Systems and methods for assisting users of respiratory treatment systems

Abstract

The method includes receiving first physiological data associated with a user. The method includes determining a first emotional score associated with the user based at least in part on the first physiological data. The method also includes altering one or more settings of a respiratory treatment system in response to determining that the first emotional score satisfies a predetermined condition.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 080,401, filed September 18, 2020, which is incorporated herein by reference in its entirety.

[0002] The present disclosure relates generally to systems and methods for assisting a user in using a respiratory treatment system, and more particularly to systems and methods for determining an affective score associated with a user and communicating one or more prompts to the user to assist in modifying the affective score. [Background technology]

[0003] Many people suffer from sleep-related and / or respiratory disorders, such as sleep-disordered breathing (SDB) disorders (e.g., periodic limb movement disorder (PLMD), restless legs syndrome (RLS), obstructive sleep apnea (OSA), Cheyne-Stokes respiration (CSR), respiratory failure, obesity hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disorders (NMD), chest wall disorders, and insomnia. While many of these disorders can be treated using respiratory treatment systems, others may be treated using alternative technologies. However, users may experience anxiety or stress when using a respiratory treatment system, for example, due to unfamiliarity (e.g., first-time users) or discomfort. This anxiety or stress can prevent users from falling asleep or cause users to abandon using a respiratory treatment system. The present disclosure aims to solve these problems and others. Summary of the Invention [Means for solving the problem]

[0004] According to some implementations of the present disclosure, a method includes receiving first physiological data associated with a user. The method includes determining a first emotional score associated with the user based at least in part on the first physiological data. The method also includes altering one or more settings of a respiratory treatment system in response to determining that the first emotional score satisfies a predetermined condition.

[0005] In some implementations of the present disclosure, a 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 affect score associated with the user based at least in part on the physiological data. The control system is further configured to change one or more settings of the respiratory treatment system in response to determining that the affect score satisfies a predetermined condition.

[0006] The above summary is not intended to describe each implementation or every aspect of the present disclosure. Additional features and benefits of the present disclosure will be apparent from the following detailed description and drawings. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a functional block diagram of a system according to some implementations of the present disclosure. [Figure 2] 2 is a perspective view of at least a portion of the system of FIG. 1, a user, and a bed partner, according to some implementations of the present disclosure. [Figure 3A] FIG. 2 is a perspective view of a user interface of the respiratory treatment system of FIG. 1 according to some implementations of the present disclosure. [Figure 3B] FIG. 3B is a perspective exploded view of the user interface of FIG. 3A according to some implementations of the present disclosure. [Figure 4] 1 illustrates an example timeline of a sleep session, according to some implementations of the present disclosure. [Figure 5] 5 illustrates an example hypnogram associated with the sleep session of FIG. 4, according to some implementations of the present disclosure. [Figure 6] 1 is a process flow diagram of a method for assisting a user according to some implementations of the present disclosure. While the present disclosure is susceptible to various modifications and alternative forms, specific implementations and embodiments of the present disclosure have been shown by way of example in the drawings and are described in detail herein. It is to be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but rather, the present disclosure is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims. DETAILED DESCRIPTION OF THE INVENTION

[0008] Many people suffer from sleep-related and / or breathing disorders, including, for example, sleep-disordered breathing (SDB) such as periodic limb movement disorder (PLMD), restless legs syndrome (RLS), obstructive sleep apnea (OSA), central sleep apnea (CSA), other types of apnea such as mixed apneas and hypopneas, respiratory effort-related arousals (RERA), Cheyne-Stokes respiration (CSR), respiratory failure, obesity hypoventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular diseases (NMD), rapid eye movement (REM) behavior disorder (also known as RBD), dream actout (DEB), hypertension, diabetes, stroke, insomnia, and chest wall disorders.

[0009] Obstructive sleep apnea (OSA) is a form of sleep-disordered breathing (SDB) characterized by events such as upper airway obstruction or obstruction during sleep due to an abnormally small upper airway combined with the normal loss of muscle tone in the tongue, soft palate, and posterior oropharynx. More generally, apnea generally refers to pauses in breathing (obstructive sleep apnea) or cessation of respiratory function (often referred to as central sleep apnea) caused by air blockage. Typically, individuals stop breathing for approximately 15 to 30 seconds during an obstructive sleep apnea event.

[0010] Other types of apnea include hypopnea, hyperpnea, and hypercapnia. Hypopnea is generally characterized by slow or shallow breathing caused by narrowing of the airway rather than airway obstruction. Hyperpnea is generally characterized by an increase in the depth and / or rate of breathing. Hypercapnia is generally characterized by a sudden or excessive amount of carbon dioxide in the bloodstream and is usually caused by insufficient breathing.

[0011] Cheyne-Stokes respiration (CSR) is another form of sleep-disordered breathing. CSR is a disturbance in the patient's respiratory control, resulting in alternating periods of waxing and waning ventilation, known as the CSR cycle. CSR is characterized by repeated deoxygenation and reoxygenation of arterial blood.

[0012] Obesity hyperventilation syndrome (OHS) is defined as the combination of severe obesity and chronic awake hypercapnia in the absence of other causes of hypoventilation. Symptoms include dyspnea, morning headache, and excessive daytime sleepiness.

[0013] Chronic obstructive pulmonary disease (COPD) encompasses any of a group of lower respiratory tract disorders that share certain characteristics, such as increased resistance to air movement, a prolonged expiratory phase of breathing, and loss of normal lung elasticity.

[0014] Neuromuscular disorders (NMDs) encompass a number of diseases and illnesses that impair muscle function directly through intrinsic muscle pathology or indirectly through neuropathology. Chest wall disorders are a group of thoracic deformities that result in inefficient connections between the respiratory muscles and the rib cage.

[0015] Respiratory effort-related arousal (RERA) events are typically characterized by increased respiratory effort for 10 seconds or more leading to arousal from sleep, without meeting the criteria for an apnea or hypopnea event. RERAs are defined as a series of breaths characterized by increased respiratory effort leading to arousal from sleep, but without meeting the criteria for an apnea or hypopnea. These events must meet both criteria: (1) a pattern of gradually increasing esophageal negative pressure terminated by a sudden drop in the negative pressure level and arousal; and (2) the event must last 10 seconds or more. In some implementations, a nasal cannula / pressure transducer system is sufficient and reliable for detecting RERAs. The RERA detector can be based on an actual flow signal derived from a respiratory therapy device. For example, a measure of flow limitation can be determined based on the flow signal. A measure of arousal can then be derived as a function of the measure of flow limitation and the measure of sudden increase in ventilation. One such method is described in WO 2008 / 138040 and U.S. Pat. No. 9,358,353, both issued to ResMed, Inc., the entire disclosures of each of which are incorporated herein by reference.

[0016] These and other disorders are characterized by specific events that can occur during sleep (e.g., snoring, apnea, hypopnea, restless legs, sleep disturbances, choking, increased heart rate, difficulty breathing, asthma attack, epileptic episode, seizure, or any combination thereof).

[0017] The apnea-hypopnea index (AHI) is an index used to indicate the severity of sleep apnea during a sleep session. The AHI is calculated by dividing the number of apnea and / or hypopnea events experienced by a user during a sleep session by the total number of hours of sleep in that sleep session. An event may be, for example, a pause in breathing lasting at least 10 seconds. An AHI of less than 5 is considered normal. An AHI of 5 to less than 15 is considered to indicate mild sleep apnea. An AHI of 15 to less than 30 is considered to indicate moderate sleep apnea. An AHI of 30 or greater is considered to indicate severe sleep apnea. In children, an AHI greater than 1 is considered abnormal. Sleep apnea can be considered "controlled" when the AHI is normal or when the AHI is normal or mild. The AHI can also be used in combination with oxygen saturation to indicate the severity of obstructive sleep apnea.

[0018] Additionally, many people also suffer from insomnia, a disorder typically characterized by dissatisfaction with sleep quality or duration (e.g., difficulty initiating sleep, frequent or prolonged awakenings after initially falling asleep, and early awakenings unable to return to sleep). It is estimated that over 2.6 billion people worldwide experience some form of insomnia, and over 750 million people worldwide are diagnosed with an insomnia disorder. In the United States, insomnia results in an estimated total economic burden of $107.5 billion per year, accounting for 13.6% of all workdays lost and 4.6% of injuries requiring medical treatment. Recent studies have also shown that insomnia is the second most common mental disorder and a leading risk factor for depression.

[0019] Nocturnal insomnia symptoms generally include, for example, poor sleep quality, shortened sleep duration, sleep onset insomnia, sleep maintenance insomnia, late-onset insomnia, mixed insomnia, and / or paradoxical insomnia. Sleep onset insomnia is characterized by difficulty initiating sleep when going to bed. Sleep maintenance insomnia is characterized by frequent and / or prolonged awakenings during the night after initially falling asleep. Late-onset insomnia is characterized by early morning awakening (e.g., before the target or desired awakening time) with failure to return to sleep. Comorbid insomnia refers to a type of insomnia in which the insomnia symptoms are caused, at least in part, by symptoms or complications of another physical or psychiatric disorder (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-onset insomnia). Paradoxical insomnia refers to a disconnect or discrepancy between a user's perceived quality of sleep and the user's actual quality of sleep.

[0020] Daytime (e.g., daytime) insomnia symptoms include, for example, fatigue, decreased energy, cognitive impairment (e.g., attention, concentration, and / or memory), difficulty functioning in academic or professional settings, and / or mood disorders. These symptoms can lead to psychological complications, such as, for example, decreased mental (and / or physical) performance, slowed reaction time, increased risk of depression, and / or increased risk of anxiety disorders. Insomnia symptoms can also lead to physiological complications, such as, for example, decreased immune system function, high blood pressure, increased risk of heart disease, increased risk of diabetes, weight gain, and / or obesity.

[0021] Coexisting insomnia and sleep apnea (COMISA) refers to a type of insomnia in which a subject experiences both insomnia and obstructive sleep apnea (OSA). OSA can be measured based on the apnea-hypopnea index (AHI) and / or oxygen desaturation levels. The AHI is calculated by dividing the number of apnea and / or hypopnea events experienced by a user during a sleep session by the total number of hours of sleep in that sleep session. An event can be, for example, a pause in breathing lasting at least 10 seconds. An AHI of less than 5 is considered normal. An AHI between 5 and 15 is considered to indicate mild OSA. An AHI between 15 and 30 is considered to indicate moderate OSA. An AHI of 30 or greater is considered to indicate severe OSA. In children, an AHI greater than 1 is considered abnormal.

[0022] Insomnia can also be classified based on its duration. For example, if an insomnia episode lasts less than three months, it is considered acute or transient. Conversely, if an insomnia episode occurs for, for example, three months or longer, it is considered chronic or persistent. Persistent / chronic insomnia episodes often require a different treatment route than acute / transient insomnia episodes.

[0023] Known risk factors for insomnia include gender (e.g., insomnia is more common in women than men), family history, and exposure to stress (e.g., severe and chronic life events). Age is a potential risk factor for insomnia. For example, sleep-onset insomnia is more common in young adults, 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, self-rated health).

[0024] Mechanisms of insomnia include predisposing factors, aggravating factors, and precipitating factors. Predisposing factors include hyperarousal, which is characterized by increased physiological arousal during sleep and wakefulness. Measures of hyperarousal include, for example, increased cortisol levels, increased autonomic nervous system activity (e.g., as indicated by increased resting heart rate and / or heart rate variability), increased brain activity (e.g., increased EEG frequency during sleep and / or increased number of awakenings during REM sleep), increased metabolic rate, elevated body temperature, and / or increased activity in the pituitary-adrenal axis. Aggravating factors include stressful life events (e.g., those related to employment or education, relationships, etc.). Precipitating factors include excessive worry about sleep deprivation and its resulting consequences, which can lead to continued insomnia symptoms even after the precipitating factor is removed.

[0025] Traditionally, diagnosing or screening for insomnia (including identifying the type of insomnia and / or specific symptoms) involves a series of steps. Often, the screening process begins with a subjective complaint from the patient (e.g., the patient cannot sleep or stay asleep).

[0026] The clinician then assesses the subjective complaints using a checklist that includes insomnia symptoms, factors that influence insomnia symptoms, health factors, and social factors. Insomnia symptoms include, for example, age at onset, precipitating events, time of onset, current symptoms (e.g., insomnia onset, sleep maintenance, and delayed-onset insomnia), symptom frequency (e.g., nightly, episodic, specific nights, situation-specific, or seasonal variations), time since symptom onset (e.g., changes in severity and / or relative occurrence of symptoms), and / or perceived daytime impact. Factors that influence insomnia symptoms include, for example, past and current treatments (including their effectiveness), factors that improve or improve symptoms, factors that worsen insomnia (e.g., stress or schedule changes), factors that maintain insomnia, including behavioral factors (e.g., going to bed too early, sleeping extra on weekends, alcohol consumption, etc.), and cognitive factors (e.g., unhelpful beliefs about sleep, worries about the effects of insomnia, fear of not getting enough sleep, etc.). Health factors include medical disorders and symptoms, conditions that interfere with sleep (e.g., pain, discomfort, treatments), and pharmacological considerations (e.g., drug warnings and sedative effects). Social factors include work schedules that are incompatible with sleep, returning home late without time to unwind, family and social responsibilities at night (e.g., caring for children or the elderly), stressful life events (e.g., past stressful events may trigger and perpetuate current stressful events), and / or sleeping with pets.

[0027] After clinicians complete a checklist and assess insomnia symptoms, symptom-influencing factors, health factors, and / or social factors, patients are often instructed to maintain a daily sleep diary and / or complete a questionnaire (e.g., the Insomnia Severity Index or Pittsburgh Sleep Quality Index). This traditional approach to insomnia screening and diagnosis is therefore prone to error because it relies on subjective complaints rather than objective sleep assessments. Misinterpretation of sleep status (paradoxical insomnia) can lead to a disconnect between a patient's subjective complaints and their actual sleep.

[0028] Furthermore, traditional approaches to diagnosing insomnia 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 failure, obesity hyperventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), neuromuscular disorders (NMD), and chest wall disorders. These other disorders are characterized by specific events that occur during sleep (e.g., snoring, apnea, hypopnea, restless legs, sleep disturbances, choking, increased heart rate, dyspnea, asthma attacks, epileptic episodes, seizures, or any combination thereof). While these other sleep-related disorders may share symptoms with insomnia, distinguishing them from insomnia is useful for customizing effective treatment plans that differentiate between characteristics that may require different treatments. For example, while fatigue is a common feature of insomnia, excessive daytime sleepiness is a characteristic feature of other disorders (e.g., PLMD) and reflects a physiological tendency to fall asleep involuntarily. Insomnia can also be linked to emotions (e.g., anxiety-induced insomnia), so tracking a patient's emotions (or anxiety) can provide insight into the management or treatment of insomnia.

