleep period is defined as the total sleep time (TST). In some implementations, the sleep period is defined as the time from the onset of sleep (t). GTS ) begins and at the awakening time (t) 觉醒 The sleep period ends at the time of sleep onset (t). In some implementations, the sleep period is defined as the time from the time of sleep onset (t) to the time of sleep onset (t). GTS ) start and at wake-up time (t 起床 The sleep period ends at bedtime. In some implementations, the sleep period is defined as the time from bedtime (t...). 入床 ) begins and at the awakening time (t) 觉醒 The sleep period ends at the initial sleep time (t). In some implementations, the sleep period is defined as the time from the start of sleep (t). 睡眠 Start at wake-up time (t) 起床 )Finish.

[0134] refer to Figure 5 The diagram illustrates the timeline 401 based on various implementation methods. Figure 4 An exemplary sleep graph 500 is shown. As illustrated, the sleep graph 500 includes a sleep-wake signal 501, a sleeplessness stage axis 510, a REM stage axis 520, a light sleep stage axis 530, and a deep sleep stage axis 540. The intersection of the sleep-wake signal 501 with one of axes 510 to 540 indicates the sleep stage at a given time during a sleep period.

[0135] The sleep-wake signal 501 may be based on physiological data associated with the user (e.g., from the sensor 130 described herein). Figure 1 One or more of the sleep-wake signals are generated. Sleep-wake signals can indicate one or more sleep states or stages, including sleeplessness, relaxed sleeplessness, micro-awakeness, REM sleep, first non-REM sleep, second non-REM sleep, third non-REM sleep, or any combination thereof. In some implementations, one or more of the first non-REM sleep, second non-REM sleep, and third non-REM sleep stages can be grouped together and categorized as light sleep stages or deep sleep stages. For example, light sleep stages may include the first non-REM sleep stage, while deep sleep stages may include the second and third non-REM sleep stages. Although sleep diagram 500 is in Figure 5 The diagram shows an axis 530 for the light sleep stage and an axis 540 for the deep sleep stage, but in some implementations, the sleep diagram 500 may include axes for each of the first non-REM stage, the second non-REM stage, and the third non-REM stage. In other implementations, the sleep-wake signal may also indicate respiratory signals, respiratory rate, inspiratory amplitude, expiratory amplitude, inspiratory-expiratory ratio, number of events per hour, event pattern, or any combination thereof. Information describing the sleep-wake signal may be stored in memory device 114.

[0136] Sleep graph 500 can be used to determine one or more sleep-related parameters, such as sleep start wait time (SOL), wake-up start after sleep (WASO), sleep efficiency (SE), sleep fragmentation index, sleep blocks, or any combination thereof.

[0137] Sleep onset wait time (SOL) is defined as sleep onset time (t). GTS ) and initial sleep time (t 睡眠The sleep onset wait time (SOT) is the time between the initial attempt to fall asleep and the actual time it takes for the user to fall asleep. In some implementations, the SOT is defined as a sustained sleep onset wait time (PSOL). The difference between PSOL and POL is that PSOL is defined as the duration between the time the user falls asleep and the predetermined amount of sustained sleep. In some implementations, the predetermined amount of sustained sleep may include, for example, at least 10 minutes of sleep within the second non-REM phase, the third non-REM phase, and / or a REM phase lasting no more than 2 minutes, the first non-REM phase, and / or the movement between them. In other words, the sustained sleep onset wait time requires up to, for example, 8 minutes of sustained sleep within the second non-REM phase, the third non-REM phase, and / or the REM phase. In other implementations, the predetermined amount of sustained sleep may include at least 10 minutes of sleep within the first non-REM phase, the second non-REM phase, the third non-REM phase, and / or the REM phase after the initial sleep time. In this type of implementation, the predetermined amount of continuous sleep may not include any micro-awakening (e.g., a ten-second micro-awakening will not restart a 10-minute period).

[0138] Post-sleep wake-onset (WASO) is associated with the total duration of wakefulness between the user's initial sleep time and wake time. Therefore, WASO includes brief and micro-awakenings during the sleep period (e.g., Figure 4 The micro-awakenings MA1 and MA2 shown are either conscious or unconscious. In some implementations, a post-awakening start (WASO) is defined as a continuous post-awakening start (PWASO) that includes only the total duration of awakenings with a predetermined length (e.g., greater than 10 seconds, greater than 30 seconds, greater than 60 seconds, greater than about 5 minutes, greater than about 10 minutes, etc.).

[0139] Sleep efficiency (SE) is defined as the ratio of total time in bed (TIB) to total sleep time (TST). For example, if the total time in bed is 8 hours and the total sleep time is 7.5 hours, then the sleep efficiency for that sleep period is 93.75%. Sleep efficiency indicates a user's sleep hygiene. For example, if a user goes to bed before sleep and spends time engaging in other activities (e.g., watching television), sleep efficiency will decrease (e.g., the user is punished). In some implementations, 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 implementations, the total time the user attempts to sleep is defined as the duration between the time to fall asleep (GTS) and the wake-up time as described herein. For example, if the total sleep time is 8 hours (e.g., between 11 p.m. and 7 a.m.), the time to fall asleep is 10:45 p.m., and the wake-up time is 7:15 a.m., then in such an implementation, the sleep efficiency parameter is calculated to be approximately 94%.

