Methods and apparatus for respiratory disorder related insomnia detection and treatment

Abstract

Systems and methods provide respiratory therapy for comorbid sleep apnea and insomnia (COMISA) patients. They may include a pressure generator (4140) for generating a flow of air for delivery to a patient interface for a respiratory therapy for the patient. They may include one or more sensors to sense one or more characteristics of operation of the generator. They may include one or more processors. They may be implemented to evaluate data in a therapy recommendation engine. The data may include one or both of objective and subjective data. The evaluation may include an assessment of the data with one or more threshold(s). They system and methods may classify, based on the evaluation, the patient according to one of a plurality of therapy states that include a COMISA state. They may be configured to output, from the therapy recommendation engine, a therapy recommendation determined in accordance with the classifying.

Description

METHODS AND APPARATUS FOR RESPIRATORY DISORDER RELATED INSOMNIA DETECTION AND TREATMENT1 CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of United States Provisional Application No. 63 / 559,504. filed 29 February 2024. the entire disclosure of which is hereby incorporated herein by reference.2 BACKGROUND OF THE TECHNOLOGY2.1 FIELD OF THE TECHNOLOGY

[0002] The present technology relates to one or more of the screening, diagnosis, monitoring, treatment, prevention and amelioration of respiratory -related disorders such as comorbid insomnia and sleep apnea (COMISA). The present technology also relates to medical devices or apparatus, and their use.2.2 DESCRIPTION OF THE RELATED ART2.2.1 Human Respiratory System and its Disorders

[0003] The respiratory system of the body facilitates gas exchange. The nose and mouth fonn the entrance to the airways of a patient.

[0004] The airways include a series of branching tubes, which become narrower, shorter and more numerous as they penetrate deeper into the lung. The prime function of the lung is gas exchange, allowing oxy gen to move from the inhaled air into the venous blood and carbon dioxide to move in the opposite direction. The trachea divides into right and left main bronchi, which further divide eventually into terminal bronchioles. The bronchi make up the conducting airways, and do not take part in gas exchange. Further divisions of the airways lead to the respiratory' bronchioles, and eventually to the alveoli. The alveolated region of the lung is where the gas exchange takes place, and is referred to as the respiratory zone. See “Respiratory Physiology” , by John B. West, Lippincott Williams & Wilkins. 9th edition published 2012.

[0005] A range of respiratory disorders exist. Certain disorders may be characterised by particular events, e.g. apneas, hypopneas, and hyperpneas.

[0006] Examples of respiratory disorders include Obstructive Sleep Apnea (OSA), Cheyne-Stokes Respiration (CSR). respiratory insufficiency, Obesity Hyperventilation Syndrome (OHS). Chronic Obstructive Pulmonary Disease (COPD). Neuromuscular Disease (NMD) and Chest wall disorders.

[0007] Obstructive Sleep Apnea (OSA), a form of Sleep Disordered Breathing (SDB), is characterised by events including occlusion or obstruction of the upper air passage during sleep. It results from a combination of an abnormally small upper airway and the normal loss of muscle tone in the region of the tongue, soft palate and posterior oropharyngeal wall duringsleep. The condition causes the affected patient to stop breathing for periods ty pically of 30 to 120 seconds in duration, sometimes 200 to 300 times per night. It often causes excessive daytime somnolence, and it may cause cardiovascular disease and brain damage. The syndrome is a common disorder, particularly in middle aged overweight males, although a person affected may have no awareness of the problem. See US Patent No. 4,944,310 (Sullivan).

[0008] Cheyne-Stokes Respiration (CSR) is another form of sleep disordered breathing. CSR is a disorder of a patient's respiratory controller in which there are rhythmic alternating periods of waxing and waning ventilation known as CSR cycles. CSR is characterised by repetitive de-oxygenation and re-oxygenation of the arterial blood. It is possible that CSR is harmful because of the repetitive hypoxia. In some patients CSR is associated with repetitive arousal from sleep, which causes severe sleep disruption, increased sympathetic activity, and increased afterload. See US Patent No. 6,532.959 (Berthon-Jones).

[0009] A range of therapies have been used to treat or ameliorate such conditions. Furthermore, otherwise healthy individuals may take advantage of such therapies to prevent respiratory disorders from arising. However, these have a number of shortcomings.2.2.2 Therapies

[0010] Various respiratory therapies, such as Continuous Positive Airway Pressure (CPAP) therapy, Non-invasive ventilation (NIV) and Invasive ventilation (IV) have been used to treat one or more of the above respiratory7disorders.2.2.2.1 Respiratory pressure therapies

[0011] Respiratory pressure therapy is the application of a supply of air to an entrance to the airways at a controlled target pressure that is nominally positive with respect to atmosphere throughout the patient’s respiratory7cycle (in contrast to negative pressure therapies such as the tank ventilator or cuirass).

[0012] Continuous Positive Airway Pressure (CPAP) therapy has been used to treat Obstructive Sleep Apnea (OSA). The mechanism of action is that continuous positive airway pressure acts as a pneumatic splint and may prevent upper airway occlusion, such as by pushing the soft palate and tongue forward and away from the posterior orophary ngeal w all. Treatment of OSA by CPAP therapy may be voluntary, and hence patients may elect not to comply with therapy if they find devices used to provide such therapy one or more of: uncomfortable, difficult to use, expensive and aesthetically unappealing.

[0013] Non-invasive ventilation (NIV) provides ventilatory support to a patient through the upper airways to assist the patient breathing and / or maintain adequate oxygen levels in the body by doing some or all of the work of breathing. The ventilatory support is provided via a non-invasive patient interface. NIV has been used to treat CSR and respiratory failure, in forms such as OHS. COPD. NMD and Chest Wall disorders. In some forms, the comfort and effectiveness of these therapies may be improved.

[0014] Invasive ventilation (IV) provides ventilatory’ support to patients that are no longer able to effectively breathe themselves and may be provided using a tracheostomy tube. In some forms, the comfort and effectiveness of these therapies may be improved.2.2.3 Respiratory therapy Systems

[0015] These respiratory therapies may be provided by a respiratory therapy system or device. Such systems and devices may also be used to screen, diagnose, or monitor a condition without treating it.

[0016] A respiratory therapy system may comprise a Respiratory Pressure Therapy Device (RPT device), an air circuit, a humidifier, a patient interface, an oxygen source, and data management.2.2.3.1 Patient Interface

[0017] A patient interface may be used to interface respiratory equipment to its wearer, for example by providing a flow of air to an entrance to the airways. The flow of air may be provided via a mask to the nose and / or mouth, a tube to the mouth or a tracheostomy tube to the trachea of a patient. Depending upon the therapy to be applied, the patient interface may form a seal, e g., with a region of the patient's face, to facilitate the delivery of gas at a pressure at sufficient variance with ambient pressure to effect therapy, e.g., at a positive pressure of about 10 cmH20 relative to ambient pressure.2.2 .2 Respiratory Pressure Therapy (RPT) Device

[0018] A respiratory pressure therapy (RPT) device may be used individually or as part of a system to deliver one or more of a number of therapies described above, such as by operating the device to generate a flow of air for deliver}’ to an interface to the airways. The flow of air may be pressure-controlled (for respirator}’ pressure therapies) or flow-controlled (for flow therapies such as HFT). Thus, RPT devices may also be configured to act as flow therapy devices. Examples of RPT devices include a CPAP device and a ventilator.2.2.3.3 Air circuit

[0019] An air circuit is a conduit or a tube constructed and arranged to allow, in use, a flow of air to travel between two components of a respirator}’ therapy system such as the RPT device and the patient interface. In some cases, there may be separate limbs of the air circuit for inhalation and exhalation. In other cases, a single limb air circuit is used for both inhalation and exhalation.2.2.3.4 Humidifier

[0020] Delivery of a flow of air without humidification may cause drying of airways. The use of a humidifier with an RPT device and the patient interface produces humidified gas that minimizes drying of the nasal mucosa and increases patient airway comfort. In addition, in cooler climates, warm air applied generally to the face area in and about the patient interface ismore comfortable than cold air. Humidifiers therefore often have the capacity to heat the flow of air was well as humidifying it.

[0021] COMIS A

[0022] Obstructive sleep apnea and insomnia are the tw o most common sleep disorders. These conditions can affect a patient's quality of life, mood, energy, daytime functioning and sleep disturbances. COMISA exists when a patient experiences both sleep disorders, that is, they suffer from comorbid insomnia and sleep apnea. This condition is a largely understudied but emerging area of research for companies specialising in one of these areas. The cooccurrence of the two disorders complicates OSA treatment, reducing compliance with PAP therapy in the presence of insomnia when not treated effectively together. Insomnia and sleep apnea are characterized by both independent and shared symptoms that can complicate the assessment of COMISA before and after treatment. Despite the prevalence of either condition alone, sleep research has not sufficiently examined how OSA and insomnia interact. The cooccurrence of these two conditions can complicate the therapeutic landscape, leading to diminished adherence to PAP therapy. It remains unclear whether OSA is a risk factor for insomnia or vice versa, yet a bidirectional relationship may exist be tween the two. People with COMISA generally have worse sleep, daytime function, mental health, cardiovascular health, productivity , and quality of life compared to people with either insomnia alone, OSA alone, or neither condition. Studies in large population-based cohorts have reported that people with COMISA have a 50%-70% increased risk of all-cause mortality7over 10-20 years of followup, compared to people with neither condition. The disparate pathophysiological underpinnings of OSA and insomnia necessitate tailored treatment strategies. Indeed, while PAP therapy has historically show n promise in alleviating insomnia symptoms in COMISA patients, a structured and holistic approach to this dual affliction remains elusive.

[0023] As previously mentioned, OSA is repetitive brief closure (apnea) or narrowing (hypopnea) of the pharyngeal airway during sleep, which can result in the reduction of airflow, commonly causing post-apnoeic arousal from sleep, and then the resumption of airflow. OSA is a result of factors, including having a narrow airway and unstable control of breathing. Having these constant respiratory events and arousal from sleep reduces quality of life, and increases tiredness and daytime sleepiness. The commonly used index of OSA severity for individuals is the AHI, w hich represents the average number of respiratory events experienced per hour of sleep. The most effective treatment for OSA is continuous PAP therapy. CPAP therapy stabilises breathing throughout the night, ultimately improving the quality of life for patients by reducing daytime sleepiness among other benefits.

[0024] Evaluation and diagnosis of COMISA is fragmented, with patients presenting across separate clinical pathways; patient's presenting complaint serves as the basis for provisional diagnosis (insomnia or OSA) which leads to parallel or separate clinical pathways. Most sleep clinics around the world currently specialize in the diagnosis and treatment of OSA, and do not include insomnia assessment or treatment / referral pathways, resulting in the comorbid insomnia going undiagnosed.

[0025] Insomnia is frequent and chronic, self-reported and / or objectively detected, difficulty initiating sleep, maintaining sleep, and / or early morning awakenings from sleep. This, in turn, leads to depreciated daytime functioning, mood, and quality of life. It has been estimated that a significant percentage of the general population suffer from chronic insomnia disorder. Cognitive Behavioural Therapy is a form of psychological treatment for a wide range of problems, including depression, anxiety, addictive disorders, depressive disorders, anxiety disorders, and other forms of mental challenges and illnesses. Cognitive Behavioural Therapy for Insomnia (CBTi) is a multi-component treatment for insomnia that targets difficulties with initiating and / or maintaining sleep. CBTi is the recommended front line therapy for insomnia by the American College of Physicians, based on its safety and efficacy profile. Phy sicians w idely prescribe antidepressants and sleeping pills for the treatment of insomnia, which dwarfs the use of CBTi. Approximately 60% of patients take drugs for the treatment of their insomnia. Similar to OSA, insomnia is frequently associated with psychological disorders. Psychological symptoms such as depression and anxiety are commonly reported in adults. Some studies have demonstrated that effectively addressing sleep-disordered breathing (SDB) can lead to an improvement in insomnia.

[0026] Co-morbid sleep disorders remain largely uncharted territories in medical research, necessitating a deeper probe into their prevalence and significance within society. The intricacies of these conditions pose unique challenges, as they often intertwine and exacerbate each other, leading to a complex clinical picture. This complexity underscores the importance of developing predictive models capable of early identification of patients at risk of co-morbid sleep disorders.

[0027] There is evidence to suggest that treating OSA through PAP therapy w ill help treat insomnia in some patients. Some studies report improved insomnia following PAP therapy in COMISA patients. It has been observed that insomnia symptoms may reduce CPAP adherence and nightly overall adherence. However, many patients with COMISA are sufficiently compliant with CPAP therapy and display improvements in both OSA and insomnia symptoms.

[0028] Other research suggests that COMISA may be treated by Cognitive Behavioral Therapy for Insomnia (CBTi) in conjunction with PAP therapy; however, CBTi can have vary ing effectiveness depending on the type of insomnia and therefore accurate categorization of COMISA is crucial. Although well-established treatments exist for OSA (this gold standard is CPAP) and insomnia (CBTi) separately , no definitive guidelines are available for how to combine or integrate these treatments in the case of COMISA. Notably, CBTi is designed for the treatment of chronic insomnia, not for COMISA patients. The majority of patients have their insomnia treated with drugs, rather than CBTi. COMISA is not just psychological but also physical, and changes to PAP therapy mode may lead to better outcomes.

[0029] Cognitive Behavioural Therapy for Insomnia (CBTi) therapy, traditionally delivered individually face-to-face over the course of 6-8 weeks, is now considered the first- line treatment option for individuals with chronic insomnia. There are several issues that hamper the widespread dissemination and implementation of CBTi. Notably, and despite its relatively short duration compared to other psychotherapeutic techniques, traditional CBTi is often considered too burdensome in its current format by patients and this is reflected in the relatively high levels of attrition and non-adherence, especially in clinical settings. There have been several attempts to modify traditional CBTi into abbreviated versions to address these issues of patient burden. An alternative perspective, highlighted by Ellis and colleagues in 2012 [Ellis J.G., Gehrman P., Espie C.A., Riemann D., Perlis M.L. Acute insomnia: Current conceptualizations and future directions. Sleep Med. Rev. 2012;16:5], is to circumvent the development of chronic insomnia by attempting to treat it during its acute phase (i.e., within the first three months of manifesting). The rationale for this being that treatment during the acute phase should be even less burdensome for the patient and faster to administer due to: (i) less conditioned arousal to the bedroom and pre-sleep routine; and (ii) a less realised self- schemata of having “insomnia” which would be evidenced by lower levels of sleep-related catastrophic worry and sleep-related dysfunctional thinking. To that end, a “one-shot” CBTi program is a brief intervention for individuals with acute insomnia. In 2015, Ellis and colleagues used a “one-shot” consisting of a self-help pamphlet and a single 60-70 min face- to-face treatment session [Ellis J.G.. Cushing T., Germain A. Treating Acute Insomnia: A Randomized Controlled Trial of a “Single-Shot” of Cognitive Behavioral Therapy for Insomnia. Sleep. 2015;38:971-978],

[0030] The prediction of COMISA is still a relatively unexplored area in modern research. There is no clear way to identify patients who are likely to have both conditions together. There remains a need for predictive models for COMISA patients.BRIEF SUMMARY OF THE TECHNOLOGY

[0031] The present technology is directed towards providing system, methods, and apparatus such as medical devices, used in the screening, diagnosis, monitoring, amelioration, treatment, or prevention of sleep related, and / or respiratory, disorders having one or more of improved comfort, cost, efficacy, ease of use and manufacturability. A first aspect of the present technology relates to apparatus used in the screening, diagnosis, monitoring, amelioration, treatment or prevention of a sleep and / or respiratory' disorders, such as insomnia in sleep disordered breathing patients.

[0032] Another aspect of the present technology relates to methods used in the screening, diagnosis, monitoring, amelioration, treatment or prevention of a sleep related disorders, including insomnia, such as COMISA.

[0033] Some examples of the present technology may serve to keep OSA patients on PAP therapy by better identifying and treating their co-morbid insomnia, and may also implement provision of behavioural support for their condition.

[0034] Some examples of the present technology may include systems and methods that detect, monitor and / or treat insomnia such as in COMISA patients. These may additionally or alternatively include accessing collected objective data relating to a user’s therapy and / or sleep, such as from one or more sensors associated with a user, which one or more sensors may be in, or associated with, for example, a PAP device. These may include accessing collected subjective data relating to the user’s sleep, such as data input via an application executed with a smart phone or laptop. The objective data and subjective data may then be input into a therapy recommendation engine (TRE), such as a processing algorithm that implements a classifier. The TRE may be configured to determine or select suitable therapy, such as a digital therapy, such as a) CBT for OSA onboarding, b) CBT for PAP therapy adherence, or c) CBTi for ongoing PAP therapy, as described further herein. As will be understood from the description herein, the digital therapies denoted as CBT or CBTi for “OSA onboarding”, “PAP therapy adherence” and “ongoing PAP therapy” can be understood to designate therapy modules suitable for different parts of the patient’s diagnosis and treatment journey and are not limited to OSA (obstructive sleep apnea) diagnosis and PAP therapy but rather encompass sleep and / or respiratory disorders, such as OSA and in particular COMISA or those in which insomnia is a component or co-morbidity, and respiratory therapies, such as PAP therapy. The objective, subjective and / or digital therapy information, that is collected before, during and / or after the digital therapies are implemented, may be presented (e.g., displayed or communicated) to the user, clinician and / or physician.

[0035] Some implementations of the present technology' may include systems and methods for treating insomnia such as COMISA. These may include mechanical therapy viaairflow supplied by respiratory device. These may include adaptive servo-ventilation (ASV) therapy modes for treating COMISA. These may include auto adjusting therapy pressure, such as an Autoset™ feature of a respiratory therapy device, that implements settings tailored to treating COMISA.

[0036] Some implementations of the present technology may include a system for providing sleep disordered breathing therapy for a comorbid sleep apnea and insomnia (COMISA) patient, such as respiratory therapy with respiratory therapy apparatus for a COMISA patient. The system may include one or more processors. The one or more processors may be configured to evaluate data in a therapy recommendation engine. The data may include one or both of objective data and subjective data. The evaluation may include an assessment of the data according to one or more thresholds. The one or more processors may be configmed to classify, based on the evaluation of the therapy recommendation engine, tire patient according to one of a plurality of therapy states, the plurality of therapy states may include a COMISA state. The COMISA state may, for example, correspond to a state related to ongoing PAP therapy and associated CBTi, therapy. The one or more processors may be configured to output, from the therapy recommendation engine, a therapy recommendation determined in accordance with the classifying.

[0037] In some implementations, the system may further include the respiratory therapy apparatus for delivering the respiratory therapy. The respiratory therapy apparatus may include a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient. The respiratory therapy apparatus may include one or more sensors to sense one or more characteristics of the operation of the pressure generator. The one or more processors may include a controller of the pressure generator, wherein the controller may be configured to control operation of the pressure generator based on the output of the therapy. The one or more processors may be part of one or more servers configured for accessing data electronically communicated from a controller of the pressure generator. The one or more processors may be part of a companion device configured for electronic communications with a controller of the pressure generator. The companion device may include a smart phone. The evaluated data may include any one or more of: a number of days from a first contact for therapy, therapy usage data, sleep quality data, mask on and / or off events data, respiratory disturbance variable data, wearable device generated data, medical record data, respiratory event data, prescribed drug data, insomnia screening or diagnosis data, and one or more respiration rate statistic data. The evaluated data may include a number of days from a first contact for therapy, therapy usage data, sleep qualitydata, and mask on and / or off events data. The evaluated data may include a number of daysfrom a first contact for therapy, therapy usage data, respiratory’ disturbance variable data, and respiration rate statistic data.

[0038] In some implementations, the output therapy recommendation may include a respiratory therapy parameter for operation of the pressure generator according to a therapy protocol. The therapy protocol may include an adaptive servo-ventilation (ASV) therapy mode, with an adjustable floor pressure, configmed to change the adjustable floor based on a calculated distribution of adjustment increments. The adjustment increments may be periods of end expiratory pressure adjustments. The therapy protocol may include a session-to-session adjustment of end expiratory pressure, wherein setting of end expiratory pressure for a next session may be based on a distribution of EEP levels in adjustment periods of a prior session. The therapy protocol may include an adaptive servo-ventilation (ASV) therapy mode configured to change operation based on a detected sleep state. The change in operation may include initiating, based on a detection of an awake state or input from the patient, a paced breathing operation configmed to induce a reduced patient respiration rate. The change in operation may include an adjustment to a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state. The therapy protocol may include an automatic positive airway pressure (APAP) therapy configured to ramp delivered pressure within a predetermined pressme range following detection of a mask on event and a detection of sleep onset. The output therapy recommendation may include a paced breathing operation configured to induce a reduced patient respiration rate, and wherein the one or more processors may be further configmed to generate output to prompt the patient to initiate the paced breathing operation based on the classif ing.

[0039] The therapy protocol may include a plural i ty of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors may be further configured to select a waveform of the plurality of different pressure waveforms dming a trial of the plurality of different pressure waveforms that may be initiated for the patient based on the classifying. The therapy protocol may include a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors may be further configured to trial the plurality’ of different pressme waveforms with the patient based on the classifying, wherein the one or more processors may be configured to select an optimal waveform from the plurality of different pressme waveforms based on monitoring the patient’s sleep quality. Monitoring the patient's sleep quality may include monitoring of sleep onset latency. The therapy protocol may include a plurality’ of different pressure waveforms for use dming a pre-sleep onset period, and the one or more processors may be further configured to trial the plurality of different pressure waveforms with the patient based on the classifying, andthe one or more processors may be configured prompt the patient to select a trialed one of the plurality of different waveforms for delivery during use of the pressure generator. The therapy protocol may include a plurality of different pressure waveforms for use during a pre-sleep onset period, and the one or more processors may be further configured to select one of the plurality of different waveforms based on any one or more of demographic data, data concerning nature of the patient's insomnia, prior therapy data, and diagnostic data. The therapy protocol may include an automatic positive airway pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode and wherein the one or more processors are configured to switch between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

[0040] In some implementations, the one or more processors may be configured to switch to the CPAP mode from the APAP mode based on a detection of an N3 sleep stage. The one or more processors may be configured to switch to the APAP mode from the CPAP mode based on detection of any one or more of a REM sleep stage and a N2 sleep stage. The one or more processors may be configured to switch to tire APAP mode from the CPAP mode based on a determined time in a REM sleep stage. The output therapy may include a digital cognitive behavioural therapy presentation. The output therapy presentation may be a digital cognitive behavioural therapy for insomnia, and wherein the classifying identifies the COMISA state. The plurality of therapy states further may include one or both of a sleep disorder onboarding state and a deficient respiratory therapy adherence state. The therapy recommendation engine may be configured to select a presentation module from a plurality of different presentation modules, wherein each of the presentation modules may be associated with a therapy state of the plurality of therapy states, and wherein the selected presentation module may include one or both of an audio therapy content and visual therapy content.

