Determining respiratory work in respiratory flow therapy system

Abstract

A respiratory apparatus configured to provide a flow of gas to a user for respiratory therapy. The apparatus comprises: a flow generator configured to generate a flow of gas for a user; and one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow. The controller is configured to: receive flow parameter data; determining a nasal pressure change value indicative of an average nasal pressure of the user based at least in part on the received flow parameter data; determining a work of breathing (WOB) indicator based at least in part on the determined nasal pressure change value; and initiating one or more actions based at least in part on the determined WOB metrics.

Description

Technical Field

[0001] This disclosure relates to determining the work of breathing during a patient's use of an unsealed breathing device (i.e., an open breathing device). Background Art

[0002] Respiratory assistance devices are used in various environments (such as hospitals, medical facilities, inpatient care, or home environments) to deliver a gas flow to a user or patient. Respiratory assistance or respiratory therapy devices (collectively referred to as "breathing devices" or "breathing apparatuses") can be used to deliver supplemental oxygen or other gases using a gas flow, and / or to deliver heated and humidified gases using a humidification device. Breathing devices can allow for adjustment and control of the characteristics of the gas flow, which include flow rate, temperature, gas concentration, humidity, pressure, etc. Sensors (such as flow sensors and / or pressure sensors) are used to measure the characteristics of the gas flow. Summary of the Invention

[0003] In a first aspect, this disclosure broadly includes a breathing device configured to provide a gas flow to a user for respiratory therapy, the breathing device comprising: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and initiate one or more actions at least in part based on the determined WOB metric.

[0004] In a second aspect, this disclosure broadly includes a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system comprising: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and initiate one or more actions at least in part based on the determined WOB metric.

[0005] The breathing device of the first aspect or the respiratory therapy system of the second aspect can further have any one or more of the following aspects or features defined in the following paragraphs.

[0006] In the configuration, the flow parameter data includes flow rate data indicating or representative of the flow rate of the gas flow provided by the flow rate generator.

[0007] In the configuration, the device includes one or more flow rate sensors configured to sense and generate flow rate data.

[0008] In the configuration, the one or more flow rate sensors are positioned in or within the flow path of the gas flow.

[0009] In the configuration, the one or more flow rate sensors are positioned at or near the outlet of the blower of the flow rate generator.

[0010] In the configuration, the one or more flow rate sensors communicate electrically with a controller.

[0011] In the configuration, the controller is further configured to process the flow rate data to remove noise and / or signal components associated with the flow rate generator.

[0012] In the configuration, the controller is configured to remove noise related to the influence of the motor on the flow rate data.

[0013] In the configuration, the controller is configured to receive data on the motor speed and, if the motor speed is below a preset threshold, discard the flow rate data of the gas flow.

[0014] In the configuration, the controller is configured to: if the controller determines that the quality of the flow rate data parameters of the gas flow is insufficient, discard the flow rate data.

[0015] In the configuration, if the flow rate data includes large transient peaks, the flow rate data is determined to be of insufficient quality.

[0016] In the configuration, the flow parameter data includes pressure data indicating or representative of the pressure of the gas flow at the outlet of the blower of the flow rate generator.

[0017] In the configuration, the device further includes one or more pressure sensors configured to sense and generate pressure data.

[0018] In the configuration, the one or more pressure sensors are positioned in or within the flow path of the gas flow.

[0019] In the configuration, the one or more pressure sensors are positioned at or near the outlet of the blower of the flow rate generator.

[0020] In the configuration, the one or more pressure sensors communicate electrically with a controller.

[0021] In the configuration, the controller is further configured to determine an initial nasal pressure estimate that indicates or represents an estimate of the user's nasal pressure based at least in part on pressure data.

[0022] In the configuration, the controller is further configured to determine a flow path conductance estimate that indicates or represents an estimate of the conductance of the flow path of the gas flow between the flow generator and the patient interface.

[0023] In the configuration, the controller is configured to determine the flow path conductance estimate based at least in part on the initial nasal pressure estimate that indicates or represents an estimate of the user's nasal pressure.

[0024] In the configuration, the controller is configured to determine the flow path conductance estimate based at least in part on flow rate data that indicates or represents the flow rate of the gas flow provided by the flow generator.

[0025] In the configuration, the controller is configured to determine the flow path conductance estimate based at least in part on pressure data that indicates or represents the pressure of the gas flow at the outlet of the blower of the flow generator.

[0026] In the configuration, the controller is configured to determine the flow path conductance estimate based at least in part on the flow rate data that indicates or represents the flow rate of the gas flow provided by the flow generator and the motor speed that represents the rotational speed of the motor of the blower of the flow generator.

[0027] In the configuration, the controller is configured to determine the flow path conductance estimate based at least in part on the flow rate data that indicates or represents the flow rate of the gas flow provided by the flow generator and the pressure data that indicates or represents the pressure of the gas flow at the outlet of the blower of the flow generator.