[0140] The fragmentation index is determined at least in part based on the number of awakenings during sleep periods. For example, if a user has two micro-awakes (e.g., Figure 5 If we consider the micro-awakenings MA1 and MA2 shown, then the fragmentation index can be represented as 2. In some implementations, the fragmentation index is scaled within a predetermined range of integers (e.g., between 0 and 10).

[0141] Sleep blocks are associated with the transition between any sleep stage (e.g., the first non-REM stage, the second non-REM stage, the third non-REM stage, and / or REM) and the sleepless stage. Sleep blocks can be calculated at a resolution of, for example, 30 seconds.

[0142] In some implementations, the systems and methods described herein may include generating or analyzing a sleep map that includes sleep-wake signals to determine or identify bedtime (t) based at least in part on the sleep-wake signals of the sleep map. 入床 ), sleep onset time (t) GTS ), initial sleep time (t) 睡眠 ), one or more first micro-awakenings (e.g., MA1 and MA2), awakening time (t) 觉醒 ), wake-up time (t) 起床 (or any combination thereof).

[0143] In other implementations, one or more of the sensors 130 can be used to determine or identify the bed entry time (t). 入床 ), sleep onset time (t) GTS ), initial sleep time (t) 睡眠 ), one or more first micro-awakenings (e.g., MA1 and MA2), awakening time (t) 觉醒 ), wake-up time (t)起床 (or any combination thereof), which in turn define sleep periods. For example, bedtime t can be determined based on data generated, for example, by motion sensor 138, microphone 140, camera 150, or any combination thereof. 入床 The time to fall asleep can be determined based on, for example, data from motion sensor 138 (e.g., data indicating that the user is not moving), data from camera 150 (e.g., data indicating that the user is not moving and / or that the user has turned off the lights), data from microphone 140 (e.g., data indicating that the TV is being turned off), data from user device 170 (e.g., data indicating that the user is no longer using user device 170), data from pressure sensor 132 and / or flow sensor 134 (e.g., data indicating that the user turns on the breathing therapy device 122, data indicating that the user puts on user interface 124, etc.) or any combination thereof.

[0144] refer to Figure 6 The illustration shows a method 600 for assisting a user, according to some implementations of this disclosure. One or more steps or aspects of method 600 may be implemented using any part or aspect of system 100 described herein.

[0145] Step 601 of method 600 includes receiving physiological data associated with a user. The physiological data may be generated by the sensor 130 described herein (…). Figure 1 One or more of the following are generated and received: The received physiological data may indicate one or more physiological parameters, such as exercise, heart rate, heart rate variability, cardiac waveform, respiratory rate, respiratory rate variability, respiratory depth, tidal volume, inspiratory amplitude, inspiratory duration, expiratory amplitude, expiratory duration, inspiratory-expiratory ratio, sweating, temperature (e.g., ambient temperature, body temperature, core body temperature, surface temperature, etc.), blood oxygen saturation, photoplethysmography, pulse transit time, blood pressure, peripheral arterial tension, cardiac oscillation, skin conduction response, sympathetic nervous system response, pulse transit time, trend associated with heart rate, trend associated with respiratory rate, trend associated with skin conduction response, or any combination thereof. The physiological data may be received from at least one of one or more sensors 130 via, for example, the electronic interface 119 and / or user equipment 170 described herein, and stored in memory device 114. Figure 1 Physiological data can be received directly or indirectly (e.g., using one or more media) from at least one of one or more sensors 130 via electronic interface 119 or user equipment 170. The physiological data may include speech, which may be a stress / anxiety indicator and can be received by microphone 140. Microphone 140 may be integrated into a microphone sensor (e.g., an Amazon® Halo device).

[0146] In some implementations, physiological data is generated during at least a portion of a sleep period. For example, the first portion of the physiological data for a sleep period may be associated with the first day (e.g., Monday) before or when the user begins their sleep period. If the first sleep period extends into the next day (e.g., Tuesday) before ending, the physiological data will also be associated with a portion of the second day. In this instance, the first portion of the physiological data may be associated with any portion of the sleep period (e.g., 10% sleep period, 25% sleep period, 50% sleep period, 100% sleep period, etc.).

[0147] In some implementations, the physiological data received in step 601 is generated or acquired (e.g., via one or more of the sensors 130) before the user wears or puts on the user interface 124. In other implementations, the physiological data is generated both before and after the user wears or puts on the user interface 124. In such implementations, the physiological data may be generated before the user wears the user interface 124 by a first sensor of one or more of the sensors 130 (e.g., physically coupled to or integrated into the user device 170 or activity tracker 190), and after the user wears the user interface 124 by a second sensor of one or more of the sensors 130 (e.g., physically coupled to or integrated into the respiratory therapy system 120).