[0041] Some implementations of the present technology may include a method of evaluating and treating a comorbid sleep apnea and insomnia (COMISA) patient using apparatus for a respiratory therapy. The method may include evaluating data in a therapy recommendation engine. The data may include one or both of objective data and subjective data. The evaluation may include an assessment of the data according to one or more thresholds. The method may include classifying, based on the evaluation of the therapy recommendation engine, the patient according to one of a plurality of therapy states, the plurality of therapy states may include a COMISA state. The method may include outputting, from the therapy recommendation engine, a therapy recommendation determined in accordance with the classifying.

[0042] In some implementations, the apparatus for the respiratory therapy may include a pressure generator and one or more sensors. The method may further include controlling the pressure generator to generate a flow of air for delivery' to a patient interface via a delivery conduit for a respiratory therapy for the patient. The method may include operating the one or more sensors to sense one or more characteristics of the operation of the pressure generator. The apparatus may be communicatively coupled to a therapy engine. The therapy engine may include one or more processors that are part of a controller of the pressure generator. The controller may be configured to control operation of the pressure generator based on the output of the therapy recommendation engine. The therapy recommendation engine may include one or more servers configured for accessing data electronically communicated from a controller of the pressure generator. The therapy recommendation engine may include a companion device configured for electronic communications with a controller of the pressure generator. The companion device may include a smart phone. The evaluated data may include any one or more of: a number of days from a first contact for therapy, usage data, sleep quality data, mask on and / or off events data, respiratory disturbance variable data, wearable device generated data, medical record data, respiratory event data, insomnia screening or diagnosis data, and one or more respiration rate statistic data. The evaluated data may include a number of days from a first contact for therapy, therapy usage data, sleep quality data, and mask on and / or off events data. The evaluated data may include a number of days from a first contact for therapy, therapy usage data, respiratory disturbance variable data, and respiration rate statistic data.

[0043] In some implementations, the output therapy recommendation may include a respiratory therapy parameter for operation of the pressure generator according to a therapy protocol. The therapy protocol may include an adaptive servo-ventilation (ASV) therapy mode, with an adjustable floor pressure, that changes the adjustable floor based on calculating a distribution of adjustment increments. The adjustment increments may be periods of end expiratory pressure adjustments. The therapy protocol makes a session-to-session adjustment of end expiratory pressure, wherein setting of end expiratory pressure for a next session is may be based on calculating a distribution of EEP levels in adjustment periods of a prior session. The therapy protocol may include an adaptive servo-ventilation (ASV) therapy mode that changes operation based on a detected sleep state. The change in operation may initiate, based detecting an awake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate. The change in operation may adjust a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state. The therapy protocol may include an automatic positive airway pressure (APAP) therapy that delivers ramping pressure within a predetermined range following detection of a mask on event and a detection of sleep onset. The output therapy recommendation may include a pacedbreathing operation that induces a reduced patient respiration rate, and wherein one or more processors generates output to prompt the patient to initiate the paced breathing operation based on the classifying. The therapy protocol may include a plurality of different pressure waveforms that are each for use during a pre-sleep onset period, and wherein the therapy protocol includes a selection of a waveform of the plurality of different pressure waveforms during a trial of the plurality of different pressure waveforms that may be initiated for the patient based on the classifying. The therapy protocol may include a plurality of different pressure waveforms that are each for use during a pre-sleep onset period, and wherein the therapy protocol includes a selection of an optimal waveform from the plurality of different pressure waveforms based on monitoring the patient's sleep quality. Monitoring the patient's sleep quality may include monitoring sleep onset latency.

[0044] In some implementations, the therapy protocol may include a plurality of different pressure w aveforms for use during a pre-sleep onset period, and the one or more processors may be further configured to trial the plurality of different pressure w aveforms with the patient based on the classifying. The one or more processors may be configured prompt the patient to select a trialed one of the plurality of different waveforms for delivery during use of the pressure generator. The therapy protocol may include a plurality' of different pressure waveforms for use during a prc-slccp onset period, and the one or more processors may be further configured to select one of the plurality of different waveforms based on any one or more of demographic data, data concerning nature of the patient's insomnia, prior therapy data, and diagnostic data. The therapy protocol may include an automatic positive airw ay pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode and wherein the therapy recommendation engine recommends switches between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles. A switch to the CPAP mode from the APAP mode may be based on a detection of an N3 sleep stage. A switch to the APAP mode from the CPAP mode may be based on detection of (i) a REM sleep stage or (ii) a N1 or N2 sleep stage. The switch to the APAP mode from the CPAP mode may be based on a determined time in the REM sleep stage.

[0045] In some implementations, the output therapy recommendation may include a digital cognitive behavioural therapy presentation. The digital cognitive behavioural therapy presentation may be a digital cognitive behavioural therapy for insomnia when the classifying identifies the COMISA state. The plurality' of therapy states further may include one or both of a sleep disorder onboarding state and a deficient respiratory' therapy adherence state. The therapy recommendation engine selects a presentation module from a plurality of differentpresentation modules. Each of the presentation modules may be associated with a therapy state of the plurality of therapy states, and the selected presentation module may include one or both of an audio therapy content and visual therapy content.|0046| Some implementations of the present technology may include, a processor readable medium configmed with program instructions for controlling one or more processors to execute a method of evaluating and treating a comorbid sleep apnea and insomnia (COMISA) patient using respiratory therapy apparatus, the method may include any aspects the methods described herein. The one or more processors may be part of one or more servers. The one or more processors may be part of a respiratory pressure therapy device. The one or more processors may be part of a smart phone or a tablet.

[0047] Some implementations of the present technology may include apparatus for providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient. The apparatus may include a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient. The apparatus may include one or more sensors to sense one or more characteristics of the operation of the pressure generator. The apparatus may include one or more processors coupled with the one or more sensors and configured as a controller to control operation of the pressure generator. The one or more processors further configured to operate the pressure generator in an adaptive servo-ventilation (ASV) mode wherein the pressure generator may be controlled according to a target ventilation that varies, whereby the pressure generator may be controlled to produce ventilation to satisfy the target ventilation. The adaptive servo-ventilation (ASV) mode further may include an adjustable floor pressure wherein the controller may be configured to change the adjustable floor based on a calculated distribution of adjustment increments.

[0048] In some implementations, the adjustment increments may be periods of end expiratory pressure adjustments made in response to detected sleep disordered breathing events. The controller may be configured to make a session-to-session adjustment of end expiratory’ pressure EEP wherein a setting of the end expiratory pressure for a next session may be based on a distribution of EEP levels in adjustment periods of a prior session. The controller may be configured to change operation of the adaptive servo-ventilation (ASV) therapy mode based on a detected sleep state. The change in operation may include initiating, based on a detection of an awake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate. The change in operation may include an adjustment to a controller gain of the adaptive servo- ventilation (ASV) therapy mode as a function of a detected sleep state.

[0049] Some implementations of the present technology- may include a method for controlling respiratory apparatus for providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient. The method may include controlling a pressure generator to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient. The method may include sensing, with one or more sensors, one or more characteristics of the operation of the pressure generator. The method may include controlling operation of the pressure generator to provide an adaptive servo-ventilation (ASV) therapy according to a target ventilation that varies, whereby the pressure generator produces ventilation to satisfy the target ventilation. The method may include controlling operation of the pressure generator to provide an adaptive servo-ventilation (ASV) therapy according to an adjustable floor pressure wherein the adjustable floor may be adapted based on calculating a distribution of adjustment increments.

[0050] In some implementations, the adjustment increments may be prior periods of end expiratory pressure adjustments made in response to detecting sleep disordered breathing events. The controller may make a session-to-session adjustment of end expiratory pressure EEP, wherein a setting of the end expiratory pressure EEP for a next session may be based on a distribution of EEP levels in adjustment periods of a prior session. The controller may change operation of the adaptive servo-ventilation (ASV) therapy mode based on a detecting a sleep state. The change in operation may include initiating, based on a detection of an awake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate. The change in operation may include an adjustment to a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state.

[0051] Some implementations of the present technology- may include a processor readable medium configured with program instructions for operating one or more processors to execute a method of controlling respiratory apparatus for providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient, the method may include any aspects of the methods described herein.

[0052] Some implementations of the present technology may include apparatus for providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient. The apparatus may include a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient. The apparatus may include one or more sensors to sense one or more characteristics of the operation of the pressure generator. The apparatus may include one or more processors coupled with the one or more sensors and configured as a controller to control operation of the pressure generator. The one or more processors may be further configured to operate the pressure generator in anautomatic positive airway pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode. The one or more processors may be further configured to switch between the APAP therapy mode and tire CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

[0053] In some implementations, the one or more processors may be configured to switch operation of the pressure generator to the CPAP mode from the APAP mode based on a detection of an N3 sleep stage. The one or more processors may be configured to switch operation of the pressure generator to the APAP mode from the CPAP mode based on detection of any one or more of a REM sleep stage and a N2 sleep stage. The one or more processors may be configured to switch operation of the pressure generator to the APAP mode from the CPAP mode based on a determined time in a REM sleep stage. The one or more processors may be configured to operate the pressure generator in the automatic positive airway pressure (APAP) therapy mode and control ramping of delivered pressure within a predetermined range upon detection of a mask on event and a sleep onset. The one or more processors may be configured to operate the pressure generator to provide a paced breathing operation configured to induce a reduced patient respiration rate, and wherein the one or more processors may be further configured to prompt the patient to initiate tire paced breathing operation. The one or more processors may be configured to operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors may be further configured to generate output to prompt the patient to input a selection of a waveform of the plurality of different pressure waveforms during a trial of the plurality of different pressure waveforms. The one or more processors may be configured to operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors may be further configured to trial the plurality of different pressure waveforms with the patient, wherein the one or more processors may be configured to select an optimal waveform from the plurality of different pressure waveforms based on monitoring of the patient's of sleep quality. The monitoring of the patient's sleep quality may include monitoring of sleep onset latency.

[0054] Some implementations of the present technology may include a method for controlling respiratory therapy apparatus to provide a respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient. The method may include controlling a pressure generator configured to generate a flow of air for delivery to a patient interface via a deliver}’ conduit for a respiratory’ therapy for the patient. The method may include sensing, with one or more sensors, one or more characteristics of the operation of the pressure generator. The method may include controlling operation of the pressure generator in an automatic positiveairway pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode. The method may include controlling switching between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

[0055] In some implementations, one or more processors may switch operation of the pressure generator to the CPAP mode from the APAP mode based on a detection of an N3 sleep stage. The one or more processors may switch operation of the pressure generator to the APAP mode from the CPAP mode based on detection of (i) a REM sleep stage or (ii) a N1 or N2 sleep stage. The one or more processors may switch operation of the pressure generator to the APAP mode from the CPAP mode based on a determined time in a REM sleep stage. The one or more processors may operate the pressure generator in the automatic positive airway pressure (APAP) therapy mode and may control ramping of delivered pressure within a predetermined range upon detection of a mask on event and a sleep onset. The one or more processors may operate the pressure generator to provide a paced breathing operation for inducing a reduced patient respiration rate, and wherein the one or more processors prompt the patient to initiate the paced breathing operation. The one or more processors may operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors may select a waveform of the plurality of different pressure waveforms during a trial of the plurality of different pressure waveforms. The one or more processors may operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors may trial the plurality of different pressure waveforms with the patient, wherein the one or more processors may select an optimal wavefonn from the plurality of different pressure waveforms based on monitoring of the patient's sleep quality during use of each of the plurality of different pressure waveforms. Monitoring the patient's sleep quality may include monitoring of sleep onset latency.

[0056] Some implementations of the present technology may include a processor readable medium configured with program instructions for operating one or more processors to execute a method of controlling respiratory apparatus for providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient, the method may include any aspects of the methods described herein.

[0057] Some implementations of the present technology may include a s stem for providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient. The system may include a pressure generator configmed to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for a patient. The system mayinclude one or more sensors to sense one or more characteristics of the operation of the pressure generator. The system may include one or more processors. The one or more processors may be configured to operate the pressure generator to control providing of the respiratory therapy. The one or more processors may be configured to evaluate one or more signals from the one or more sensors to detect biomarkers indicative of use of a pharmacological treatment for insomnia. The one or more processors may be configured to output a change to therapy based on the evaluation of the one or more signals.

[0058] In some implementations, the change to therapy may include generating a digital therapy presentation for insomnia. The change to therapy may include an adjustment to the respirator) therapy provided to the patient. The adjustment to respiratory therapy may include a paced breathing operation configured to induce a reduced patient respiration rate. The evaluated one or more signals may include any one or more of: respirator)' rate variability, respiratory rate distribution over one or more periods, volume and / or length of expiratory pauses, a number of obstructive and / or central apneas, and a cycle length of sleep disordered breathing events. The evaluation of the one or more signals from the one or more sensors to detect use of a pharmacological treatment for insomnia may include detection of a number of transitions into and out of an S2 sleep state.

[0059] Some implementations of the present technology may include a method for monitoring and providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient. The method may include controlling a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for a patient. The method may include sensing, with one or more sensors, one or more characteristics of the operation of the pressure generator. The method may include evaluating one or more signals from the one or more sensors to detect use of a pharmacological treatment for insomnia. The method may include outputting a change to therapy based on the evaluation of the one or more signals.

[0060] In some implementations, the change to therapy may include generating a digital therapy presentation. The change to therapy may include an adjustment to the respirator)' therapy. The adjustment to respiratory therapy may include providing a paced breathing operation to induce a reduced patient respiration rate. The evaluated one or more signals may include any one or more of: respirator)' rate variability, respiratory rate distribution over one or more periods, volume and / or length of expiratory pauses, a number of obstructive and / or central apneas, and a cycle length of sleep disordered breathing events. The evaluating one or more signals from the one or more sensors to detect use of a pharmacological treatment for insomnia may include detection of a number of transitions into and out of an S2 sleep state.

[0061] Some implementations of the present technology may include a processor readable medium configured with program instructions for operating one or more processors to execute a method of controlling respiratory apparatus for monitoring and providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient, the method may include any aspects of the methods described herein.

[0062] The methods, systems, devices and apparatus described may be implemented so as to improve the functionality of a processor, such as a processor of a specific purpose computer, respiratory monitor and / or a respiratory therapy apparatus. Moreover, the described methods, systems, devices and apparatus can provide improvements in the technological field of automated management, monitoring and / or treatment of respirator}’ conditions, including, for example, sleep disordered breathing.

[0063] Of course, portions of the aspects may form sub-aspects of the present technology. Also, various ones of the sub-aspects and / or aspects may be combined in various manners and also constitute additional aspects or sub-aspects of the present technology.

[0064] Other features of the technology will be apparent from consideration of the information contained in the following detailed description, abstract, drawings and claims.3 BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The present technology is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings, in which like reference numerals refer to similar elements including:3.1 RESPIRATORY THERAPY SYSTEMS

[0066] Fig. 1A shows a system including a patient 1000 wearing a patient interface 3000, in the form of nasal pillows, receiving a supply of air at positive pressure from an RPT device 4000. Air from the RPT device 4000 is conditioned in a humidifier 5000. and passes along an air circuit 4170 to the patient 1000. A bed partner 1100 is also shown.

[0067] Fig. IB shows a system including a patient 1000 wearing a patient interface 3000, in the form of a nasal mask, receiving a supply of air at positive pressure from an RPT device 4000. Air from the RPT device is humidified in a humidifier 5000. and passes along an air circuit 4170 to the patient 1000.

[0068] Fig. 1C shows a system including a patient 1000 wearing a patient interface 3000. in the form of a full-face mask, receiving a supply of air at positive pressure from an RPT device 4000. Air from the RPT device is humidified in a humidifier 5000, and passes along an air circuit 4170 to the patient 1000.3.2 RESPIRATORY SYSTEM AND FACIAL ANATOMY

[0069] Fig. 2 shows an overview of a human respiratory system including the nasal and oral cavities, the larynx, vocal folds, oesophagus, trachea, bronchus, lung, alveolar sacs, heart and diaphragm.3.3 PATIENT INTERFACE

[0070] Fig. 3 shows a patient interface in the form of a nasal mask in accordance with one form of the present technology.3.4 RPT DEVICE

[0071] Fig. 4A shows an RPT device in accordance with one form of the present technology.

[0072] Fig. 4B is a schematic diagram of the pneumatic path of an RPT device in accordance with one form of the present technology. The directions of upstream and downstream are indicated with reference to the blower and the patient interface. The blower is defined to be upstream of the patient interface and the patient interface is defined to be downstream of the blower, regardless of the actual flow direction at any particular moment. Items which are located within the pneumatic path between the blower and the patient interface are downstream of the blower and upstream of the patient interface.

[0073] Fig. 4C is a schematic diagram of the electrical components of an RPT device in accordance with one form of the present technology.

[0074] Fig. 4C-1 is a schematic diagram illustrating the interconnection of various electrical components of the RPT device.

[0075] Fig. 4D is a schematic diagram of the processing implemented in an RPT device in accordance with one form of the present technology.

[0076] Fig. 4E is a flow chart illustrating a method 4500 carried out by the central controller 4230 to continuously compute the base pressure Poas part of an APAP therapy implementation of the therapy parameter determination algorithm 4329, when the pressure support A is identically zero.

[0077] Fig. 4F is a schematic diagram of the processing elements that may be implemented with one or more processors, such as an RPT device and / or one or more servers and / or companion devices (e.g., smart phone, tablet, etc.) in communication with an RPT device, in accordance with some implementations of the present technology.

[0078] Fig. 5A shows a humidifier 5000 that may change the absolute humidity of air or gas for delivery to a patient relative to ambient air. The humidifier 5000 may increase the absolute humidity and increase the temperature of the flow of air (relative to ambient air) before delivery to the patient’s airways.

[0079] Fig. 5B shows a separate view of humidifier 5000 with humidifier base 5006 and heating element 5420.

[0080] Fig. 6A shows an example of the inspirator}' portion of a normal unobstructed by an inspiratory flow limitation determination algorithm.

[0081] Fig. 6B depicts polysomnography channels (pulse oximetry, flow rate, thoracic movement, and abdominal movement) of a patient during non-REM sleep breathing normally over a period of about ninety seconds treated with automatic PAP therapy.

[0082] Fig. 6C shows polysomnography of a patient before treatment. There are eleven signal channels from top to bottom with a 6-minute horizontal span. Channels depicted include two EEG (electroencephalogram) from different scalp locations, submental EMG (electromyogram, EOG (electro-oculogram), electrocardiogram, pulse oximetry (SpO2). chest movement, and abdomen movement.

[0083] Fig. 6D shows patient flow rate data where the patient is experiencing a series of total obstructive apneas. Fig. 7A shows example modules for implementing different dCBT and dCBTi presentation content for different patient subgroups, which may be activated based on a classification of a therapy recommendation engine described herein, such as a machine learning classifier.

[0084] Fig. 7B illustrates an example of timing of delivery of such modules in relation different stages of a patient's therapy pathway.

[0085] Fig. 8 shows one example of an RDV responding to respiratory effort related arousals (RERAs) in the flow signal.

[0086] Fig. 9 provides an example of where the floor pressure is calculated using this method.

[0087] Fig. 10 shows an example of a histogram that describes EEP when an increment was prescribed over 60 minutes

[0088] Fig. 11 illustrates a histogram of EEP levels at which there were pressure increments throughout an entire treatment session.

[0089] Fig. 12 shows an example of a hypnogram during one sleep cycle.

[0090] Fig. 13 shows an example of a patient on benzodiazepines or opioids.4 DETAILED DESCRIPTION OF EXAMPLES OF THE TECHNOLOGY

[0091] Before the present technology is described in further detail, it is to be understood that the technology is not limited to the particular examples described herein, which may vary.It is also to be understood that the terminology used in this disclosure is for the purpose of describing only the particular examples discussed herein, and is not intended to be limiting.

[0092] The following description is provided in relation to various examples which may share one or more common characteristics and / or features. It is to be understood that one or more features of any one example may be combinable with one or more features of another example or other examples. In addition, any single feature or combination of features in any of the examples may constitute a further example.4.1 THERAPY

[0093] The present technology may be applied to a method for treating a respiratory disorder that may include a patient with insomnia or COMI SA. The therapy may include control that apply positive pressure to the entrance of the airways of a patient 1000 and / or presentation of a digital therapy, such as CBTi.4.2 RESPIRATORY THERAPY SYSTEMS

[0094] The present technology may be applied to a respiratory therapy system for treating a respiratory' disorder. A respiratory therapy system may comprise an RPT device 4000 for supplying a flow of air to the patient 1000 via an air circuit 4170 and a patient interface 3000.4.3 PATIENT INTERFACE

[0095] A non-invasive patient interface 3000 in accordance with one aspect of the present technology comprises the following functional aspects: a seal -forming structure 3100. a plenum chamber 3200, a positioning and stabilising structure 3300, a vent 3400, one form of connection port 3600 for connection to air circuit 4170, and a forehead support 3700. In some forms a functional aspect may be provided by one or more physical components. In some forms, one physical component may provide one or more functional aspects. In use the seal -forming structure 3100 is arranged to surround an entrance to the airway s of the patient so as to maintain positive pressure at the cntrancc(s) to the airways of the patient 1000. The scaled patient interface 3000 is therefore suitable for delivery' of positive pressure therapy.4.3.1 Vent

[0096] In one form, the patient interface 3000 includes a vent 3400 constructed and arranged to allow for the washout of exhaled gases, e.g. carbon dioxide.