[0029] Once insomnia is diagnosed, various techniques can be used or recommendations can be provided to the patient to manage or treat the insomnia. Typically, patients are encouraged or recommended to practice generally healthy sleep habits (e.g., getting enough exercise and daytime activity, having a daily routine, not sleeping during the day, eating dinner early, relaxing before bed, avoiding caffeine in the afternoon, avoiding alcohol, making the bedroom comfortable, removing distractions from the bedroom, getting out of bed if not sleepy, waking up at the same time each day regardless of bedtime) or are discouraged from certain habits (e.g., not working in bed, not going to bed too early, not going to bed when not tired). Patients can additionally or alternatively be treated with sleep medications and medical therapies, such as prescription sleep aids, over-the-counter sleep aids, and / or home herbal remedies.

[0030] Patients can also be treated using cognitive behavioral therapy (CBT) or cognitive behavioral therapy for insomnia (CBT-I), which generally includes sleep hygiene education, relaxation therapy, stimulus control, sleep restriction, and sleep management tools and devices. Sleep restriction is a method designed to restrict time in bed (sleep window or duration) to actual sleep and strengthen homeostatic sleep drive. The sleep window can be gradually increased over days or weeks until the patient achieves optimal sleep time. Stimulus control includes providing patients with a set of instructions designed to strengthen the association between the bed, bedroom, and sleep and 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 sleep (e.g., no reading or television), waking up at the same time each morning, and not taking naps). Relaxation training includes clinical procedures aimed at reducing autonomic nervous system 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 worries about sleep and restructure unhelpful beliefs about insomnia and its daytime effects (e.g., using Socratic questioning, action-experience, and paradoxical intention). Generally, sleep hygiene refers to personal practices (e.g., diet, exercise, substance use, bedtime, pre-sleep activities, in-bed activities before sleep, etc.) and / or environmental parameters (e.g., ambient light, ambient noise, ambient temperature, etc.). At least in some cases, sleep hygiene can be improved by going to bed at a specific bedtime each night, sleeping continuously for a specific amount of time, waking up at a specific time, changing environmental parameters, or any combination thereof. Sleep hygiene education includes general guidelines regarding healthy habits (e.g., diet, exercise, substance use) and environmental factors (e.g., light, noise, excessive temperature) that may disrupt sleep. Mindfulness-based interventions include, for example, meditation.

[0031] 1, a system 100 according to some implementations of the present disclosure is shown. The system 100 includes a control system 110, a memory device 114, an electronic interface 119, a respiratory treatment system 120, one or more sensors 130, one or more user devices 170, a light source 180, and an activity tracker 190.

[0032] Control system 110 includes one or more processors 112 (hereinafter processors 112). Control system 110 is generally used to control (e.g., operate) various components of system 100 and / or analyze data acquired and / or generated by the components of system 100. Processor 112 may be a general-purpose or special-purpose processor or microprocessor. While one processor 112 is shown in FIG. 1 , control system 110 may include any suitable number of processors (e.g., one processor, two processors, five processors, ten processors, etc.), which may reside within a single housing or may be located remotely from one another. Control system 110 may be coupled to and / or located within the housing of user device 170, a portion (e.g., housing) of respiratory treatment system 120, and / or one or more of sensor 130, for example. Control system 110 may be centralized (within one such housing) or distributed (within two or more such housings that are physically separate). In such implementations that include two or more housings that house control system 110, such housings may be located proximate to and / or distant from one another.

[0033] The memory device 114 stores machine-readable instructions executable by the processor 112 of the control system 110. The memory device 114 may be any suitable computer-readable memory device or medium, such as, for example, a random-access or serial-access memory device, a hard drive, a solid-state drive, a flash memory device, etc. Although one memory device 114 is shown in FIG. 1 , the system 100 may include any suitable number of memory devices 114 (e.g., one memory device, two memory devices, five memory devices, ten memory devices, etc.). The memory device 114 may be coupled to and / or located within the housing of the respiratory treatment device 122, the housing of the user device 170, the housing of one or more of the activity tracker 190, the sensor 130, or any combination thereof. Like the control system 110, the memory device 114 may be centralized (within one such housing) or distributed (within two or more of such physically distinct housings).

[0034] In some implementations, the memory device 114 (FIG. 1) stores a user profile associated with the user. The user profile may include, for example, demographic information associated with the user, biometric information associated with the user, medical information associated with the user, self-reported user feedback, sleep parameters associated with the user (e.g., sleep-related parameters recorded from one or more previous sleep sessions), or any combination thereof. Demographic information may include, for example, information indicative of the user's age, the user's gender, the user's race, the user's geographic location, relationship status, family history of insomnia, the user's employment status, the user's education status, the user's socioeconomic status, or any combination thereof. Medical information may include, for example, information indicative of one or more medical conditions associated with the user, medication usage by the user, or both. Medical information data may also include results or scores of a Multiple Sleep Latency Test (MSLT) and / or a Pittsburgh Sleep Quality Index (PSQI) score or value. The medical information data may include results from one or more of a polysomnography (PSG) test, a CPAP titration, or a home sleep test (HST), respiratory therapy system settings from one or more sleep sessions, sleep-related respiratory events from one or more sleep sessions, or any combination thereof. The self-reported user feedback may include information indicative of a self-reported subjective sleep score (e.g., poor, fair, good), the user's self-reported subjective stress level, the user's self-reported subjective fatigue level, the user's self-reported subjective health status, recent life events experienced by the user, or any combination thereof.

[0035] The electronic interface 119 is configured to receive data (e.g., physiological data and / or audio data) from one or more sensors 130, which can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. Physiological parameters can be determined and / or calculated using the received data, such as physiological data, flow data, pressure data, motion data, and acoustic data. The electronic interface 119 can communicate with the one or more sensors 130 using a wired or wireless connection (e.g., using an RF communication protocol, a Wi-Fi communication protocol, a Bluetooth® communication protocol, an IR communication protocol, a cellular network, other optical communication protocols, etc.). The electronic interface 119 can include an antenna, a receiver (e.g., an RF receiver), a transmitter (e.g., an RF transmitter), a transceiver, or any combination thereof. The electronic interface 119 can also include another processor and / or another memory device that are the same as or similar to the processor 112 and memory device 114 described herein. In some implementations, the electronic interface 119 is coupled to or integrated with the user device 170. In other implementations, the electronic interface 119 is coupled to or integrated with (e.g., within a housing) the control system 110 and / or the memory device 114.

[0036] As mentioned above, in some implementations, system 100 optionally includes a respiratory treatment system 120. Respiratory treatment system 120 can include a respiratory pressure therapy (RPT) device 122 (referred to herein as a respiratory treatment device 122), a user interface 124, a conduit 126 (also referred to as a tubing or air circuit), a display device 128, a humidification tank 129, or a combination thereof. In some implementations, control system 110, memory device 114, display device 128, one or more of sensors 130, and humidification tank 129 are part of respiratory treatment device 122. Respiratory pressure therapy refers to the application of an air supply to the entrance of a user's airways at a controlled target pressure that is nominally positive relative to the atmosphere throughout the user's respiratory cycle (as opposed to negative pressure therapies such as, for example, a tank ventilator or a positive-negative pressure extracorporeal ventilator (cuirass)). Respiratory treatment system 120 is generally used to treat individuals suffering from one or more sleep-related breathing disorders (eg, obstructive sleep apnea, central sleep apnea, or mixed sleep apnea).

[0037] Respiratory treatment device 122 is generally used to generate pressurized air delivered to a user (e.g., using one or more motors driving one or more compressors). In some implementations, respiratory treatment device 122 generates a continuous, constant air pressure delivered to a user. In other implementations, respiratory treatment device 122 generates two or more predetermined pressures (e.g., a first predetermined air pressure and a second predetermined air pressure). In yet other implementations, respiratory treatment device 122 is configured to generate a variety of different air pressures within a predetermined range. For example, respiratory treatment device 122 can deliver pressurized air at a pressure of at least about 6 cmH2O, at least about 10 cmH2O, at least about 20 cmH2O, between about 6 cmH2O and about 10 cmH2O, between about 7 cmH2O and about 12 cmH2O, etc. Respiratory treatment device 122 can also deliver pressurized air at a predetermined flow rate, e.g., between about -20 L / min and about 150 L / min, while maintaining a positive pressure (relative to ambient pressure).

[0038] The user interface 124 engages a portion of the user's face and delivers pressurized air from the respiratory treatment device 122 to the user's airway to help prevent the airway from narrowing and / or closing while sleeping. This may also increase the user's oxygen intake while sleeping. Generally, the user interface 124 engages the user's face to deliver pressurized air to the user's airway through the user's mouth, nose, or both the user's mouth and nose. The respiratory treatment device 122, the user interface 124, and the conduit 126 together form an airway fluidly coupled to the user's airway. The pressurized air also increases the user's oxygen intake while sleeping.

[0039] Depending on the therapy being applied, the user interface 124 may, for example, form a seal with an area or portion of the user's face to facilitate delivery of gas at a pressure sufficiently different from ambient pressure to effect the therapy, for example, about 10 cm H2O positive pressure relative to ambient pressure. In other forms of therapy, such as oxygen delivery, the user interface may not include a seal sufficient to facilitate delivery of a gas supply to the airways at about 10 cm H2O positive pressure.

[0040] As shown in FIG. 2 , in some implementations, the 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, the user interface 124 is a nasal mask that provides air to the user's nose or a nasal pillow mask that delivers air directly to the user's nostrils. The user interface 124 can 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 a conformable cushion (e.g., silicone, plastic, foam, etc.) that helps provide an airtight seal between the user interface 124 and the user. In some examples, the user interface 124 can be a tube-up mask, with the straps of the mask configured to act as a conduit for delivering pressurized air to the face or nasal mask. The user interface 124 can also include one or more vents to allow carbon dioxide and other gases exhaled by the user 210 to escape. In other implementations, the user interface 124 includes a mouthpiece (eg, a night guard mouthpiece shaped to fit over the user's teeth, a mandibular repositioning device, etc.).

[0041] A conduit 126 (also referred to as an air circuit or tubing) allows air to flow between two components of the respiratory treatment system 120, such as the respiratory treatment device 122 and the user interface 124. In some implementations, this conduit may have separate branches for inhalation and exhalation. In other implementations, a single-branch conduit is used for both inhalation and exhalation.

[0042] One or more of the respiratory treatment device 122, the user interface 124, the conduit 126, the display device 128, and the humidification tank 129 may house one or more sensors (e.g., a pressure sensor, a flow sensor, a humidity sensor, a temperature sensor, or more generally, any of the other sensors 130 described herein) that may be used, for example, to measure the air pressure and / or flow rate of the pressurized air supplied by the respiratory treatment device 122.

[0043] The display device 128 is generally used to display image(s), including still images, video, or both, and / or information about the respiratory treatment device 122. For example, the display device 128 can provide information about the status of the respiratory treatment device 122 (e.g., whether the respiratory treatment device 122 is on / off, the pressure of the air being delivered by the respiratory treatment device 122, the temperature of the air being delivered by the respiratory treatment device 122, etc.) and / or other information (e.g., a sleep score and / or a therapy score (e.g., a myAir® score as described in WO 2016 / 061629, each of which is incorporated herein by reference in its entirety), the current date / time, personal information of the user 210, etc.). In some implementations, the display device 128 functions as a human-machine interface (HMI) that includes as an input interface a graphical user interface (GUI) configured to display images. The display device 128 can be an LED display, an OLED display, an LCD display, etc. The input interface may be, for example, a touch screen or touch-sensitive board, a mouse, a keyboard, or any sensor system configured to sense inputs made by a human user interacting with the respiratory treatment device 122 .

[0044] The humidification tank 129 is coupled to or integrated with the respiratory treatment device 122. The humidification tank 129 includes a reservoir of water that can be used to humidify the pressurized air delivered from the respiratory treatment device 122. The respiratory treatment device 122 can include a heater that heats water in the humidification tank 129 to humidify the pressurized air provided to the user. Additionally, in some implementations, the conduit 126 can also include a heating element (e.g., coupled to and / or embedded in the conduit 126) that heats the pressurized air delivered to the user. The humidification tank 129 is fluidly coupled to a water vapor inlet of the air path and can deliver water vapor to the air path via the water vapor inlet, or can be formed in-line with the air path as part of the air path itself. In other implementations, the respiratory treatment device 122 or the conduit 126 can include a waterless humidifier. The waterless humidifier can incorporate sensors that interface with other sensors positioned elsewhere in the system 100.

[0045] Respiratory therapy system 120 can be used, for example, as a mechanical ventilator or a positive airway pressure (PAP) system, such as a continuous positive airway pressure (CPAP) system, an automatic 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. CPAP systems deliver a predetermined air pressure (e.g., determined by a sleep physician) to a user. APAP systems automatically vary the air pressure delivered to a user, for example, based on respiratory data associated with the user. BPAP or VPAP systems are configured to deliver a first predetermined pressure (e.g., inspiratory positive airway pressure or IPAP) and a second predetermined pressure (e.g., expiratory positive airway pressure or EPAP) that is lower than the first predetermined pressure. HFT systems typically provide a continuous, heated, humidified flow of air through an unsealed or open patient interface at a "therapeutic flow rate" that remains substantially constant throughout the respiratory cycle. The therapeutic flow is nominally set to exceed the patient's peak inspiratory flow.

[0046] Referring to FIG. 1 , a portion of system 100 ( FIG. 1 ) is shown according to some implementations. A user 210 and bedmate 220 of respiratory treatment system 120 are positioned in bed 230, lying on mattress 232. User interface 124 is a face mask (e.g., a full face mask) that covers the nose and mouth of user 210. Alternatively, user interface 124 may be a nasal mask that provides 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 (e.g., face) of user 210, and a conformable cushion (e.g., silicone, plastic, foam, etc.) that helps provide an airtight seal between user interface 124 and user 210. User interface 124 may also include one or more vents to allow carbon dioxide and other gases exhaled by user 210 to escape. In other implementations, the user interface 124 is a mouthpiece (e.g., a night guard mouthpiece molded to fit the user's teeth, a mandibular repositioning device, etc.) that directs pressurized air into the mouth of the user 210.