[0148] Step 602 of method 600 includes determining an emotion score associated with the user, at least in part, based on physiological data. Typically, the emotion score indicates the level of anxiety or stress the user is currently experiencing. For example, when wearing the user interface 124 of the breathing therapy system 120, especially when the user is not accustomed to wearing the user interface 124, the user may experience anxiety, stress, worry, discomfort, etc. Higher levels of stress, anxiety, discomfort, etc., may make it more difficult for the user to fall asleep and / or may prompt the user to abandon the use of the breathing therapy system 120. Quantifying the user's stress or anxiety through the emotion score can be used to suggest or recommend actions or activities to reduce anxiety or stress and help the user fall asleep and adapt to using the breathing therapy system 120.

[0149] A mood score can be an absolute value or a relative value. A mood score can be a numerical value on a predetermined scale (e.g., between 1 and 10, between 1 and 100, etc.), a letter rating (e.g., A, B, C, D, or F), or a descriptor (e.g., high, low, medium, poor, normal, abnormal, average, good, excellent, average, below average, above average, needs improvement, satisfied, etc.). In some implementations, the mood score is determined relative to a previous mood score (e.g., a mood score better than a previous mood score (e.g., the previous day's mood score), a mood score worse than a previous mood score, a mood score the same as a previous mood score, etc.) or a baseline mood score (e.g., a mood score 50% greater than the baseline mood score, a mood score equal to the baseline mood score, etc.). In some implementations, the previous score can be a target mood score. Examples of target mood scores include a score indicating the user's ability to fall asleep, a score indicating the user has a short sleep initiation waiting time, etc.

[0150] In some implementations, the quantification of a user's stress or anxiety can be based on changes in a baseline mood score. The quantification can take the form of a difference (relative or absolute) from a target mood score.

[0151] In some implementations, the physiological data generated in step 601 represents the baseline emotional score before the user wears or puts on user interface 124. In some implementations, the baseline emotional score can be determined from the physiological data when the user is expected to relax (e.g., when the user is about to fall asleep, when the user has just fallen asleep, etc.). Physiological data indicating sleep stages can be used to determine different times. The baseline emotional score can be determined based on wearable electronic devices worn by the user (e.g., activity tracker 190), subjective information obtained by the user, etc. In some implementations, one or more cues may be provided to the user to determine the baseline emotional score.

[0152] In some implementations, step 602 includes determining one or more physiological parameters associated with the user, such as exercise, respiratory rate, heart rate, heart rate variability, cardiac waveform, respiratory rate, respiratory rate variability, respiratory depth, tidal volume, inspiratory amplitude, inspiratory duration, expiratory amplitude, expiratory duration, inspiratory-expiratory ratio, sweating, temperature (e.g., ambient temperature, body temperature, core body temperature, surface temperature, etc.), blood oxygen, photoplethysmography (e.g., which can be used to measure SpO2, peripheral perfusion, peripheral arterial tension, pulse rate, other cardiac-related parameters, etc.), pulse transit time, blood pressure, cardiac oscillation, skin conduction response, sympathetic nervous system response, pulse conduction time, trends associated with heart rate, trends associated with skin conduction response, trends associated with respiratory rate, or any combination thereof.

[0153] These physiological parameters can indicate a user's mood or anxiety. For example, hyperventilation, increased respiratory rate (e.g., relative to a user-associated baseline, a group of users' baseline, normative values, etc.), decreased heart rate variability (e.g., relative to a user-associated baseline, a group of users' baseline, normative values, etc.), arrhythmias, heart rate, and blood pressure (e.g., adjusting for whether the user is hypertensive or non-hypertensive, nocturnal blood pressure decreases, etc.) can indicate an increased level of anxiety. Conversely, increased heart rate variability (e.g., relative to a user-associated baseline, a group of users' baseline, normative values, etc.) can indicate a more relaxed state. A mood score can be determined at least in part by scaling or normalizing one or more of the physiological parameters stored in the aforementioned user profile, based on previously recorded physiological parameters of the user, physiological parameters of several other previously recorded users, or both. Alternatively, a mood score can be determined by scaling the associated physiological parameters with expected or target values ​​for the parameters.

[0154] Physiological parameters can be individual-specific. Physiological parameters can be monitored to determine if they are within a range. For example, a typical adult respiratory rate may be between 12 and 20 breaths per minute (bpm), and a respiratory rate greater than 25 bpm may indicate anxiety / stress. Similarly, a typical adult heart rate may be between 60 and 100 beats per minute, and a heart rate greater than 120 bpm may indicate anxiety / stress. Elevated body temperature may also indicate anxiety / stress. Furthermore, if the value of a physiological parameter changes after stimulation, such as the start of treatment or increased treatment stress, but then subsequently returns to baseline relatively quickly (e.g., within 5 to 10 minutes, or other predetermined timeframe), an increase in mood score is acceptable. An increase in mood score is acceptable because a slight increase is temporary, and therefore requires (or minimally requires) adjustment of the mood score.