[0097] In certain forms the vent 3400 is configured to allow a continuous vent flow from an interior of the plenum chamber 3200 to ambient whilst the pressure within the plenum chamber is positive with respect to ambient. The vent 3400 is configured such that the vent flow rate has a magnitude sufficient to reduce rebreathing of exhaled CO:by the patient while maintaining the therapeutic pressure in the plenum chamber in use.

[0098] One form of vent 3400 in accordance with the present technology comprises a plurality of holes, for example, about 20 to about 80 holes, or about 40 to about 60 holes, or about 45 to about 55 holes.

[0099] The vent 3400 may be located in the plenum chamber 3200. Alternatively, the vent 3400 is located in a decoupling structure, e.g., a swivel.4.4 AIR CIRCUIT

[0100] An air circuit 4170 in accordance with an aspect of the present technology is a conduit or a tube constructed and arranged to allow, in use, a flow of air to travel between two components such as RPT device 4000 and the patient interface 3000 or 3800.

[0101] In particular, the air circuit 4170 may be in fluid connection with the outlet of the pneumatic block 4020 and the patient interface 3000. The air circuit may be referred to as an air delivery tube.4.4.1 Supplementary gas delivery

[0102] In one form of the present technology, supplementary gas, e.g. oxygen. 4180 is delivered to one or more points in the pneumatic path, such as upstream of the pneumatic block 4020. to the air circuit 4170, and / or to the patient interface 3000 or 3800.4.5 RPT DEVICE

[0103] An RPT device 4000 in accordance with one aspect of the present technology comprises mechanical, pneumatic, and / or electrical components and is configured to execute one or more algorithms 4300, such as any of the methods, in whole or in part, described herein. The RPT device 4000 may be configured to generate a flow of air for delivery to a patient’s airways, such as to treat one or more of the respiratory conditions described elsewhere in the present document.

[0104] In one form, the RPT device 4000 is constructed and arranged to be capable of delivering a flow of air in a range of -20 L / min to +150 L / min while maintaining a positive pressure of at least 6 cmH20, or at least 10cmH2O, or at least 20 cmH20.

[0105] The RPT device may have an external housing 4010, formed in two parts, an upper portion 4012 and a low er portion 4014. Furthermore, the external housing 4010 may include one or more panel(s) 4015. The RPT device 4000 comprises a chassis 4016 that supports one or more internal components of the RPT device 4000. The RPT device 4000 may include a handle 4018.

[0106] The pneumatic path of the RPT device 4000 may comprise one or more air path items, e g., an inlet air filter 4112, an inlet muffler 4122. a pressure generator 4140 capable of supplying air at positive pressure (e g., a blower 4142). an outlet muffler 4124 and one or more transducers 4270, such as pressure sensors 4272 and flow rate sensors 4274.

[0107] One or more of the air path items may be located within a removable unitary structure which will be referred to as a pneumatic block 4020. The pneumatic block 4020 may be located within the external housing 4010. In one form a pneumatic block 4020 is supported by, or formed as part of the chassis 4016.

[0108] The RPT device 4000 may have an electrical power supply 4210, one or more input devices 4220, such as to receive objective and / or subjective data, a central controller 4230 (which may have a therapy engine and / or a therapy recommendation engine or communicate with a system (e.g., one or more servers) that has a therapy engine and / or a therapy recommendation engine), a therapy device controller 4240, a pressure generator 4140, one or more protection circuits 4250, memory 4260, transducers 4270, data communication interface 4280 and one or more output devices 4290. Electrical components 4200 may be mounted on a single Printed Circuit Board Assembly (PCBA) 4202. In an alternative fonn. the RPT device 4000 may include more than one PCBA 4202.4.5.1 RPT device mechanical & pneumatic components

[0109] An RPT device may comprise one or more of the following components in an integral unit. In an alternative form, one or more of the following components may be located as respective separate units.4.5.1.1 Air filter(s)

[0110] An RPT device in accordance with one form of the present technology may include an air filter 4110. or a plurality of air filters 4110.

[0111] In one form, an inlet air filter 4112 is located at the beginning of the pneumatic path upstream of a pressure generator 4140.

[0112] In one form, an outlet air filter 4114, for example an antibacterial filter, is located between an outlet of the pneumatic block 4020 and a patient interface 3000.4.5.1.2 Muffler(s)

[0113] An RPT device in accordance with one form of the present technology may include a muffler 4120, or a plurality of mufflers 4120.

[0114] In one form of the present technology , an inlet muffler 4122 is located in the pneumatic path upstream of a pressure generator 4140.

[0115] In one form of the present technology, an outlet muffler 4124 is located in the pneumatic path between the pressure generator 4140 and a patient interface 3000.4.5.1.3 Pressure generator

[0116] In one fonn of the present technology, a pressure generator 4140 for producing a flow, or a supply, of air at positive pressure is a controllable blower 4142. For example the blower 4142 may include a brushless DC motor 4144 with one or more impellers. The impellers may be located in a volute. The blower may be capable of delivering a supply of air. for example at a rate of up to about 120 litres / minute, at a positive pressure in a range from about 4 cmH2O to about 20 cmH2O, or in other forms up to about 30 cmH2O when delivering respiratory pressure therapy. The blower may be as described in any one of the following patents or patent applications the contents of which are incorporated herein by reference in their entirety: U.S.Patent No. 7,866,944; U.S. Patent No. 8,638,014; U.S. Patent No. 8,636,479; and PCT Patent Application Publication No. WO 2013 / 020167.

[0117] The pressure generator 4140 is under the control of the therapy device controller 4240.

[0118] In other forms, a pressure generator 4140 may be a piston-driven pump, a pressure regulator connected to a high pressure source (e.g. compressed air reservoir), or a bellows.4.5.1.4 Transducer(s)

[0119] Transducers may be internal of the RPT device, or external of the RPT device. External transducers may be located for example on or form part of the air circuit, e.g.. the patient interface. External transducers may be in the form of non-contact sensors such as a Doppler radar movement sensor that transmit or transfer data to the RPT device.

[0120] In one form of the present technology, one or more transducers 4270 are located upstream and / or downstream of the pressure generator 4140. The one or more transducers 4270 may be constructed and arranged to generate signals representing properties of the flow of air such as a flow rate, a pressure or a temperature at that point in the pneumatic path.

[0121] In one form of the present technology, one or more transducers 4270 may be located proximate to the patient interface 3000.

[0122] In one form, a signal from a transducer 4270 may be filtered, such as by low-pass, high-pass or band-pass filtering.4.5.1.4.1 Flow rate sensor

[0123] A flow rate sensor 4274 in accordance with the present technology may be based on a differential pressure transducer, for example, an SDP600 Series differential pressure transducer from SENSIRION.

[0124] In one form, a signal generated by the flow rate sensor 4274 and representing a flow rate of the flow of air is received by the central controller 4230.4.5.1.4.2 Pressure sensor

[0125] A pressure sensor 4272 in accordance with the present technology' is located in fluid communication with the pneumatic path. An example of a suitable pressure sensor is a transducer from the HONEYWELL ASDX series. An alternative suitable pressure sensor is a transducer from the NPA Series from GENERAL ELECTRIC.

[0126] In one form, a signal generated by the pressure sensor 4272 and representing a pressure of the flow of air is received by the central controller 4230.4.5.1.4.3 Motor speed transducer

[0127] In one form of the present technology a motor speed transducer 4276 is used to determine a rotational velocity of the motor 4144 and / or the blower 4142. A motor speed signal from the motor speed transducer 4276 may be provided to the therapy device controller 4240.The motor speed transducer 4276 may, for example, be a speed sensor, such as a Hall effect sensor.4.5.1.5 Anti-spill back valve

[0128] In one form of the present technology, an anti-spill back valve 4160 is located between the humidifier 5000 and the pneumatic block 4020. The anti-spill back valve is constructed and arranged to reduce the risk that water will flow upstream from the humidifier 5000, for example to the motor 4144.4.5.2 RPT device electrical components4.5.2.1 Power supply

[0129] A power supply 4210 may be located internal or external of the external housing 4010 of the RPT device 4000.

[0130] In one form of the present technology, power supply 421 provides electrical power to the RPT device 4000 only. In another form of the present technology, power supply 4210 provides electrical power to both RPT device 4000 and humidifier 5000.4.5.2.2 Input devices

[0131] In one form of the present technology, an RPT device 4000 includes one or more input devices 4220 in the form of buttons, switches or dials to allow a person to interact with the device. The buttons, switches or dials may be physical devices, or software devices accessible via a touch screen. The buttons, switches or dials may, in one form, be physically connected to the external housing 4010, or may, in another form, be in wireless communication with a receiver that is in electrical connection to the central controller 4230. Such wireless communications may include communications from a companion device, such as a smart phone or tablet, configured to communicate with the RPT.

[0132] In one form, the input device 4220 may be constructed and arranged to allow a person to select a value and / or a menu option.4.5.2.3 Central controller

[0133] In one form of die present technology , the central controller 4230 is one or a plurality of processors suitable to control an RPT device 4000.

[0134] Suitable processors may include an x86 INTEL processor, a processor based on ARM® Cortex®-M processor from ARM Holdings such as an STM32 series microcontroller from ST MICROELECTRONIC. In certain alternative fonns of the present technology, a 32- bit RISC CPU, such as an STR9 series microcontroller from ST MICROELECTRONICS or a 16-bit RISC CPU such as a processor from the MSP430 family of microcontrollers, manufactured by TEXAS INSTRUMENTS may also be suitable.

[0135] In one form of the present technology, the central controller 4230 is a dedicated electronic circuit.

[0136] In one form, the central controller 4230 is an application-specific integrated circuit. In another form, the central controller 4230 comprises discrete electronic components.

[0137] The central controller 4230 may be configured to receive input signal(s) from one or more transducers 4270, one or more input devices 4220, and the humidifier 5000.

[0138] The central controller 4230 may be configured to provide output signal(s) to one or more of an output device 4290. a therapy device controller 4240, a data communication interface 4280, and the humidifier 5000.

[0139] In some forms of the present technology, the central controller 4230 is configured to implement the one or more methodologies described herein, such as the one or more algorithms 4300, or methodologies that may determine or classify COMISA state(s), insomnia state(s). therapy for such states, such as control settings for an RPT, such as for or based on detection of such states or events related thereto, by analysis of stored data expressed as computer programs stored in a non-transitory computer readable storage medium, such as memory 4260. Other therapy may be a digital therapy as described in more detail herein. In some forms of the present technology, the central controller 4230 may be integrated with an RPT device 4000. However, in some forms of the present technology, some methodologies may be performed by a remotely located device. For example, the remotely located device, such as one or more servers, and / or a companion device, may determine or classify COMISA state(s), insomnia state(s), therapy, therapy control settings, such as for an RPT, such as for or based on detection of such states or events related thereto, by analysis of stored data, such as from any of the sensors described herein or entered input, that may be received from, for example, an RPT device at the one or more servers.4.5.2.4 Clock

[0140] The RPT device 4000 may include a clock 4232 that is connected to the central controller 4230.4.5.2.5 Therapy device controller

[0141] In one form of the present technology, therapy device controller 4240 is a therapy control module 4330 that forms part of the algorithms 4300 executed by the central controller 4230.

[0142] In one form of the present technology, therapy device controller 4240 is a dedicated motor control integrated circuit. For example, in one form a MC33035 brushless DC motor controller, manufactured by ONSEMI is used.4.5.2.6 Protection circuits

[0143] The one or more protection circuits 4250 in accordance with the present technology may comprise an electrical protection circuit, a temperature and / or pressure safety circuit.4.5.2.7 Memory

[0144] In accordance with one form of the present technology the RPT device 4000 includes memory 4260, e.g., non-volatile memory. In some forms, memory 4260 may include battery' powered static RAM. In some forms, memory 4260 may include volatile RAM.

[0145] Memory 4260 may be located on tire PCBA 4202. Memory 4260 may be in the form of EEPROM, or NAND flash.

[0146] Additionally or alternatively, RPT device 4000 includes a removable form of memory 4260. for example a memory card made in accordance with the Secure Digital (SD) standard.

[0147] In one form of the present technology, the memory 4260 acts as a non-transitory computer readable storage medium on which is stored computer program instructions expressing the one or more methodologies described herein, such as the one or more algorithms 4300.4.5.2.8 Data communication systems

[0148] In one form of the present technology, a data communication interface 4280 is provided, and is connected to the central controller 4230. Data communication interface 4280 may be connectable to a remote external communication network 4282 and / or a local external communication network 4284. The remote external communication network 4282 may be connectable to a remote external device 4286. The local external communication network 4284 may be connectable to a local external device 4288.

[0149] In one form, data communication interface 4280 is part of the central controller 4230. In another form, data communication interface 4280 is separate from the central controller 4230, and may comprise an integrated circuit or a processor.

[0150] In one form, remote external communication network 4282 is the Internet. The data communication interface 4280 may use wired communication (c.g. via Ethernet, or optical fibre) or a wireless protocol (e.g. CDMA, GSM, LTE) to connect to the Internet.

[0151] In one form, local external communication network 4284 utilises one or more communication standards, such as Bluetooth, or a consumer infrared protocol.

[0152] In one form, remote external device 4286 is one or more computers, such as the aforementioned one or more servers, or, for example, a cluster of networked computers. In one form, remote external device 4286 may be virtual computers, rather than physical computers. In either case, such a remote external device 4286 may be accessible to an appropriately authorised person such as a clinician.

[0153] The local external device 4288 may be a personal computer, mobile phone or smart phone, tablet or remote control.4.5.1.9 Output devices including optional display, alarms

[0154] An output device 4290 in accordance with the present technology may take the form of one or more of a visual, audio and haptic unit. A visual display may be a Liquid Crystal Display (LCD) or Light Emitting Diode (LED) display.4.5.2.9.1 Display driver

[0155] A display driver 4292 receives as an input the characters, symbols, or images intended for display on the display 4294, and converts them to commands that cause the display 4294 to display those characters, symbols, or images.4.5.2.9.2 Display

[0156] A display 4294 is configured to visually display characters, symbols, or images in response to commands received from the display driver 4292. For example, the display 4294 may be an eight-segment display, in which case the display driver 4292 converts each character or symbol, such as the figure “0”. to eight logical signals indicating whether the eight respective segments are to be activated to display a particular character or symbol.4.5.3 RPT device algorithms

[0157] As mentioned above, in some forms of the present technology, the central controller 4230 may be configured to implement one or more algorithms 4300 expressed as computer programs stored in a non-transitory computer readable storage medium, such as memory 4260. The algorithms 4300 may be generally grouped into groups referred to as modules.

[0158] In other forms of the present technology, some portion or all of the algorithms 4300 may be implemented by a controller of an external device such as the local external device 4288 and / or the remote external device 4286. In such forms, data representing the input signals and / or intermediate algorithm outputs necessary for the portion of the algorithms 4300 to be executed at the external device may be communicated to the external device via the local external communication network 4284 or the remote external communication network 4282. In such forms, the portion of die algorithms 4300 to be executed at the external device may be expressed as computer programs stored in a non-transitory computer readable storage medium accessible to the controller of the external device. Such programs configure the controller of the external device to execute the portion of the algorithms 4300.

[0159] In such forms, the therapy determination or therapy parameters generated by the external device via the therapy engine module 4320 and / or the therapy recommendation engine 4329A (if such form part of the portion of the algorithms 4300 executed by the external device) may be communicated to a companion device (e.g.. smart phone or tablet) and / or the central controller 4230 to be passed to the therapy control module 4330 or other output device for generating for example a presentation. Thus, in some example configurations, an external device (e.g.. a remote or local server or other computer that may be in communication with anRPT device) may be configured with the TRE, which may make and communicate recommendations to other devices, such as for presenting a CBT or CBTi therapy with a local external device (e.g., a companion device such as a smart phone or tablet) and / or the RPT device. In some example configurations, a local external device (e.g., a companion device that may be in communication with an RPT device) may be configured with the TRE, which may make and communicate recommendations, such as for presenting a CBT or CBTi therapy (e.g., as output by / on the companion device (such as a smart phone or tablet) and / or the RPT device).4.5.3.1 Pre-processing module

[0160] A pre-processing module 4310 in accordance with one form of the present technology receives as an input a signal from a transducer 4270. for example a flow rate sensor 4274 or pressure sensor 4272, and optionally the pressure-flow curve parameters estimated by the system characterisation algorithm 4305, and performs one or more process steps to calculate one or more output values that will be used as an input to another module, for example a therapy engine module 4320. The pre-processing module 4310 is therefore carried out during therapy with minimal latency between input signals and output signals.

[0161] In one implementation of the present technology , the output values include the interface pressure Pm, the vent flow rate Qv. the respiratory flow rate Qr, and the leak flow rate Qi-

[0162] In various implementations of the present technology, the pre-processing module 4310 comprises one or more of the following algorithms: dynamic pressure drop determination 4311, interface pressure estimation 4312, vent flow rate estimation 4314, leak flow rate estimation 4316. and respiratory flow rate estimation 4318.4.5.3.1.1 Dynamic pressure drop determination 4311

[0163] The pressure drop AP of gas flow through the air circuit may be a parameter that is used by the processor or controller to determine and / or control pressure in the patient interface. In this regard, such a pressure drop AP is typically a static characterization of the patient circuit 4170 that is typically known such that it is entered into the system or determined with a controlled calibration process. In this regard, it is predetermined (prior to use of the therapy apparatus) and may be used by the therapy device for therapy. Such a pressure drop AP may be characterized by a pressure-versus-flow rate curve and will generally remain constant during use of the patient circuit with the RPT.

[0164] In one implementation of the present technology, an interface pressure estimation algorithm 4312 receives as inputs a signal from the pressure sensor 4272 representative of the pressure in the pneumatic path proximal to an outlet of the pneumatic block (the device pressure Pd) and a signal from the flow rate sensor 4274 representative of the flow rate of the airflowleaving the RPT device 4000 (the device flow rate Qd) and provides as an output an estimated pressure, Pm, in the patient interface 3000, which may be taken by the system to be the actual mask therapy pressure.

[0165] In one implementation, the interface pressure estimation algorithm 4312 first computes the total flow rate Qt as the device flow rate Qd plus the flow rate of any supplementary gas 4180. The interface pressure estimation algorithm 4312 then applies equation Error! Reference source not found, to estimate the interface pressure Pm as the device pressure Pd minus the air circuit pressure drop P at the total flow rate Qt. using the pressure drop characteristic P(Q) of the air circuit 4170 or alternatively using the dynamically determined pressure drop to the patient interface APd^,^ as a function of the measure flow rate or total flow rate Qt.

[0166] Optionally, with such an estimation, parameter(s) of operation of the RPT device may be adjusted, by its controller, based on the estimation. For example, a flow or pressure therapy control parameter, such as for operation of the blower, may be adjusted based on the estimation. Optionally, such an adjusted control parameter may thereafter be applied by the RPT device so as to operate the blower to provide any respiratory therapy described herein based on the adjusted control parameter.4.5.3.1.2 Vent flow rate estimation

[0167] In one implementation of the present technology, a vent flow rate estimation algorithm 4314 receives as an input an estimated pressure, Pm, in the patient interface 3000 from the interface pressure estimation algorithm 4312 and estimates a vent flow rate of air, Qv, from the vent 3400 in the patient interface 3000. The relationship between the vent flow rate Qv and the interface pressure Pm for the particular vent 3400 in use is modelled by the vent characteristic f of equation Error! Reference source not found., which may be provided by the sy stem characterisation algorithm 4305 from its knowledge of the type of patient interface 3000 in use.

[0168] Optionally, with such an estimation, parameter(s) of operation of the RPT device may be adjusted, by its controller, based on the estimation. For example, a flow or pressure therapy control parameter, such as for operation of the blower, may be adjusted based on the estimation. Optionally, such an adjusted control parameter may thereafter be applied by the RPT device so as to operate the blower to provide any respiratory therapy described herein based on the adjusted control parameter.4.5.3.1.3 Leak flow rate estimation

[0169] In one implementation of the present technology, a leak flow rate estimation algorithm 4316 receives as an input the total flow rate Qt from the interface pressure estimation algorithm 4312. the vent flow rate Qv from the vent flow rate estimation algorithm 4314. and provides as an output an estimate of the leak flow rate QI.

[0170] In one implementation, the leak flow rate estimation algorithm 4316 estimates the leak flow rate QI by calculating a filtered version (e.g., a low-pass filtered version) of the nonvent flow rate (equal to the difference between the total flow rate Qt and the vent flow rate Qv from the vent flow rate estimation algorithm 4314). The time constant of the low-pass filter is sufficiently long to include several respiratory cycles.

[0171] In one implementation, the leak flow rate estimation algorithm 4316 receives as an input the total flow rate Qt, the vent flow rate Qv, and the estimated pressure Pm in the patient interface 3000 from the interface pressure estimation algorithm 4312. and provides as an output a leak flow rate QI. by calculating a leak conductance, and determining the leak flow rate QI to be a function of leak conductance and interface pressure Pm. Leak conductance may be calculated as the quotient of low pass filtered non-vent flow rate and low-pass filtered square root of interface pressure Pm, where the low-pass filter time constant has a value sufficiently long to include several respiratory cycles. The leak flow rate QI may be estimated as the product of leak conductance and a function, e.g. the square root, of interface pressure Pm.

[0172] In one implementation, the leak flow rate estimation algorithm 4316 receives as an input the total flow rate Qt and the device pressure Pd, and provides as an output an estimate of the leak flow rate QI.