[0047] The user interface 124 is fluidly coupled and / or connected to the respiratory treatment device 122 via the conduit 126. The respiratory treatment device 122 then delivers pressurized air to the user 210 via the conduit 126 and the user interface 124, increasing the air pressure in the user's 210 throat and helping to prevent the airway from closing and / or narrowing during sleep. The respiratory treatment device 122 can be positioned on a nightstand 240 directly adjacent to the bed 230, as shown in FIG. 2, or more generally on any surface or structure generally adjacent to the bed 230 and / or user 210.

[0048] Generally, users prescribed the use of respiratory treatment system 120 tend to experience better quality sleep and reduced daytime fatigue after using respiratory treatment system 120 while sleeping compared to not using respiratory treatment system 120 (especially if the user suffers from sleep apnea or other sleep-related disorders). For example, user 210 may suffer from obstructive sleep apnea and rely on user interface 124 (e.g., a full-face mask) to deliver pressurized air from respiratory treatment device 122 via conduit 126. Respiratory treatment device 122 may be a continuous positive airway pressure (CPAP) machine used to increase air pressure in the throat of user 210 to prevent the airway from closing and / or narrowing during sleep. People with sleep apnea may experience narrowing or obstruction of the airway during sleep, resulting in reduced oxygen intake, forced awakenings, and / or disrupted sleep. CPAP machines prevent narrowing or obstruction of the airway and minimize awakenings or airway disruptions due to reduced oxygen intake. Although the respiratory therapy device 122 attempts to maintain a medically prescribed air pressure during sleep, users may experience sleep discomfort due to the therapy.

[0049] Referring again to FIG. 1A , the one or more sensors 130 of the system 100 may include a pressure sensor 132, a flow sensor 134, a temperature sensor 136, a motion sensor 138, a microphone 140, a speaker 142, a radio frequency (RF) receiver 146, an RF transmitter 148, a camera 150, an infrared sensor 152, a photoplethysmogram (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 electromyogram (EMG) sensor 166, an oxygen sensor 168, an analyte sensor 174, a moisture sensor 176, a ranging (LiDAR) sensor 178, an electrodermal sensor, an accelerometer, an electrooculogram (EOG) sensor, a light sensor, a humidity sensor, an air quality sensor, or any combination thereof. Generally, each of the one or more sensors 130 is configured to output sensor data that is received and stored in memory device 114 or one or more other memory devices.

[0050] The one or more sensors 130 are illustrated and described as including each of a pressure sensor 132, a flow sensor 134, a temperature sensor 136, a motion sensor 138, a microphone 140, a speaker 142, an RF receiver 146, an RF transmitter 148, a camera 150, an infrared sensor 152, a photoelectric (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 electromyogram (EMG) sensor 166, an oxygen sensor 168, an analyte sensor 174, a moisture sensor 176, and a LiDAR sensor 178, but more generally, the one or more sensors 130 may include any combination and any number of each of the sensors described and / or illustrated herein.

[0051] As described herein, system 100 generally can be used to generate data (e.g., physiological data, flow data, pressure data, motion data, acoustic data, etc.) associated with a user (e.g., a user of respiratory treatment system 120 shown in FIG. 2 ) before, during, and / or after a sleep session. The generated data can be analyzed to generate one or more physiological parameters (e.g., before, during, and / or after a sleep session) and / or sleep-related parameters (e.g., during a sleep session), which can include any parameter, measurement, etc. related to the user. Examples of the one or more physiological parameters include breathing pattern, breathing rate, inspiratory amplitude, expiratory amplitude, heart rate, heart rate variability, length of time between breaths, maximum inspiratory time, maximum expiratory time, mandatory breathing parameters (e.g., distinction between breath release and mandatory expiratory time), respiratory variability, respiratory morphology (e.g., one or more breath shapes), movement of user 210, temperature, EEG activity, EMG activity, ECG data, sympathetic response parameters, parasympathetic response parameters, etc. One or more sleep-related parameters that may be determined for the user 210 during a sleep session may include, for example, an apnea-hypopnea index (AHI) score, a sleep score, a therapy score, a flow signal, a pressure signal, a respiratory signal, a breathing pattern, a breathing rate, an inhalation amplitude, an exhalation amplitude, an inhalation-to-exhalation ratio, a number of events (e.g., apnea events) per hour, a pattern of events, a sleep state and / or a sleep stage, a heart rate, a heart rate variability, movement of the user 210, a temperature, an EEG activity, an EMG activity, an arousal, snoring, choking, coughing, wheezing, wheezing, or any combination thereof.

[0052] The one or more sensors 130 can be used to generate, for example, physiological data, audio data, or both. The physiological data generated by one or more of the sensors 130 can be used by the control system 110 to determine the duration and quality of sleep of the user 210. For example, there is a sleep-wake signal and one or more sleep-related parameters associated with the user 210 during a sleep session. The sleep-wake signal can indicate one or more sleep states, including sleep, wakefulness, relaxed wakefulness, micro-arousal, or distinct sleep stages such as a rapid eye movement (REM) stage, a first non-REM stage (often referred to as "N1"), a second non-REM stage (often referred to as "N2"), a third non-REM stage (often referred to as "N3"), or any combination thereof. Methods for determining sleep states and / or sleep stages from physiological data generated by one or more sensors, such as sensor 130, are described, for example, in International Publication Nos. WO 2014 / 047310, WO 2014 / 0088373, WO 2017 / 132726, WO 2019 / 122413, and WO 2019 / 122414, each of which is incorporated herein by reference in its entirety.

[0053] The sleep-wake signal may also be time-stamped to determine the time the user gets into bed, the time the user gets out of bed, the time the user attempts to fall asleep, etc. The sleep-wake signal may be measured by one or more sensors 130 at a predetermined sampling rate during the sleep session, such as one sample per second, one sample per 30 seconds, one sample per minute, etc. In some implementations, the sleep-wake signal may also indicate the respiratory signal, respiratory rate, inspiration amplitude, expiration amplitude, inspiration-to-expiration ratio, number of events per hour, pattern of events, pressure setting of the respiratory treatment device 122, or any combination thereof during the sleep session.

[0054] Events include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, mouth leak, mask leak (e.g., leaking through the user interface 124), restless legs, sleep disturbances, choking, increased heart rate, heart rate variability, labored breathing, asthma attack, epileptic episode, seizure, fever, coughing, sneezing, snoring, gasping, presence of illness such as a cold or flu, or any combination thereof. In some implementations, mouth leak can include a continuous mouth leak or a flap-like mouth leak (i.e., varying with the duration of the breath) where the lips of a user using a nasal / nasal pillows mask pop open during exhalation, typically. Mouth leak can lead to dry mouth and bad breath, sometimes colloquially referred to as "sandpaper mouth."

[0055] The one or more sleep-related parameters that can be determined for a user during a sleep session based on the sleep-wake signal include, for example, sleep quality metrics such as total time in bed, total sleep time, sleep onset latency, sleep sleep onset parameters, sleep efficiency, fragmentation index, or any combination thereof.

[0056] Data generated by one or more sensors 130 (e.g., physiological data, flow data, pressure data, motion data, acoustic data, etc.) can also be used to determine the respiratory signal. The respiratory signal generally indicates the user's breathing. The respiratory signal can indicate a breathing pattern, which can include, for example, respiratory rate, respiratory rate variability, inspiratory amplitude, expiratory amplitude, inspiratory-to-expiratory ratio, and other breathing-related parameters, and any combination thereof. In some cases, during a sleep session, the respiratory signal can include the number of events per hour (e.g., during sleep), the pattern of events, the pressure setting of the respiratory therapy device 122, or any combination thereof. The event(s) can include snoring, apnea (e.g., central apnea, obstructive apnea, mixed apnea, and hypopnea), mouth leak, mask leak (e.g., from the user interface 124), restless legs, sleep disorder, choking, increased heart rate, dyspnea, asthma attack, epileptic episode, seizure, or any combination thereof.

[0057] Generally, a sleep session includes any time after the user 210 lies or sits in bed 230 (or another area or object used for sleeping) and / or turns on the respiratory treatment device 122 and / or puts on the user interface 124. Thus, a sleep session may include (i) a time period during which the user 210 is using the CPAP system but before attempting to fall asleep (e.g., a time period during which the user 210 is lying in bed 230 reading a book), (ii) a time period during which the user 210 begins to attempt to fall asleep but is still awake, (iii) a time period during which the user 210 is in light sleep (also called stages 1 and 2 of non-rapid eye movement (non-REM) sleep), (iv) a time period during which the user 210 is in deep sleep (also called slow wave sleep (SWS) or stage 3 of non-REM sleep), (v) a time period during which the user 210 is in rapid eye movement (REM) sleep, (vi) a time period during which the user 210 is waking periodically between light sleep, deep sleep, or REM sleep, or (vii) a time period during which the user 210 is awake and does not return to sleep.

[0058] A sleep session can generally be defined as ending when the user 210 removes the user interface 124, turns off the respiratory treatment device 122, and / or leaves the bed 230. In some implementations, a sleep session can include additional periods of time or be limited to only some of the times disclosed above. For example, a sleep session can be defined to encompass a period of time that begins when the respiratory treatment device 122 begins to deliver pressurized air to the airway or user 210 and ends when the respiratory treatment device 122 stops delivering pressurized air to the airway of the user 210, and includes some or all of the points in between when the user 210 is asleep or awake.

[0059] In some cases, the pre-sleep period can be defined as the time before the user falls asleep (e.g., before the user enters light, deep, or REM sleep), which can include the time before and / or after the user lies or sits in bed 230 (or another area or object in which they intend to sleep). In some cases, the personalized entrainment disclosed herein can be used during this pre-sleep period, but need not always be. In some cases, for example, the personalized entrainment can be used during a sleep session (e.g., while the user is asleep or while the user is waking periodically between light, deep, or REM sleep) and / or after the sleep session (e.g., after the user wakes up and decides to stay awake, etc.). In some cases, the personalized entrainment disclosed herein can continue to be used during the pre-sleep period, during a sleep session (e.g., in the same or modified form), and / or after the sleep session has ended (e.g., in the same form).

[0060] 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., a barometric sensor) that generates sensor data indicative of a user's breathing (e.g., inhalation and / or exhalation) and / or ambient pressure of respiratory treatment system 120. In such implementations, pressure sensor 132 can be coupled to or integrated with respiratory treatment device 122, user interface 124, or conduit 126. Pressure sensor 132 is used to determine the air pressure within respiratory treatment device 122, the air pressure within conduit 126, the air pressure within user interface 124, or any combination thereof. Pressure sensor 132 can be, for example, a capacitive sensor, an electromagnetic sensor, an inductive sensor, a resistive sensor, a piezoelectric sensor, a strain gauge sensor, an optical sensor, a potentiometric sensor, or any combination thereof. In one example, pressure sensor 132 can be used to determine the user's blood pressure.

[0061] The flow sensor 134 outputs flow data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. In some implementations, the flow sensor 134 is used to determine the airflow rate from the respiratory treatment 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 with the respiratory treatment device 122, the user interface 124, or the conduit 126. The flow sensor 134 can be, for example, a mass flow sensor such as a rotary flow meter (e.g., a Hall effect flow meter), a turbine flow meter, an orifice flow meter, an ultrasonic flow meter, a hot wire sensor, a vortex sensor, a film sensor, or any combination thereof.

[0062] The flow sensor 134 can be used to generate flow data associated with a user 210 ( FIG. 2 ) of the respiratory treatment device 122 during a sleep session. Examples of flow sensors (e.g., flow sensor 134) are described in International Publication No. WO 2012 / 012835, which is incorporated by reference herein in its entirety. In some implementations, the flow sensor 134 is configured to measure airflow (e.g., intentional “leak”), unintentional leak (e.g., mouth leak and / or mask leak), patient flow (e.g., air entering or leaving the lungs), or any combination thereof. In some implementations, the flow data can be analyzed to determine the user's cardiogenic oscillations.

[0063] The temperature sensor 136 outputs temperature data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. In some implementations, the temperature sensor 136 generates temperature data indicative of the core body temperature of the user 210 ( FIG. 2 ), the skin temperature of the user 210, the temperature of the air flowing from the respiratory treatment device 122 and / or through the conduit 126, the temperature of the air within the user interface 124, the ambient temperature, or any combination thereof. The temperature sensor 136 can be, for example, a thermocouple sensor, a thermistor sensor, a silicon bandgap temperature sensor or semiconductor-based sensor, a resistance temperature detector, or any combination thereof.

[0064] The motion sensor 138 outputs motion data that can be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. The motion sensor 138 can be used to detect the movement of the user 210 during a sleep session and / or the movement of any of the components of the respiratory treatment system 120, such as the respiratory treatment device 122, the user interface 124, or the conduit 126. The motion sensor 138 can include one or more inertial sensors, such as, for example, an accelerometer, a gyroscope, and a magnetometer. In some implementations, the motion sensor 138 alternatively or additionally generates one or more signals representative of the user's body movements, from which a signal representative of the user's sleep state or sleep stage can be obtained, for example, via the user's respiratory movements. In some implementations, the motion data from the motion sensor 138 can be used in conjunction with additional data from another sensor 130 to determine the user's sleep state or sleep stage. In some implementations, the motion data can be used to determine the user's position, body position, and / or changes in body position.

[0065] The microphone 140 outputs audio data that may be stored in the memory device 114 and / or analyzed by the processor 112 of the control system 110. The audio data generated by the microphone 140 can be played back as one or more sounds (e.g., sounds from the user 210) during a sleep session. As described in further detail herein, the audio data from the microphone 140 can also be used to identify events experienced by the user during a sleep session (e.g., using the control system 110). The microphone 140 can be coupled to or integrated with the respiratory treatment device 122, the user interface 124, the conduit 126, or the user device 170. In some implementations, the system 100 includes multiple microphones (e.g., two or more microphones and / or an array of microphones with beamforming capabilities) such that the audio data generated by each of the multiple microphones can be used to distinguish audio data generated by another of the multiple microphones.

[0066] The speaker 142 outputs sound waves. In one or more implementations, the sound waves may be audible to a user of the system 100 (e.g., user 210 in FIG. 2 ) or may be inaudible to a user of the system (e.g., ultrasound). The speaker 142 may be used, for example, as an alarm clock or to play alerts or messages to the user 210 (e.g., in response to an identified body position and / or change in body position). In some implementations, the speaker 142 may be used to communicate audio data generated by the microphone 140 to the user. The speaker 142 may be coupled to or integrated with the respiratory treatment device 122, the user interface 124, the conduit 126, or the user device 170.