[0155] In some implementations, step 602 further includes receiving subjective feedback from the user and determining an emotion score based at least in part on the received subjective feedback. Subjective feedback may include self-reported user feedback indicating the user's current stress or anxiety level in the form of descriptive indicators (e.g., high, low, medium, uncertain), numerical values ​​(e.g., on a scale of 1 to 10, where 10 is very stressful and 0 is no stress at all). The user's stress or anxiety level may be based on or correspond to a Likert scale. For example, subjective feedback may be received via user device 170. In such implementations, step 602 may include conveying one or more prompts to the user to request subjective feedback (e.g., via display device 172 of user device 170).

[0156] In some implementations, step 602 includes determining an emotion score based at least in part on demographic information associated with the user. Demographic information may include information indicating the user's age, gender, weight, body mass index (BMI), height, ethnicity, interpersonal or marital status, family history of insomnia, employment status, education level, socioeconomic status, or any combination thereof. Demographic information may also include medical information associated with the user, such as information indicating one or more medical conditions associated with the user, medication use, or both. The demographic information may be stored in memory device 114. Figure 1 The information is received and stored therein. Demographic information can be provided manually by the user, for example, via user device 170 (e.g., via a questionnaire or survey presented via display device 172). Alternatively, demographic information can be automatically collected from one or more data sources associated with the user (e.g., medical records). Demographic information can be a useful input for determining mood scores, as certain physiological parameters (e.g., heart rate) can change as a function of age, medical conditions, etc.

[0157] Step 603 of method 600 includes determining whether a first emotional score meets predetermined conditions. Typically, predetermined conditions indicate that the user's anxiety or stress is at an acceptable level (e.g., allowing the user to fall asleep, initiating use of the breathing therapy system 120, increasing the pressure of the air supplied to the user via the user interface 124, etc.). In other words, when the emotional score meets the predetermined conditions, the user is sufficiently relaxed, allowing the user to fall asleep and / or to use the breathing therapy system 120 and / or to increase the pressure of the air supplied to the user via the user interface 124. When the user begins using the breathing therapy system 100, the acceptable level can be obtained from the user during multiple sleep periods and / or during calibration periods. The acceptable level can be obtained from user groups (e.g., clusters), normative values, etc.

[0158] For example, if a higher mood score indicates higher anxiety or stress, the predetermined condition could be a value indicating that the user's anxiety or stress is at an acceptable level. In this example, the mood score meets the predetermined condition if it is equal to or less than the predetermined condition.

[0159] In some implementations, predetermined conditions are determined at least in part based on previously recorded physiological data associated with the user. In such implementations, machine learning algorithms can be used to determine the predetermined conditions. The machine learning algorithm can be trained using previously recorded physiological data associated with the user (e.g., using supervised or unsupervised training techniques) to configure the algorithm to determine the predetermined conditions. In such implementations, the previously recorded physiological data may include data related to the user's ability to fall asleep, such as sleep onset wait time, wake-up time after sleep onset, sleep efficiency, fragmentation index, bedtime, total bedtime, total sleep time, or any combination thereof. The previously recorded data used to train the machine learning algorithm may also include subjective feedback from the user, as described herein. The previously recorded data used to train the machine learning algorithm may be data from user groups or user cohorts residing in a demographic similar to the user. Data from user cohorts can be used for initial setup before learning from the user's physiological data.

[0160] In some implementations, method 600 includes communicating one or more indications of the determined mood score to the user (e.g., in the form of a report). For example, the indications of the determined mood score may be communicated to the user via user device 170. These indications may be communicated to the user before, during, or after a sleep period. Additionally or alternatively, the indications of the determined mood score may be communicated to a third party (e.g., a healthcare provider, doctor, etc.). Additionally, method 600 may also include communicating one or more indications of any of the sleep-related parameters described herein to the user. For example, indications of sleep-related parameters may be communicated to the user before, during, or after a sleep period via user device 170. Mood and / or anxiety, as measured by a mood score, can lead to insomnia (e.g., anxiety-induced insomnia). Therefore, tracking mood through scoring can help interpret a user's insomnia.

[0161] Step 604 of method 600 includes, in response to determining that the determined emotion score (step 602) does not meet predetermined conditions (step 603), causing one or more cues to be communicated to the user to help modify the emotion score. The one or more cues are typically used to help modify (e.g., improve) the determined first emotion score. The one or more cues may include one or more visual cues, one or more audio cues, one or more tactile cues, or any combination thereof. The one or more visual cues may be communicated to the user, for example, via display device 128 of the respiratory therapy system 120, via display device 172 of the user device 170, via light source 180, activity tracker 190, or any combination thereof. The one or more audio and / or tactile cues may be communicated to the user via a transducer such as speaker 142, which may be physically coupled to or integrated into, for example, the respiratory therapy device 122, user device 170, or activity tracker 190. The one or more audio and / or tactile cues may be conducted to the user via, for example, user interface 124 and / or conduit 126, and / or via bone conduction. One or more audio and / or tactile cues may be conveyed in a predetermined pattern, such as continuous, pulsed, periodic communication of varying intensities or any combination thereof.