[0173] The method may apply a filter such as a low-pass filter with a time constant of many respiratory cycles to the device pressure Pd, to obtain a filtered device pressure Pd. The method may also compute the total flow rate Qt as the device flow rate Qd, optionally plus the flow rate of any supplementary gas 4180, and applies a filter, such as a low-pass filter, e.g. the same low -pass filter as previously mentioned, to the total flow rate Qt to obtain a filtered total flow rate Qt.

[0174] The next step may find the bias flow rate Qb at the current filtered device pressure Pd using the pressure-flow curve parameters or a lookup table provided by the system characterisation algorithm 4305. This step may involve inverting the pressure-flow curve to find the bias flow rate Qb at the current filtered device pressure Pd. This may be done analytically in the implementations of the technology in which the pressure-flow curve is a quadratic. Alternatively, a lookup table may be created by the system characterisation algorithm 4305, in which values of bias flow rate Qb are tabulated against values of device pressure Pd computed using the pressure-flow curve. The method may then make use of tire lookup table to find the bias flow rate Qb.

[0175] The method may subtract the bias flow rate Qb from the filtered total flow rate Qt to obtain an estimate of the leak flow rate QI.

[0176] Optionally, with such an estimation, an output may be generated. The output may have many forms. In one form, parameter(s) of operation of the RPT device may be adjusted,by its controller, based on the estimation. For example, a flow or pressure therapy control parameter, such as for operation of the blower, may be adjusted based on the estimation. Optionally, such an adjusted control parameter may thereafter be applied by the RPT device so as to operate the blower to provide any respiratory therapy described herein based on the adjusted control parameter. Alternatively, the output may include generating a message (e.g., notification of the leak or recommendation for a specific action to be taken), which is then sent to the user or to a third party, sending data to a remote server etc.4.5.3.1.4 Respiratory flow rate estimation

[0177] In one implementation of the present technology, a respiratory flow rate estimation algorithm 4318 receives as an input the total flow rate Qt. the vent flow rate Qv, and the leak flow rate QI. and estimates a respiratory flow rate Qr by subtracting the vent flow rate Qv and the leak flow rate QI from the total flow rate Qt.

[0178] It may be seen that accurate knowledge of the therapy system pressure-flow characteristic curve, as provided by the therapy system characterisation algorithm 4305, ripples through to accurate estimation of leak flow rate, vent flow rate, and respiratory flow rate by the algorithms of the pre-processing module 4310. with consequent benefits to the efficacy of the respiratory therapy. The therapy engine module 4320 benefits in particular from accurate estimation of the respiratory flow rate Qr.

[0179] For example, with such an estimation, parameter(s) of operation of the RPT device may be adjusted, by its controller, based on the estimation. For example, a flow or pressure therapy control parameter, such as for operation of the blower, may be adjusted based on the estimation. Optionally, such an adjusted control parameter may thereafter be applied by the RPT device so as to operate the blower to provide any respiratory therapy described herein based on the adjusted control parameter.4.5.3.2 Therapy Engine Module

[0180] In some examples of the present technology, a therapy engine module 4320 may be configured to receive data inputs as described in more detail herein, and may provide one or more outputs, such as for providing a COMISA therapy, such as with one or more respiratoiy therapy parameters or digital therapy. Such a therapy engine may comprise, or be communicatively coupled or otherwise cooperate with, a therapy recommendation engine (TRE), such as therapy recommendation engine 4329A, as discussed in more detail herein. As such, the therapy engine module as described herein may include functions of the therapy recommendation engine, such as for determining recommended respiratory and / or digital therapies for COMISA, or implement operations based on recommendations generated by the therapy recommendation engine, such as recommendations related to respiratory therapy for COMISA as described herein. Such functionality may also be discretely implemented by distinct modules, such as to be implemented by one or more processors (e.g.. modules in distinctprocessors, such as a therapy engine module in a first processor as well as a distinct therapy recommendation engine in a second processor, and which may be implemented in the same or different processing devices as described herein, such as any one or more of an external device, such as a local external device or a remote external device (e g., one or more servers), and / or a respiratory therapy (e.g., PAP) device).

[0181] In one form of the present technology, a therapy engine module 4320 may receive as inputs one or more of a pressure. Pm, in a patient interface 3000, and a respiratory flow rate of air to a patient. Qr. and provides as an output one or more therapy parameters.

[0182] In one form of the present technology7, a therapy parameter is a treatment pressure Pt.

[0183] In one form of the present technology, therapy parameters are one or more of an amplitude of a pressure variation, a base pressure, and a target ventilation.

[0184] In various forms, the therapy engine module 4320 comprises one or more of the following algorithms: phase determination 4321, waveform determination 4322, ventilation determination 4323, inspiratory flow limitation determination 4324, apnea / hypopnea determination 4325, snore determination 4326, airw ay patency determination 4327, target ventilation determination 4328, and therapy determination 4329 such as a rccommcndation / prcscntation module and / or therapy parameter determination such as via a therapy parameter determination algorithm 4329 and / or therapy recommendation engine 4329A as described in more detail herein.4.5.3.2.1 Phase determination

[0185] In one form of tire present technology, the RPT device 4000 does not determine phase.

[0186] In one form of the present technology7, a phase determination algorithm 4321 receives as an input a signal representative of respiratory flow rate, Qr, and provides as an output a phase of a current respiratory cycle of a patient 1000.

[0187] In some fonns, known as discrete phase determination, the phase output is a discrete variable. One implementation of discrete phase determination provides a bi-valued phase output with values of either inhalation or exhalation, for example represented as values of 0 and 0.5 revolutions respectively, upon detecting the start of spontaneous inhalation and exhalation respectively. RPT devices 4000 that “trigger” and “cycle” effectively perform discrete phase determination, since the trigger and cycle points are the instants at which the phase changes from exhalation to inhalation and from inhalation to exhalation, respectively. In one implementation of bi-valued phase determination, the phase output is determined to have a discrete value of 0 (thereby “triggering” the RPT device 4000) when the respiratory flow rate Qr has a value that exceeds a positive threshold, and a discrete value of 0.5 revolutions (thereby“cycling” the RPT device 4000) when a respiratory flow rate Qr has a value that is more negative than a negative threshold. The inhalation time Ti and the exhalation time Te may be estimated as typical values over many respiratory cycles of the time spent with phase equal to 0 (indicating inspiration) and 0.5 (indicating expiration) respectively.

[0188] Another implementation of discrete phase determination provides a tri-valued phase output with a value of one of inhalation, mid-inspiratory pause, and exhalation.

[0189] In other forms, known as continuous phase determination, the phase output is a continuous variable, for example varying from 0 to 1 revolutions, or 0 to 2 radians. RPT devices 4000 that perform continuous phase determination may trigger and cycle when the continuous phase reaches 0 and 0.5 revolutions, respectively. In one implementation of continuous phase determination, the phase is first discretely estimated from the respiratory flow rate Qr as described above, as are the inhalation time Ti and the exhalation time Te. The continuous phase at any instant may be determined as the half the proportion of the inhalation time Ti that has elapsed since the previous trigger instant, or 0.5 revolutions plus half the proportion of the exhalation time Te that has elapsed since the previous cycle instant (whichever instant was more recent).4.5.3.2.2 Waveform determination

[0190] In one form of the present technology, the therapy parameter determination algorithm 4329 provides an approximately constant treatment pressure throughout a respiratory cycle of a patient.

[0191] In other forms of the present technolog . the therapy control module 4330 controls the pressure generator 4140 to provide a treatment pressure Pt that varies as a function of phase of a respiratory' cycle of a patient according to a waveform template

[0192] In one form of the present technology , a waveform determination algorithm 4322 provides a waveform template ( ) with values in the range [0, 1] on the domain of phase values provided by the phase determination algorithm 4321 to be used by the therapy parameter determination algorithm 4329.

[0193] In one form, suitable for either discrete or continuously-valued phase, the waveform template ( ) is a square-wave template, having a value of 1 for values of phase up to and including 0.5 revolutions, and a value of 0 for values of phase above 0.5 revolutions. In one form, suitable for continuously -valued phase, the waveform template ( ) comprises two smoothly curved portions, namely a smoothly curved (e.g. raised cosine) rise from 0 to 1 for values of phase up to 0.5 revolutions, and a smoothly curved (e.g. exponential) decay from 1 to 0 for values of phase above 0.5 revolutions. In one form, suitable for continuously-valued phase, the waveform template ( ) is based on a square wave, but with a smooth rise from 0 to 1 for values of phase up to a “rise time” that is less than 0.5 revolutions, and a smooth fallfrom 1 to 0 for values of phase within a “fall time’’ after 0.5 revolutions, with a “fall time” that is less than 0.5 revolutions.

[0194] In some forms of the present technology, the waveform determination algorithm 4322 selects a waveform template ( ) from a library of waveform templates, dependent on a setting of the RPT device. Each waveform template ( ) in the library may be provided as a lookup table of values against phase values . In other forms, the waveform determination algorithm 4322 computes a waveform template ( ) “on the fly” using a predetennined functional form, possibly parametrised by one or more parameters (e.g.. time constant of an exponentially curved portion). The parameters of the functional fonn may be predetermined or dependent on a current state of the patient 1000.

[0195] In some forms of the present technology, suitable for discrete bi-valued phase of either inhalation ( = 0 revolutions) or exhalation ( = 0.5 revolutions), the waveform determination algorithm 4322 computes a waveform template “on the fly” as a function of both discrete phase and time t measured since the most recent trigger instant. In one such form, the waveform determination algorithm 4322 computes the waveform template ( . / ) m two portions (inspiratory and expiratory) as follows:

[0196] where ,(I) ande( are inspiratory and expiratory portions of the wavefonn template ( . / ). In one such form, the inspiratory portion ,(f) of the waveform template is a smooth rise from 0 to 1 parametrised by a rise time, and the expiratory portione(0 of the waveform template is a smooth fall from 1 to 0 parametrised by a fall time.4.5.3.2.3 Determination of Inspiratory Flow limitation

[0197] In one form of the present technology, the central controller 4230 executes an inspiratory flow limitation determination algorithm 4324 for the determination of the extent of inspiratory flow limitation.

[0198] In one form, the inspiratory' flow limitation determination algorithm 4324 receives as an input a respiratory flow rate signal Qr and provides as an output a metric of the extent to which the inspiratory' portion of the breath exhibits inspiratory flow limitation.

[0199] In one form of the present technology, the inspiratory portion of each breath is identified by a zero-crossing detector. A number of evenly spaced points (for example, sixty- five), representing points in time, are interpolated by an interpolator along the inspiratory flow rate-time curve for each breath. The curve described by the points is then scaled by a scalar to have unity length (duration / period) and unity' area to remove the effects of changing breathing rate and depth. The scaled breaths arc then compared in a comparator with a pre-stored template representing a normal unobstructed breath, similar to the inspiratory portion of the breath shownin Fig. 6A. Breaths deviating by more than a specified threshold (ty pically 1 scaled unit) at any time during the inspiration from this template, such as those due to coughs, sighs, swallows and hiccups, as determined by a test element, are rejected. For non-rejected data, a moving average of the first such scaled point is calculated by the central controller 4230 for the preceding several inspiratory events. This is repeated over tire same inspirator} events for the second such point, and so on. Thus, for example, sixty-five scaled data points are generated by the central controller 4230, and represent a moving average of the preceding several inspiratory events, e.g., three events. The moving average of continuously updated values of the (e.g., sixty-five) points are hereinafter called the "scaled flow rate ", designated as Qs(t). Alternatively, a single inspiratory event can be utilised rather than a moving average.

[0200] From the scaled flow rate, two shape factors relating to the determination of partial obstruction may be calculated.

[0201] Shape factor 1 is the ratio of the mean of the middle (e.g. thirty-two) scaled flow rate points to the mean overall (e.g. sixty-five) scaled flow rate points. Where this ratio is in excess of unity, the breath will be taken to be normal. Where the ratio is unity or less, the breath will be taken to be obstructed. A ratio of about 1.17 is taken as a threshold between partially obstructed and unobstructed breathing, and equates to a degree of obstruction that would permit maintenance of adequate oxygenation in a typical patient.

[0202] Shape factor 2 is calculated as the RMS deviation from unit scaled flow rate, taken over the middle (e.g. thirty-two) points. An RMS deviation of about 0.2 units is taken to be normal. An RMS deviation of zero is taken to be a totally flow-limited breath. The closer the RMS deviation to zero, the breath will be taken to be more flow limited.

[0203] Shape factors 1 and 2 may be used as alternatives, or in combination. In other forms of the present technology , the number of sampled points, breaths and middle points may differ from those described above. Furthermore, the threshold values can be other than those described.4.5.3.2.4 Determination of apneas and hypopneas

[0204] In one form of the present technology, the central controller 4230 executes an apnea / hypopnea determination algorithm 4325 for the determination of the presence of apneas and / or hypopneas.

[0205] In one form, the apnea / hypopnea determination algorithm 4325 receives as an input a respiratory flow rate signal Qr and provides as an output a flag that indicates that an apnea or a hypopnea has been detected.

[0206] In one form, an apnea will be said to have been detected when a function of respiratory flow rate Qr falls below a flow rate threshold for a predetermined period of time. The function may determine a peak flow rate, a relatively short-term mean flow rate, or a flowrate intermediate of relatively short-term mean and peak flow rate, for example an RMS flow rate. The flow rate threshold may be a relatively long-term measure of flow rate.

[0207] In one form, a hypopnea will be said to have been detected when a function of respirator)' flow rate Qr falls below a second flow rate threshold for a predetermined period of time. The function may determine a peak flow, a relatively short-term mean flow rate, or a flow rate intermediate of relatively short-term mean and peak flow rate, for example an RMS flow rate. The second flow rate threshold may be a relatively long-term measure of flow rate. The second flow rate threshold is greater than the flow rate threshold used to detect apneas.4.5.3.2.5 Determin ation of snore

[0208] In one fonn of the present technology, the central controller 4230 executes one or more snore determination algorithms 4326 for the determination of the extent of snore.

[0209] In one form, the snore determination algorithm 4326 receives as an input a respiratory flow rate signal Qr and provides as an output a metric of the extent to which snoring is present.

[0210] The snore determination algorithm 4326 may comprise the step of determining the intensity of the flow rate signal in the range of 30-300 Hz. Further, the snore determination algorithm 4326 may comprise a step of fdtering the respiratory flow rate signal Qr to reduce background noise, e.g., the sound of airflow in the system from the blower.4.5.3.2.6 Determin ation of airway paten cy

[0211] In one form of the present technology, the central controller 4230 executes one or more airway patency determination algorithms 4327 for the determination of the extent of airway patency.

[0212] In one form, the airway patency determination algorithm 4327 receives as an input a respiratory flow rate signal Qr, and determines the power of the signal in the frequency range of about 0.75 Hz and about 3 Hz. The presence of a peak in this frequency range is taken to indicate an open airway. The absence of a peak is taken to be an indication of a closed airway.

[0213] In one form, the frequency range within w hich the peak is sought is the frequency of a small forced oscillation in the treatment pressure Pt. In one implementation, the forced oscillation is of frequency 2 Hz w ith amplitude about 1 cmH20.

[0214] In one fonn, airway patency determination algorithm 4327 receives as an input a respirator,' flow rate signal Qr, and determines die presence or absence of a cardiogenic signal. The absence of a cardiogenic signal is taken to be an indication of a closed airway.4.5.3.2. 7 COMISA Screening, Diagnosis and TreatmentGeneral

[0215] Examples of the present technology provide mechanisms to determine COMISA. such as type, severity, etc., and provide suitable therapy. Such examples may include systems.methods and apparatus for the diagnosis and treatment of COMISA. An example of the technologj' may be considered in relation to the schematic diagram of Fig. 4F.

[0216] Some implementations of the present technology may detect COMISA, and therefore, by predictive modelling techniques, including rules-based classification and / or Machine Learning (ML) methods that may be implemented in a COMISA targeted therapy recommendation engine 4329A, which may be integrated with, or be configured to communicate with, a therapy engine 4320 or parameter determination algorithm 4329 thereof. Other modelling techniques may be implemented and would be known to a person skilled in the art.

[0217] The automated modelling / classification techniques of COMISA and / or insomnia states may be considered a therapy recommendation engine that evaluates data that comprises objective information (e.g., calculated metrics such as based one or more sensor signals) and optionally input subjective information. Thus, the therapy recommendation engine may be implemented by, for example, a trained, machine learning classifier. The objective date may be from one or more objective data sources 4317. Subjective information may be from one or more subjective data sources 4313 and may be, for example, entered as in response to questionnaires, such as input to an RPT device, such as via a user interface, or a device linked thereto such as a smart device (e g., smart phone or tablet, etc ), where such questionnaires may be periodically presented to a user of the device(s). Objective information may involve data recording / calculation, such as sleep quality data and event detection, using such RPT devices such as any aforementioned RPT detection methodologies or devices, optionally comprising sensors, associated therewith or associated with the user. Based on its evaluation, the engine may generate therapy output 4331 for controlling or providing a therapy or change to an existing one. such as a suggestion or recommendation for therapy . The therapy may be a digital therapy or other therapy described herein. Such a therapy may be, for example, a modification to a therapy control parameter such as a pressure setting, ventilation setting or flow rate setting, or any other therapy described herein. Such therapies may include or concern, for example, CBT or CBTi for a) OSA onboarding or sleep disorder onboarding (i.e., patient state during an initial period after the patient has been screened for and / or diagnosed with a sleep disorder (such as sleep apnea (e.g., OSA), insomnia, COMISA, etc.), and during which the patient may or may not have been prescribed a therapy for the sleep disorder), b) PAP therapy adherence (i.e., patient state during a period after which the patient has been prescribed or recommended therapy, the state indicating the nature of the patient's adherence to their therapy and / or usage regimen for a respiratory therapy device (e.g., PAP device), such as adherent or deficient), or c) ongoing PAP therapy (i.e.. patient state during a period after which the patient has engaged with the prescribed or recommended therapy, the state indicating the nature of the patient's ongoing therapy which includes issues such as poor sleep quality, insomnia, etc.), which maybe distinctly selected based on a classification of a classifier of the therapy recommendation engine 4329 A, such as by the COMISA assessment module. The digital therapy for treating insomnia may, in some implementations, include ‘’one-shot” therapy intended for treatment of acute, not chronic insomnia. Other digital therapy may be more periodic such as for chronic insomnia.

[0218] Objective data may include, for example, any one or more of: usage hours such as therapy usage hours, respiratory event data (such as number and type of apnea events, the apnea events including obstructive apneas, central apneas, hypopneas. flow limitations, RERA events and may include any of an apnea index, an hypopnea index or an AHI or other sleep disordered breathing event information), leak (such as amount and / or type of leak), mask-on mask-off events (MOMOs). Such data may additionally or alternatively include sleep quality data, OSA screening and / or diagnostic data, which may be obtained from contact sensors such as wearables (e.g.. smart watches, health trackers, etc.), dedicated screening and / or diagnostic devices such as polysomnography or home sleep tests such as ResMed’s ApneaLink Air™ and Ectosense’s NightOwl™ devices, or non-contact sensors such as radar-based sensors or sonarbased sensors. Sleep quality data may include any one or more of sleep stage information, as well as sleep state data, sleep duration, sleep onset latency, sleep efficiency, and physiological data during sleep such as heart rate, heart rate variability, respiration rate, respiration rate variability.

[0219] Subjective data may include, for example, any one of more of: answers to insomnia screening questions, such as may be provided to a patient via e.g., a PAP input feature (e.g., Care Check-In) or a companion device application such as ResMed’s my Air™ app. In some implementations, such questions may be pushed to the patient user of the device only if signs of insomnia are detected from the objective data. Insomnia symptoms can be highly subjective, and prone to misperception. This additional step can therefore verify that the patient is perceiving the issue with their sleep and mitigate false positives prior to treatment.

[0220] As discussed in more detail herein, the proposed methods and systems that measure, analyse, and / or evaluate data may be implemented by any one or more of the aforementioned processors, controllers, external devices, one or more servers, smart phone or tablet, etc., previously mentioned. Such devices may then be implemented to, when suitable, such as based on the classification, present a digital program such as a form of CBTi. (e.g., a one-shot program) to the user and / or modify control parameters of a respiratory therapy device so as to provide a therapy suitable for COMISA patients.COMISA based Therapy

[0221] Thus, the systems, methods and apparatus described herein may be used to direct treatment regimens for COMISA and related sleep and breathing disorders. For example, a PAP device may adjust a treatment pressure to support a particular insomnia classification, such as by providing initial lower pressure for insomnia patients with sleep onset issues. Similarly, breathing exercises for relaxing such patients, which may in part be instructed with generated output from an RPT. such as pressure-based breathing exercises or paced breathing, and may also include provision of an automated CBT or CBTi presentation. These and other implementations are discussed in more detail herein.

[0222] For example, the present technology may include a therapy recommendation engine (TRE) configured to apply defined rules and predetermined thresholds based on objective and / or subjective data. The engine may determine a classification of a patient as a COMISA patient and generate or select a therapy for such patients. The TRE may optionally also incorporate a user’s relative progress in their therapy pathway (e.g., from sleep apnea diagnosis, to beginning therapy, to ongoing therapy, etc.) to further recommend a digital therapy / C BT / C BTi .

[0223] For example, as illustrated in Fig. 6A and 6B, the TRE may make a digital therapy / CBT recommendation or presentation concerning a selection between a plurality of modules, where a module of the modules may be tailored for patients who are newly diagnosed with OSA. The TRE may use. as a rule / threshold for the delivery, the number of “days” a patient is in a monitoring system (e.g., number of days since first contact with a sleep physician, or other care provider, in relation to potential therapy for a sleep disorder) or since the patient began a participation in a screening process (with a screening device such as a wearable, e.g.. smart watch) or a diagnostic process (with a diagnostic device such as a home sleep test device, e.g., ResMed's ApneaLink Air™ or Ectosense's NightOwl™)), to make the selection, which may also guide the implementation of the module recommendation that is provided, although other inputs may be used. The TRE may further use sleep quality data, that may include any one or more of sleep stage data, sleep duration data, sleep onset latency data, sleep efficiency data, and physiological data such as heart rate, heart rate variability, and respiration rate during sleep. The TRE may also use medical record data (e.g., previous diagnosis of insomnia etc., AHI, and drugs prescribed, etc.). As such, the TRE may make digital therapy / CBT recommendations tailored for patients who have received their OSA diagnosis within days (e.g., 30 days) of diagnosis. This may also include patients who have not yet been prescribed PAP, nor made their treatment selection and encompasses content on alternative therapies, e.g., mandibular devices, neurostimulation, surgery , pharmaceuticals.