[0067] The microphone 140 and the speaker 142 can be used as independent devices. In some implementations, the microphone 140 and the speaker 142 can be combined into an acoustic sensor 141 (e.g., a SONAR sensor), for example, as described in International Publication Nos. WO 2018 / 050913 and WO 2020 / 104465, each of which is incorporated by reference in its entirety. In such implementations, the speaker 142 generates or emits sound waves at predetermined intervals and / or frequencies, and the microphone 140 detects reflections of the sound waves emitted from the speaker 142. In one or more implementations, the sound waves generated or emitted by the speaker 142 can have a frequency that is inaudible to the human ear (e.g., below 20 Hz or above about 18 kHz) so as not to disturb the sleep of the user 210 or bedmate 220 ( FIG. 2 ). Based at least in part on data from microphone 140 and / or speaker 142, control system 110 can determine one or more of the position of user 210 (FIG. 2) and / or sleep-related parameters described herein (e.g., identified body positions and / or changes in body positions) and / or respiration-related parameters described herein, such as, for example, breathing pattern, breathing signal (e.g., from which respiration morphology can be determined), respiration rate, inspiration amplitude, expiration amplitude, inspiration-to-expiration ratio, number of events per hour, pattern of events, sleep state, sleep stage, or any combination thereof. In this context, sonar sensor may be understood to involve active acoustic sensing, such as by generating / transmitting ultrasound or low-frequency ultrasound sensing signals (e.g., within a frequency range of about 17-23 kHz, 18-22 kHz, or 17-18 kHz) into the air. Such a system can be considered in connection with the above-mentioned WO 2018 / 050913 and WO 2020 / 104465.

[0068] In some cases, the microphone 140 and / or speaker 142 may be incorporated into a separate device, such as a body-worn device, such as one or a set of earphones or headphones. In some cases, such a device may include other of the one or more sensors 130.

[0069] In some implementations, sensor 130 includes (i) a first microphone that is the same as or similar to microphone 140 and integrated into acoustic sensor 141, and (ii) a second microphone that is the same as or similar to microphone 140 but is independent and separate from the first microphone that is integrated into acoustic sensor 141.

[0070] The RF transmitter 148 generates and / or emits radio waves having a predetermined frequency and / or a predetermined amplitude (e.g., within a high frequency band, within a low frequency band, a long wave signal, a short wave signal, etc.). The RF receiver 146 detects reflections of the radio waves emitted from the RF transmitter 148, and this data can be analyzed by the control system 110 to determine the position and / or body position of the user 210 ( FIG. 2 ) and / or one or more of the sleep-related parameters described herein. Additionally, the RF receiver (either the RF receiver 146 or the RF transmitter 148, or another RF pair) can be used for wireless communication between the control system 110, the respiratory treatment device 122, the one or more sensors 130, the user device 170, or any combination thereof. While the RF receiver 146 and the RF transmitter 148 are shown in FIG. 1 as separate and distinct elements, in some implementations the RF receiver 146 and the 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 particular form of RF communication may be Wi-Fi, Bluetooth, etc.

[0071] In some implementations, the 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, mesh routers, and mesh gateways, each of which may be mobile / movable or fixed. In such implementations, the Wi-Fi mesh system includes a Wi-Fi router and / or a Wi-Fi controller, and one or more satellites (e.g., access points), each of which includes an RF sensor the same as or similar to the RF sensor 147. The Wi-Fi router and satellite continuously communicate 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 signal between the router and the satellite (e.g., differences in received signal strength) due to the movement of an object or person partially obstructing the signal. This motion data may indicate movement, breathing, heart rate, gait, falls, behavior, etc., or any combination thereof.

[0072] The camera 150 outputs image data that can be reproduced as one or more images (e.g., still images, video, thermal images, or any combination thereof) that can be stored in the memory device 114. The image data from the camera 150 can be used by the control system 110 to determine one or more of the sleep-related parameters described herein. The control system 110 can use the image data from the camera 150 to determine one or more of the sleep-related parameters described herein, such as, for example, one or more events (e.g., periodic limb movement or restless legs syndrome), a respiratory signal, a respiratory rate, an inhalation amplitude, an exhalation amplitude, an inhalation-to-exhalation ratio, a number of events per hour, a pattern of events, a sleep state, a sleep stage, or any combination thereof. Additionally, the image data from the camera 150 can be used to identify the position and / or body position of the user, determine chest movement of the user 210, determine airflow at the mouth and / or nose of the user 210, determine the time the user 210 enters the bed 230, and determine the time the user 210 leaves the bed 230. The camera 150 can also be used to track eye movement, pupil dilation (if one or both of the user's 210 eyes are open), blink rate, or any changes during REM sleep.

[0073] The infrared (IR) sensor 152 outputs infrared image data that can be played back as one or more infrared images (e.g., still images, moving images, or both) that can be stored in the memory device 114. The infrared data from the IR sensor 152 can be used to determine one or more sleep-related parameters during a sleep session, including the temperature of the user 210 and / or the movement of the user 210. The IR sensor 152 can also be used in combination with the camera 150 in measuring the presence, location, and / or movement of the user 210. The IR sensor 152 can detect infrared light having a wavelength between about 700 nm and about 1 mm, for example, while the camera 150 can detect visible light having a wavelength between about 380 nm and about 740 nm.

[0074] The PPG sensor 154 outputs physiological data associated with the user 210 ( FIG. 2 ), which may be used to determine one or more sleep-related parameters, such as, for example, heart rate, heart rate pattern, heart rate variability, cardiac cycle, respiratory rate, inspiration amplitude, expiration amplitude, inspiration-to-expiration ratio, estimated blood pressure parameters, or any combination thereof. The PPG sensor 154 is worn by the user 210, embedded in clothing and / or fabric worn by the user 210, embedded in and / or coupled to the user interface 124 and / or its associated headgear (e.g., straps, etc.). In some cases, the PPG sensor 154 may be a non-contact PPG sensor capable of performing PPG at a remote location. In some cases, the PPG sensor 154 may be used to determine pulse arrival time (PAT). PAT may determine the time interval required for the pulse wave to travel from the heart to a distal location on the body, such as a finger or other location. In other words, PAT may 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 a respiration signal to derive respiratory information such as respiration rate. In some cases, the PPG signal provides SpO2 data, which can be used to detect sleep-related disorders such as OSA.

[0075] The ECG sensor 156 outputs physiological data associated with the electrical activity of the user's 210 heart. In some implementations, the ECG sensor 156 includes one or more electrodes positioned on or around a portion of the user 210 during a sleep session. The physiological data from the ECG sensor 156 can be used, for example, to determine one or more of the sleep-related parameters described herein. In some cases, changes in the amplitude and / or morphology of the ECG electrical trace can be used to identify a respiration curve and identify respiration information, such as respiration rate.

[0076] In some cases, ECG and / or PPG signals can be used in conjunction with a secondary estimate of parasympathetic and / or sympathetic innervation, such as via a galvanic skin response (GSR) sensor. Such signals can be used to determine what the actual breathing curve is and whether it has a positive, neutral, or negative impact on an individual's stress level.

[0077] The EEG sensor 158 outputs physiological data associated with electrical activity of the brain of the user 210. In some implementations, the EEG sensor 158 includes one or more electrodes placed on or around the scalp of the user 210 during a sleep session. The physiological data from the EEG sensor 158 can be used, for example, to determine the sleep state or sleep stage of the user 210 at any given time during the sleep session. In some implementations, the EEG sensor 158 can be integrated into the user interface 124 and / or headgear (e.g., straps, etc.) associated therewith.

[0078] The capacitance sensor 160, the force sensor 162, and the strain gauge sensor 164 output data that can be stored in the memory device 114 and used by the control system 110 to determine one or more of the sleep-related parameters described herein. The EMG sensor 166 outputs physiological data associated with electrical activity produced by one or more muscles. The oxygen sensor 168 outputs oxygen data indicative of the oxygen concentration of a gas (e.g., in the conduit 126 or at the user interface 124). The oxygen sensor 168 can be, for example, an ultrasonic oxygen sensor, an electrical oxygen sensor, a chemical oxygen sensor, an optical oxygen sensor, or any combination thereof. In some implementations, the one or more sensors 130 also include a galvanic skin response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a sphygmomanometer sensor, an oximetry sensor, or any combination thereof.

[0079] The analyte sensor 174 can be used to detect the presence of analytes in the exhaled breath of the user 210. Data output by the analyte sensor 174 is stored in the memory device 114 and can be used by the control system 110 to determine the identity and concentration of any analytes in the user's 210 breath. In some implementations, the analyte sensor 174 is positioned near the mouth of the user 210 to detect analytes in breath exhaled from the user's 210 mouth. For example, if the user interface 124 is a face mask that covers the nose and mouth of the user 210, the analyte sensor 174 can be positioned within the face mask to monitor the user's 210 mouth breathing. In other implementations, if the user interface 124 is a nasal mask or nasal pillows mask, the analyte sensor 174 can be positioned near the nose of the user 210 to detect analytes in the breath exhaled from the user's nose. In yet another implementation, if the user interface 124 is a nasal mask or nasal pillows mask, the analyte sensor 174 can be positioned near the mouth of the user 210. In this implementation, the analyte sensor 174 can be used to detect whether air is inadvertently leaking from the mouth of the 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 the user 210 is breathing through their nose or mouth. For example, if the presence of an analyte is detected by data output by an analyte sensor 174 positioned near the mouth of the user 210 or within a face mask (in implementations where the user interface 124 is a face mask), the control system 110 can use this data as an indication that the user 210 is breathing through their mouth.

[0080] The moisture sensor 176 outputs data that can be stored in the memory device 114 and used by the control system 110. The moisture sensor 176 can be used to detect moisture in various areas surrounding the user (e.g., inside the conduit 126 or the user interface 124, near the face of the user 210, near the junction of the conduit 126 and the user interface 124, near the junction of the conduit 126 and the respiratory treatment device 122, etc.). Thus, in some implementations, the moisture sensor 176 can be located within the user interface 124 or the conduit 126 to monitor the humidity of the pressurized air from the respiratory treatment device 122. In other implementations, the moisture sensor 176 is located near any area where humidity levels need to be monitored. The moisture sensor 176 can also be used to monitor the humidity of the ambient environment surrounding the user 210, such as the air in the user's 210 bedroom. The moisture sensor 176 can also be used to track the user's 210 biological response to environmental changes.

[0081] 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 objects and create a three-dimensional (3D) map of a surrounding environment, such as a living space. LiDAR generally utilizes a pulsed laser to measure time of flight. LiDAR is also referred to as 3D laser scanning. In one use case of such a sensor, a fixed or mobile device (such as a smartphone) equipped with a LiDAR sensor 178 can measure and map an area more than five meters away from the sensor. LiDAR data can be fused with point cloud data estimated, for example, by an electromagnetic RADAR sensor. The LiDAR sensor 178 can also automatically create a geofence for a RADAR system by using artificial intelligence (AI) to detect and classify features in space that may pose a problem to the RADAR system, such as glass windows (which may be highly reflective to RADAR). LiDAR can also be used to estimate a person's height, as well as changes in height that occur when a person sits down, falls, etc. LiDAR can be used to create a 3D mesh representation of the environment. In a further application, for solid surfaces through which radio waves pass (e.g., radio-transparent materials), LiDAR can reflect off such surfaces, allowing classification of different types of obstacles.

[0082] In some implementations, the one or more sensors 130 also include a galvanic skin response (GSR) sensor, a blood flow sensor, a respiration sensor, a pulse sensor, a blood pressure sensor, an oximetry 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 direction sensor, a rain sensor, a soil moisture sensor, a water flow sensor, an alcohol sensor, or any combination thereof.

[0083] 1 , any combination of one or more sensors 130 may be integrated with and / or coupled to any one or more of the components of system 100, including respiratory treatment device 122, user interface 124, conduit 126, humidification tank 129, control system 110, user device 170, or any combination thereof. For example, microphone 140 and speaker 142 are integrated with and / or coupled to user device 170, and pressure sensor 130 and / or flow sensor 132 are integrated with and / or coupled to respiratory treatment device 122. In some implementations, at least one of the one or more sensors 130 is not coupled to respiratory treatment device 122, control system 110, or user device 170, but is positioned generally adjacent to user 210 during a sleep session (e.g., placed on or in contact with a portion of user 210, worn by user 210, coupled to or positioned on a nightstand, coupled to a mattress, coupled to a ceiling, etc.).

[0084] Data from one or more sensors 130 can be analyzed to determine one or more physiological parameters, which may include a respiratory signal, respiratory rate, respiratory pattern or morphology, respiratory rate variability, inhalation amplitude, exhalation amplitude, inhalation to exhalation ratio, length of time between breaths, maximum inhalation time, maximum exhalation time, mandatory breathing parameters (e.g., distinction between respiratory release and mandatory exhalation), occurrence of one or more events, number of events per hour, pattern of events, sleep state, sleep stage, apnea hypopnea index (AHI), heart rate, heart rate variability, movement of the user 210, temperature, EEG activity, EMG activity, ECG data, sympathetic response parameters, parasympathetic response parameters, or any combination thereof. The one or more events may include snoring, apnea, central apnea, obstructive apnea, mixed apnea, hypopnea, intentional mask leak, unintentional mask leak, mouth leak, coughing, restless legs, sleep disorder, choking, increased heart rate, labored breathing, asthma attack, epileptic episode, seizure, elevated blood pressure, or any combination thereof. While many of these physiological parameters are sleep-related parameters, in some cases, data from one or more sensors 130 may 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 may also be determined based on either data from one or more sensors 130 or other types of data.

[0085] User device 170 ( FIG. 1 ) includes a display device 172. User device 170 can be, for example, 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 television), or another smart home device (e.g., a smart speaker, optionally having a display, such as a Google Home®, Google Nes®, Amazon Echo®, Amazon Echo Show®, or Alexa®-enabled device). In some implementations, user device 170 is a wearable device (e.g., a smart watch). Display device 172 is typically used to display images, including still images, moving images, or both. In some implementations, display device 172 functions 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, an OLED display, an LCD display, or the like. The input interface may be, for example, a touch screen or touch-sensitive board, a mouse, a keyboard, or any sensor system configured to sense inputs made by a human user interacting with user device 170. In some implementations, one or more user devices may be used by and / or included in system 100.