[0162] In some implementations, step 604 includes conveying one or more visual cues to the user via light source 180 to help modify the mood score. As described herein, in some instances, light source 180 may be physically coupled to or integrated into respiratory therapy system 120. Alternatively, light source 180 may be physically separate from and distinct from respiratory therapy system 120 (e.g., physically coupled to or integrated into user device 170, activity tracker 190, etc.). In such implementations, step 604 includes causing light source 180 to emit light having a predetermined color, predetermined intensity, predetermined frequency (e.g., light pulses), or any combination thereof. One or more cues may include, for example, changing the color of the light emitted from light source 180, changing the intensity of the light emitted from light source 180, or both.

[0163] As described above, among other things, step 602 may include determining a breathing rate associated with the user. Step 604 may include causing the light source 180 to emit light pulses at a predetermined frequency to help modify (e.g., reduce) the breathing rate. For example, each light pulse may signal the user to breathe in (e.g., at the start of the pulse) and / or breathe out (e.g., at the end of the pulse) to help modify the breathing rate, and thus the mood score. In some implementations, based on the detected breathing rate of the user, the pattern of the light pulses may initially reflect the user's breathing rate and then gradually change (e.g., decrease) to encourage the user's breathing rate to change to a desired rate, and thus to a desired mood score. Alternatively, step 602 may include conveying one or more cues to the user to perform breathing exercises to help modify the breathing rate, and thus the mood score. In some implementations, the target breathing pattern may override the pressure settings of the respiratory therapy system, for example by introducing modulation on the motor RPM as the target pattern to provide gentle guided breathing without performing ventilation. In this type of implementation, the pressure can be adjusted at a low pressure (e.g., 10% of the maximum pressure setting, 25% of the maximum pressure setting, 50% of the maximum pressure setting, etc.), either before or along with the pressure ramp, which typically occurs at the start of the treatment. Once the emotional score meets the predetermined criteria and / or the user has entered sustained sleep, the pressure ramp or target pressure can continue.

[0164] As described above, in some instances, the user wears the user interface 124 when the first physiological data is generated (step 601). Therefore, in some implementations, one or more prompts communicated to the user in step 604 may include prompts or suggestions to remove the user interface 124 to help modify the mood score. For example, the user may be prompted to remove the user interface 124 for a predetermined duration (e.g., 1 minute, 5 minutes, 10 minutes, etc.). Once the interface 124 has been removed, the user may be further prompted to perform breathing exercises to further help modify the mood score.

[0165] In some implementations, one or more prompts conveyed to the user include one or more instructions to perform an activity. Instructions to perform an activity may be conveyed visually (e.g., via alphanumeric text displayed on display device 172, an image or photograph displayed on display device 172, etc.) and / or via audio (e.g., via user device 170 or speaker 142). These instructions may include, for example, how to assemble user interface 300 before wearing it. Figure 3A and Figure 3B The assembly instructions for each component of the user interface 300. These assembly instructions can include information about the function or purpose of each component and can often help modify the mood score.

[0166] In some implementations, one or more prompts conveyed to the user in step 604 may include media content that further assists in modifying the sentiment score. For example, the media content may include audio (e.g., music, e-books, etc.), video (e.g., television programs, movies), photos, etc., to help modify the sentiment score. The media content may be delivered to the user, for example, via user device 170 or another device (e.g., television, laptop, tablet, etc.).

[0167] In some implementations, step 604 includes selecting one or more cues to be conveyed to the user. For example, the selection of one or more cues may be based at least in part on previously recorded user-associated data (e.g., based on the user's previous responses to one or more cues). In such implementations, a machine learning algorithm may be trained with previously recorded physiological data and / or user-associated mood scores, recorded before and / or after the one or more cues are conveyed to the user. Therefore, selecting one or more cues may include using a trained (e.g., using supervised or unsupervised techniques) machine learning algorithm to receive current physiological data and / or user-associated mood scores as input, and determining one or more cues as output to be conveyed to the user to help modify the determined mood scores. In this way, the method may, for example, identify one or more cues that allow the user's mood score to reach predetermined conditions. In a particular implementation, the method may identify one or more cues, such as instructing deep breathing, changing the inspiratory-expiratory ratio, etc., which optimally lower heart rate, increase heart rate variability, and lead to a faster transition to light sleep N1.

[0168] As described above, step 604 is executed in response to determining in step 603 that the emotion score does not meet the predetermined conditions. After one or more prompts are communicated to the user in step 604, steps 601 to 604 may be repeated once or more to help modify the emotion score until the emotion score meets the predetermined conditions. In response to determining that the emotion score meets the predetermined conditions, method 600 continues to execute step 605.

[0169] Step 605 of method 600 includes modifying one or more settings of the respiratory therapy system in response to determining that a first emotional score meets predetermined conditions (step 603). Alternatively or additionally, modifying one or more settings of the respiratory therapy system is in response to determining the user's sleep state (e.g., awake, asleep, etc.) and / or sleep stage (e.g., N1, N2, etc.). For example, step 605 may include modifying the pressure settings of the respiratory therapy device 122 (e.g., turning the respiratory therapy device 122 on / off to deliver pressurized air, increasing the pressure, decreasing the pressure, modifying the maximum pressure setting, modifying the minimum pressure setting, modifying the ramp duration, etc.), modifying the catheter temperature, modifying the humidification of the pressurized air, modifying comfort settings such as expiratory pressure relief (EPR), or any combination thereof.