[0224] Such patients newly diagnosed with OSA may receive, e.g., digitally, a module grormded in psychoeducation, including materials designed to educate patients and review diagnostic results. Other modules may seek to address patient motivation. Modules may be focused on supporting change and improving motivation. Such modules may occur over 2-3 sessions but may be adjusted based on external factors or the needs of the patient. The module may address motivation issues by examining motivation rationales, values, and decisions. The module may include presentations, e.g., videos and user success stories, to aid patient motivation. Such modules may be presented by the aforementioned devices, such as the RPT device, a companion device (e.g., a smart phone or tablet configured to work with the RPT device) and / or one or more servers that communicates with the RPT device and / or the companion device (e.g., a smart phone or tablet). For example, messages may be communicated to such patients that can be used as a link to such modules over a network such as the Internet where the modules may be provided remotely from one or more servers.

[0225] In another example, the TRE may make digital therapy / CBT recommendations / presentations for PAP therapy adherence. As further described in Fig. 6Asuch a module may target non-adherent patients (e.g., patients with low adherence indications such as number of nights of usage, number of consecutive nights of usage, nightly or cumulative hours of usage, etc.) and may be customized based on patient’s personal barriers to adherence. The module may be triggered by rule(s) that evaluate adherence data, and itself start with an assessment, such as via an electronic questionnaire or survey, of the barriers leading to non-adherence. Presentation content from the module may then be personalized based on such assessment and may include material related to, e.g., knowledge deficiency, patient interface (e g., type of user interface), pressure, humidifier settings, insomnia (e.g., type, severity, etc.), accidental non-adherence, claustrophobia or other comfort-related parameters, motivation mental health, and medical co-morbidity.

[0226] The TRE may use “nightly usage hours” and / or “days” in the system as rule(s) which, when compared to predetermined threshold(s), guide the recommendation provided. For example, the TRE may make digital therapy / CBT recommendations tailored for patients receiving PAP therapy with, e.g., PAP usage less than 4 horns per night for 70% of nights over the first 90 days. Such module information may be provided based on usage data, such as therapy usage data, from an RPT device. These rules and respective thresholds may be adjusted based on a variety of factors, including, for example, insurance reimbursement requirements. Other recommendations / presentations may be configured and the rules for triggering module presentation may be modified by region, e.g.. based on local requirements such as local regulatory and / or insurance reimbursement requirements.

[0227] Such non-adherent patients may also be targeted as potential therapy quitters and may be detected from hours of PAP usage per night, nights of usage per week (frequency), changes in PAP usage habits (including, for example, a decrease in usage and / or frequency, changes in start or stop times), increased number of mask-on-mask-off-events (MOMOs), exacerbation in insomnia symptoms.

[0228] In yet another example, the TRE may make digital / CBTi recommendations to COMISA patients receiving ongoing PAP therapy. Thus, CBTi (or one-shot CBTi) may be implemented as a digital program recommended and / or delivered for timely intervention, before acute insomnia becomes chronic. As shown in the example of Fig. 6A, presentation content of the therapy may include instruction or information concerning sleep hygiene, stimulus control and sleep restriction, relaxation strategies, worry time, identifying cognitive errors, cognitive restructuring, and maintenance and relapse prevention. Other content related to COMISA patients receiving ongoing PAP therapy may be included. The modules may be configured to provide the therapy for a limited period of time, such as, for example approximately 5-10 weeks in duration, but may change the duration based on additional factors. CBTi content may be contextualized and adapted for concurrent treatment with a PAP.

[0229] Fig. 7B also illustrates an example of a timeline for when certain CBT modules may be triggered for a patient during care. This timeline is offered as an example of how the modules may be incorporated and may be modified as patient needs and contexts are assessed.

[0230] As previously mentioned, the TRE may use either objective and / or subjective inputs for determining when to trigger a given module and / or for determining what content to present for a given module. For example, objective inputs may include any one or more of: " sleep staging information", "mask events", a "respiratory disturbance variable” (RDV), and other “respiration rate” summary statistics. Subjective inputs may include any one or more of: survey questions and insomnia screening questions. Other objective and subjective factors may be implemented. The TRE may present content that makes recommendations for patients using a PAP that experience difficulty falling asleep and / or staying asleep. Difficulty falling asleep and / or staying asleep may be determined such as by determining that a patient is experiencing sleep related difficulty three or more times weekly for three or more months (i.e., chronic insomnia). The TRE may present to patients with difficulty falling asleep and / or staying asleep three or more times weekly for two or more weeks, a “one-shot” version of a CBTi program. A “one-shot” may be a brief version of a therapy program.

[0231] The therapy recommendation engine may further utilise screening and / or diagnostic data when implementing a digital therapy / CBTi recommendation / presentation of amodule. Such data may include screening / diagnostic data such as from Home Sleep Tests (e.g., ResMed's ApneaLink Air™ or Ectosense's NightOwl™), from PSG tests or from the patient’s Electronic Medical Record (EMR), which may be integrated into the system to capture further information about the patient’s condition. This includes data such as: diagnostic AHI (which indicates type and severity of OSA), medical history (including drug prescriptions, previously documented complaints and previous diagnosis) and demographic data (age, gender, body mass index, etc.).

[0232] Alternatives to the digital behavioural treatments described may include other variants of CBT or CBTi therapy (e.g., individual vs group therapy, in-person vs telemedicine, physical vs digital delivery of therapy, interactive vs hybrid therapy).

[0233] Alternatives for diagnosis or screening of COMISA might include development of a diagnostic or screening questionnaires. Such alternatives may be adopted in sleep labs for identifying patients with COMISA.

[0234] Data concerning a previous diagnosis of insomnia or drug prescription, such as for sleeping medication, may be input into the therapy recommendation engine. The type of insomnia (initial, middle or late) is also relevant for the TRE, and may influence the course of treatment.

[0235] The TRE may also receive or access data (such as by pulling data via an API) from consumer wearable devices. This permits the engine to also evaluate overnight sleep information and longitudinal sleep data from wearable devices such as Apple Watch™, Fitbit™ etc. so that the engine may consider such data in triggering or implementing a module of digital therapy, such as CBT or CBTi.

[0236] Other objective measures may include sleep staging data such as the generated via analysis of airflow signal, radio frequency (RF) sensor and / or sound-based sensing (e.g.. passive sensing or active sensing, such as sonar) as described in, for example, U.S. Patent Nos. 9.687, 177, 10.376.670, and U.S. Patent Application publication no. 2021 / 0275056. the entire disclosures of each of which are incorporated herein by reference.

[0237] Other objective measures for input to the therapy recommendation engine, such as for determining whether a patient is a COMISA patient and generating a suitable therapy, may include a Respiratory Disturbance Variable (RDV). RDV is a continuous metric based on envelope analysis of the flow signal (derived from flow sensor data generated by a flow sensor comprised in a respiratory' device such as a PAP device), which quantitatively reflects departure from normal sinusoidal breathing at each epoch (e.g., periods of time (such as 30 seconds), oneor more respirator}' cycles, etc.), providing an intensity’ scale for breathing disturbance. RDV captures disturbance in the flow signal due to, e.g., movement, wake state, arousals including respiratory' effort related arousals (RERAs), snoring, flow limitation, hypopneas and apneas. As shown in Table 1, thresholds can be applied to the continuous metric to classify states such as Normal Breathing, Disturbed Breathing, Hypopneas or Apneas.

[0238] The distribution of the RDV can be analysed, and summary statistics calculated, and which may indicate that a patient spending a prolonged period in the Disturbed Breathing state, e.g., 95thpercentile of the RDV. AHI may be calculated by the based e.g. on flow signal data, can subsequently be used to discriminate patients whose RDV is high due to residual apneas and hypopneas occurring. Patients with a right skew of their RDV (as indicated by a higher value for the 75thor 95dlpercentile statistic), but low AHI may be suffering from disturbed sleep and / or insomnia such that they may thereby be deemed a COMI SA patient and a suitable COMISA related therapy may then be provided. RDV may also be used to monitor a patient's insomnia, such as COMISA, over time and in response to the digital therapies described herein, mechanical therapies such as PAP and ASV as described herein, pharmaceutical interventions, etc.

[0239] By way of example, and for further illustration, RDV may be calculated by first filtering the flow signal and finding the signal envelope (SE). A 4th order low-pass Butterworth filter may be used at a cut-off frequency of 0.40 Hz. This calculation may' further use a Hilbert transform in order to find the SE. Next, the flow signal is sequenced using a Variable Sliding Window (VSW) algorithm. Discrete variable epochs are analysed and a high absolute difference or standard deviation in the SE are an indicator of sufficient change. RDV may be calculated as:<TH * 0.523

[0240] Three applications of VSW are used and the average is taken to give a more reliable result. After the creation of variable length epochs, the output can be smoothed by eliminating excess noise. A rolling incremental point may be used to track the changes thatoccur in the output. This action can remove both rising and falling edges and excess peaks and troughs based on the output’s relative magnitude and duration.

[0241] Fig. 8illustrates a plot of an example of the RD V responding to RERAs in the flow signal while using a PAP respiratory therapy device. When a RERA occurs, the RDV rises in response to this event in the flow signal. When the event is over, and normal breathing resumes, the RDV reduces back to baseline levels. These changes in the RDV metric may be taken as an indication of sleep disturbance and, as such, used to indicate a potential COMISA patient.

[0242] Another aspect of the present technology involves the provision of a respiratory therapy suitable for a COMISA patient. This technology may include an adaptation of a mechanical therapy via airflow supplied by a respiratory’ device such as an RPT as described in more detail herein. Such a respiratory' therapy device may produce a therapy, such as with a determination by the aforementioned engine which may detect COMISA, and may then modify therapy parameters to provide a COMISA adapted respiratory therapy. Such a respiratory therapy may include an adaptive servo-ventilation (ASV) therapy mode for treating COMISA and / or Automatic Positive Airway Pressure (APAP, also known as auto-adjusting Positive Airway Pressure) therapy, which is an automatic titration of a therapy pressure, but tailored for treating COMISA.ASV with Adaptive Floor Pressure

[0243] Certain adjustments can be made to ASV therapy, for the specific treatment of COMISA patients. Such adjustments include ASV with an adaptive floor pressure. An adaptive floor pressure calculation involves a moving end expiratory pressure (EEP) that generally remains static during expiration. Previous algorithms have incorporated an adaptive floor pressure that w orks on the basis that if two obstructive apneas occur, the pressure reached by the end of tire second apnea will become a new APAP minimum pressure for the night. If pressure is automatically titrated higher due to subsequent event detection in that night, but afterward decays due to an absence of events, the titrated pressure goes no lower than that new raised APAP minimum. This approach potentially does not provide enough support for complex insomnia patients. Complex insomnia patients tend to have a low arousal threshold and consequently require a more aggressive EEP titration scheme.

[0244] One possible implementation to address the problem, and which targets an aggressively titrating floor pressure, the therapy engine may generate an ASV therapy that is based on analysing the distribution of EEP increments. For example, if there are X number of increments within Y minutes of each other, this may be taken as reflecting a situation w herethe EEP level below the currently set level is insufficient and would therefore be advantageous to prevent pressure decay below it (e.g., by setting a new minimum for automated pressure titration based on the evaluation of the distribution). In this example, if at time point A die EEP is 4 cmH2O and then at time point B - 3 minutes after time point A - the EEP is 8.5 cmH20 and there have been 10 increments between points A and B. If the threshold for number of increments (X) is 9 and the threshold for time between points (Y) is 5 minutes, the floor pressure would be set because there were greater than 9 increments and the time between time points is less than 5 minutes.

[0245] As an additional evaluation to the above method, the aggregate increment may also be considered. For example, if the aggregate increments and the time between the time points is greater than 3 cmH2O in addition to the aforementioned example conditions, the floor pressure may also be set.

[0246] Fig. 9 illustrates an example of a calculated floor pressure according to this algorithm. As illustrated, whenever there are quick successive increments involving the EEP titration, the floor pressure is incremented (e.g., raised) in response.

[0247] A more complex approach might involve analysing the distribution of pressure increments over a long period of time (e.g.. 60 minutes). Based on a parametric or nonparametric statistical analysis, a determination whether to set (adjust) or not a floor pressure can be made. Fig. 10 shows an example of a histogram that describes EEP when an increment was prescribed over 60 minutes. In this example, if pressure is applied at the point at which the highest peak occurs (peak location of the histogram), the floor pressure would be set at 7 cmH2O. This process could be subsequently repeated, for example, every 60 minutes. The analysis period could typically range anywhere between 30 to 300 minutes but could vary based on external factors. The frequency of the analysis (i.e., how often the statistical analysis of pressure increments would be done), could be the same. However, time periods outside the specified range could also be used.

[0248] A manual titration with ramp may be employed to achieve specific benefits. For example, if it is known what pressure is necessary to maintain patency, it may only be beneficial to deviate from this predetermined pressure while the patient is awake.

[0249] Traditional approaches where lower pressure is viewed as providing more beneficial outcomes have had equivocal clinical support. Cardiovascular outcomes may be diminished due to higher event rates. If a patient is inherently benefitting from bilevel (described below) to counter the discomfort, mask seal is maintained at higher pressures (whichis an underlying assumption during pressure support), mouth leak is not worse at higher pressure, and humidification is common, then reasons for backing off EEP might be limited to wake periods.[0250| An automated approach for an RPT device (e.g., algorithm for any of the aforementioned processors in a therapy engine) that identifies an effective pressure (such as by auto-titration of EEP) and only permits decay (i.e., adjusts downward) if the engine detects that the patient is awake, such as by analysis of a signal from one or more of the sensors (e.g., a mask off event or detection of arousal etc.), is a potentially desirable therapy for COMISA patients. Such an approach would be similar to the method described above but could also be extended across multiple nights. A middle-ground approach could involve being reactive to events each night but prepared to increase EEP if previous nights have established similar effective pressures.ASV with Slow Moving EEP

[0251] Another adjustment to ASV therapy, for the specific treatment of COMISA patients, includes ASV with Slow Moving EEP. The Slow Moving EEP feature that may be provided by the therapy engine is a night-to-night learning of EEP. Slow Moving EEP may be used instead of or in combination with the Adaptive Floor Pressure previously mentioned. Methods involving learning 95thpercentile or median of the EEP have been previously suggested for Slow Moving EEP. However, these methods tend to compromise the benefits that standard automatically adjusting EEP techniques provide (i.e., only providing really high pressures if there is a change in body position or if in specific sleep stage) because they may lock in a high pressure for the entire treatment duration.

[0252] The therapy engine may be configured to determine and analyse the distribution of the EEP levels in which increments occur in one session and set one for a next session based on the distribution. In this regard, the distribution may reveal an EEP level which may be required for most of a treatment period (i.e., a night of sleep). Thus, the engine may set a new EPP level for a next session based on such an analysis. As an example. Fig. 11 illustrates a histogram of EEP levels at which there were pressure increments throughout an entire treatment session, which may be detennined by the therapy engine. In this case, the EEP for the next treatment session would be set to 7 cm H20 (because it is at a level that addresses most of the incidents - i.e., not many adjustment intervals exceeded that pressure or a majority (e.g.. more than half or a higher percentage etc.) of interval counts occurred below that pressure). This would be sufficient for large periods and still allow for the pressure to climb if necessary. A patient may benefit from lower leak levels and increased comfort.Sleep-State ASV

[0253] In some versions the TRE may generate, or other set or adjust, therapy settings, or generate a therapy recommendation such as an ASV therapy, based on a detected sleep state. Such a Sleep-State based ASV may implement a detected sleep state as a weight on the controller gain (i.e., a gain-based sleep state), such as the gain G of equation (2) described in more detail herein. Sleep State and / or sleep stage can be inferred from various sensors, such as from a flow signal from a flow sensor as described in e.g.. PCT Application Publication No. WO 2002 / 249013A1. the entire disclosure of which is incorporated herein by reference. Sleep state is generally understood to include wake and asleep states, and sleep stages, as defined by the American Academy of Sleep Medicine (AASM), include five sleep stages: awake, N1 (SI), N2 (S2). N3 (S3 + S4). and REM., Sleep State and / or sleep stage information may be used to weight the controller gain of the ASV algorithm according to the following calculation:ModifiedControllerGain — SleepStateWeight * Raw Controller Gain

[0254] Complex insomnia patients often experience an elevated state of anxiety and stress and thus may be particularly vulnerable to being unsettled by changes in therapy. Substantial pressure swings while patients are awake may be undesirable. Consequently, the Sleep State ASV algorithm could be particularly useful for this type of patient. If the algorithm infers the patient being in a wake state, the weight would be close to 0. Conversely, if the algorithm infers the patient is in a sleep state, the weight may be closer to 1 . The transition from a weight of 0 to 1 (and vice versa) could be linear, exponential, or a binary change.

[0255] The Sleep State detection may also be implemented by the therapy engine to change the therapy so as to initiate applying a paced breathing algorithm if the patient is awake such as at the start of the treatment session or as a result of an awakening at a later point during the treatment session. Sleep State may inferred or determined from any suitable sensor such as being be inferred from a flow signal from a flow signal (as previously described). Sleep State may also be inferred from external signals (e.g., PPG, EEG. ECG, Actigraphy, or Skin Conductance measurement). Such a paced breathing algorithm may be according to the method described in U.S. Patent Application Publication No. 2023-0277786, the entire disclosure of which is incorporated herein by reference.Automatic Positive Airway Pressure (APAP) therapy mode for COMISA

[0256] An Automatic Positive Airway Pressure (APAP) such as ResMed's Autoset™ technolog}', may be adapted for COMISA patients so that it can operate as a therapy mode designed to treat OSA patients with co-morbid insomnia. A design goal may be to improvesleep in these particular patients (e.g., fall asleep faster, stay asleep for longer) and consequently prevent or reduce non-adherence with PAP therapy provided by the RPT device. This PAP therapy setting for the RPT device may improve treatment in COMISA patients and may, for example, be remotely administered by physicians (e.g., activated without a change in hardware) but it also may be activated based on a classification made by the therapy engine. As such, it may be configured as a temporary' change in settings to help patients manage a period of insomnia before switching back to their regular APAP therapy mode, such as by setting the mode for a limited period of time, or triggering disabling of the mode in the absence of a subsequent / contemporary COMISA classification by the therapy engine.

[0257] For example, at the beginning of the night, the APAP configured for COMISA may have a number of operations designed to help patients to fall asleep faster. One example may include incorporating a paced breathing therapy’ control algorithm that uses a combination of audio, visual and PAP pressure cues to reduce a patient’s breathing rate and relax them to sleep (e.g., a paced breathing technology such as described in U.S. Patent Application Publication No. 2023-0277786). Other examples may include visual and / or audio cues for paced breathing from an application or "app" miming on a smart phone or a local external device that may operate independently or in conjunction with (e.g., synchronized with) the cues of PAP device. Although it may be triggered by the classification of the therapy recommendation engine 4329 A, it may still be offered as an opt-in program to patients. For example, the RPT device or companion device application may prompt a user to consider using the paced breathing therapy and the user’s acceptance that is input to any of such devices may then activate the controller to generate / provide the paced breathing with the RPT device and optionally with the companion device as well that may provide additional visual and / or audio support for the paced therapy.

[0258] Additionally, another therapy modification for the COMISA mode may concern starting pressures that are initially provided at more comfortable levels at detected mask on event(s) and which are gradually ramped higher to therapeutic pressure(s) or a prescribed therapy pressure. Instead, the APAP may’ implement sleep staging detection that monitors for sleep onset before activating the pressure ramping following mask on event detection (e.g.. by monitoring pressure change indicative of patient initially donning a mask). This sleep onset triggered ramping may be activated by a COMISA related classification of the therapy engine and may be deactivated in an absence of such a classification. This sleep onset pressure ramping control may maintain pressure(s) at a comfortable minimum level(s) until the sleep onset event is detected and then may increase according to a ramping algorithm thereafter. The sleep onset pressure ramping control may maintain pressures within a predetermined range. Such sleepdetection may, for example, be made by monitoring a flow signal for indications of changes in respiration suggestive of a beginning of sleep (e g., slowing and / or steadying of respiration rate).|0259| Additionally, another therapy modification for the C0M1SA mode may enable the patient to choose an alternative pressure waveform (e.g., the time varying shape of pressure changes during any given respiration cycle) that is provided by the RPT device for comfort preceding or during the sleep onset period. This may be triggered and offered to the patient based on. or in response to, a COMISA classification of the therapy engine. When so triggered, the patient may be offered to trial or sample a range of pressure waveforms designed for comfort and prompt the patient to select one of their preference. Such a patient selection of waveforms or the different types of waveforms may be provided as disclosed in U.S. Provisional Patent Application No. 63 / 496,054, filed on April 14, 2023 and / or PCT / AU2023 / 051038, filed on October 19, 2023, the entire disclosures of each of which are incorporated herein by reference. Optionally, in the absence of such a manual selection or manual selection process, the RPT device may randomise or otherwise provide different waveforms on different nights during a learning period (e.g., the first few nights of PAP therapy) and select, for later sessions, one that is most effective for inducing sleep onset and / or maintaining sleep for the patient by monitoring the resulting sleep onset latency and sleep quality associated with the different waveforms. The process can then select the optimum waveform, based on the best sleep onset latency and / or best sleep quality data, as one drat can serve as the patient's personal preference thereafter. Additionally, the therapy of the RPT device may be modified to use CO2 to assist patients in falling asleep and / or with selection of a best wavefonn for inducing sleeping. Such a configuration can permit the RPT device to monitor CO2 levels in the mask, such as with a CO2 sensor, to ensure that levels remain within a safe range. Some waveforms may be associated with a build-up of CO2 and the PAP system may provide or modify the waveform so that different CO2 levels can be provided during the waveform selection process (e.g., waveform with gentle EPAP that only varies from IPAP by a few cm H2O). Thereafter, an optimum CO2 related waveform may be used when determined to be optimal for inducing sleep onset.