[0086] Light source 180 is generally used to emit light having an intensity and wavelength (e.g., color). For example, light source 180 can emit light having a wavelength between about 380 nm and about 700 nm (e.g., wavelengths in the visible light spectrum). Light source 180 can include, for example, one or more light-emitting diodes (LEDs), one or more organic light-emitting diodes (OLEDs), light bulbs, lamps, incandescent bulbs, CFL bulbs, halogen bulbs, or any combination thereof. In some implementations, the intensity and / or wavelength (e.g., color) of light emitted from light source 180 can be changed by control system 110. Light source 180 can also emit light in a predetermined emission pattern, such as, for example, continuous emission, pulsed emission, periodic emission of different intensities (e.g., an emission cycle including a gradual increase in intensity followed by a decrease in intensity), or any combination thereof. Light emitted from light source 180 can be viewed directly by a user or can be reflected or refracted before reaching a user. In some implementations, light source 180 includes one or more light pipes.

[0087] In some implementations, the light source 180 is physically coupled to or integrated with the respiratory treatment system 120. For example, the light source 180 can be physically coupled to or integrated with the respiratory treatment device 122, the user interface 124, the conduit 126, the display device 128, or any combination thereof. In some implementations, the light source 180 is physically coupled to or integrated with the user device 170 or the activity tracker 190. In other implementations, the light source 180 is separate and distinct from each of the respiratory treatment system 120, the user device 170, and the activity tracker 190. In such implementations, the light source 180 can be positioned, for example, on a nightstand 240, a bed 230, other furniture, a wall, a ceiling, etc., facing the user 210 ( FIG. 2 ).

[0088] The activity tracker 190 is generally used to help generate physiological data for determining activity metrics associated with a user. Activity metrics may include, for example, number of steps, distance traveled, number of steps climbed, duration of physical activity, type of physical activity, intensity of physical activity, time spent standing, respiration rate, average respiration rate, resting respiration rate, maximum respiration rate, respiration rate variability, heart rate, average heart rate, resting heart rate, maximum heart rate, heart rate variability, calorie expenditure, blood oxygen saturation (SqO2), electrodermal activity (also known as skin conductance or galvanic skin response), user position, user posture, or any combination thereof. The activity tracker 190 may include one or more sensors 130 described herein, such as, for example, a motion sensor 138 (e.g., one or more accelerometers and / or gyroscope), a PPG sensor 154, and / or an ECG sensor 156.

[0089] In some implementations, the activity tracker 190 is a wearable device that can be worn by a user, such as a smartwatch, wristband, ring, or patch. For example, referring to FIG. 2 , the activity tracker 190 is worn on the wrist of the user 210. The activity tracker 190 can also be coupled to or integrated with an outfit or garment worn by the user. Alternatively, the activity tracker 190 can be coupled to or integrated (e.g., within the same housing) with the user device 170. More generally, the activity tracker 190 can be communicatively coupled to or physically integrated (e.g., within the housing) with the control system 110, the memory 114, the respiratory treatment system 120, and / or the user device 170.

[0090] 1 describes and illustrates control system 110 and memory device 114 as separate and distinct components of system 100, in some implementations control system 110 and / or memory device 114 are integrated into user device 170 and / or respiratory treatment device 122. Alternatively, in some implementations control system 110 or portions thereof (e.g., processor 112) can be located in the cloud (e.g., integrated into a server, integrated into an Internet of Things (IoT) device, connected to the cloud, subject to edge cloud processing, etc.), located on one or more servers (e.g., remote servers, local servers, etc., or any combination thereof).

[0091] Although system 100 is shown as including all of the above components, implementations of the present disclosure may include more or fewer components in a system for generating physiological data and determining recommended notifications or actions for a user. For example, a first alternative system includes control system 110, memory device 114, and at least one of one or more sensors 130. As another example, a second alternative system includes control system 110, memory device 114, at least one of one or more sensors 130, and user device 170. As yet another example, a third alternative system includes control system 110, memory device 114, respiratory treatment system 120, at least one of one or more sensors 130, and user device 170. Thus, any portion of the components shown and described herein may be used and / or combined with one or more other components to form a variety of systems.

[0092] 3A and 3B, a user interface 300 is shown according to some implementations of the present disclosure. The user interface 300 can be the same as or similar to the user interface 124 (FIGS. 1 and 2) and can be used with the system 100 described herein. The user interface 300 includes a strap assembly 310, a cushion 330, a frame 350, and a connector 370. The strap assembly 310 is configured to be generally positioned around at least a portion of a user's head when the user wears the user interface 300. The strap assembly 310 is coupled 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.

[0093] In some implementations, the cushion 330 is positioned between the user's face and the frame 350 to form a seal with the user's face. A first end 372A of the connector 370 can be coupled to the frame 350, and a second end 372B of the connector 370 can be coupled to a conduit (e.g., the conduit 126 shown in FIGS. 1 and 2 ). The conduit can then be coupled to an air outlet of a respiratory treatment device (e.g., a respiratory treatment device 122 described herein). A blower motor within the respiratory treatment device is operable to flow pressurized air from the air outlet, thereby providing the pressurized air to the user. The pressurized air can flow from the respiratory treatment device through the conduit, the connector 370, the frame 350, and the cushion 330 until the air reaches the user's airway through the user's mouth, nose, or both.

[0094] The strap assembly 310 is formed from a rear portion 312, a pair of upper straps 314A and 314B, and a pair of lower straps 316A and 316B. The rear portion 312 of the strap assembly is generally positioned behind the user's head when the user wears the user interface 300. The upper straps 314A, 314B and the lower straps 316A, 316B extend from the rear portion 312 toward the front of the user's face. In the illustrated implementation, the rear portion 312 is circular. However, the rear portion 312 may have other shapes. The rear portion 312, the upper straps 314A, 314B, and the lower straps 316A, 316B may be formed or woven from a generally stretchable or resilient material, such as fabric, elastic, rubber, or any combination of materials. In some implementations, the strap assembly 310 has a hollow interior or channel through which electrical wires or traces may extend, as described in further detail below.

[0095] Upper straps 314A, 314B and lower straps 316A, 316B each have a first end that originates from rear portion 312 and a second end that connects to frame 350. When a user wears user interface 300, tension provided by strap assembly 310 holds frame 350 against the user's face, thus securing user interface 300 to the user's head.

[0096] In some implementations, a tension sensor can be embedded in one of the straps of the strap assembly. For example, FIG. 3B shows a tension sensor 313 embedded in an upper strap 314A. The tension sensor 313 is configured to measure the tension of the strap of the user interface 124. As discussed, the user interface 124 is generally secured to the head of the user 210 using a strap that may be fastened using a hook-and-loop fastener. The tension sensor 313 can sense the tension of the strap, which can then be used to inform and / or instruct the user 210 about the correct fitting of the user interface 124. The tension sensor 313 can be incorporated into threads, fibers, wires, carbon fibers, warp threads, webs, etc. As the tension of the strap increases or decreases, the sensor element of the tension sensor 313 deflects, changing the voltage of the output signal. The tension sensor 313 can have high elasticity, low resistance, and be washable. In some implementations, the tension sensor 313 measures the diameter of the inflatable body by the principles of respiratory inductance plethysmography. The tension sensor 313 can also be an electrical impedance plethysmography sensor, a magnetometer, a strain gauge sensor, or can be made of a piezoresistive material displacement sensor.

[0097] Frame 350 is generally formed from a body 352 defining a first surface 354A and an opposing second surface 354B. When a user wears user interface 300, first surface 354A faces away from the user's face, and second surface 354B faces toward the user's face. The frame also defines an annular opening 356 through which cushion 330 and connector 370 can be inserted, thereby physically coupling cushion 330 and connector 370 to frame 350.

[0098] The cushion 330 can be coupled to the inside of the frame 350 adjacent the second surface 354B such that the cushion 330 is positioned between the user's face and the frame 350. The cushion 330 can be made from the same or similar material as the cushion of the user interface 124, for example, a conformal material that helps form an airtight seal with the user's face. The cushion 330 defines an opening 336 and includes an annular protrusion 338 extending from the cushion 330 around the opening 336 in the cushion. The annular protrusion 338 is inserted into the annular opening 356 of the frame 350 such that the annular opening 336 of the cushion 330 overlaps with the annular opening 356 of the frame 350. In some implementations, the annular protrusion 338 of the cushion 330 is releasably secured to the body 352 of the frame 350 via a friction fit between the annular protrusion 338 and the body 352 around the annular opening 356.

[0099] In other implementations, the annular protrusion 338 and the frame 350 can have mating features that mate with each other to secure the cushion 330 to the frame 350. For example, the annular protrusion 338 of the cushion 330 can include an outwardly extending peripheral flange, and the body 352 of the frame 350 can include a corresponding inwardly extending peripheral flange around the annular opening 356. When the annular protrusion 338 of the cushion 330 is inserted into the annular opening 356 of the frame 350, the peripheral flanges can slide or snap together, thereby securing the cushion 330 to the frame 350. In additional implementations, the cushion 330 is held in place by tension provided by the strap assembly 310 and is not physically coupled to the frame 350. In still other implementations, the cushion 330 and the frame 350 can be formed as a single, integral piece.

[0100] Connector 370 can be coupled to the opposite side of frame 350 in a similar manner to cushion 330. A first end 372A of connector 370 has a generally cylindrical shape and can be inserted into annular opening 356 of frame 350 such that a hollow interior 376 of end 372A overlaps annular opening 356 and opening 336 of cushion 330. An opposite second end 372B of connector 370 is then coupled to a conduit such that the user's face (including the user's mouth and / or nose) is in fluid communication with the conduit through cushion 330, frame 350, and connector 370.

[0101] First end 372A of connector 370 is generally annular in shape and fits into annular opening 356 of frame 350. Frame 350 also includes an annular protrusion 358 extending from second surface 354B of frame 350 and formed around annular opening 356. When first end 372A is inserted into annular opening 356 of frame 350, the inner surface of annular protrusion 358 overlaps the outer surface of first end 372AA of connector 370.

[0102] In some implementations, a friction fit between the annular protrusion 358 and the first end 372A secures the connector 370 to the frame 350. In other implementations, the connector 370 may include a fastener 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 fasteners are one or more deflectable latches formed on the first end 372A of the connector 370. When the first end 372A is slidably inserted into the annular protrusion 358, the deflectable latch slides over the peripheral flange such that the deflectable latch is positioned outside the annular protrusion 358. When the deflectable latch clears the peripheral flange, the peripheral flange pushes the deflectable latch away from the annular protrusion 358. The deflectable latch then returns to its original position so that the connector 370 will not disengage from the frame 350 unless the deflectable latch is manually biased away from the annular projection 358 .

[0103] The frame 350 includes a T-shaped extension strip 360 that extends upward from the upper end 351A of the main body 352. In some implementations, the extension strip 360 is integrally formed with the main body 352. In other implementations, the extension strip 360 is a separate component coupled to the main body 352. When a user wears the user interface 300, the extension strip 360 extends generally to the user's forehead. In some implementations, the extension strip 360 includes a cooling portion or mechanism that contacts and cools the forehead of the user 210, which can help a user with insomnia fall asleep.

[0104] Lower straps 316A, 316B extend from rear portion 312 of strap assembly 310 toward frame 350 and are coupled to opposite sides of lower end 351B of body 352. Upper straps 314A, 314B extend from rear portion 312 of strap assembly 310 toward frame 350 and are coupled to opposite sides of upper end 361 of extension strip 360 (e.g., at the generally horizontal "cross" of a T). Frame 350 can include a variety of different strap attachment points for coupling with upper straps 314A, 314B and lower straps 316A, 316B.

[0105] One type of strap attachment point is shown on extension strip 360. The top end 361 of extension strip 360 includes two openings 362A, 362B. These openings may be integrally formed in extension strip 360 itself or may be formed as part of a separate component or part that is coupled to extension strip 360. Openings 362A, 362B are shaped to allow ends 315A, 315B of upper straps 314A, 314B to be inserted through openings 362A, 362B. Ends 315A, 315B can then be looped back and secured to the remainder of upper straps 314A, 314B via any suitable mechanism, such as hook-and-loop fasteners, adhesive, or the like. Thus, upper straps 314A, 314B are secured to extension strip 360 of frame 350.

[0106] Frame 350 is shown with different types of strap attachment points used to couple lower straps 316A, 316B to frame 350. Frame 350 includes two side strips 364A, 364B extending away from opposite ends of lower end 351B of body 352. A first end of each side strip 364A, 364B is coupled to body 352, and a corresponding magnet 366A, 366B is disposed at the second end of each side strip 364A, 364B. Magnet 318A is coupled to end 317A of lower strap 316A, and magnet 318B is coupled to end 317B of lower strap 316B. Magnet 318A can be secured to magnet 366A via magnetic attraction, and magnet 318B can be secured to magnet 366B via magnetic attraction, thereby coupling lower straps 316A, 316B to body 352 of frame 350.

[0107] In some implementations, the frame 350 does not include the extension strips 360, and instead the top straps 314A, 314B are coupled to the frame above the side strips 364A, 364B. The top straps 314A, 314B in these implementations extend past the temples of the user 210 and around to the back of the head of the user 210. The frame 350 may also include top side strips to which the top straps 314A, 314B are coupled.

[0108] The user interface 300 may also include one or more sensors 390. While FIG. 3B generally shows only a single sensor, any number of sensors may be coupled to the strap assembly 310. In some implementations, the one or more sensors 390 are coupled to the strap assembly 310 and configured to be adjacent a target area of ​​the user when the user wears the user interface 300. The target area may be the user's forehead, temples, throat, neck, ears, etc. In other implementations, the one or more sensors 390 are not coupled to the strap assembly 310 but instead are located elsewhere within the user interface 300, such as within the connector 370. The sensors 390 may be any one or more of the sensors 130 described herein with respect to FIG. 1 and may additionally or alternatively include other types of sensors.

[0109] In some implementations, the one or more sensors 390 include one or more contact sensors that contact a target area of ​​the user. For example, the one or more sensors 390 can 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 galvanic skin response (GSR) sensor, or any combination thereof.

[0110] 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 CO2 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.

[0111] In further implementations, the 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 strap assembly 310, but instead are located on the cushion 330, the frame 350, or the connector 370. Furthermore, the user interface 300 can include multiple non-contact sensors located in any combination of these locations.