[0028] In the configuration, the controller is configured to determine a nasal pressure change value based at least in part on the flow path conductance estimate.

[0029] In the configuration, the controller is configured to determine the nasal pressure change value based at least in part on the flow rate data that indicates or represents the flow rate of the gas flow provided by the flow generator.

[0030] In the configuration, the controller is configured to determine the nasal pressure change value based at least in part on minute ventilation data that indicates or represents the average volume of gas provided by the flow generator per minute.

[0031] In the configuration, the controller is configured to determine the minute ventilation data by fitting a plurality of splines to the flow parameter data of the gas flow, wherein the plurality of splines are fitted using a least squares criterion and the minute ventilation data is determined by integrating along the plurality of splines.

[0032] In the configuration, the controller is configured to determine the minute ventilation data by determining the integral of the absolute value of the first term of the line fitting the flow parameter data of the gas flow.

[0033] In the configuration, the controller is configured to determine the device minute ventilation data by dividing the integral of the absolute value of the data of the line fitting the flow parameter data of the gas flow by the time range.

[0034] In the configuration, the controller is configured to determine the device minute ventilation data by determining the average value of the absolute value of the line fitting the flow parameter data of the gas flow across a series of time points within the time range.

[0035] In the configuration, the nasal pressure change value is determined at a frequency selected within the range of 1 Hz to 20 Hz.

[0036] In the configuration, the nasal pressure change value is continuously determined as a rolling average.

[0037] In the configuration, the device further includes a non-transitory computer-readable medium that is accessible or in data communication with the controller, and preferably wherein the non-transitory computer-readable medium includes non-volatile memory, and preferably wherein the device further includes a patient nostril model stored in the non-volatile memory.

[0038] In the configuration, the controller is further configured to determine an estimated user respiratory flow rate indicative of or representative of the user's respiratory flow rate at least in part based on flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator and the patient nostril model.

[0039] In the configuration, the controller is configured to determine the estimated user respiratory flow rate at least in part based on an estimated flow path conductance value that indicates or represents an estimated conductance of the flow path of the gas flow between the flow generator and the patient interface.

[0040] In the configuration, the controller is configured to determine the estimated user respiratory flow rate at least in part based on the minute ventilation data indicative of or representative of the average gas volume provided by the flow generator per minute.

[0041] In the configuration, the controller is configured to determine an estimated nostril conductance value that indicates or represents an estimated conductance of the flow path of the gas flow between the patient interface and the user's nostrils at least in part based on data indicative of the patient interface size and an estimate of nostril blockage of the patient interface.

[0042] In the configuration, the controller is configured to determine the estimated user respiratory flow rate at least in part based on the determined or calculated estimated nostril conductance value.

[0043] In a configuration, the controller is configured to determine a work of breathing metric based at least in part on a nasal pressure change value and a user respiratory flow rate estimation signal.

[0044] In a configuration, the controller is configured to determine a smoothness value indicative of or representative of the smoothness of minute ventilation data, the minute ventilation data indicative of or representative of the average gas volume provided per minute by a flow generator.

[0045] In a configuration, the controller is configured to determine a work of breathing metric based at least in part on a nasal pressure change value and a smoothness value.

[0046] In a configuration, the device further includes a display screen, and preferably wherein the display screen displays a graphical user interface, and / or preferably wherein the display screen is in electrical communication with the controller.

[0047] In a configuration, the display screen is removable from the device or the housing of the device.

[0048] In a configuration, the controller is configured to display a graphical metric representative of the determined work of breathing metric on the display screen.

[0049] In a configuration, the graphical metric includes any one or more of the following: a numerical value, text, a waveform, an illustration, or an animation.

[0050] In a configuration, the graphical metric indicates or represents whether the determined work of breathing metric is increasing or decreasing.

[0051] In a configuration, the controller is configured to trigger or generate a warning, an alarm, and / or a notification based at least in part on the determined work of breathing metric and one or more thresholds.

[0052] In a configuration, the warning, the alarm, and / or the notification is triggered or generated based at least in part on determining that the work of breathing metric has increased above a threshold.

[0053] In a configuration, the warning, the alarm, and / or the notification is triggered or generated based at least in part on determining that the work of breathing metric has decreased below a threshold.

[0054] In a configuration, the threshold is a disconnection detection threshold.

[0055] In a configuration, the warning, the alarm, and / or the notification is triggered or generated based at least in part on determining that the work of breathing metric has continuously decreased below a threshold for an associated predetermined duration condition.

[0056] In a configuration, the controller is configured to generate a warning, an alarm, and / or a notification in a form selected from any one or more of the following: auditory, visual, and / or tactile.

[0057] In a configuration, the device further includes an audio output device in electrical communication with the controller, and wherein the controller is configured to audibly generate warnings, alerts, and / or notifications via the audio output device.