[0260] An APAP mode for COMISA that adjusts therapy pressures based on SDB events throughout the night may also be activated and / or deactivated based on sleep staging detection and knowledge of sleep cycle durations. For periods where the patient is asleep and less likely to be aroused, the therapy may change from the APAP mode to a CPAP mode. A CPAP mode typically remains at a prescribed therapy pressure and as such, does not respond to detected SDB events by changing pressure. Fig. 12 shows an example of a hypnogram during one sleep cycle. N3 is the most difficult stage to be awakened, and so, based on the detection of thepresence of this stage, the therapy may remain in the CPAP mode. For others stages where there is a higher probability of arousal (e.g., N2 and / or REM), the therapy may be change to the APAP mode, which may maximise comfort. For example, if sleep staging detects REM sleep, the system may monitor the duration of the REM cycle. Towards the expected end of the REM period (e.g., a probability based on learned knowledge of the user's sleep architecture, which includes information on sleep stages and sleep cycles) the therapy may switch to the APAP mode. Unprovoked awakening occurs most commonly during or after a period of REM sleep, as body temperature is rising - the use of adjusting pressures in the APAP mode (which may be lower than the CPAP mode) is intended to prevent or minimise this disturbance to patient sleep when in this stage. However, many patients experience most of their OSA events during REM sleep (REM predominant OSA). It is therefore beneficial to balance comfort with maximising treatment for as long as possible during these periods (CPAP). Knowledge of sleep architecture may be built into the process of the engine based on scientific evidence in the literature. The engine process may also incorporate a patient’s diagnostic data (e.g., PSGdata). This PSG data may allow for personalised calibration of the sleep cycle knowledge of the system. The process then can learn and reinforce this information with patient sleep staging detection as the patient uses the RPT device for several nights.

[0261] Additionally, the therapy engine may predict the end of the patient's sleep (i.c., the end of the sleep night) based on patients’ prior behaviours and habits as seen from the end time of historical PAP recordings. It may also pull comparable information from an alarm time setting, if set by the patient. At such a predicted “end of the night,’’ the process may then switch again to an APAP mode.

[0262] Another aspect of the present technology may concern a detection of the use of a pharmacological treatment (e.g., benzodiazepines or opioids) for insomnia and providing a suitable therapy based on such a detection. In some such implementations, biomarkers of pharmacological treatment may be detected in a flow signal, from which a respiration signal may be derived, a respiration signal otherw ise derived such as from a contact or non-contact sensor, or identified by input by a user or physician such as in response to a questionnaire. The present technology may aid in selecting and providing therapy, such as digital therapy and / or mechanical therapy, for treating insomnia based on the pharmacological treatment.

[0263] For example, the therapy engine may be configured for identification of pharmacological treatment of insomnia based on one or more respiration biomarkers or other parameters of the flow signal. Phannacological treatment may also be identified by user (e.g., patient) or physician input. The present technology may identify both the use of pharmacological treatment as well as changes in that pharmacological treatment (e.g., reducedor increased usage in terms of frequency and / or dose of the pharmacological treatment). Changes may be detected, such as by the therapy engine and may be flagged to a physician (e.g., changes that indicates increased use. decreased use, ceased use) by generating a message based on tire detected change. The use of pharmacological treatments, and / or changes in that treatment, may then be implemented as a basis for adjustments to digital and / or mechanical therapies. Changes may also serve as a basis to monitor and promote decreases in usage (i.e., weaning off) of pharmacological treatment with physician input or authorization.

[0264] It is known that respiratory depressant drugs (e.g., benzodiazepines or opioids) tend to suppress breathing and may leave a signature in a flow signal such as of an RPT device. For example, this may be manifested in longer expiratory breathing pauses and an altered breathing cycle length. This may also be related to any one or more of respiratory rate variability, respiratory rate distribution over a period (e.g., hourly, daily), volume and / or length of respiratory pauses, obstructive and / or central apneas (e.g., a number and / or severity of such events), and apnea and / or hyperpnea cycle lengths or central apnea cycle lengths (e.g.. start of first apnea to next apnea, or peak distance between hypemea). Any one or more of such features determined from the flow signal may then be detected and classified by the therapy engine, such as, to determine whether or not a pharmacological treatment is present, newly present, no longer present, and / or changing (e.g., increasing or decreasing). Based on such a classification, which may also be implemented as an indication of a COMI SA status accordingly, the therapy engine may modify a therapy, such as described herein. For example, a detection of a new presence of such a pharmacological treatment may serve as a basis to initiate a therapy change to a COMISA related therapy (e.g., a digital and / or pressure therapy change as previously discussed). Similarly, a detection of a new absence of such a phannacological treatment may serve as a basis to terminate a COMISA related therapy (e.g., a digital and / or pressure therapy change as previously discussed).

[0265] Fig. 13 shows an example of a patient on benzodiazepines or opioids. The bottom trace is the PAP flow signal while the top trace is the PSG EEG that is scored for sleep state. Increased expiratory pauses at IEP, a number of transitions in and out of S2 sleep (corresponding to N2 sleep stage) at S2T, and short cycle lengths at SCL are present in the signals. A number of such detected events, such as when compared to respective thresholds, may be taken as an indication of pharmacological use.4.5.3.2.8 Determin ation of th erapy parameters

[0266] Thus, in some forms of the present technology, the central controller 4230 executes one or more therapy determination and / or parameter determination algorithms 4329 for the determination of one or more therapy parameters using the values returned by one ormore of the other algorithms in the therapy engine module 4320. Such output may include, for example, providing initial lower pressures or a paced breathing therapy as previously discussed in more detail.

[0267] In some forms of the present technology, the therapy parameter is an instantaneous treatment pressure Pt. In one implementation of this form, the therapy parameter determination algorithm 4329 determines the treatment pressure Pt using the equation / 7 = / 4n (O ) +o(1)

[0268] where:• A is the amplitude,• ( f) is the waveform template value (in the range 0 to 1) at the current value of phase and / of time, and• Po is a base pressure.

[0269] If the waveform detennination algorithm 4322 provides the waveform template( as a lookup table of values indexed by phase . the therapy parameter determination algorithm 4329 applies equation (1) by locating the nearest lookup table entry to the current value of phase returned by the phase determination algorithm 4321, or by interpolation between the two entries straddling the current value of phase.

[0270] The values of the amplitude A and the base pressure Po may be set by the therapy parameter determination algorithm 4329 depending on the chosen respiratory pressure therapy mode in the manner described below.4.5.33 Therapy Control module

[0271] The therapy control module 4330 in accordance with one aspect of the present technology receives as inputs the therapy parameters from the therapy parameter determination algorithm 4329 of the therapy engine module 4320, and controls the pressure generator 4140 to deliver a flow of air in accordance with the therapy parameters.

[0272] In one form of the present technology, the therapy parameter is a treatment pressure Pt, and the therapy control module 4330 controls the pressure generator 4140 to deliver a flow of air whose interface pressure Pm at the patient interface 3000 is equal to the treatment pressure Pt.4.6 RESPIRATORY THERAPY MODES

[0273] Various respiratory therapy modes may be implemented by the disclosed respiratory therapy system including the RPT and based on a determination by the therapy engine.4.6.1 CPAP therapy

[0274] In some implementations of respiratory pressure therapy, the central controller 4230 sets the treatment pressure Pt according to the treatment pressure equation (1) as part ofthe therapy parameter determination algorithm 4329. In one such implementation, the amplitude A is identically zero, so the treatment pressure Pt (which represents a target value to be achieved by the interface pressure Pm at the current instant of time) is identically equal to the base pressure Po throughout the respiratory' cycle. Such implementations are generally grouped under the heading of CPAP therapy. In such implementations, there is no need for the therapy engine module 4320 to determine phase or the waveform template ( ).

[0275] In CPAP therapy, the base pressure Po may be a constant value that is hard-coded or manually entered to the RPT device 4000. Alternatively, the central controller 4230 may repeatedly compute the base pressure Po as a function of indices or measures of sleep disordered breathing returned by the respective algorithms in the therapy engine module 4320, such as one or more of flow limitation, apnea, hypopnea, patency, and snore. This alternative is sometimes referred to as APAP therapy.

[0276] Fig. 4E is a flow chart illustrating a method 4500 carried out by the central controller 4230 to continuously compute the base pressure Po as part of an APAP therapy implementation of the therapy parameter determination algorithm 4329. when the pressure support A is identically zero.

[0277] The method 4500 starts at step 4520. at which the central controller 4230 compares the measure of the presence of apnea / hypopnea with a first threshold, and determines whether the measure of the presence of apnea / hypopnea has exceeded the first threshold for a predetermined period of tune, indicating an apnea / hypopnea is occurring. If so, the method 4500 proceeds to step 4540; otherwise, the method 4500 proceeds to step 4530. At step 4540, the central controller 4230 compares the measure of airway patency with a second threshold. If the measure of airway patency exceeds the second threshold, indicating the airway is patent, the detected apnea / hypopnea is deemed central, and the method 4500 proceeds to step 4560; otherwise, the apnea / hypopnea is deemed obstructive, and the method 4500 proceeds to step 4550.

[0278] At step 4530, the central controller 4230 compares the measure of flow limitation with a third threshold. If the measure of flow limitation exceeds die third threshold, indicating inspiratory flow is limited, the method 4500 proceeds to step 4550; otherwise, the method 4500 proceeds to step 4560.

[0279] At step 4550. die central controller 4230 increases the base pressure Po by a predetermined pressure increment P, provided the resulting treatment pressure Pt would not exceed a maximum treatment pressure Pmax. In one implementation, the predetermined pressure increment P and maximum treatment pressure Pmax are 1 cmH20 and 25 cmH20 respectively. In other implementations, the pressure increment P can be as low as 0.1 cmH20 and as high as 3 cmH2O, or as low as 0.5 cmH2O and as high as 2 cmH2O. In other implementations, the maximum treatment pressure Pmax can be as low as 15 cmH20 and ashigh as 35 cmH20, or as low as 20 cmH2O and as high as 30 cmH2O. The method 4500 then returns to step 4520.

[0280] At step 4560, the central controller 4230 decreases the base pressure Po by a decrement, provided the decreased base pressure Po would not fall below a minimum treatment pressure Pmin. The method 4500 then returns to step 4520. In one implementation, the decrement is proportional to the value of P0-Pmin, so that the decrease in Poto the minimum treatment pressure Pmin in the absence of any detected events is exponential. In one implementation, the constant of proportionality is set such that the time constant of the exponential decrease of Po is 60 minutes, and the minimum treatment pressure Pmin is 4 cmH2O. In other implementations, the time constant could be as low as 1 minute and as high as 300 minutes, or as low as 5 minutes and as high as 180 minutes. In other implementations, the minimum treatment pressure Pmin can be as low as 0 cmH2O and as high as 8 cmH20, or as low as 2 cmH2O and as high as 6 cmH2O. Alternatively, the decrement in Po could be predetermined, so the decrease in Po to the minimum treatment pressure Pmin in the absence of any detected events is linear.4.6.2 Bi-level therapy

[0281] In other implementations of this form of the present technology, the value of amplitude A in equation (1) may be positive. Such implementations are known as bi-level therapy, because in determining the treatment pressure Pt using equation (1) with positive amplitude A, the therapy parameter determination algorithm 4329 oscillates the treatment pressure Pt between two values or levels in synchrony with the spontaneous respiratory effort of the patient 1000. That is, based on the ty pical waveform templates ( t) described above, the therapy parameter determination algorithm 4329 increases the treatment pressure Pt to Po + A (known as the IPAP) at the start of, or during, or inspiration and decreases the treatment pressure Pt to the base pressure Po (known as the EPAP) at the start of, or during, expiration.

[0282] In some forms of bi-level therapy, the IPAP is a treatment pressure that has the same purpose as the treatment pressure in CPAP therapy modes, and the EPAP is the IPAP minus the amplitude A, which has a “small” value (a few cmH2O) sometimes referred to as the Expiratory' Pressure Relief (EPR). Such forms are sometimes referred to as CPAP therapy with EPR, which is generally thought to be more comfortable than straight CPAP therapy. In CPAP therapy with EPR. either or both of tire IPAP and the EPAP may be constant values that are hard-coded or manually entered to the RPT device 4000. Alternatively, the therapy parameter determination algorithm 4329 may repeatedly compute the IPAP and / or the EPAP during CPAP with EPR. In this alternative, the therapy parameter determination algorithm 4329 repeatedly computes the EPAP and / or the IPAP as a function of indices or measures of sleep disordered breathing returned by the respective algorithms in the therapy engine module 4320in analogous fashion to the computation of the base pressure Po in APAP therapy described above.

[0283] In other forms of bi-level therapy, the amplitude A is large enough that the RPT device 4000 does some or all of the work of breathing of the patient 1000. In such forms, known as pressure support ventilation therapy, the amplitude A is referred to as the pressure support, or swing. In pressure support ventilation therapy, the IPAP is the base pressure Po plus the pressure support A. and the EPAP is the base pressure Po.

[0284] In some fonns of pressure support ventilation therapy, known as fixed pressure support ventilation therapy, the pressure support A is fixed at a predetermined value, e.g. 10 cmH2O. The predetermined pressure support value is a setting of the RPT device 4000, and may be set for example by hard-coding during configuration of the RPT device 4000 or by manual entry through the input device 4220.

[0285] In other fonns of pressure support ventilation therapy, broadly known as servoventilation, the therapy parameter determination algorithm 4329 takes as input some currently measured or estimated parameter of the respiratory cycle (e.g. the current measure Vent of ventilation) and a target value of that respiratory parameter (e.g. a target value Vtgt of ventilation) and repeatedly adjusts the parameters of equation (1) to bring the current measure of the respiratory parameter towards the target value. In a form of servo-ventilation known as adaptive servo-ventilation (ASV). which has been used to treat CSR, the respiratory parameter is ventilation, and the target ventilation value Vtgt is computed by the target ventilation determination algorithm 4328 from the ty pical recent ventilation Vtyp, as described above.

[0286] In some fonns of servo-ventilation, the therapy parameter detennination algorithm 4329 applies a control methodology to repeatedly compute the pressure support A so as to bring the current measure of tire respiratory' parameter towards the target value. One such control methodology' is Proportional-Integral (PI) control. In one implementation of PI control, suitable for ASV modes in which a target ventilation Vtgt is set to slightly less than the ty pical recent ventilation Vty p, the pressure support A is repeatedly computed as:A = G J (I ’em - Vtgt it

[0287] where G is the gain of the PI control. Larger values of gain G can result in positive feedback in the therapy engine module 4320. Smaller values of gain G may permit some residual untreated CSR or central sleep apnea. In some implementations, the gain G is fixed at a predetermined value, such as -0.4 cmH2O / (L / min) / sec. Alternatively, the gain G may be varied between therapy sessions, starting small and increasing from session to session until a value that substantially eliminates CSR is reached. Conventional means for retrospectively analysing the parameters of a therapy session to assess the severity of CSR during the therapysession may be employed in such implementations. In yet other implementations, the gain G may vary depending on the difference betw een the current measure Vent of ventilation and the target ventilation Vtgt.

[0288] Other servo-ventilation control methodologies that may be applied by the therapy parameter determination algorithm 4329 include proportional (P), proportional-differential (PD), and proportional-integral-differential (PID).

[0289] The value of the pressure support A computed via equation (2) may be clipped to a range defined as [Amin, Amax] . In this implementation, the pressure support A sits by default at the minimum pressure support Amin until the measure of current ventilation Vent falls below the target ventilation Vtgt, at which point A starts increasing, only falling back to Amin when Vent exceeds Vtgt once again.

[0290] The pressure support limits Amin and Amax are settings of the RPT device 4000. set for example by hard-coding during configuration of the RPT device 4000 or by manual entry through the input device 4220.

[0291] In pressure support ventilation therapy modes, the EPAP is the base pressure Po. As with the base pressure Po in CPAP therapy, the EPAP may be a constant value that is prescribed or determined during titration. Such a constant EPAP may be set for example by hard-coding during configuration of the RPT device 4000 or by manual entry through the input device 4220. This alternative is sometimes referred to as fixed-EPAP pressure support ventilation therapy. Titration of the EPAP for a given patient may be performed by a clinician during a titration session with the aid of PSG. with the aim of preventing obstructive apneas, thereby maintaining an open airway for the pressure support ventilation therapy, in similar fashion to titration of the base pressure Po in constant CPAP therapy.

[0292] Alternatively, the therapy parameter determination algorithm 4329 may repeatedly compute the base pressure Po during pressure support ventilation therapy . In such implementations, the therapy parameter determination algorithm 4329 repeatedly computes the EPAP as a function of indices or measures of sleep disordered breathing returned by the respective algorithms in the therapy engine module 4320, such as one or more of flow limitation, apnea, hypopnea, patency, and snore. Because the continuous computation of the EPAP resembles the manual adjustment of the EPAP by a clinician during titration of the EPAP, this process is also sometimes referred to as auto-titration of the EPAP, and the therapy mode is known as auto-titrating EPAP pressure support ventilation therapy, or auto-EPAP pressure support ventilation therapy.4.6.2.1 Detection of fault conditions

[0293] In one form of the present technology, the central controller 4230 executes one or more methods 4340 for the detection of fault conditions. The fault conditions detected by the one or more methods 4340 may include at least one of the following:• Power failure (no power, or insufficient power)• Transducer fault detection• Failure to detect the presence of a component• Operating parameters outside recommended ranges (e.g. pressure, flow rate, temperature, PaO2)• Failure of a test alarm to generate a detectable alarm signal.

[0294] Upon detection of the fault condition, the corresponding algorithm 4340 signals the presence of the fault by one or more of the following:• Initiation of an audible, visual & / or kinetic (e.g. vibrating) alarm• Sending a message to an external device• Logging of the incident4.7 HUMIDIFIER4.7.1 Humidifier overview

[0295] In one form of the present technology there is provided a humidifier 5000 (e.g. as shown in Fig. 5 A) to change the absolute humidity of air or gas for delivery to a patient relative to ambient air. Typically, the humidifier 5000 is used to increase the absolute humidity and increase the temperature of the flow of air (relative to ambient air) before delivery to the patient’s airways.

[0296] The humidifier 5000 may comprise a humidifier reservoir 5110, a humidifier inlet 5002 to receive a flow of air. and a humidifier outlet 5004 to deliver a humidified flow of air. In some forms, as shown in Fig. 5A and Fig. 5B, an inlet and an outlet of the humidifier reservoir 5110 may be the humidifier inlet 5002 and the humidifier outlet 5004 respectively. The humidifier 5000 may further comprise a humidifier base 5006. which may be adapted to receive the humidifier reservoir 5110 and comprise a heating element 5240.4.8 BREATHING WAVEFORMS

[0297] Fig. 6A shows a model typical breath waveform of a person while sleeping. The horizontal axis is time, and the vertical axis is respiratory flow rate. While the parameter values may vary, a typical breath may have the following approximate values: tidal volume Vt 0.5L, inhalation time Ti 1.6s, peak inspiratory flow rate Qpeak 0.4 L / s, exhalation time Te 2.4s, peak expiratory How rate Qpeak -0.5 L / s. The total duration of the breath, Ttot, is about 4s. The person typically breathes at a rate of about 15 breaths per minute (BPM), with Ventilation Vent about 7.5 L / min. A typical duty cycle, the ratio of Ti to Ttot, is about 40%.

[0298] Fig. 6B shows selected polysomnography channels (pulse oximetry', flow' rate, thoracic movement, and abdominal movement) of a patient during non-REM sleep breathing normally over a period of about ninety seconds, w ith about 34 breaths, being treated with automatic PAP therapy, and the interface pressure being about 11 cmH20. The top chaimelshows pulse oximetry (oxy gen saturation or SpO ). the scale having a range of saturation from 90 to 99% in the vertical direction. The patient maintained a saturation of about 95% throughout the period shown. The second channel shows quantitative respiratory airflow, and the scale ranges from -1 to +1 LPS in a vertical direction, and with inspiration positive. Thoracic and abdominal movement are shown in the third and fourth channels.

[0299] Fig. 6C shows polysomnography of a patient before treatment. There are eleven signal channels from top to bottom with a 6-minute horizontal span. The top two channels are both EEG (electroencephalogram) from different scalp locations. Periodic spikes in the second EEG represent cortical arousal and related activity. The third channel down is submental EMG (electromyogram). Increasing activity around the time of arousals represents genioglossus recruitment. The fourth & fifth channels are EOG (electro-oculogram). The sixth channel is an electrocardiogram. The seventh channel shows pulse oximetry (SpO2) with repetitive desaturations to below 70% from about 90%. The eighth channel is respiratory airflow using a nasal cannula connected to a differential pressure transducer. Repetitive apneas of 25 to 35 seconds alternate with 10 to 15 second bursts of recovery breathing coinciding with EEG arousal and increased EMG activity. The ninth channel shows movement of chest and the tenth shows movement of abdomen. The abdomen shows a crescendo of movement over the length of the apnea leading to the arousal. Both become untidy7during the arousal due to gross body movement during recovery7hyperpnea. The apneas are therefore obstructive, and the condition is severe. The lowest channel is posture, and in this example it does not show change.

[0300] Fig. 6D shows patient flow rate data where the patient is experiencing a series of total obstructive apneas. The duration of the recording is approximately 160 seconds. Flow rates range from about +1 L / s to about -1.5 L / s. Each apnea lasts approximately 10-15s.4.9 RESPIRATORY THERAPY MODES

[0301] Various respiratory therapy modes may be implemented by the disclosed respiratory7therapy system.4.9.1 CPAP therapy

[0302] In some implementations of respiratory pressure therapy, the central controller 4230 sets the treatment pressure Pt according to the treatment pressure equation (1) as part of the therapy parameter determination algorithm 4329. In one such implementation, the amplitude A is identically zero, so the treatment pressure Pt (which represents a target value to be achieved by the interface pressure Pm at the current instant of time) is identically equal to the base pressure Po throughout the respiratory7cycle. Such implementations are generally grouped under the heading of CPAP therapy. In such implementations, there is no need for the therapy engine module 4320 to determine phase or the waveform template ( ).