[0170] In some implementations, step 605 includes supplying pressurized air to the respiratory therapy device 122 of the respiratory therapy system 120. In such implementations, the respiratory therapy device 122 does not deliver pressurized air, or delivers pressurized air at low pressure, until a predetermined condition is met for the emotional score. In other words, in such implementations, step 605 includes activating or turning on the respiratory therapy device 122.

[0171] In some implementations, the respiratory therapy device 122 of the respiratory therapy system 120 supplies pressurized air at a first predetermined pressure before determining that a first emotion score meets a predetermined condition (step 603). In such implementations, step 605 may include supplying pressurized air at a second predetermined pressure different from the first predetermined pressure by the respiratory therapy device 122 of the respiratory therapy system 120. In some implementations, the second predetermined pressure is greater than the first predetermined pressure. For example, if the determined first emotion score is below a predetermined threshold (e.g., indicating that the user is relaxed), the second predetermined pressure may be greater than the first predetermined pressure. In this example, the first predetermined pressure may be gradually increased until the second predetermined pressure is reached. In other implementations, the second predetermined pressure is less than the first predetermined pressure. For example, if the determined first emotion exceeds a predetermined threshold (e.g., the user feels anxious while wearing interface 124 and receiving pressurized air), the first predetermined pressure may be reduced to the second predetermined pressure to further help modify the emotion score.

[0172] In some implementations, step 605 includes modifying one or more settings of one or more devices external to the respiratory therapy system 120. For example, step 605 may include modifying one or more settings of user device 170 (e.g., content displayed on display device 172) and / or one or more settings of activity tracker 190. As another example, step 605 may include modifying one or more settings of one or more Internet of Things (IoT) devices, such as smart devices (e.g., televisions), smart thermostats or HVAC systems, smart lighting, etc. The user's response to the modified settings (e.g., a change in mood score) can be used to determine one or more cues to be communicated to the user to help modify the mood score in the future.

[0173] In some implementations, method 600 includes determining treatment recommendations for the user based at least in part on a first emotion score. In such implementations, method 600 may include communicating instructions for the recommendations to the user, a third party (e.g., a healthcare provider), or both. Treatment recommendations may include, for example, suggestions to modify the user interface type used for the respiratory therapy system (e.g., a full-face mask, nasal pillow mask, nasal cannula, etc.). Treatment recommendations may also include medication recommendations, suggestions to discontinue the use of the respiratory therapy system, suggestions to use alternative medical devices (e.g., jaw repositioning devices, neurostimulation devices, etc.), or any combination thereof.

[0174] As described above, steps 601 to 604 can be repeated once or multiple times until the mood score meets predetermined conditions. Furthermore, after modifying one or more settings of the respiratory therapy system in step 605, steps 601 to 604 can be repeated once or multiple times. For example, if a user falls asleep using user interface 124 but wakes up in the middle of a sleep period, the mood score is updated based on physiological data. If the mood score does not meet a predetermined threshold, one or more settings of the respiratory therapy system can be further modified (e.g., turning off, reducing stress, prompting the user to remove user interface 124, etc.). One advantage of some implementations of this disclosure is that if a user does not adhere to their treatment prescription, the doctor / medical device vendor can better understand the reasons for non-compliance. For example, the doctor / medical device vendor can determine that the user is not comfortable using the respiratory therapy device 122 and is stressed, rather than, for example, lazy or forgetful.

[0175] While the above refers to a sleep period, one or more steps of method 600 may be repeated once or multiple times for additional sleep periods (e.g., 2 sleep periods, 3 sleep periods, 10 sleep periods, 100 sleep periods, 500 sleep periods, etc.). If, for example, the breathing therapy device 122 is operating at a suboptimal treatment setting / low pressure setting, and it is detected that the user does not experience anxiety during several treatment periods, the treatment may be adjusted to a setting closer to the optimal (e.g., prescribed) treatment setting. Furthermore, although steps 601 to 605 are shown and described herein in a specific order, more generally, steps 601 to 605 may be performed in any suitable order and / or simultaneously.

[0176] One or more elements, aspects or steps or any part thereof from any one of claims 1 to 62 below may be combined with one or more elements, aspects or steps or any part thereof from any one of the other claims 1 to 62, or a combination thereof, to form one or more additional implementations and / or claims of this disclosure.

[0177] While this disclosure has been described with reference to one or more specific embodiments or implementations, those skilled in the art will recognize that many modifications can be made thereto without departing from the spirit and scope of this disclosure. Each of these implementations, and its obvious variations, is contemplated to be within the spirit and scope of this disclosure. It is also contemplated that additional implementations according to various aspects of this disclosure may combine any number of features from any of the implementations described herein.