[0058] In a configuration, the controller is configured to visually generate warnings, alerts, and / or notifications via a display screen of the device.

[0059] In a configuration, the controller is configured to send or transmit data representative of warnings, alerts, and / or notifications to a remote device or system in data communication with the device.

[0060] In a configuration, the controller is operable to configure or adjust the one or more of the thresholds or any parameters associated with the one or more of the thresholds, at least in part, based on user input via a graphical user interface of a display screen of the device.

[0061] In a configuration, the controller is configured to generate or provide recommended thresholds and / or parameters associated with the one or more thresholds, at least in part, based on a work of breathing metric.

[0062] In a configuration, the controller is further configured to determine a ratio or percentage of a work of breathing metric of a user relative to a nominal equivalent work of breathing metric of a nominal average healthy person.

[0063] In a configuration, the nominal equivalent work of breathing metric is determined at least in part based on a magnitude of a nominal nasal pressure change of a nominal average healthy person.

[0064] In a configuration, the magnitude of the nominal nasal pressure change of a nominal average healthy person is determined at least in part based on a predetermined physiological parameter of the nominal average healthy person.

[0065] In a configuration, the magnitude of the nominal nasal pressure change of a nominal average healthy person is determined at least in part based on a manually input physiological parameter associated with the user.

[0066] In a configuration, the magnitude of the nominal nasal pressure change of a nominal average healthy person is determined at least in part based on a nominal measure of nostril occlusion of a nominal nasal cannula prong of a patient interface.

[0067] In a configuration, the magnitude of the nominal nasal pressure change of a nominal average healthy person is determined at least in part based on a manually input measure of nostril occlusion of a nasal cannula prong of a patient interface.

[0068] In a configuration, the controller is configured to generate one or more warnings, alerts, and / or notifications based at least in part on: a value representing a ratio or percentage of a user's work of breathing metric relative to a nominal equivalent work of breathing metric of a nominal average healthy person or trend data associated with the ratio or percentage, and one or more thresholds.

[0069] In a configuration, the controller is configured to visually display on a display screen of the device the value of the ratio or percentage and / or trend data relating to the ratio or percentage.

[0070] In a configuration, the controller is configured to generate warnings, alerts, and / or notifications including data indicating a recommended adjustment to one or more therapy settings and / or device settings based at least in part on: a value representing a ratio or percentage of a user's work of breathing metric relative to a nominal equivalent work of breathing metric of a nominal average healthy person or trend data associated with the ratio or percentage, and one or more thresholds.

[0071] In a configuration, the therapy setting and / or device setting includes a flow rate setting and / or a gas flow oxygen concentration setting (e.g., FiO2 setting or FdO2 setting).

[0072] In a configuration, the device or system further includes a housing, and wherein the housing includes or integrates the following: a flow generator; a humidifier configured to heat and humidify a gas flow; a sensing block or sensor module including the one or more sensors configured to generate flow parameter data indicative or representative of the gas flow; and a controller.

[0073] In a configuration, the sensing block or sensor module includes a flow rate sensor and a pressure sensor.

[0074] In a third aspect, the present disclosure broadly includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the user's average nasal pressure based at least in part on the received flow parameter data; determining a work of breathing (WOB) metric based at least in part on the determined nasal pressure change value; and initiating one or more actions based at least in part on the determined WOB metric.

[0075] In a configuration, the flow parameter data includes flow rate data indicative or representative of the gas flow provided by the flow generator.

[0076] In a configuration, the device includes one or more flow rate sensors configured to sense and generate flow rate data.

[0077] In a configuration, the one or more flow rate sensors are positioned in or along the flow path of the gas flow.

[0078] In a configuration, the one or more flow rate sensors are positioned at or near the outlet of the blower of the flow generator.

[0079] In a configuration, the one or more flow rate sensors are in electrical communication with a controller.

[0080] In a configuration, the method further includes: processing the flow rate data to remove noise and / or signal components associated with the flow generator.

[0081] In a configuration, the method includes: removing noise related to the influence of the motor on the flow rate data.

[0082] In a configuration, the method includes: receiving data on the motor speed, and if the motor speed is below a preset threshold, discarding the flow rate data of the gas flow.

[0083] In a configuration, the method includes: discarding the flow rate data if it is determined that the quality of the flow rate data of the gas flow is insufficient.

[0084] In a configuration, if the flow rate data includes large transient peaks, the flow rate data is determined to be of insufficient quality.

[0085] In a configuration, the flow parameter data includes pressure data indicating or representing the pressure at the outlet of the blower of the flow generator of the gas flow.

[0086] In a configuration, the device further includes one or more pressure sensors configured to sense and generate pressure data.

[0087] In a configuration, the one or more pressure sensors are positioned in or along the flow path of the gas flow.

[0088] In a configuration, the one or more pressure sensors are positioned at or near the outlet of the blower of the flow generator.

[0089] In a configuration, the one or more pressure sensors are in electrical communication with a controller.