[0112] Generally, one or more sensors 390 of user interface 300 need to be electrically connected to a control system and memory device of the respiratory treatment system (such as control system 110 and memory device 114 of system 100) to transmit data to the control system and memory device. This data can be used to modify the operation of the ventilator device, and can be used for other purposes as well. To transmit data from one or more sensors 390 to the control system and memory device, one or more sensors 390 can be electrically connected to various portions of user interface 300, including frame 350 and connector 370. Data from one or more sensors 390 can be transmitted using electrical connections between one or more sensors 390, frame 350, and connector 370. Therefore, if one or more sensors 390 are located in user interface 300, the one or more sensors 390 need to be electrically connectable to the control system and memory device.

[0113] As used herein, a sleep session can be defined in several ways, for example, based on an initial start time and an end time. Referring to FIG. 1, an exemplary timeline 400 of a sleep session is shown. The timeline 400 includes a time from bedtime (t bed ) and sleep onset time (t GTS ) and initial sleep time (t sleep ), the first micro-awakening MA1, the second micro-awakening MA2, and the wake-up time (t wake ) and wake-up time (t rise ) and includes.

[0114] In some implementations, a sleep session is the duration of time that a user is asleep. In such implementations, a sleep session has a start time and an end time, and during a sleep session, the user does not wake up until the end time. That is, the time that the user is awake is not included in the sleep session. From this first definition of a sleep session, if a user wakes up and falls asleep multiple times in one night, each sleep period separated by a wake period constitutes a sleep session.

[0115] Alternatively, in some implementations, a sleep session has a start time and an end time, and during a sleep session, the user may wake up without the sleep session ending as long as the continuous duration the user is awake is below a wakefulness duration threshold. The wakefulness duration threshold can be defined as a percentage of the sleep session. The wakefulness duration threshold can be, for example, about 20 percent of the sleep session, about 15 percent of the sleep session duration, about 10 percent of the sleep session duration, about 5 percent of the sleep session duration, about 2 percent of the sleep session duration, or any other threshold percentage. In some implementations, the wakefulness duration threshold is defined as a certain amount of time, such as about 1 hour, about 30 minutes, about 15 minutes, about 10 minutes, about 5 minutes, about 2 minutes, or any other amount of time.

[0116] In some implementations, a sleep session is defined as the total time from when a user first goes to bed that night to when the user last gets out of bed the next morning. In other words, a sleep session can be defined as the time beginning at a first time (e.g., 10:00 PM) on a first date (e.g., Monday, January 6, 2020) that may refer to the current night when the user first goes to bed with the intention to sleep (as opposed to, for example, when the user first intends to watch TV or use their smartphone before going to sleep) and ending at a second time (e.g., 7:00 AM) on a second date (e.g., Tuesday, January 7, 2020) that may refer to the next morning when the user first wakes up with the intention not to go back to sleep that next morning.

[0117] In some implementations, a user may manually define the start of a sleep session and / or manually end a sleep session. For example, a user may select (e.g., by clicking or tapping) a user-selectable element displayed on display device 172 ( FIG. 1 ) of user device 170 to manually start or end a sleep session.

[0118] bedtime t bed is associated with the time the user first enters bed (e.g., bed 230 in FIG. 2) before falling asleep (e.g., when the user is lying down or sitting in bed). bed can be identified based on a bedtime threshold duration to distinguish between a time when a user goes to bed to sleep and a time when a user goes to bed for other reasons (e.g., to watch television). For example, the bedtime threshold duration can be at least about 10 minutes, at least about 20 minutes, at least about 30 minutes, at least about 45 minutes, at least about 1 hour, at least about 2 hours, etc. As used herein, the bedtime t in relation to a bed is bed However, more generally, the bedtime t bed may represent the time when a user first settles down to sleep in some location (e.g., sofa, chair, sleeping bag, etc.).

[0119] The time of sleep onset (GTS) is the time when the user goes to bed (t bed ) is associated with the time when the user first attempts to fall asleep after getting into bed. For example, after getting into bed, the user may engage in one or more activities to relax before trying to fall asleep (e.g., reading, watching television, listening to music, using the user device 170, etc.). The initial sleep time (t sleep ) is the time when the user first falls asleep. For example, the initial sleep time (t sleep ) may be the time when the user first entered the first non-REM sleep stage.

[0120] wake up time t wake is the time associated with the time the user wakes up without going back to sleep (as opposed to, for example, the user waking up in the middle of the night and going back to sleep). After the user initially falls asleep, they may experience one of many involuntary micro-awakenings (e.g., micro-awakenings MA1 and MA2) that have short durations (e.g., 4 seconds, 10 seconds, 30 seconds, 1 minute, etc.). The wake-up time t wake In contrast to the above, the user goes through micro-awakenings MA1 and MA2, respectively, and then falls asleep again. Similarly, the user may have one or more conscious awakenings (e.g., Awakening A) after initially falling asleep (e.g., waking 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 user may wake up at the wake-up time t wake can be defined, for example, based on the wake-up threshold duration (eg, the user has been awake for 15 minutes or more, 20 minutes or more, 30 minutes or more, 1 hour or more, etc.).

[0121] Similarly, the wake-up time t rise is associated with the time when the user gets up and is absent from bed with the intent of ending a sleep session (as opposed to, for example, the user getting up to go to the bathroom during the night, caring for a child or pet, sleepwalking, etc.). In other words, the wake-up time t rise is the time when the user last left bed without returning to bed until the next sleep session (e.g., the next night). Therefore, the wake-up time t risecan be defined, for example, based on a wake-up threshold duration (e.g., the user has left bed for 15 minutes or more, 20 minutes or more, 30 minutes or more, 1 hour or more, etc.). bed can also be defined based on wake threshold duration (eg, when the user has been out of bed for more than 4 hours, more than 6 hours, more than 8 hours, more than 12 hours, etc.).

[0122] As mentioned above, the user must first bed to the last t rise In some implementations, the patient may wake up and leave the bed one or more times during the night. wake and / or last wake-up time t rise The threshold duration is identified or determined based on a predetermined threshold duration of time following an event (e.g., falling asleep or leaving bed). Such threshold duration can be customized for the user. For a typical user who goes to bed at night and wakes up and gets out of bed in the morning, the threshold duration can be any time between about 12 hours and about 18 hours (between the time the user wakes up (t)). wake ) or wake up (t rise ) and the user goes to bed (t bed ), falling asleep (t GTS ) or sleep (t sleep ) can be used. For users who sleep longer, a shorter threshold period (e.g., between about 8 hours and about 14 hours) can be used. The threshold period may be initially selected and / or later adjusted based on the system monitoring the user's sleep behavior.

[0123] Total time in bed (TIB) is the time from bedtime t bed From wake-up time t riset. The total sleep time (TST) is the duration from the initial sleep time t to the wake-up time, excluding conscious or unconscious awakenings and / or microarousals in between. Typically, the total sleep time (TST) will be shorter than the total time in bed (TIB) (e.g., 1 minute shorter, 10 minutes shorter, 1 hour shorter, etc.). For example, referring to the timeline 401 of FIG. 4, the total sleep time (TST) is the duration from the initial sleep time t sleep and alarm time t wake , but excluding the duration of the first micro-awakening MA1, the second micro-awakening MA2, and the awakening A. As shown, in this example, the total sleep time (TST) is less than the total time in bed (TIB).

[0124] In some implementations, total sleep time (TST) can be defined as total continuous sleep time (PTST). In such implementations, total continuous sleep time excludes a predetermined initial portion or period of a first non-REM stage (e.g., a light sleep stage). For example, this predetermined initial portion can be about 30 seconds to about 20 minutes, about 1 minute to about 10 minutes, about 3 minutes to about 5 minutes, etc. Total continuous sleep time is a measure of continuous sleep and smooths the sleep-wake hypnogram. For example, when a user first falls asleep, the user may enter the first non-REM stage for a very short time (e.g., about 30 seconds), then return to a wakefulness stage for a short time (e.g., 1 minute), before returning to the first non-REM stage. In this example, total continuous sleep time excludes the first instance (e.g., about 30 seconds) of the first non-REM stage.

[0125] In some implementations, a sleep session begins at bedtime (t bed ) and wake-up time (t rise ), i.e., a sleep session is defined as the total time in bed (TIB). In some implementations, a sleep session is defined as ending at the initial sleep time (t sleep ) and wake up at the alarm time (t wake) In some implementations, a sleep session is defined as total sleep time (TST). In some implementations, a sleep session is defined as a sleep session ending at sleep onset time (t GTS ) and wake up at the alarm time (t wake ) In some implementations, a sleep session is defined as ending at sleep onset time (t GTS ) and wake-up time (t rise ) In some implementations, a sleep session is defined as ending at bedtime (t bed ) and wake up at the alarm time (t wake ) In some implementations, a sleep session is defined as ending at an initial sleep time (t sleep ) and wake-up time (t rise ) is defined as ending in

[0126] 1, an exemplary hypnogram 500 corresponding to the timeline 401 (FIG. 4) is shown according to some implementations. As shown, the hypnogram 500 includes a sleep-wake signal 501, a wake 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 the axes 510-540 indicates the sleep stage at any given time during the sleep session.

[0127] The sleep-wake signal 501 can be generated based on physiological data associated with the user (e.g., generated by one or more of the sensors 130 (FIG. 1) described herein). The sleep-wake signal can indicate one or more sleep states or stages, including a wakefulness state, a relaxed wakefulness state, a microarousal state, a REM stage, a first non-REM stage, a second non-REM stage, a third non-REM stage, or any combination thereof. In some implementations, one or more of the first non-REM stage, the second non-REM stage, and the third non-REM stage can be grouped and classified as a light sleep stage or a deep sleep stage. For example, a light sleep stage may include a first non-REM stage, and a deep sleep stage may include a second non-REM stage and a third non-REM stage. 5 shows the hypnogram 500 as including a light sleep stage axis 530 and a deep sleep stage axis 540, in some implementations the hypnogram 500 can include an axis for each of a first non-REM stage, a second non-REM stage, and a third non-REM stage. In other implementations, the sleep-wake signal can indicate a respiratory signal, a respiratory rate, an inhalation amplitude, an exhalation amplitude, an inhalation-exhalation ratio, an event count per hour, an event pattern, or any combination thereof. Information describing the sleep-wake signal can be stored in the memory device 114.

[0128] The hypnogram 500 can be used to determine one or more sleep-related parameters, such as, for example, sleep onset latency (SOL), wake-up-after-sleep (WASO), sleep efficiency (SE), sleep fragmentation index, sleep blocks, or any combination thereof.

[0129] Sleep onset latency (SOL) is the time of sleep onset (t GTS ) to the initial sleep time (t sleep) In other words, sleep onset latency indicates the time it takes from the user's first attempt to fall asleep to actually falling asleep. In some implementations, sleep onset latency is defined as persistent sleep onset latency (PSOL). Continuous sleep onset latency differs from sleep onset latency in that it is defined as the duration from the time of sleep onset to a predetermined amount of continuous sleep. In some implementations, the predetermined amount of continuous sleep may include, for example, at least 10 minutes of sleep in the second non-REM stage, the third non-REM stage, and / or within a REM stage with 2 minutes or less of wake, the first non-REM stage, and / or transitions therebetween. In other words, continuous sleep onset latency requires, for example, a maximum of 8 minutes of continuous sleep in the second non-REM stage, the third non-REM stage, and / or the REM stage. In other implementations, the predetermined amount of continuous sleep can include at least 10 minutes of sleep in a first non-REM stage, a second non-REM stage, a third non-REM stage, and / or a REM stage following the initial sleep time. In such implementations, the predetermined amount of continuous sleep can exclude any microarousals (e.g., after a 10-second microarousal, the 10 minutes are not resumed).

[0130] A wake-up-after-sleep-onset (WASO) is associated with the total duration a user is awake between the initial sleep time and the wake-up time. Thus, a wake-up-after-sleep-onset (WASO) includes brief microarousals (e.g., microarousals MA1 and MA2 shown in FIG. 4 ) during a sleep session, whether conscious or unconscious. In some implementations, a wake-up-after-sleep-onset (WASO) is defined as a persistent wake-up-after-sleep-onset (PWASO), which includes only total durations of awakenings having a predetermined length (e.g., 10 seconds or more, 30 seconds or more, 60 seconds or more, about 5 minutes or more, about 10 minutes or more, etc.).

[0131] Sleep efficiency (SE) is determined as the ratio of total time in bed (TIB) to total sleep time (TST). For example, if the total time in bed is 8 hours and the total sleep time is 7.5 hours, the sleep efficiency for that sleep session is 93.75%. Sleep efficiency indicates a user's sleep hygiene. For example, if a user goes to bed and spends time on other activities (e.g., watching TV) before going to sleep, sleep efficiency decreases (e.g., the user is penalized). 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 fall asleep. In such implementations, the total time the user attempts to fall asleep is defined as the duration from the GTS time to the wake-up time as described herein. For example, in an implementation where the total sleep time is 8 hours (e.g., from 11 PM to 7 AM), the fall asleep time is 10:45 PM, and the wake-up time is 7:15 AM, the sleep efficiency parameter is calculated to be approximately 94%.

[0132] The fragmentation index is determined based at least in part on the number of arousals during a sleep session. For example, if a user had two micro-arousals (e.g., micro-arousals MA1 and MA2 shown in FIG. 5), the fragmentation index may be expressed as 2. In some implementations, the fragmentation index is scaled between a predetermined range of integers (e.g., between 0 and 10).

[0133] Sleep blocks are associated with transitions between any sleep stage (e.g., a first non-REM stage, a second non-REM stage, a third non-REM stage, and / or REM) and a wake stage. For example, sleep blocks can be calculated with a 30-second resolution.

[0134] In some implementations, the systems and methods described herein generate or analyze a hypnogram including a sleep-wake signal to determine a time to bed (t) based at least in part on the sleep-wake signal of the hypnogram. bed ), sleep onset time (t GTS ), initial sleep time (t sleep ), one or more first micro-arousals (e.g., MA1 and MA2), wake-up time (twake ), wake-up time (t rise ), or any combination thereof.