[0303] In CPAP therapy, the base pressure Po may be a constant value that is hard-coded or manually entered to the RPT device 4000. Alternatively, the central controller 4230 mayrepeatedly compute the base pressure Po as a function of indices or measures of sleep disordered breathing returned by the respective algorithms in the therapy engine module 4320, such as one or more of flow limitation, apnea, hypopnea, patency, and snore. This alternative is sometimes referred to as APAP therapy.

[0304] Fig. 4E is a flow chart illustrating a method 4500 carried out by the central controller 4230 to continuously compute the base pressure Po as part of an APAP therapy implementation of the therapy parameter determination algorithm 4329, such as when the pressure support^ is identically zero.

[0305] The method 4500 starts at step 4520, at which the central controller 4230 compares the measure of the presence of apnea / hypopnea with a first threshold, and detennines whether the measure of the presence of apnea / hypopnea has exceeded the first threshold for a predetermined period of time, indicating an apnea / hypopnea is occurring. If so, the method 4500 proceeds to step 4540; otherwise, the method 4500 proceeds to step 4530. At step 4540. the central controller 4230 compares the measure of airway patency with a second threshold. If the measure of airway patency exceeds the second threshold, indicating the airway is patent, the detected apnea / hypopnea is deemed central, and the method 4500 proceeds to step 4560; otherwise, the apnea / hypopnea is deemed obstructive, and the method 4500 proceeds to step 4550.

[0306] At step 4530, the central controller 4230 compares the measure of flow limitation with a third threshold. If the measure of flow limitation exceeds the third threshold, indicating inspiratory flow is limited, the method 4500 proceeds to step 4550; otherwise, the method 4500 proceeds to step 4560.

[0307] At step 4550, the central controller 4230 increases the base pressure Po by a predetermined pressure increment P, provided the resulting treatment pressure Pt would not exceed a maximum treatment pressure Pmax. In one implementation, the predetermined pressure increment P and maximum treatment pressure Pmax are 1 cmFbO and 25 cml I2O respectively . In other implementations, the pressure increment P can be as low as 0.1 cm I PO and as high as 3 cmH2O. or as low as 0.5 cmH20 and as high as 2 c H2O. In other implementations, the maximum treatment pressure Pmax can be as low as 15 c H2O and as high as 35 cmH2O, or as low as 20 cmH2O and as high as 30 cmH2O. The method 4500 then returns to step 4520.

[0308] At step 4560. the central controller 4230 decreases the base pressure Po by a decrement, provided the decreased base pressure Po would not fall below a minimum treatment pressure Pmin. The method 4500 then returns to step 4520. In one implementation, the decrement is proportional to the value of Po-Pmin, so that the decrease in Poto the minimum treatment pressure Pmin in the absence of any detected events is exponential. In one implementation, the constant of proportionality is set such that the time constant of theexponential decrease of Po is 60 minutes, and the minimum treatment pressure Pmin is 4 cmH2O. In other implementations, the time constant could be as low as 1 minute and as high as 300 minutes, or as low as 5 minutes and as high as 180 minutes. In other implementations, the minimum treatment pressure Pmin can be as low as 0 cmEEO and as high as 8 cmEEO, or as low as 2 cmEEO and as high as 6 cmFhO. Alternatively, the decrement in Po could be predetennined, so the decrease in Poto the minimum treatment pressure Pmin in the absence of any detected events is linear.4.9.2 Bi-level therapy

[0309] In other implementations of this form of the present technology, the value of amplitude A in equation (1) may be positive. Such implementations are known as bi-level therapy, because in determining the treatment pressure Pt using equation (1) with positive amplitude A, the therapy parameter determination algorithm 4329 oscillates the treatment pressure Pt betw een two values or levels in synchrony with the spontaneous respiratory effort of the patient 1000. That is. based on the typical waveform templates ( t) described above, the therapy parameter determination algorithm 4329 increases the treatment pressure Pt to Po + A (known as the IPAP) at the start of. or during, or inspiration and decreases the treatment pressure Pt to the base pressure o (known as the EPAP) at the start of, or during, expiration.

[0310] In some forms of bi-level therapy, the IPAP is a treatment pressure that has the same purpose as the treatment pressure in CPAP therapy modes, and the EPAP is the IPAP minus the amplitude A, which has a “small” value (a few cmH2O) sometimes referred to as tire Expiratory' Pressure Relief (EPR). Such forms are sometimes referred to as CPAP therapy w ith EPR, which is generally thought to be more comfortable than straight CPAP therapy. In CPAP therapy with EPR, either or both of the IPAP and the EPAP may be constant values that are hard-coded or manually entered to the RPT device 4000. Alternatively , the therapy parameter determination algorithm 4329 may repeatedly compute the IPAP and / or the EPAP during CPAP with EPR. In this alternative, the therapy parameter determination algorithm 4329 repeatedly computes the EPAP and / or the IPAP as a function of indices or measures of sleep disordered breathing returned by the respective algorithms in the therapy engine module 4320 in analogous fashion to the computation of the base pressure Po in APAP therapy described above.4.10 GLOSSARY

[0311] For the purposes of the present technology disclosure, in certain forms of the present technology, one or more of the following definitions may apply. In other forms of the present technology, alternative definitions may apply.4.10.1 General

[0312] Air. In certain forms of the present technology, air may be taken to mean atmospheric air, and in other forms of the present technology air may be taken to mean some other combination of breathable gases, e.g. atmospheric air enriched with oxygen.

[0313] Ambient: In certain forms of the present technology, the term ambient will be taken to mean (i) external of the treatment system or patient, and (ii) immediately surrounding the treatment system or patient.

[0314] For example, ambient humidity with respect to a humidifier may be the humidity of air immediately surrounding the humidifier, e.g. the humidity in the room where a patient is sleeping. Such ambient humidity may be different to the humidity outside the room where a patient is sleeping.

[0315] In another example, ambient pressure may be the pressure immediately surrounding or external to the body.

[0316] In certain forms, ambient (e.g., acoustic) noise may be considered to be the background noise level in the room where a patient is located, other than for example, noise generated by an RPT device or emanating from a mask or patient interface. Ambient noise may be generated by sources outside the room.

[0317] Automatic Positive Airway Pressure (APAP) therapy: CPAP therapy in which the treatment pressure is automatically adjustable, e.g. from breath to breath, between minimum and maximum limits, depending on the presence or absence of indications of SDB events.

[0318] Continuous Positive Airway Pressure (CPAP) therapy: Respiratory' pressure therapy in which the treatment pressure is approximately constant through a respiratory cycle of a patient. In some forms, the pressure at the entrance to the airways will be slightly higher during exhalation, and slightly lower during inhalation. In some forms, the pressure will vary between different respiratory cycles of the patient, for example, being increased in response to detection of indications of partial upper airway obstruction, and decreased in the absence of indications of partial upper airway obstruction.

[0319] Flow rate: The volume (or mass) of air delivered per unit time. Flow rate may refer to an instantaneous quantity . In some cases, a reference to flow rate will be a reference to a scalar quantity, namely a quantity having magnitude only. In other cases, a reference to flow rate will be a reference to a vector quantity, namely a quantity having both magnitude and direction. Flow rate may be given the symbol Q. ‘Flow rate’ is sometimes shortened to simply ‘flow’ or ‘airflow’.

[0320] In the example of patient respiration, a flow rate may be nominally positive for the inspiratory portion of a respiratory cycle of a patient, and hence negative for the expiratory portion of the respiratory cycle of a patient. Device flow rate. Qd. is the flow rate of air leaving the RPT device. Total flow rate, Qt. is the flow rate of air and any supplementary gas reachingthe patient interface via the air circuit. Vent flow rate, Qv, is the flow rate of air leaving a vent to allow washout of exhaled gases. Leak flow rate, QI, is the flow rate of leak from a patient interface system or elsewhere. Respiratory' flow rate, Qr, is the flow rate of air that is received into the patient's respiratory' system.

[0321] Humidifier. The word humidifier will be taken to mean a humidifying apparatus constructed and arranged, or configured with a physical structure to be capable of providing a therapeutically beneficial amount of water (H2O) vapour to a flow of air to ameliorate a medical respiratory' condition of a patient.

[0322] Leak'. An unintended flow of air. In one example, leak may occur as the result of an incomplete seal between a mask and a patient's face. In another example leak may occur in a swivel elbow to the ambient.

[0323] Patient. A person, whether or not they are suffering from a respiratory condition.

[0324] Pressure: Force per unit area. Pressure may be expressed in a range of units, including cmH20, g-f / cm2and hectopascal. 1 cm FLO is equal to 1 g-f / cm2and is approximately 0.98 hectopascal (1 hectopascal = 100 Pa = 100 N / m2= 1 millibar ~ 0.001 atm). In this specification, unless othenvise stated, pressure is given in units of cmH2O.

[0325] The pressure in the patient interface is given the symbol Pm. yvhile the treatment pressure, which represents a target value to be achieved by the interface pressure Pm at the current instant of time, is given the symbol Pt.

[0326] Respiratory Pressure Therapy (RPT): The application of a supply of air to an entrance to the airyvays at a treatment pressure that is typically positive yvith respect to atmosphere.

[0327] Ventilator. A mechanical device that provides pressure support to a patient to perform some or all of the yvork of breathing.4.10.2 Respiratory cycle

[0328] Apnea: According to some definitions, an apnea is said to have occurred when flow falls beloyv a predetermined threshold for a duration, e.g. 10 seconds. An obstructive apnea will be said to have occurred when, despite patient effort, some obstruction of the airway does not alloyv air to flow. A central apnea yy ill be said to have occurred yvhen an apnea is detected that is due to a reduction in breathing effort, or the absence of breathing effort, despite the airway being patent. A mixed apnea occurs when a reduction or absence of breathing effort coincides with an obstructed airway.

[0329] Breathing rate: The rate of spontaneous respiration of a patient, usually measured in breaths per minute.

[0330] Duty cycle: The ratio of inhalation time, Ti to total breath time. / tot.

[0331] Effort (breathing) : The w ork done by a spontaneously breathing person attempting to breathe.

[0332] Expiratory portion of a respiratory cycle: The period from the start of expiratory flow to the start of inspiratory' flow.

[0333] Flow limitation: Flow limitation will be taken to be the state of affairs in a patient's respiration where an increase in effort by the patient does not give rise to a corresponding increase in flow. Where flow limitation occurs during an inspiratory portion of the respiratory cycle it may be described as inspiratory' flow limitation. Where flow limitation occurs during an expiratory portion of the respiratory cycle it may be described as expiratory flow limitation.

[0334] Hypopnea: According to some definitions, a hypopnea is taken to be a reduction in flow, but not a cessation of flow. In one fonn, a hypopnea may be said to have occurred when there is a reduction in flow below a threshold rate for a duration. A central hypopnea will be said to have occurred when a hypopnea is detected that is due to a reduction in breathing effort. In one form in adults, either of the following may be regarded as being hypopneas:(i) a 30% reduction in patient breathing for at least 10 seconds plus an associated 4% desaturation; or(ii) a reduction in patient breathing (but less than 50%) for at least 10 seconds, with an associated desaturation of at least 3% or an arousal.

[0335] Hyperpnea: An increase in flow to a level higher than normal.

[0336] Inspiratory portion of a respiratory: cycle: The period from the start of inspiratory flow to the start of expiratory flow will be taken to be the inspiratory portion of a respiratory cycle.

[0337] Patency (airway) : The degree of the airway being open, or the extent to which the airway is open. A patent airway is open. Airway patency may be quantified, for example with a value of one (1) being patent, and a value of zero (0), being closed (obstructed).

[0338] Positive End-Expiratory Pressure (PEEP) : The pressure above atmosphere in the lungs that exists at the end of expiration.

[0339] Peak flow rate (Qpeak): The maximum value of flow rate during the inspiratory portion of the respiratory flow waveform.

[0340] Respiratory flow rate, patient airflow rate, respiratory airflow rate (Qr) : These terms may be understood to refer to the RPT device’s estimate of respiratory flow rate, as opposed to “true respiratory flow rate” or “true respiratory' flow rate”, which is the actual respiratory' flow rate experienced by the patient, usually expressed in litres per minute.

[0341] Tidal volume (Vt): The volume of air inhaled or exhaled during nonnal breathing, when extra effort is not applied. In principle the inspiratory volume Vi (the volume of air inhaled) is equal to the expiratory volume Ve (the volume of air exhaled), and therefore a single tidal volume Vt may be defined as equal to either quantity. In practice die tidal volume Vt is estimated as some combination, e.g. the mean, of the inspiratory volume Vi and the expiratory volume Ve.

[0342] (inhalation) Time (Ti): The duration of the inspiratory' portion of the respiratory flow rate waveform.

[0343] (exhalation) Time (Te): The duration of the expiratory' portion of the respiratory flow rate waveform.

[0344] (total) Time (Ttot): The total duration between the start of one inspiratory portion of a respiratory flow rate waveform and the start of the following inspiratory portion of the respiratory' flow rate wavefonn.

[0345] Typical recent ventilation'. The value of ventilation around which recent values of ventilation Vent over some predetermined timescale tend to cluster, that is, a measure of the central tendency of tire recent values of ventilation.

[0346] Upper airway obstruction (UAO): includes both partial and total upper airway obstruction. This may be associated with a state of flow limitation, in which the flow rate increases only slightly or may even decrease as the pressure difference across the upper airway increases (Starling resistor behaviour).

[0347] Ventilation (Vent) A measure of a rate of gas being exchanged by the patient’s respiratory system. Measures of ventilation may include one or both of inspiratory and expiratory' flow, per unit time. When expressed as a volume per minute, this quantity7is often referred to as “minute ventilation”. Minute ventilation is sometimes given simply as a volume, understood to be the volume per minute.4.10.3 Ventilation

[0348] Adaptive Servo-Ventilator (AS V) : A servo-ventilator that has a changeable, rather than fixed target ventilation. The changeable target ventilation may be learned from some characteristic of the patient, for example, a respiratory characteristic of the patient such as via the TRE as described herein.

[0349] Backup rate: A parameter of a ventilator that establishes the minimum breathing rate (ty pically in number of breaths per minute) that the ventilator will deliver to the patient, if not triggered by spontaneous respiratory' effort.

[0350] Cycled: The termination of a ventilator's inspiratory phase. When a ventilator delivers a breath to a spontaneously breathing patient, at the end of the inspiratory portion of the breathing cycle, the ventilator is said to be cycled to stop delivering the breath.

[0351] Expiratory' positive airway pressure (EPAP): a base pressure, to which a pressure vary ing within the breath is added to produce the desired interface pressure which the ventilator will attempt to achieve at a given time.

[0352] End expiratory pressure (EEP): Desired interface pressure which the ventilator will attempt to achieve at the end of the expiratory portion of the breath. If the pressure waveform template n(cp) is zero-valued at the end of expiration, i.e. n(<p) = 0 when cp = 1. the EEP is equal to the EPAP.

[0353] Inspirator}' positive airway pressure (IPAP): Maximum desired interface pressure which the ventilator will attempt to achieve during the inspiratory' portion of the breath.

[0354] Pressure support: A number that is indicative of the increase in pressure during ventilator inspiration over that during ventilator expiration, and generally means the difference in pressure between the maximum value during inspiration and the base pressure (e.g.. PS = IPAP - EPAP). In some contexts, pressure support means the difference which the ventilator aims to achieve, rather than what it actually achieves.

[0355] Servo-ventilator: A ventilator that measures patient ventilation, has a target ventilation, and which adjusts the level of pressure support to bring the patient ventilation towards the target ventilation.

[0356] Spontaneous / Timed (S / T): A mode of a ventilator or other device that attempts to detect the initiation of a breath of a spontaneously breathing patient. If however, the device is unable to detect a breath within a predetermined period of time, the device will automatically initiate delivery of the breath.

[0357] Swing: Equivalent term to pressure support.

[0358] Triggered: When a ventilator, or other respiratory therapy device such as an RPT device or portable oxygen concentrator, delivers a volume of breathable gas to a spontaneously breathing patient, it is said to be triggered to do so. Triggering usually takes place at or near the initiation of the respiratory portion of the breathing cycle by the patient's efforts.4.11 OTHER REMARKS

[0359] A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in Patent Office patent files or records, but otherwise reser es all copyright rights whatsoever.

[0360] Unless the context clearly dictates otherwise and where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit, between the upper and lower limit of that range, and any other stated or intervening value in that stated range is encompassed within the technology. The upper and lower limits of these intervening ranges, which may be independently included in the intervening ranges, are also encompassed within the technology, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the technology.

[0361] Furthermore, where a value or values are stated herein as being implemented as part of the technology, it is understood that such values may be approximated, unless otherwise stated, and such values may be utilized to any suitable significant digit to the extent that a practical technical implementation may permit or require it.

[0362] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this technologj' belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present technology, a limited number of the exemplary methods and materials are described herein.

[0363] When a particular material is identified as being used to construct a component, obvious alternative materials with similar properties may be used as a substitute. Furthermore, unless specified to the contrary, any and all components herein described are understood to be capable of being manufactured and. as such, may be manufactured together or separately.

[0364] It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include their plural equivalents, unless the context clearly dictates otherwise.

[0365] All publications mentioned herein are incorporated herein by reference in their entirety to disclose and describe the methods and / or materials which are the subject of those publications. The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present technology is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates, which may need to be independently confirmed.

[0366] The terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced.

[0367] The subject headings used in the detailed description are included only for the ease of reference of the reader and should not be used to limit the subject matter found throughout the disclosure or the claims. The subject headings should not be used in construing the scope of the claims or the claim limitations.

[0368] Although the technology herein has been described with reference to particular examples, it is to be understood that these examples are merely illustrative of the principles and applications of the technology. In some instances, the terminology and symbols may imply specific details that are not required to practice the technology. For example, although the terms "first" and "second" may be used, unless otherwise specified, they are not intended to indicate any order but may be utilised to distinguish between distinct elements. Furthermore, although process steps in the methodologies may be described or illustrated in an order, such an ordering is not required. Those skilled in the art will recognize that such ordering may be modified and / or aspects thereof may be conducted concurrently or even synchronously.

[0369] It is therefore to be understood that numerous modifications may be made to the illustrative examples and that other arrangements may be devised without departing from the spirit and scope of the technology.4.12 REFERENCE SIGNS LIST patient 1000 bed partner 1100 patient interface 3000 seal - fonning structure 3100 plenum chamber 3200 structure 3300 vent 3400 connection port 3600 forehead support 3700RPT device 4000 external housing 4010 upper portion 4012 portion 4014 panel s 4015 chassis 4016 handle 4018 pneumatic block 4020 air filters 4110 inlet air fdter 4112 outlet air filter 4114 mufflers 4120 inlet muffler 4122 outlet muffler 4124 pressure generator 4140 blower 4142 motor 4144 anti - spill back valve 4160 air circuit 4170 supplementary gas 4180 electrical components 4200Printed Circuit Board Assembly 4202 power supply 4210input devices 4220 central controller 4230 clock 4232 therapy device controller 4240 protection circuits 4250 memory 4260 transducers 4270 pressure sensor 4272 flow rate sensor 4274 motor speed transducer 4276 data communication interface 4280 remote external communication network 4282 local external communication network 4284 remote external device 4286 local external device 4288 output device 4290 display driver 4292 display 4294 algorithms 4300 system characterization algorithm 4305 pre - processing module 4310 interface pressure estimation algorithm 4312 vent flow rate estimation algorithm 4314 leak flow rate estimation algorithm 4316 respiratory flow rate estimation algorithm 4318 therapy engine module 4320 phase determination algorithm 4321 waveform determination algorithm 4322 ventilation determination 4323 inspiratory flow limitation detennination algorithm 4324 apnea / hypopnea determination algorithm 4325 snore detennination algorithm 4326 airway patency determination algorithm 4327 target ventilation determination 4328 therapy parameter determination algorithm 4329 therapy recommendation engine 4329 Atherapy control module 4330 methods 4340 method 4500 step 4520 step 4530 step 4540 step 4550 step 4560 humidifier 5000 humidifier inlet 5002 humidifier outlet 5004 humidifier base 5006 humidifier reservoir 5110 humidifier reservoir dock 5130 heating element 5240

Claims

6 CLAIMS1. A system for providing sleep disordered breathing therapy for a comorbid sleep apnea and insomnia (COMISA) patient, the system comprising: one or more processors configured to: evaluate data in a therapy recommendation engine, the data comprising one or both of objective data and subjective data, the evaluation comprising an assessment of the data according to one or more thresholds; classify, based on the evaluation of the therapy recommendation engine, the patient according to one of a plurality of therapy states, the plurality of therapy states comprising a COMISA state; and output, from the therapy recommendation engine, a therapy recommendation determined in accordance with the classify ing.

2. The system according to claim 1, further comprising a respiratory therapy apparatus for delivering respiratory therapy to the patient.

3. The system according to claim 2. wherein the respiratory therapy apparatus comprises a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient; and one or more sensors to sense one or more characteristics of the operation of the pressure generator.

4. The system according to claim 3, wherein the one or more processors comprises a controller of the pressure generator, wherein the controller is configured to control operation of the pressure generator based on the output of the therapy.

5. The system according to any one of claims 3 to 4, wherein the one or more processors comprises one or more servers configured for accessing data electronically communicated from a controller of the pressure generator.

6. The system according to any one of claims 3 to 5, wherein the one or more processors comprises a companion device configured for electronic communications with a controller of the pressure generator.