[0090] In a configuration, the method further includes: determining an initial nasal pressure estimate indicating or representing an estimate of the user's nasal pressure based at least in part on the pressure data.

[0091] In a configuration, the method further includes: determining an estimate of the flow path conductance, the estimate of the flow path conductance indicating or representing an estimate of the conductance of the flow path of the gas flow between the flow generator and the patient interface.

[0092] In a configuration, the method includes: determining an estimate of the flow path conductance at least in part based on an initial nasal pressure estimate indicating or representing an estimate of the user's nasal pressure.

[0093] In a configuration, the method includes: determining an estimate of the flow path conductance at least in part based on flow rate data indicating or representing the flow rate of the gas flow provided by the flow generator.

[0094] In a configuration, the method includes: determining an estimate of the flow path conductance at least in part based on pressure data indicating or representing the pressure of the gas flow at the outlet of the blower of the flow generator.

[0095] In a configuration, the method includes: determining an estimate of the flow path conductance at least in part based on flow rate data indicating or representing the flow rate of the gas flow provided by the flow generator and a motor speed representing the motor speed of the blower of the flow generator.

[0096] In a configuration, the method includes: determining an estimate of the flow path conductance at least in part based on flow rate data indicating or representing the flow rate of the gas flow provided by the flow generator and pressure data indicating or representing the pressure of the gas flow at the outlet of the blower of the flow generator.

[0097] In a configuration, the method includes: determining a nasal pressure change value at least in part based on the estimate of the flow path conductance.

[0098] In a configuration, the method includes: determining a nasal pressure change value at least in part based on flow rate data indicating or representing the flow rate of the gas flow provided by the flow generator.

[0099] In a configuration, the method includes: determining a nasal pressure change value at least in part based on minute ventilation data indicating or representing the average volume of gas provided by the flow generator per minute.

[0100] In a configuration, the method includes: determining the minute ventilation data by fitting a plurality of splines to the flow parameter data of the gas flow, wherein the plurality of splines are fitted using a least squares criterion and the minute ventilation data is determined by integrating along the plurality of splines.

[0101] In a configuration, the method includes: determining the minute ventilation data by determining the integral of the absolute value of the first term of the line fitted to the flow parameter data of the gas flow.

[0102] In a configuration, the method includes determining minute ventilation data for the device by dividing the integral of the absolute value of the line of data of the flow parameters fitted to the gas flow by the time range.

[0103] In a configuration, the method further includes determining minute ventilation data for the device by determining the average value of the absolute value of the line of data of the flow parameters fitted to the gas flow across a series of time points within the time range.

[0104] In a configuration, the method includes determining a nasal pressure change value at a frequency selected within the range of 1 Hz to 20 Hz.

[0105] In a configuration, the method includes continuously determining the nasal pressure change value as a rolling average.

[0106] In a configuration, the device further includes a non - transitory computer - readable medium that is accessible or in data communication with the controller, and preferably wherein the non - transitory computer - readable medium includes non - volatile memory, and preferably wherein the device further includes a patient nostril model stored in the non - volatile memory.

[0107] In a configuration, the method further includes determining an estimated user respiratory flow rate indicative of or representing the user's respiratory flow rate at least in part based on flow rate data indicative of or representing the flow rate of the gas flow provided by the flow generator and the patient nostril model.

[0108] In a configuration, the method includes determining an estimated user respiratory flow rate at least in part based on an estimated flow path conductance value that indicates or represents an estimated conductance of the flow path of the gas flow between the flow generator and the patient interface.

[0109] In a configuration, the method includes determining an estimated user respiratory flow rate at least in part based on minute ventilation data indicative of or representing the average gas volume provided per minute by the flow generator.

[0110] In a configuration, the method includes determining an estimated nostril conductance value at least in part based on data indicative of the patient interface size and an estimate of nostril blockage by the patient interface, the estimated nostril conductance value indicating or representing an estimated conductance of the flow path of the gas flow between the patient interface and the user's nostrils.

[0111] In a configuration, the method includes determining an estimated user respiratory flow rate at least in part based on the determined or calculated estimated nostril conductance value.

[0112] In a configuration, the method includes determining a respiratory work index at least in part based on the nasal pressure change value and the estimated user respiratory flow rate signal.

[0113] In a configuration, the method includes: determining a smoothness value indicative of or representative of the smoothness of minute ventilation data, the minute ventilation data indicative of or representative of the average gas volume provided per minute by a flow generator.

[0114] In a configuration, the method includes: determining a work of breathing metric at least in part based on a nasal pressure change value and the smoothness value.

[0115] In a configuration, the device further includes a display screen, and preferably wherein the display screen displays a graphical user interface, and / or preferably wherein the display screen is in electrical communication with a controller.

[0116] In a configuration, the display screen is removable from the device or the housing of the device.

[0117] In a configuration, the method includes: displaying a graphical metric representative of the determined work of breathing metric on the display screen.