[0135] In other implementations, one or more of the sensors 130 are used to measure bedtime (t bed ), sleep onset time (t GTS ), initial sleep time (t sleep ), one or more first micro-arousals (e.g., MA1 and MA2), wake-up time (t wake ), wake-up time (t rise ) or any combination thereof to define a sleep session. bed may be determined based on data generated by, for example, motion sensor 138, microphone 140, camera 150, or any combination thereof. Sleep onset time may be determined based on, for example, data from motion sensor 138 (e.g., data indicating no movement by the user), data from camera 150 (e.g., data indicating no movement by the user and / or that the user has turned off the lights), data from microphone 140 (e.g., data indicating that the user has turned off the television), 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 has turned on respiratory treatment device 122, data indicating that the user has put on user interface 124, etc.), or any combination thereof, etc.

[0136] 1, a method 600 for assisting a user is shown in accordance with some implementations of the present disclosure. One or more steps or aspects of the method 600 may be implemented using any portion or aspect of the system 100 described herein.

[0137] Step 601 of method 600 includes receiving physiological data associated with a user. The physiological data can be generated and received by one or more of the sensors 130 (FIG. 1) described herein. The received physiological data can be indicative of one or more physiological parameters, such as, for example, movement, heart rate, heart rate variability, cardiac waveform, respiration rate, respiration rate variability, respiration depth, tidal volume, inspiration amplitude, inspiration duration, expiration amplitude, expiration duration, inspiration-to-expiration ratio, sweating, temperature (e.g., ambient temperature, body temperature, core temperature, surface temperature, etc.), blood oxygenation, photoplethysmography, pulse transit time, blood pressure, peripheral arterial tone, cardiogenic oscillations, galvanic skin response, sympathetic nervous system response, pulse transit time, heart rate-related trends, respiration rate-related trends, galvanic skin response-related trends, or any combination thereof. The physiological data may be received from at least one of the one or more sensors 130 by, for example, the electronic interface 119 and / or the user device 170 described herein and stored in memory 114 ( FIG. 1 ). The physiological data may be received directly or indirectly (e.g., through one or more intermediaries) by the electronic interface 119 or the user device 170 from at least one of the one or more sensors 130. The physiological data may include audio, which may be indicative of stress / anxiety, and may be received by the microphone 140. The microphone 140 may be incorporated into a microphone sensor (e.g., an Amazon® Halo device).

[0138] In some implementations, physiological data is generated during at least a portion of a sleep session. For example, a first portion of physiological data for a sleep session may be associated with the first day (e.g., Monday) before or when a user begins the sleep session. If the first sleep session is extended into the next day (e.g., Tuesday) before it ends, the physiological data may also be associated with a portion of the second day. In this example, the first portion of physiological data may be associated with any portion of the sleep session (e.g., 10% of the sleep session, 25% of the sleep session, 50% of the sleep session, 100% of the sleep session, etc.).

[0139] In some implementations, the physiological data received in step 601 is generated or acquired (e.g., by one or more of the sensors 130) before the user puts on or wears the user interface 124. In other implementations, the physiological data is generated before or after the user puts on or wears the user interface 124. In such implementations, the physiological data can be generated by a first sensor of the one or more sensors 130 (e.g., a sensor physically coupled to or integrated with the user device 170 or the activity tracker 190) before the user puts on the user interface 124 and by a second sensor of the one or more sensors 130 (e.g., a sensor physically coupled to or integrated with the respiratory treatment system 120) after the user puts on the user interface 124.

[0140] Step 602 of method 600 includes determining a first affective score associated with the user based at least in part on the physiological data. Generally, the affective score indicates the anxiety or stress the user is currently experiencing. For example, the user may experience anxiety, stress, concern, discomfort, etc. when wearing the user interface 124 of the respiratory treatment system 120, especially when the user is not accustomed to wearing the user interface 124. Increased levels of stress, anxiety, discomfort, etc. may make it difficult for the user to fall asleep and / or may lead the user to abandon use of the respiratory treatment system 120. Quantifying the user's stress or anxiety via the affective score can be used to suggest or recommend actions or activities to reduce the anxiety or stress and assist the user in falling asleep and becoming accustomed to using the respiratory treatment system 120.

[0141] The affect score can be an absolute value or a relative value. The affect score can be, for example, a number on a predetermined scale (e.g., between 1 and 100, between 1 and 100, etc.), a letter grade (e.g., A, B, C, D, or F), or a descriptive term (e.g., high, low, average, poor, normal, abnormal, fair, good, excellent, average, below average, above average, needs improvement, satisfactory, etc.). In some implementations, the affect score is determined relative to a previous affect score (e.g., the affect score is better than the previous affect score (e.g., the affect score from the previous day), the affect score is worse than the previous affect score, the affect score is the same as the previous affect score, etc.) or a baseline affect score (e.g., the affect score is 50% higher than the baseline affect score, the affect score is equal to the baseline affect score, etc.). In some implementations, the previous affect score can be the target affect score. Examples of target emotion scores include a score where the user was able to fall asleep, a score where the user had a short sleep onset latency, etc.

[0142] In some implementations, quantification of a user's stress or anxiety can be based on a change from a baseline emotion score, which can take the form of a difference (relative or absolute) from a target emotion score.

[0143] In some implementations, the physiological data generated before the user puts on or wears the user interface 124 in step 601 represents a baseline emotional score. In some implementations, the baseline emotional score can be determined from the physiological data when the user is expected to be relaxed (e.g., when the user is going to sleep, when the user has just fallen asleep, etc.). The physiological data indicative of sleep stages can be used to determine different times. The baseline emotional score can be determined from wearable electronics worn by the user (e.g., activity tracker 190), subjective information obtained by the user, etc. In some implementations, one or more prompts can be provided to the user to confirm the baseline emotional score.

[0144] In some implementations, step 602 may include determining one or more physiological parameters such as, for example, movement, 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-to-expiratory ratio, sweating, temperature (e.g., ambient temperature, body temperature, core body temperature, surface temperature, etc.), blood oxygenation, photoplethysmography (which may be used to measure, for example, SpO2, peripheral perfusion, peripheral arterial tone, pulse rate, other cardiac-related parameters, etc.), pulse transit time, blood pressure, cardiogenic oscillations, galvanic skin response, sympathetic nervous system response, pulse transit time, heart rate-related trends, respiratory rate-related trends, galvanic skin response-related trends, respiratory rate-related trends, or any combination thereof.

[0145] These physiological parameters may indicate a user's emotion or anxiety. For example, hyperventilation, increased respiratory rate (e.g., relative to a standard associated with the user, a standard for a group of users, a norm, etc.), decreased heart rate variability (e.g., relative to a standard associated with the user, a standard for a group of users, a norm, etc.), cardiac arrhythmia, heart rate, and blood pressure (e.g., adjusting for whether the user is hypertensive or non-hypertensive, nocturnal blood pressure drop, etc.) may indicate an elevated level of anxiety. Conversely, increased heart rate variability (e.g., relative to a standard associated with the user, a standard for a group of users, a norm, etc.) may indicate a more relaxed state. The emotion score may be determined at least in part by scaling or standardizing one or more of the physiological parameters based on the user's previously recorded physiological parameters stored in the user profile, previously recorded physiological parameters of multiple other users, or both. Alternatively, the emotion score may be determined by scaling the associated physiological parameter(s) by a desired or target value for the parameter(s).

[0146] Physiological parameters can be individualized. Physiological parameters can be monitored to determine whether they are within range. For example, a typical adult's respiratory rate is 12-20 breaths per minute (bpm), and a respiratory rate above 25 bpm may indicate anxiety / stress. Similarly, a typical adult's heart rate is 60-100 beats per minute, and a heart rate above 120 bpm may indicate anxiety / stress. An increase in body temperature may indicate anxiety or stress. Furthermore, if the value of a physiological parameter changes after a stimulus, such as the initiation of therapy or an increase in therapy pressure, but then returns to baseline values ​​relatively quickly (e.g., within 5-10 minutes or another predetermined period), an increase in the affective score may be acceptable. Because a slight increase in the affective score is temporary, the increase in the affective score is acceptable, and therefore no adjustment of the affective score (or a minimal number of prompts) is necessary.

[0147] In some implementations, step 602 further includes receiving subjective feedback from the user and determining an affect score based at least in part on the received subjective feedback. The subjective feedback may include, for example, self-reported user feedback indicating the user's current stress or anxiety level in the form of a descriptive indicator (e.g., high, low, medium, unknown), a numerical value (e.g., a scale of 1 to 10, with 10 being very stressed and 0 being no stress), or the like. The user's stress or anxiety level may be based on or correspond to a Likert scale. The subjective feedback may be received, for example, via user device 170. In such implementations, step 602 may include communicating one or more prompts to the user (e.g., via display device 172 of user device 170) to request subjective feedback.

[0148] In some implementations, step 602 includes determining the emotion score based at least in part on demographic information associated with the user. The demographic information may include information indicating the user's age, the user's gender, the user's weight, the user's body mass index (BMI), the user's height, the user's race, the user's relationship or marital status, a family history of insomnia, the user's employment status, the user's education status, the user's socioeconomic status, or any combination thereof. The demographic information may also include medical information associated with the user, such as indicating one or more medical conditions associated with the user, medication use by the user, or both. The demographic information may be received and stored by memory 114 (FIG. 1). The demographic information may be manually provided by the user, for example, via user device 170 (e.g., via a questionnaire or survey presented through display device 172). Alternatively, the demographic information may be collected automatically from one or more data sources associated with the user (e.g., medical records). Demographic information can be a useful input for determining the affective score, as certain physiological parameters (such as heart rate) can change as a function of age, medical condition, etc.

[0149] Step 603 of method 600 includes determining whether the first affective score satisfies a predetermined condition. Typically, the predetermined condition indicates that the user's anxiety or stress is at an acceptable level (e.g., so that the user can fall asleep, begin using respiratory treatment system 120, increase the pressure of the air delivered to the user via user interface 124, etc.). In other words, if the affective score meets the predetermined condition, the user is sufficiently relaxed to allow the user to fall asleep and / or use respiratory treatment system 120 and / or increase the pressure of the air delivered to the user via user interface 124. The acceptable level may be learned from the user when the user begins using respiratory treatment system 100, over multiple sleep sessions, and / or over a calibration period. The acceptable level may be learned from a population (e.g., a cohort) of users, normative values, etc.

[0150] For example, if a high emotional score indicates high anxiety or stress, the predetermined condition may be a numerical value that indicates that the user's anxiety or stress is at an acceptable level. In this example, if the emotional score is at or below the predetermined condition, the emotional score satisfies the predetermined condition.

[0151] In some implementations, the predetermined condition is determined based at least in part on previously recorded physiological data associated with the user. In such implementations, a machine learning algorithm can be used to determine the predetermined condition. The machine learning algorithm can be trained (e.g., using supervised or unsupervised training techniques) using previously recorded physiological data associated with the user to be configured to determine the predetermined condition. In such implementations, the previously recorded physiological data can include corresponding data regarding the user's sleep ability, such as sleep onset latency, wake-ups during sleep, sleep efficiency, fragmentation index, bedtime, total time in bed, total sleep time, or any combination thereof. The previously recorded data for training the machine learning algorithm can include subjective feedback from the user, as described herein. The previously recorded data for training the machine learning algorithm can be data from the user's population or a cohort of users living in a similar demographic to the user. Data from the cohort of users can be used for initial configuration before learning from the user's physiological data.

[0152] In some implementations, method 600 includes communicating one or more indicators of the determined emotional score to the user (e.g., in the form of a report). For example, the indicator of the determined emotional score can be communicated to the user via user device 170. The indicator can be communicated to the user before, during, or after the sleep session. Additionally or alternatively, the indicator of the determined emotional score can be communicated to a third party (e.g., a healthcare provider, a doctor, etc.). Additionally, method 600 can further include communicating one or more indicators of any of the sleep-related parameters described herein to the user. For example, the indicator of the sleep-related parameter can be communicated to the user via user device 170 before, during, or after the sleep session. Emotions and / or anxiety targeted by the emotional score can cause insomnia (e.g., anxiety-induced insomnia). Thus, tracking emotions through scoring can help explain a user's insomnia state.

[0153] Step 604 of method 600 includes, in response to determining (step 603) that the determined affective score (step 602) does not satisfy a predetermined condition, communicating one or more prompts to the user to assist in changing the affective score. The one or more prompts are generally used to help change (e.g., improve) the determined first affective score. The one or more prompts may include one or more visual prompts, one or more audio prompts, one or more tactile prompts, or any combination thereof. The one or more visual prompts may be communicated to the user, for example, via the display device 128 of the respiratory treatment system 120, via the display device 172 of the user device 170, via the light source 180, the activity tracker 190, or any combination thereof. The one or more audio and / or tactile prompts may be communicated to the user via a transducer, such as a speaker 142, which may be physically coupled to or integrated with the respiratory treatment device 122, the user device 170, or the activity tracker 190. The one or more audio and / or tactile prompts may be communicated to the user, for example, by user interface 124 and / or conduit 126 and / or by bone conduction. The one or more audio and / or tactile prompts may be delivered in a predetermined pattern, such as continuous, pulsed, periodic communications at different intensities, or any combination thereof.

[0154] In some implementations, step 604 includes communicating one or more visual prompts to the user via light source 180 to assist in modifying the affective score. As described herein, in some examples, light source 180 can be physically coupled to or integrated with respiratory treatment system 120. Alternatively, light source 180 can be physically separate and distinct from respiratory treatment system 120 (e.g., physically integrated with or coupled to user device 170, activity tracker 190, etc.). In such implementations, step 604 includes causing light source 180 to emit light having a predetermined color, a predetermined intensity, a predetermined frequency (e.g., light pulses), or any combination thereof. The one or more prompts can include, for example, changing the color of light emitted from light source 180, changing the intensity of light emitted from light source 180, or both.

[0155] As described above, step 602 may include, among other things, determining a respiratory rate associated with the user. Step 604 may include causing light source 180 to emit light pulses at a predetermined frequency to assist in changing (e.g., decreasing) the respiratory rate. For example, each light pulse may signal the user to inhale (e.g., at the beginning of the pulse) and / or exhale (e.g., at the end of the pulse) to assist in changing the respiratory rate and, therefore, the emotional score. In some implementations, based on the detected user's respiratory rate, the pattern of light pulses may initially reflect the user's respiratory rate and then gradually change (e.g., decrease) to prompt the user to change the user's respiratory rate to a desired respiratory rate and, therefore, the emotional score. Alternatively, step 602 may include communicating one or more prompts to the user to perform breathing exercises to assist in changing the respiratory rate and, therefore, the emotional score. In some implementations, the target breathing pattern may be superimposed on the pressure setting of the respiratory treatment system, for example, by introducing modulation to the motor RPM as a target pattern to provide gentle guided breathing without performing artificial ventilation. In such implementations, modulation can occur 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.) before or along with the pressure gradient that typically occurs at the beginning of a therapy session. The pressure gradient or target pressure can then continue once the emotional score meets predetermined conditions and / or the user enters sustained sleep.