7. The system of claim 6, wherein the companion device comprises a smart phone.

8. The system according to any one of claims 1 to 7, wherein the evaluated data comprises any one or more of: a number of days from a first contact for therapy, therapy usage data, sleep quality data, mask on and / or off events data, respiratory disturbance variable data, wearable device generated data, medical record data, respiratory event data, prescribed drug data, insomnia screening or diagnosis data, and one or more respiration rate statistic data.

9. The system according to any one of claims 1 to 8, wherein the evaluated data comprises a number of days from a first contact for therapy, therapy usage data, sleep quality data, and mask on and / or off events data.

10. The system according to any one of claims 1 to 8. wherein the evaluated data comprises a number of days from a first contact for therapy, therapy usage data, respiratory disturbance variable data, and respiration rate statistic data.

11. The system according to any one of claims 3 to 10. wherein the output therapy recommendation comprises a respiratory therapy parameter for operation of the pressure generator according to a therapy protocol.

12. The system according to claim 11. wherein the therapy protocol comprises an adaptive servo-ventilation (ASV) therapy mode, with an adjustable floor pressure, configured to change the adjustable floor based on a calculated distribution of adjustment increments.

13. The system according to claim 12, wherein the adjustment increments are periods of end expiratory pressure adjustments.

14. The system according to any one of claims 11 to 13, wherein the therapy protocol comprises a session-to-session adjustment of end expiratoiy pressure, wherein setting of end expiratoiy pressure for a next session is based on a distribution of EEP levels in adjustment periods of a prior session.

15. The system according to any one of claims 11 to 14, wherein the therapy protocol comprises an adaptive servo-ventilation (ASV) therapy mode configured to change operation based on a detected sleep state.

16. The system according to claim 15, wherein the change in operation comprises initiating, based on a detection of an aw ake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate.

17. The system according to any one of claims 15 to 16, wherein the change in operation comprises an adjustment to a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state.

18. The system according to any one of claims 15 to 17, wherein the therapy protocol comprises an automatic positive airway pressure (APAP) therapy configured to ramp delivered pressure within a predetermined pressure range following detection of a mask on event and a detection of sleep onset.

19. The system according to any one of claims 1 to 18, wherein the output therapy recommendation comprises a paced breathing operation configured to induce a reduced patient respiration rate, and wherein the one or more processors is further configured to generate output to prompt the patient to initiate the paced breathing operation based on the classifying.

20. The system according to any one of claims 15 to 19, wherein the therapy protocol comprises a plurality’ of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to select a waveform of the plurality of different pressure waveforms during a trial of the plurality of different pressure waveforms that is initiated for the patient based on the classify ing.

21. The system according to any one of claims 15 to 20, wherein the therapy protocol comprises a plurality of different pressure w aveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to trial the plurality’ of different pressure waveforms with the patient based on the classifying, wherein the one or more processors is configured to select an optimal waveform from the plurality of different pressure waveforms based on monitoring the patient’s sleep qualify.

22. The system according to claim 21 wherein monitoring the patient's sleep quality comprises monitoring of sleep onset latency.

23. The system according to any one of claims 15 to 19. wherein the therapy protocol comprises a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to trial the plurality of different pressurewaveforms with the patient based on the classify ing, wherein the one or more processors is configured prompt the patient to select a trialed one of the plurality of different w aveforms for delivery during use of the pressure generator.

24. The system according to claim 23, wherein the therapy protocol comprises a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to select one of the plurality of different waveforms based on any one or more of demographic data, data concerning nature of the patient's insomnia, prior therapy data, and diagnostic data.

25. The system according to any one of claims 15 to 24, wherein the therapy protocol comprises an automatic positive airway pressure (APAP) therapy mode and a continuous positive airway pressure (CP AP) therapy mode and wherein the one or more processors are configured to switch between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

26. The system according to claim 25. wherein the one or more processors is configured to switch to the CPAP mode from the APAP mode based on a detection of an N3 sleep stage.

27. The system according to any one of claims 25 to 26, wherein the one or more processors is configured to switch to the APAP mode from the CPAP mode based on detection of any one or more of a REM sleep stage and a N2 sleep stage.

28. The system according to any one of claims 25 to 27, wherein the one or more processors is configured to switch to the APAP mode from the CPAP mode based on a determined time in a REM sleep stage.

29. The system according to any one of claims 1 to 28, wherein the output therapy comprises a digital cognitive behavioural therapy presentation.

30. The system according to claim 29, wherein the output therapy presentation is a digital cognitive behavioural therapy for insomnia, and wherein the classifying identifies the COMISA state.

31. The system according to any one of claims 1 to 30, wherein the plurality of therapy states further comprises one or both of a sleep disorder onboarding state and a deficient respiratory therapy adherence state.

32. The system according to any one of claims 29 to 31, wherein the therapy recommendation engine is configured to select a presentation module from a plurality of different presentation modules, wherein each of the presentation modules is associated with a therapy state of the plurality of therapy states, and wherein the selected presentation module comprises one or both of an audio therapy content and visual therapy content.

33. A method of evaluating and treating a comorbid sleep apnea and insomnia (COMISA) patient using apparatus for a respiratory therapy, the method comprising: evaluating data in a therapy recommendation engine, the data comprising one or both of objective data and subjective data, the evaluation comprising an assessment of the data according to one or more thresholds; classifying, based on the evaluation of the therapy recommendation engine, the patient according to one of a plurality of therapy states, the plurality of therapy states comprising a COMISA state; and outputting, from the therapy recommendation engine, a therapy recommendation determined in accordance with the classifying.

34. The method according to claim 33, wherein the apparatus for the respiratory therapy comprises a pressure generator and one or more sensors, and the method further comprises: controlling the pressure generator to generate a flow of air for delivery to a patient interface via a deliver} conduit for a respiratory therapy for the patient; and operating the one or more sensors to sense one or more characteristics of the operation of the pressure generator.

35. The method according to claim 34, wherein the apparatus is communicatively coupled to a therapy engine, wherein the therapy engine comprises one or more processors comprising a controller of the pressure generator, and wherein the controller is configured to control operation of the pressure generator based on the output of the therapy recommendation engine.

36. The method according to any one of claims 34 to 35. wherein the therapy recommendation engine comprises one or more servers configured for accessing data electronically communicated from a controller of the pressure generator.

37. The method according to any one of claims 34 to 36. wherein the therapy recommendation engine comprises a companion device configured for electronic communications with a controller of the pressure generator.

38. The method of claim 37, wherein the companion device comprises a smart phone.

39. The method according to any one of claims 33 to 38, wherein the evaluated data comprises any one or more of: a number of days from a first contact for therapy, usage data, sleep quality data, mask on and / or off events data, respiratory disturbance variable data, wearable device generated data, medical record data, respiratory event data, insomnia screening or diagnosis data, and one or more respiration rate statistic data.

40. The method according to any one of claims 33 to 39. wherein the evaluated data comprises a number of days from a first contact for therapy, therapy usage data, sleep quality data, and mask on and / or off events data.

41. The method according to any one of claims 33 to 39, wherein the evaluated data comprises a number of days from a first contact for therapy, therapy usage data, respiratory disturbance variable data, and respiration rate statistic data.

42. The method according to any one of claims 35 to 41, wherein the output therapy recommendation comprises a respiratory therapy parameter for operation of the pressure generator according to a therapy protocol.

43. The method according to claim 42, wherein the therapy protocol comprises an adaptive servo- ventilation (ASV) therapy mode, with an adjustable floor pressure, that changes the adjustable floor based on calculating a distribution of adjustment increments.

44. The method according to claim 43, wherein the adjustment increments are periods of end expiratory pressure adjustments.

45. The method according to any one of claims 42 to 44, wherein the therapy protocol makes a session-to-session adjustment of end expiratory pressure, wherein setting of end expiratory pressure for a next session is based on calculating a distribution of EEP levels in adjustment periods of a prior session.

46. The method according to any one of claims 42 to 44. wherein the therapy protocol comprises an adaptive servo-ventilation (ASV) therapy mode that changes operation based on a detected sleep state.

47. The method according to claim 46, wherein the change in operation initiates, based detecting an awake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate.

48. The method according to any one of claims 46 to 47, wherein the change in operation adjusts a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state.

49. The method according to any one of claims 42 to 48. wherein the therapy protocol comprises an automatic positive airway pressure (APAP) therapy that delivers ramping pressure within a predetermined range following detection of a mask on event and a detection of sleep onset.

50. The method according to any one of claims 33 to 49, wherein the output therapy recommendation comprises a paced breathing operation that induces a reduced patient respiration rate, and wherein one or more processors generates output to prompt the patient to initiate the paced breathing operation based on the classifying.

1. The method according to any one of claims 33 to 50, wherein the therapy protocol comprises a plurality of different pressure waveforms that are each for use during a pre-sleep onset period, and wherein the therapy protocol includes a selection of a waveform of the plurality of different pressure waveforms during a trial of the plurality of different pressure waveforms that is initiated for the patient based on the classifying.

52. The method according to any one of claims 33 to 51, wherein the therapy protocol comprises a plurality of different pressure waveforms that are each for use during a pre-sleep onset period, and wherein tire therapy protocol includes a selection of an optimal waveform from the plurality of different pressure waveforms based on monitoring the patient's sleep quality .

53. The method according to claim 52 wherein monitoring the patient's sleep quality comprises monitoring sleep onset latency.

54. The method according to any one of claims 42 to 53, wherein the therapy protocol comprises a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to trial the plurality of different pressure waveforms with the patient based on the classifying, wherein the one or more processors isconfigured prompt the patient to select a trialed one of the plurality of different waveforms for delivery during use of the pressure generator.

55. The method according to any one of claims 42 to 54, wherein the therapy protocol comprises a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to select one of the plurality of different waveforms based on any one or more of demographic data, data concerning nature of the patient's insomnia, prior therapy data, and diagnostic data.

56. The method according to any one of claims 42 to 53. wherein the therapy protocol comprises an automatic positive airway pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode and wherein the therapy recommendation engine recommends switches between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

57. The method according to claim 56. wherein a switch to the CPAP mode from the APAP mode is based on a detection of an N3 sleep stage.

58. The method according to any one of claims 56 to 57. wherein a switch to the APAP mode from the CPAP mode is based on detection of (i) a REM sleep stage or (ii) a Nl or N2 sleep stage.

59. The method according to claim 58, wherein the switch to the APAP mode from the CPAP mode is based on a determined time in the REM sleep stage.

60. The method according to any one of claims 33 to 59, wherein the output therapy recommendation comprises a digital cognitive behavioural therapy presentation.

61. The method according to claim 60. wherein the digital cognitive behavioural therapy presentation is a digital cognitive behavioural therapy for insomnia when the classifying identifies the COMISA state.

62. The method according to any one of claims 33 to 61, wherein the plurality of therapy states further comprises one or both of a sleep disorder onboarding state and a deficient respiratory therapy adherence state.

63. The method according to any one of claims 60 to 62, wherein the therapy recommendation engine selects a presentation module from a plurality of different presentation modules, wherein each of the presentation modules is associated with a therapy state of the plurality of therapy states, and wherein the selected presentation module comprises one or both of an audio therapy content and visual therapy content.

64. A processor readable medium configured with program instructions for controlling one or more processors to execute a method of evaluating and treating a comorbid sleep apnea and insomnia (COMISA) patient using respiratory therapy apparatus, the method comprising the method of any one of claims 33 to 63.

65. The processor readable medium of claim 64. wherein the one or more processors comprises one or more servers.

66. The processor readable medium of any one of claims 64 to 65, wherein the one or more processors comprises a respiratory pressure therapy device.

67. The processor readable medium of any one of claims 64 to 66, wherein the one or more processors comprises a smart phone or a tablet.

68. Apparatus for providing respiratory’ therapy for a comorbid sleep apnea and insomnia (COMISA) patient, the apparatus comprising: a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery’ conduit for a respiratory' therapy for the patient; one or more sensors to sense one or more characteristics of the operation of the pressure generator; and one or more processors coupled with the one or more sensors and configured as a controller to control operation of the pressure generator, the one or more processors further configured to: operate the pressure generator in an adaptive servo-ventilation (ASV) mode wherein the pressure generator is controlled according to a target ventilation that varies, whereby the pressure generator is controlled to produce ventilation to satisfy the target ventilation, wherein the adaptive servo-ventilation (ASV) mode further comprises an adjustable floor pressure wherein the controller is configured to change the adjustable floor based on a calculated distribution of adjustment increments.

69. The apparatus according to claim 68, w herein the adjustment increments are periods of end expiratory pressure adjustments made in response to detected sleep disordered breathing events.

70. The apparatus according to any one of claims 68 to 69, wherein the controller is configured to make a session-to-session adjustment of end expiratory pressure EEP, wherein a setting of the end expiratory pressure for a next session is based on a distribution of EEP levels in adjustment periods of a prior session.

71. The apparatus according to any one of claims 68 to 70, wherein the controller is configured to change operation of the adaptive servo-ventilation (ASV) therapy mode based on a detected sleep state.

72. The apparatus according to claim 71, wherein the change in operation comprises initiating, based on a detection of an awake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate.

73. The apparatus according to any one of claims 71 to 72, wherein the change in operation comprises an adjustment to a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state.

74. A method for controlling respiratory apparatus for providing respiratory therapy to a comorbid sleep apnea and insomnia (COMI SA) patient, the method comprising: controlling a pressure generator to generate a flow of air for delivery’ to a patient interface via a delivery conduit for a respiratory therapy for the patient; sensing, with one or more sensors, one or more characteristics of the operation of the pressure generator; controlling operation of the pressure generator to provide an adaptive servo-ventilation (ASV) therapy according to a target ventilation that varies, whereby the pressure generator produces ventilation to satisfy the target ventilation; and controlling operation of the pressure generator to provide an adaptive servo-ventilation (ASV) therapy according to an adjustable floor pressure wherein the adjustable floor is adapted based on calculating a distribution of adjustment increments.

75. The method according to claim 74, wherein the adjustment increments are prior periods of end expiratory pressure adjustments made in response to detecting sleep disordered breathing events.

76. The method according to any one of claims 74 to 75, wherein the controller makes a session-to-session adjustment of end expiratory pressure EEP, wherein a setting of the end expiratory pressure EEP for a next session is based on a distribution of EEP levels in adjustment periods of a prior session.

77. The method according to any one of claims 74 to 76, wherein the controller changes operation of the adaptive servo-ventilation (ASV) therapy mode based on a detecting a sleep state.

78. The method according to claim 77, wherein the change in operation comprises initiating, based on a detection of an awake state or input from the patient, a paced breathing operation configured to induce a reduced patient respiration rate.

79. The method according to any one of claims 74 to 78, wherein the change in operation comprises an adjustment to a controller gain of the adaptive servo-ventilation (ASV) therapy mode as a function of a detected sleep state.

80. A processor readable medium configured with program instructions for operating one or more processors to execute a method of controlling respiratory apparatus for providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient, the method comprising the method of any one of claims 74 to 79.

81. Apparatus for providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient, the apparatus comprising: a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient; one or more sensors to sense one or more characteristics of the operation of the pressure generator; and one or more processors coupled with the one or more sensors and configured as a controller to control operation of the pressure generator, the one or more processors further configured to: operate the pressure generator in an automatic positive airway pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode; andswitch between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

82. The apparatus according to claim 81, wherein the one or more processors is configured to switch operation of the pressure generator to the CPAP mode from the APAP mode based on a detection of an N3 sleep stage.

83. The apparatus according to any one of claims 81 to 82, wherein the one or more processors is configured to switch operation of the pressure generator to the APAP mode from the CPAP mode based on detection of any one or more of a REM sleep stage and a N2 sleep stage.

84. The apparatus according to any one of claims 81 to 83. wherein the one or more processors is configured to switch operation of the pressure generator to the APAP mode from the CPAP mode based on a determined time in a REM sleep stage.

85. The apparatus according to any one of claims 81 to 84, wherein the one or more processors is configured to operate the pressure generator in the automatic positive airway pressure (APAP) therapy mode and control ramping of delivered pressure within a predetermined range upon detection of a mask on event and a sleep onset.

86. The apparatus according to any one of claims 81 to 85, w herein the one or more processors is configured to operate the pressure generator to provide a paced breathing operation configured to induce a reduced patient respiration rate, and wherein the one or more processors is further configured to prompt the patient to initiate the paced breathing operation.

87. The apparatus according to any one of claims 81 to 86, wherein the one or more processors is configured to operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to generate output to prompt the patient to input a selection of a waveform of the plurality of different pressure waveforms during a trial of the plurality of different pressure waveforms.

88. The apparatus according to any one of claims 81 to 86, wherein the one or more processors is configured to operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors is further configured to trial the plurality of different pressure waveforms w ith the patient, whereinthe one or more processors is configured to select an optimal waveform from the plurality of different pressure waveforms based on monitoring of the patient's of sleep quality.

89. The apparatus according to claim 88, wherein the monitoring of the patient's sleep quality comprises monitoring of sleep onset latency.

90. A method for controlling respiratory therapy apparatus to provide a respiratory therapy for a comorbid sleep apnea and insomnia (COMI SA) patient, the method comprising: controlling a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for the patient; sensing, with one or more sensors, one or more characteristics of the operation of the pressure generator; controlling operation of the pressure generator in an automatic positive airway pressure (APAP) therapy mode and a continuous positive airway pressure (CPAP) therapy mode; and controlling switching between the APAP therapy mode and the CPAP therapy mode based on one or more of: one or more detected sleep stages, and one or more detected sleep cycles.

91. The method according to claim 90, wherein one or more processors switches operation of the pressure generator to the CPAP mode from the APAP mode based on a detection of an N3 sleep stage.

92. The method according to any one of claims 90 to 91, wherein the one or more processors switches operation of the pressure generator to the APAP mode from the CPAP mode based on detection of (i) a REM sleep stage or (ii) a N1 or N2 sleep stage.

93. The method according to claim 92, wherein the one or more processors switches operation of the pressure generator to the APAP mode from the CPAP mode based on a determined time in a REM sleep stage.

94. The method according to any one of claims 90 to 93, wherein the one or more processors operate the pressure generator in the automatic positive airway pressure (APAP) therapy mode and control ramping of delivered pressure within a predetermined range upon detection of a mask on event and a sleep onset.

95. The method according to any one of claims 90 to 94, wherein the one or more processors operate the pressure generator to provide a paced breathing operation for inducing a reducedpatient respiration rate, and wherein the one or more processors prompt the patient to initiate the paced breathing operation.

96. The method according to any one of claims 90 to 95, wherein the one or more processors operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein die one or more processors selects a waveform of the plurality of different pressure wavefonns during a trial of the plurality of different pressure waveforms.

97. The method according to any one of claims 90 to 96, wherein one or more processors operate the pressure generator to provide a plurality of different pressure waveforms for use during a pre-sleep onset period, and wherein the one or more processors trial the plurality of different pressure wavefonns with the patient, wherein the one or more processors select an optimal waveform from the plurality of different pressure waveforms based on monitoring of the patient's sleep quality during use of each of the plurality of different pressure waveforms.

98. The method according to claim 97. wherein monitoring the patient's sleep quality comprises monitoring of sleep onset latency.

99. A processor readable medium configured with program instructions for operating one or more processors to execute a method of controlling respiratory apparatus for providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient, the method comprising the method of any one of claims 90 to 98.

100. A system for providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient, the system comprising: a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for a patient; one or more sensors to sense one or more characteristics of the operation of the pressure generator; and one or more processors configured to: operate the pressure generator to control providing of the respiratory therapy; evaluate one or more signals from the one or more sensors to detect biomarkers indicative of use of a pharmacological treatment for insomnia; and output a change to therapy based on the evaluation of the one or more signals.

101. The sy stem according to claim 100, wherein the change to therapy comprises generating a digital therapy presentation for insomnia.

102. The system according to any one of claims 100 to 101, wherein the change to therapy comprises an adjustment to the respiratory therapy provided to the patient.

103. The system according to claim 102, wherein the adjustment to respiratory therapy comprises a paced breathing operation configured to induce a reduced patient respiration rate.

104. The system according to any one of claims 100 to 103, wherein the evaluated one or more signals comprises any one or more of: respiratory rate variability, respiratory rate distribution over one or more periods, volume and / or length of expiratory pauses, a number of obstructive and / or central apneas, and a cycle length of sleep disordered breathing events.

105. The system according to any one of claims 100 to 104, wherein the evaluation of the one or more signals from the one or more sensors to detect use of a pharmacological treatment for insomnia comprises detection of a number of transitions into and out of an S2 sleep state.

106. A method for monitoring and providing respiratory therapy for a comorbid sleep apnea and insomnia (COMISA) patient, the method comprising: controlling a pressure generator configured to generate a flow of air for delivery to a patient interface via a delivery conduit for a respiratory therapy for a patient; sensing, with one or more sensors, one or more characteristics of the operation of the pressure generator; evaluating one or more signals from the one or more sensors to detect use of a pharmacological treatment for insomnia; and outputting a change to therapy based on the evaluation of the one or more signals.

107. The method according to claim 106, wherein the change to therapy comprises generating a digital therapy presentation.

108. The method according to any one of claims 106 to 107, wherein the change to therapy comprises an adjustment to the respiratory' therapy.

109. The method according to claim 108, wherein the adjustment to respiratory therapy comprises providing a paced breathing operation to induce a reduced patient respiration rate.

110. The method according to any one of claims 106 to 109, wherein the evaluated one or more signals comprises any one or more of: respiratory rate variability , respiratory rate distribution over one or more periods, volume and / or length of expiratory' pauses, a number of obstructive and / or central apneas, and a cycle length of sleep disordered breathing events.

111. The method according to any one of claims 106 to 110, wherein the evaluating one or more signals from the one or more sensors to detect use of a pharmacological treatment for insomnia comprises detection of a number of transitions into and out of an S2 sleep state.

112. A processor readable medium configured with program instructions for operating one or more processors to execute a method of controlling respiratory apparatus for monitoring and providing respiratory therapy to a comorbid sleep apnea and insomnia (COMISA) patient, the method comprising the method of any one of claims 106 to 111.

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