[0118] In a configuration, the graphical metric includes any one or more of the following: a numerical value, text, a waveform, an illustration, or an animation.

[0119] In a configuration, the graphical metric indicates or represents whether the determined work of breathing metric is increasing or decreasing.

[0120] In a configuration, the method includes: triggering or generating a warning, an alarm, and / or a notification at least in part based on the determined work of breathing metric and one or more thresholds.

[0121] In a configuration, the method includes: triggering or generating a warning, an alarm, and / or a notification at least in part based on determining that the work of breathing metric has increased above a threshold.

[0122] In a configuration, the method includes: triggering or generating a warning, an alarm, and / or a notification at least in part based on determining that the work of breathing metric has decreased below a threshold.

[0123] In a configuration, the threshold is a disconnection detection threshold.

[0124] In a configuration, the method includes: triggering or generating a warning, an alarm, and / or a notification at least in part based on determining that the work of breathing metric has continuously decreased below a threshold for an associated predetermined duration condition.

[0125] In a configuration, the method includes generating a warning, an alarm, and / or a notification in a form selected from any one or more of the following: auditory, visual, and / or tactile.

[0126] In a configuration, the device further includes an audio output device in electrical communication with the controller, and wherein the method includes: audibly generating a warning, an alarm, and / or a notification via the audio output device.

[0127] In a configuration, the method includes: visually generating warnings, alerts, and / or notifications via a display screen of a device.

[0128] In a configuration, the method includes: sending or transmitting data representing warnings, alerts, and / or notifications to a remote device or system that communicates data with the device.

[0129] In a configuration, the method includes: configuring or adjusting the one or more of the thresholds or any parameters associated with the one or more of the thresholds, at least in part based on user input via a graphical user interface of a display screen of the device.

[0130] In a configuration, the method includes: generating or providing recommended thresholds and / or parameters associated with the one or more thresholds, at least in part based on a work of breathing metric.

[0131] In a configuration, the method further includes: determining a ratio or percentage of a work of breathing metric of a user relative to a nominal equivalent work of breathing metric of a nominal average healthy person.

[0132] In a configuration, the method includes: determining the nominal equivalent work of breathing metric, at least in part based on a magnitude of a nominal nasal pressure change of a nominal average healthy person.

[0133] In a configuration, the method includes: determining the magnitude of the nominal nasal pressure change of a nominal average healthy person, at least in part based on a predetermined physiological parameter of the nominal average healthy person.

[0134] In a configuration, the method includes: determining the magnitude of the nominal nasal pressure change of a nominal average healthy person, at least in part based on a manually input physiological parameter associated with the user.

[0135] In a configuration, the method includes: determining the magnitude of the nominal nasal pressure change of a nominal average healthy person, at least in part based on a nominal measure of nostril blockage by a nominal nasal cannula prong of a patient interface.

[0136] In a configuration, the method includes: determining the magnitude of the nominal nasal pressure change of a nominal average healthy person, at least in part based on a manually input measure of nostril blockage by a nasal cannula prong of a patient interface.

[0137] In a configuration, the method includes: generating one or more warnings, alerts, and / or notifications, at least in part based on: a value of a ratio or percentage of a work of breathing metric of a user relative to a nominal equivalent work of breathing metric of a nominal average healthy person or associated trend data of the ratio or percentage, and one or more thresholds.

[0138] In a configuration, the method includes visually displaying on a display screen of a device a value of a ratio or percentage and / or trend data relating to a ratio or percentage.

[0139] In a configuration, the method includes generating, at least in part based on: a value of a ratio or percentage representing a ratio of a user's work of breathing metric relative to a nominal equivalent work of breathing metric of a nominal average healthy person or trend data associated with the ratio or percentage; and one or more thresholds, a warning, alert, and / or notification including data indicative of a suggested adjustment to one or more therapy settings and / or device settings.

[0140] In a configuration, the therapy setting and / or device setting includes a flow rate setting and / or a gas flow oxygen concentration setting (e.g., FiO2 setting or FdO2 setting).

[0141] In a configuration, the device further includes a housing, and wherein the housing includes or integrates: a flow generator; a humidifier configured to heat and humidify a gas flow; a sensing block or sensor module including the one or more sensors configured to generate data indicative of or representative of flow parameters of the gas flow; and a controller.

[0142] In a configuration, the sensing block or sensor module includes a flow rate sensor and a pressure sensor.

[0143] In a fourth aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate data indicative of or representative of flow parameters of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of an average nasal pressure of the user, at least in part based on the received flow parameter data; determine a user respiratory flow rate estimate indicative of or representative of a respiratory flow rate of the user; determine a work of breathing (WOB) metric, at least in part based on the determined nasal pressure change value and the user respiratory flow rate estimate; and initiate one or more actions, at least in part based on the determined WOB metric.