[0156] As described above, in some examples, the user is wearing the user interface 124 when the first physiological data is being generated (step 601). Accordingly, in some implementations, the one or more prompts communicated to the user in step 604 may include a prompt or recommendation to remove the user interface 124 to assist in changing the affective 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 is removed, the user may be further prompted to perform a breathing exercise to further assist in changing the affective score.

[0157] In some implementations, the one or more prompts communicated to the user include one or more instructions for performing an activity. The instructions for performing an activity can be communicated visually (e.g., via alphanumeric text displayed on display device 172, images or pictures displayed on display device 172, etc.) and / or audibly (e.g., via user device 170 or speaker 142). The instructions can include, for example, instructions on how to assemble the various components of user interface 300 ( FIGS. 3A and 3B ) before wearing user interface 300. These assembly instructions for user interface 300 can include information regarding the function or purpose of each component and can generally assist in modifying the affective score.

[0158] In some implementations, the one or more prompts communicated to the user in step 604 can include media content to further assist in modifying the affective score. For example, the media content can include audio (e.g., music, e-books, etc.), video (e.g., television programs, movies), photos, etc. to assist in modifying the affective score. The media content can be delivered to the user, for example, via user device 170 or another device (e.g., television, laptop, tablet, etc.).

[0159] In some implementations, step 604 includes selecting one or more prompts to be communicated to the user. For example, the one or more prompts can be selected based at least in part on previously recorded data associated with the user (e.g., based on the user's previous responses to the one or more prompts). In such implementations, a machine learning algorithm can be trained using previously recorded physiological data and / or an emotional score associated with the user, recorded before and / or after the one or more prompts are communicated to the user. Thus, selecting the one or more prompts can include using a machine learning algorithm (e.g., using supervised or unsupervised techniques) trained to receive as input current physiological data and / or an emotional score associated with the user and determine as output one or more prompts to communicate to the user to assist in changing the determined emotional score. In this manner, the method can identify, for example, one or more prompts that enable the user's emotional score to achieve a predetermined condition. In certain implementations, the method can identify one or more prompts, such as instructions for deep breathing, altering the inhalation-to-exhalation ratio, etc., that most likely reduce heart rate, increase heart rate variability, and hasten the transition to light sleep N1.

[0160] As described above, step 604 is performed in response to determining in step 603 that the affective score does not satisfy the predetermined condition. After one or more prompts are communicated to the user in step 604, steps 601-604 may be repeated one or more times to assist in modifying the affective score until the affective score satisfies the predetermined condition. In response to determining that the affective score does satisfy the predetermined condition, method 600 proceeds to step 605.

[0161] Step 605 of method 600 includes altering one or more settings of the respiratory treatment system in response to determining that the first affective score satisfies a predetermined condition (step 603). Alternatively, or additionally, altering one or more settings of the respiratory treatment system is in response to determining the user's sleep state (e.g., wakefulness, sleep, etc.) and / or sleep stage (e.g., N1, N2, etc.). For example, step 605 may include altering a pressure setting of the respiratory treatment device 122 (e.g., turning the respiratory treatment device 122 on / off to deliver pressurized air, increasing the pressure, decreasing the pressure, changing a maximum pressure setting, changing a minimum pressure setting, changing a gradient duration, etc.), altering a conduit temperature, altering the humidification of the pressurized air, altering a comfort setting such as an expiratory pressure relief (EPR), or any combination thereof.

[0162] In some implementations, step 605 includes causing a respiratory treatment device 122 of respiratory treatment system 120 to supply pressurized air. In such implementations, respiratory treatment device 122 does not deliver pressurized air or delivers pressurized air at a low pressure before determining that the emotion score meets the predetermined condition. In other words, in such implementations, step 605 includes activating or turning on respiratory treatment device 122.

[0163] In some implementations, the respiratory treatment device 122 of the respiratory treatment system 120 supplies pressurized air at a first predetermined pressure before determining that the first emotional score satisfies the predetermined condition (step 603). In such implementations, step 605 may include causing the respiratory treatment device 122 of the respiratory treatment system 120 to supply pressurized air at a second predetermined pressure that is different from the first predetermined pressure. In some implementations, the second predetermined pressure is greater than the first predetermined pressure. For example, if the determined first emotional 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 it reaches the second predetermined pressure. 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., if the user experiences anxiety while wearing interface 124 and receiving pressurized air), the first predetermined pressure may be reduced to a second predetermined pressure to further assist in modifying the emotion score.

[0164] In some implementations, step 605 includes changing one or more settings of one or more devices external to respiratory treatment system 120. For example, step 605 may include changing 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 changing one or more settings of one or more Internet of Things (IoT) devices, such as, for example, smart appliances (e.g., televisions), smart thermostats or HVAC systems, smart lighting, etc. The user's response to the changed settings (e.g., change in affect score) may be used to determine one or more prompts to communicate to the user to assist in changing future affect scores.

[0165] In some implementations, method 600 includes determining a therapy recommendation for the user based at least in part on the first affective score. In such implementations, method 600 can include communicating an indication of the recommendation to the user, a third party (e.g., a healthcare provider), or both. The therapy recommendation can include, for example, a recommendation to change the type of user interface of the respiratory treatment system (e.g., a full face mask, a nasal pillows mask, a nasal mask, etc.). The therapy recommendation can also include a medication recommendation, a recommendation to discontinue use of the respiratory treatment system, a recommendation to use an alternative medical device (e.g., a mandibular repositioning device, a neurostimulation device, etc.), or any combination thereof.

[0166] As described above, steps 601 through 604 can be repeated one or more times until the emotional score meets a predetermined condition. Additionally, steps 601 through 604 can be repeated one or more times after one or more settings of the respiratory treatment system are changed in step 605. For example, if the user falls asleep using the user interface 124 but wakes up midway through the sleep session, the emotional score is updated based on the physiological data. If the emotional score does not meet a predetermined threshold, one or more settings of the respiratory treatment system can be further changed (e.g., turned off, reduced pressure, prompting the user to remove the user interface 124, etc.). One advantage of some implementations of the present disclosure is that if a user is not complying with a therapy prescription, a physician / medical equipment provider can better understand the reason for the non-compliance. For example, the physician / medical equipment provider can determine that the user is not comfortable using the respiratory treatment device 122 and is stressed, rather than, for example, being lazy or forgetful.

[0167] Although described above with respect to one sleep session, one or more steps of method 600 may be repeated one or more times for additional sleep sessions (e.g., two sleep sessions, three sleep sessions, ten sleep sessions, one hundred sleep sessions, five hundred sleep sessions, etc.). For example, if it is detected that the user is not feeling anxious over multiple therapy sessions because the respiratory treatment device 122 is operating at a suboptimal therapy / low pressure setting, the therapy may be adjusted to be closer to the optimal (e.g., prescribed) therapy setting. Furthermore, although steps 601-605 are shown and described herein in a particular order, more generally, steps 601-605 may be performed in any suitable order and / or simultaneously.

[0168] One or more elements, aspects, steps or portions thereof from any one or more of the following claims 1-62 may be combined with one or more elements, aspects, steps or portions thereof from any one or more other claims 1-62 or combinations thereof to form one or more further implementations and / or claims of the present disclosure.

[0169] While the present disclosure has been described with reference to one or more particular embodiments or implementations, those skilled in the art will recognize that many modifications are possible without departing from the spirit and scope of the present disclosure. Each of these implementations and obvious variations thereof is contemplated as falling within the spirit and scope of the present disclosure. It is also contemplated that further implementations according to various aspects of the present disclosure may combine any number of features from any of the implementations described herein.

Claims

1. a respiratory treatment system; a memory storing machine-readable instructions; a control system including one or more processors; wherein the one or more processors execute the machine-readable instructions to receiving first physiological data associated with a user; determining a first emotional score associated with the user based at least in part on the first physiological data, the first emotional score being determined in relation to a previous emotional score when the user was able to fall asleep; determining to modify one or more settings of a respiratory treatment system in response to determining that the first affective score satisfies a predetermined condition; A system configured to:

2. 2. The system of claim 1, wherein the control system is configured to execute the machine-readable instructions such that one or more prompts are communicated to the user to assist in modifying the first affective score.

3. The system of claim 2 , wherein the one or more prompts include a visual prompt, an audio prompt, or both.

4. The system of claim 3 , wherein the visual prompt comprises light emitted from a light source.

5. The system of claim 4 , wherein the visual prompt comprises changing the color of the light, changing the intensity of the light, changing the lighting pattern of the light, or any combination thereof.

6. the one or more prompts include breathing exercises to assist the user in modifying their breathing rate; determining a first emotional score associated with the user includes determining a respiratory rate associated with the user based at least in part on the first physiological data; The system according to any one of claims 3 to 5.

7. one or more light pulses are emitted from a light source at a predetermined frequency to assist in altering a breathing rate associated with the user; determining a first emotional score associated with the user includes determining a respiratory rate associated with the user based at least in part on the first physiological data; 6. The system according to claim 4 or claim 5.

8. 8. The system of claim 4, claim 5 or claim 7, wherein the light source is physically coupled to or integrated with a user device.

9. the light source is physically coupled to or integrated with a portion of the respiratory treatment system; the part of the respiratory treatment system is a user interface, a conduit, or a respiratory treatment device; 9. The system of claim 4, claim 5, claim 7, or claim 8.

10. the audio prompt is communicated to the user via a transducer; the transducer is physically coupled to or integrated with the respiratory treatment system; The system according to any one of claims 3 to 9.

11. 11. The system of claim 1, wherein determining the first emotional score associated with the user comprises determining movement, respiration rate, respiration rate variability, respiration depth, tidal volume, inspiration amplitude, inspiration duration, expiration amplitude, expiration duration, inspiration-to-expiration ratio, heart rate, heart rate variability, cardiac waveform, sweating, blood oxygenation, blood pressure, peripheral arterial tone, cardiogenic oscillations, galvanic skin response, sympathetic nervous system response, skin temperature, ambient temperature, photoplethysmography, pulse wave transit time, core body temperature, a respiration rate-related trend, a heart rate-related trend, a galvanic skin response-related trend, or any combination thereof.

12. The system of any one of claims 1 to 11, wherein the alteration of the one or more settings of the respiratory treatment system causes a respiratory treatment device of the respiratory treatment system to supply pressurized air at a predetermined pressure.

13. the first physiological data is received while the user is wearing a user interface of the respiratory treatment system; the respiratory treatment system delivering pressurized air at a first predetermined pressure before determining that the first emotional score satisfies the predetermined condition; the alteration of the one or more settings of the respiratory treatment system causes the respiratory treatment system to supply pressurized air at a second predetermined pressure different from the first predetermined pressure. A system according to any one of claims 1 to 12.

14. The system of claim 13 , wherein the second predetermined pressure is greater than the first predetermined pressure.

15. 15. The system of claim 1, wherein determining that the first emotional score satisfies the predetermined condition comprises determining that the first emotional score is less than a predetermined threshold.

16. The system of any one of claims 1 to 15, wherein the first physiological data is generated by one or more sensors.

17. The system of any preceding claim, wherein at least a portion of the first physiological data is associated with at least a portion of a first sleep session of the user.

18. The control system further executes the machine-readable instructions to: receiving second physiological data associated with the user following implementation of the determined change in one or more settings of the respiratory treatment system, the second physiological data being associated with a first sleep session of the user; and determining a second emotional score associated with the user based at least in part on the second physiological data, the second emotional score being determined relative to the previous emotional score; The system of any one of claims 1 to 17, configured to:

19. 20. The system of claim 18, further comprising communicating an indication of the first emotional score, the second emotional score, or both, to the user, a third party, or both during or after the first sleep session.

20. The control system further executes the machine-readable instructions to:

20. The system of claim 18 or claim 19, configured to make further changes to the one or more settings of the respiratory treatment system in response to determining that the second emotional score does not satisfy a predetermined condition.

21. 21. The system of claim 18, further comprising: modifying one or more settings of one or more Internet of Things (IoT) devices based at least in part on the determined second emotional score.

22. The control system further executes the machine-readable instructions to:

22. The system of claim 1, further comprising: determining a therapy recommendation for the user based at least in part on the first emotional score; and communicating an indication of the recommendation to the user, a third party, or both.

23. the therapy recommendation includes a recommendation to change a type of user interface for the respiratory treatment system; the type of user interface of the respiratory treatment system is a full face mask, a nasal pillows mask, or a nasal mask; 23. The system of claim 22.

24. 23. The system of claim 22, wherein the therapy recommendation includes a recommendation to discontinue use of the respiratory treatment system.

25. 25. The system of claim 1, wherein the first physiological data is generated during at least a portion of a first sleep session, and the user uses the respiratory treatment system with the altered one or more settings during at least a portion of the first sleep session.

26. The control system further executes the machine-readable instructions to: receiving second physiological data associated with the user during at least a portion of a second sleep session subsequent to the first sleep session; determining a second emotion score associated with the user based at least in part on the second physiological data; and one or more prompts are communicated to the user to assist in modifying the determined second affective score, the second affective score being determined relative to the previous affective score; configured to: the one or more prompts for assisting in changing the determined second affective score are different from the one or more prompts for assisting in changing the determined first affective score.

26. The system of claim 25.

27. 27. The system of claim 26, further comprising determining a change to one or more settings of the respiratory treatment system for the second sleep session based at least in part on the first emotional score, the second emotional score, or both.

28. The control system further executes the machine-readable instructions to: determining one or more first sleep-related parameters associated with the first sleep session based at least in part on the first physiological data; determining one or more second sleep-related parameters associated with the second sleep session based at least in part on the second physiological data; and after the second sleep session, communicating an 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, to the user, a third party, or both; 27. The system of claim 26 configured to:

29. the respiratory treatment system includes a user interface configured to engage a portion of the user, the user interface including a vent; implementing the determined change to the one or more settings of the respiratory treatment system includes changing a position of the vent; changing the position of the vent includes moving the vent from a generally open position toward a generally closed position. A system according to any one of claims 1 to 28.

30. The system of claim 2 , wherein the one or more prompts include one or more prompts for configuring a user interface of the respiratory treatment system.

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