Claims

1. A system for assisting a user of a respiratory therapy system, comprising: An electronic interface configured to receive first physiological data associated with the user; Memory, the memory storing machine-readable instructions; as well as The control system includes one or more processors configured to execute the machine-readable instructions to: A first emotion score associated with the user is determined at least in part based on the first physiological data. The first emotion score is determined relative to a previous emotion score that satisfies predetermined conditions that enable the user to fall asleep. The predetermined conditions are determined at least in part based on previously received physiological data associated with the user, including data related to the user's ability to fall asleep. Determine whether the first emotion score meets the predetermined conditions; In response to determining that the first emotion score does not meet the predetermined condition, one or more prompts are communicated to the user until the first emotion score meets the predetermined condition; as well as In response to determining that the first emotion score meets the predetermined conditions, a modification is made to one or more settings of the respiratory therapy system.

2. The system of claim 1, wherein the one or more cues include visual cues, the visual cues comprising light emitted from a light source having color, intensity, and emission pattern.

3. The system of claim 2, wherein the visual cue comprises modifying the color of the light, modifying the intensity of the light, modifying the emission mode of the light, or any combination thereof.

4. The system of claim 2, wherein the one or more prompts include breathing exercises to help modify the user's breathing rate.

5. The system of claim 4, wherein determining the first emotion score associated with the user includes determining the breathing rate associated with the user based at least in part on the first physiological data.

6. The system of claim 5, wherein one or more light pulses are emitted from the light source at a predetermined frequency to help modify the breathing rate associated with the user.

7. The system according to any one of claims 2 to 6, wherein the light source is physically coupled to or integrated into the user equipment.

8. The system according to claim 7, wherein the light source is a display device of the user equipment.

9. The system according to any one of claims 2 to 6, wherein the light source is physically coupled to or integrated into a part of the respiratory therapy system.

10. The system of claim 9, wherein the portion of the respiratory therapy system is a user interface, a catheter, or a respiratory therapy device.

11. The system according to any one of claims 1 to 6, wherein determining the first emotion score associated with the user comprises determining: movement, respiratory rate, respiratory rate variability, respiratory depth, tidal volume, inspiratory amplitude, inspiratory duration, expiratory amplitude, expiratory duration, inspiratory-expiratory ratio, heart rate, heart rate variability, cardiac waveform, sweating, blood oxygen, blood pressure, peripheral arterial tension, cardiogenic oscillation, skin conductance, sympathetic nervous system response, skin temperature, ambient temperature, photoplethysmography, pulse conduction time, core body temperature, trend associated with the respiratory rate, trend associated with the heart rate, trend associated with the skin conductance, or any combination thereof.

12. The system according to any one of claims 1 to 6, wherein the modification of one or more settings of the respiratory therapy system causes the respiratory therapy device of the respiratory therapy system to supply pressurized air at a predetermined pressure.

13. The system according to any one of claims 1 to 6, wherein the first physiological data is received when the user is wearing the user interface of the respiratory therapy system.

14. The system of claim 13, wherein the respiratory therapy system supplies pressurized air at a first predetermined pressure before determining that the first emotion score satisfies the predetermined condition.

15. The system of claim 14, wherein the modification of one or more settings of the respiratory therapy system causes the respiratory therapy system to supply pressurized air at a second predetermined pressure different from the first predetermined pressure.

16. The system of claim 15, wherein the second predetermined pressure is greater than the first predetermined pressure.

17. The system according to any one of claims 1 to 6, wherein determining that the first emotion score satisfies the predetermined condition includes determining that the first emotion score is less than a predetermined threshold.

18. The system according to any one of claims 1 to 6, wherein the first physiological data is generated by one or more sensors.

19. The system of claim 18, wherein at least one of the one or more sensors is physically coupled to or integrated into the respiratory therapy system.

20. The system of claim 18, wherein at least one of the one or more sensors is physically coupled to or integrated into the user device or activity tracker, the user device or activity tracker being separate from and distinct from the respiratory therapy system.

21. The system according to any one of claims 1 to 6, wherein the respiratory therapy system is a continuous positive airway pressure system.

22. The system according to any one of claims 1 to 6, wherein at least a portion of the first physiological data is associated with at least a portion of the user's first sleep period.

23. The system according to any one of claims 1 to 6, wherein the one or more processors are configured to execute the machine-readable instructions to: After implementing determined modifications to one or more settings of the respiratory therapy system, second physiological data associated with the user is received, the second physiological data being associated with the user's first sleep period; and A second emotion score associated with the user is determined at least in part based on the second physiological data, the second emotion score being determined relative to the previous emotion score.

24. The system of claim 23, wherein the one or more processors are configured to execute the machine-readable instructions to communicate an indication of the first mood score, the second mood score, or both to the user, a third party, or both during or after the first sleep period.

25. The system of claim 23, wherein the one or more processors are configured to execute the machine-readable instructions to further modify the one or more settings of the respiratory therapy system in response to determining that the second emotion score does not meet the predetermined conditions.