[0144] In a fifth aspect, the present disclosure broadly includes a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy. The respiratory therapy system includes: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller. The controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine an estimated user breathing flow rate indicative of or representative of the breathing flow rate of the user; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value and the estimated user breathing flow rate; and initiate one or more actions at least in part based on the determined WOB metric.

[0145] In a sixth aspect, the present disclosure broadly includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy. The device includes: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller. The method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determining an estimated user breathing flow rate indicative of or representative of the breathing flow rate of the user; determining a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value and the estimated user breathing flow rate; and initiating one or more actions at least in part based on the determined WOB metric.

[0146] In a seventh aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy. The respiratory device includes: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller. The controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a breathing smoothness value indicative of the rate of change of nasal pressure fluctuations of the user; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value and the breathing smoothness value; and initiate one or more actions at least in part based on the determined WOB metric.

[0147] In an eighth aspect, the present disclosure broadly includes a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of an average nasal pressure of the user at least in part based on the received flow parameter data; determine a respiratory smoothness value indicative of a rate of change of nasal pressure fluctuations of the user; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value and the respiratory smoothness value; and initiate one or more actions at least in part based on the determined WOB metric.

[0148] In a ninth aspect, the present disclosure broadly includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of an average nasal pressure of the user at least in part based on the received flow parameter data; determining a respiratory smoothness value indicative of a rate of change of nasal pressure fluctuations of the user; determining a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value and the respiratory smoothness value; and initiating one or more actions at least in part based on the determined WOB metric.

[0149] The fourth to ninth aspects of the present disclosure may further have any one or more of the features described in the first to third aspects with respect to the above paragraphs.

[0150] In a tenth aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a display connected to or in data communication with the respiratory device; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of an average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and display or cause to be displayed on the display WOB data at least in part based on the determined WOB metric.

[0151] In a eleventh aspect, the present disclosure includes a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a display coupled to or in data communication with the respiratory system; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of an average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and display or cause to be displayed on the display WOB data at least in part based on the determined WOB metric.

[0152] The respiratory device of the tenth aspect or the respiratory therapy system of the eleventh aspect may further have any one or more of the following aspects or features defined in the following paragraphs.

[0153] In a configuration, the display includes a display screen of the respiratory device.

[0154] In a configuration, the display screen is removable from the respiratory device or the housing of the respiratory device.

[0155] In a configuration, the display includes a user interface of the respiratory device.

[0156] In a configuration, the display includes a graphical user interface (GUI).

[0157] In a configuration, the display is provided on a remote device or system in data communication with the respiratory device.

[0158] In a configuration, the controller is further configured to transmit the WOB data for display to a remote device or system for display.

[0159] In a configuration, the controller is configured to display on the display screen of the respiratory device one or more graphical metrics representative of the WOB data.

[0160] In a configuration, the graphical metrics include any one or more of the following: numerical values, text, waveforms, illustrations, or animations.

[0161] In a configuration, the graphical metrics may indicate or represent whether the determined WOB metric is increasing or decreasing.

[0162] In a configuration, the WOB data displayed on the display includes data indicative of the raw or absolute WOB metric.

[0163] In the configuration, the controller is further configured to process the determined WOB metric to generate a ratio or percentage representing the determined WOB metric of the user relative to the nominal equivalent WOB metric of a nominal average healthy person.

[0164] In the configuration, the WOB data displayed on the display includes data indicating a ratio or percentage representing the determined WOB metric of the user relative to the nominal equivalent WOB metric of a nominal average healthy person.

[0165] In the configuration, the controller is further configured to process a portion or window of the determined WOB metric over time to generate one or more WOB metric trends or trend data.

[0166] In the configuration, the WOB data displayed on the display includes data indicating one or more WOB metric trends or trend data.

[0167] In the configuration, the WOB data displayed on the display includes WOB metric trends or trend data indicating or representing any one or more of the following: increasing WOB, decreasing WOB, and / or stable WOB.

[0168] In the configuration, the WOB data displayed on the display may include data indicating any one or more of the following data types: raw or absolute WOB metric data, a ratio or percentage representing the determined WOB metric of the user relative to the nominal equivalent WOB metric of a nominal average healthy person, and / or WOB metric trends or trend data.

[0169] In the configuration, one or more of the data types may be displayed on the display in isolation or in combination with any one or more of the other data types.

[0170] In the configuration, the data is displayed on a graphical user interface (GUI) of the display screen, and the GUI includes a first GUI element configured to display a first type of WOB data and a second GUI element configured to display a second type of WOB data.

[0171] In one example configuration, the first GUI element includes graphical metrics representing the following: raw or absolute WOB metric data; and / or a ratio or percentage representing the determined WOB metric of the user relative to the nominal equivalent WOB metric of a nominal average healthy person, and the second GUI element includes graphical metrics representing the following: WOB metric trends or trend data.

[0172] In a twelfth aspect, the present disclosure includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a display connected to or in data communication with the respiratory device; and a controller, wherein the method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determining a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and displaying or causing to be displayed on the display WOB data at least in part based on the determined WOB metric.

[0173] The method of the twelfth aspect may include any one or more of the features mentioned with respect to the tenth or eleventh aspect of the present disclosure as described in the above paragraphs.

[0174] In a thirteenth aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generate one or more warnings, alerts, and / or notifications at least in part based on comparing the determined WOB metric or associated WOB data with one or more thresholds.

[0175] In a fourteenth aspect, the present disclosure includes: a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generate one or more warnings, alerts, and / or notifications at least in part based on comparing the determined WOB metric or associated WOB data with one or more thresholds.

[0176] The respiratory device of the thirteenth aspect or the respiratory therapy system of the fourteenth aspect may further have any one or more of the following aspects or features defined in the following paragraphs.

[0177] In a configuration, the controller is configured to generate a warning, an alarm, and / or a notification at least in part based on determining that the WOB metric or associated WOB data has increased above a threshold.

[0178] In a configuration, the controller is configured to generate a warning, an alarm, and / or a notification at least in part based on determining that the WOB metric or associated WOB data has decreased below a threshold.

[0179] In a configuration, the controller is configured to generate a warning, an alarm, and / or a notification in any one or more of the following forms: auditory, visual, and / or tactile.

[0180] In a configuration, the device or system further includes an audio output device in electrical communication with the controller, and wherein the controller is configured to audibly generate a warning, an alarm, and / or a notification via the audio output device.

[0181] In a configuration, the device or system further includes a display in electrical or data communication with the controller, and the controller is configured to visually generate a warning, an alarm, and / or a notification via the display.

[0182] In a configuration, the controller is configured to send or transmit data representing the generated warning, alarm, and / or notification to a remote device or system in data communication with the device or system.

[0183] In a configuration, the controller is configured to send or transmit the determined WOB metric and / or associated WOB data to a remote device or system in data communication with the device or system.

[0184] In a configuration, the remote device or system displays or presents data representing the warning, alarm, and / or notification (e.g., whether visual, auditory, and / or tactile), and / or relays / transmits the warning, alarm, and / or notification to another remote electronic device or system.

[0185] In a configuration, the display includes a display screen of the respiratory device.

[0186] In a configuration, the display screen is removable from the respiratory device or the housing of the respiratory device.

[0187] In a configuration, the display includes a user interface of the respiratory device.

[0188] In a configuration, the display includes a graphical user interface (GUI).

[0189] In the configuration, the display is set on a remote device or system that communicates data with the breathing device.

[0190] In the configuration, the controller is configured to display graphical metrics representing the generated warnings, alerts, and / or notifications on the display screen of the breathing device.

[0191] In the configuration, the graphical metrics include any one or more of the following: numerical values, text information, graphical forms or formats, trend lines, data plotted over time or represented in a chart, waveforms, illustrations, icons, animations, and / or color-coded information.

[0192] In the configuration, the controller is configured to simultaneously display data indicating or representing the determined WOB metric or associated WOB data, and data indicating the generated warnings, alerts, and / or notifications.

[0193] In the configuration, the controller is configured to generate one or more different types of warnings, alerts, and / or notifications based at least in part on comparing the determined WOB metric or associated WOB data with one or more thresholds or threshold criteria.

[0194] In the configuration, the controller is configured to determine the user's WOB status based at least in part on comparing the determined WOB metric or associated WOB data with one or more thresholds or threshold criteria.

[0195] In the configuration, the controller is configured to generate a first type of warning, alert, and / or notification that includes data indicating the determined WOB status of the user (e.g., current status and / or trend status). In one example configuration, the determined WOB status can be selected from any one or more of the following: increasing WOB, decreasing WOB, stable WOB, high WOB, and / or low WOB.

[0196] In the configuration, the controller is configured to generate a second type of warning, alert, and / or notification that includes data indicating the recommended remedial action or response to the determined WOB status of the user. In one example configuration, the recommended actions can be selected from any one or more of the following: check the patient, adjust the treatment settings, and / or the recommended change to the treatment settings (e.g., increase or decrease the flow rate setting).

[0197] In the configuration, the controller can be configured such that the second type of warning, alert, and / or notification can be triggered or generated in response to the generation or triggering of the first type of warning, alert, and / or notification.

[0198] In a configuration, the controller can be configured to display data indicative of a first type of warning, alert, and / or notification concurrently with data indicative of a second type of warning, alert, and / or notification.

[0199] In a configuration, the displayed determined WOB metric or associated WOB data includes data indicative of any one or more of the following: a raw or absolute WOB metric, a ratio or percentage representing the user's determined WOB metric relative to a nominal equivalent WOB metric of a nominal average healthy person, and / or one or more WOB metric trends or trend data.