26. The system of claim 23, wherein the one or more processors are configured to execute the machine-readable instructions to modify one or more settings of one or more Internet of Things devices, at least in part, based on the determined second emotion score.

27. The system of any one of claims 1 to 6, wherein the one or more processors are configured to execute the machine-readable instructions to determine treatment recommendations for the user based at least in part on the first emotion score, and to communicate the instructions of the recommendations to the user, a third party, or both.

28. The system of claim 27, wherein the treatment recommendations include recommendations to modify the type of user interface used for the respiratory therapy system.

29. The system of claim 28, wherein the type of user interface for the respiratory therapy system is a full-face mask, a nasal pillow mask, or a nasal mask.

30. The system of claim 27, wherein the treatment recommendation includes a medication recommendation.

31. The system of claim 27, wherein the treatment recommendation includes a recommendation to discontinue the use of the respiratory therapy system.

32. The system of claim 31, wherein the treatment recommendation includes a recommendation to use an alternative medical device.

33. The system of claim 32, wherein the alternative medical device comprises a mandibular repositioning device, a nerve stimulation device, or both.

34. The system according to any one of claims 1 to 6, wherein the first physiological data is generated during at least a portion of the first sleep period, and during at least a portion of the first sleep period, the user uses the respiratory therapy system with one or more modified settings.

35. The system of claim 34, wherein the one or more processors are configured to execute the machine-readable instructions to: Second physiological data associated with the user is received during at least a portion of a second sleep period following the first sleep period; A second emotion score associated with the user is determined at least in part based on the second physiological data; as well as One or more prompts are communicated to the user to help modify the determined second emotion score, which is determined relative to the previous emotion score.

36. The system of claim 35, wherein one or more prompts for assisting in modifying the determined second emotion score are different from one or more prompts for assisting in modifying the determined first emotion score.

37. The system of claim 36, wherein the one or more processors are configured to execute the machine-readable instructions to determine, at least in part, modifications to one or more settings of the respiratory therapy system for the second sleep period based on the first mood score, the second mood score, or both.

38. The system of claim 36, wherein the one or more processors are configured to execute the machine-readable instructions to: One or more first sleep-related parameters associated with the first sleep period are determined, at least in part, based on the first physiological data; One or more second sleep-related parameters associated with the second sleep period are determined, at least in part, based on the second physiological data; as well as The indication of at least one of the one or more first sleep-related parameters, at least one of the one or more second sleep-related parameters, or both, is communicated to the user, a third party, or both after the second sleep period.

39. The system according to any one of claims 1 to 6, wherein the respiratory therapy system includes a user interface configured to engage a portion of the user, the user interface including an airway.

40. The system of claim 39, wherein the determined modification of the one or more settings of the respiratory therapy system includes modifying the position of the ventilator.

41. The system of claim 40, wherein modifying the position of the vent includes moving the vent from an open position toward a closed position.

42. The system according to any one of claims 1 to 6, wherein the one or more prompts include one or more prompts for assembling the user interface of the respiratory therapy system.

43. The system according to any one of claims 1 to 6, wherein the one or more processors are configured to execute the machine-readable instructions to convey one or more instructions to the user.

44. The system according to claim 1, further comprising the respiratory therapy system.

45. The system of claim 44, wherein the respiratory therapy system comprises a respiratory therapy device, a catheter, a user interface, or any combination thereof.

46. ​​The system of claim 45 further includes one or more sensors configured to generate the first physiological data.

47. The system of claim 46, wherein a first sensor of the one or more sensors is physically coupled to or integrated into the respiratory therapy system, the first sensor being configured to generate first physiological data associated with the user when the user wears the user interface.

48. The system of claim 47, wherein the second sensor of the one or more sensors is configured to generate first physiological data associated with the user when the user is not wearing the user interface.

49. The system of claim 45, wherein the control system is configured to supply air to the respiratory therapy device at a first predetermined pressure before modifying the one or more settings of the respiratory therapy system, and to supply air to the respiratory therapy device at a second predetermined pressure after modifying the one or more settings of the respiratory therapy system.

50. The system of claim 49, wherein the second predetermined pressure is greater than the first predetermined pressure.

51. The system according to any one of claims 1, 44 to 50, wherein the respiratory therapy system is a continuous positive airway pressure system or a high-flow therapy system.

52. A computer program product comprising instructions, said instructions, when executed by a computer, causing the computer to: An emotional score associated with a user of a respiratory therapy system is determined at least in part based on physiological data, which is determined relative to a previous emotional score that enables the user to fall asleep when predetermined conditions are met. These predetermined conditions are determined at least in part based on previously received physiological data associated with the user, including data related to the user's ability to fall asleep. Determine whether the emotion score meets the predetermined conditions; In response to determining that the emotion score does not meet the predetermined condition, one or more prompts are communicated to the user until the emotion score meets the predetermined condition; as well as In response to determining that the emotion score meets the predetermined conditions, a modification is made to one or more settings of the respiratory therapy system.

53. The computer program product of claim 52, wherein the computer program product is a non-transitory computer-readable medium.

Images