[0200] In a configuration, the data is displayed on a graphical user interface (GUI) of a display screen, and the GUI includes one or more GUI elements or panes or regions for displaying one or more of the generated warnings, alerts, and / or notifications.

[0201] In a configuration, the data displayed on the GUI of the display screen includes: a first GUI element or pane or region for displaying a first type of warning, alert, and / or notification indicative of the user's determined WOB status; and a second GUI element or pane or region for displaying a second type of warning, alert, and / or notification indicative of a recommended remedial action or in response to the user's determined WOB status.

[0202] In a configuration, the controller can be configured to generate the first and / or second type of warning, alert, and / or notification audibly via an associated audio output device and / or using one or more audible cues or voice commands.

[0203] In a fifteenth aspect, the present disclosure includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the user's average nasal pressure based at least in part on the received flow parameter data; determining a work of breathing (WOB) metric based at least in part on the determined nasal pressure change value; and generating one or more warnings, alerts, and / or notifications based at least in part on comparing the determined WOB metric or associated WOB data with one or more thresholds.

[0204] The method of the fifteenth aspect can include any one or more of the features mentioned with respect to the thirteenth or fourteenth aspect of the present disclosure as described in the above paragraphs.

[0205] In a sixteenth aspect, the present disclosure broadly includes a system that includes: a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and send or transmit the WOB metric or associated WOB data to a remote device or system in data communication with the respiratory device, and wherein: the remote device or system is configured to generate one or more warnings, alerts, and / or notifications at least in part based on comparing the determined WOB metric or associated WOB data with one or more thresholds.

[0206] In a configuration, the remote device or system is configured to present the one or more warnings, alerts, and / or notifications generated (e.g., whether visual, audible, and / or tactile).

[0207] In a configuration, the remote device or system is configured to push or transmit or relay the WOB metric and / or associated WOB data and / or the one or more warnings, alerts, and / or notifications generated to another electronic device or system.

[0208] The system of the sixteenth aspect may further include any one or more of the features mentioned in the thirteenth to fifteenth aspects of the present disclosure in the above paragraphs. In one example, the remote device or system may be configured to implement any one or more of the functions of the controller of the respiratory device or system, including generating and / or presenting (e.g., displaying or audibly presenting) alerts, warnings, and / or notifications.

[0209] In a seventeenth aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the user's average nasal pressure at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generate one or more suggestions for adjusting treatment parameter settings at least in part based on the determined WOB metric or associated WOB data.

[0210] In an eighteenth aspect, the present disclosure includes a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generate one or more treatment parameter setting adjustment recommendations at least in part based on the determined WOB metric or associated WOB data.

[0211] The respiratory device of the seventeenth aspect or the respiratory therapy system of the eighteenth aspect may further have any one or more of the following aspects or features defined in the following paragraphs.

[0212] In a configuration, the controller is configured to generate the one or more treatment parameter setting adjustment recommendations at least in part based on comparing the determined WOB metric or associated WOB data with one or more thresholds.

[0213] In a configuration, the WOB metric or associated WOB data may include data indicative of or representative of any one or more of the following: a raw or absolute WOB metric, a ratio or percentage representing the determined WOB metric of the user relative to a nominal equivalent WOB metric of a nominal average healthy person, and / or one or more WOB metric trends or trend data.

[0214] In a configuration, the controller may be configured to display or present the generated treatment parameter setting adjustment recommendations on a display screen of the respiratory device.

[0215] In a configuration, the controller may be configured to transmit, send, or relay the generated treatment parameter setting adjustment recommendations to one or more remote devices or systems in data communication with the respiratory device or system.

[0216] In a configuration, the controller may be configured to apply the generated treatment parameter setting adjustment recommendations to the treatment settings of the respiratory device (e.g., flow rate settings and / or gas flow oxygen concentration settings, such as FiO2 settings and / or FdO2 settings) in response to an input or confirmation from a user or clinician via a user interface of the respiratory device and / or the remote device or system.

[0217] In a nineteenth aspect, the present disclosure includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device comprising: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and comprises the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determining a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generating one or more treatment parameter setting adjustment recommendations at least in part based on the determined WOB metric or associated WOB data.

[0218] The method of the nineteenth aspect may include any one or more of the features mentioned in relation to the seventeenth or eighteenth aspect of the present disclosure as described in the above paragraph.

[0219] In a twentieth aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device comprising: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and process the WOB metric or associated WOB data to detect a disconnection event.

[0220] In a twenty - first aspect, the present disclosure includes: a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system comprising: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and process the WOB metric or associated WOB data to detect a disconnection event.

[0221] The respiratory device of the twentieth aspect or the respiratory therapy system of the twenty - first aspect may further have any one or more of the following aspects or features defined in the following paragraphs.

[0222] In a configuration, a disconnection event can indicate or represent a disconnection of any portion of a flow path (e.g., a patient breathing circuit and / or a patient interface), and / or a disconnection or detachment of a user from the patient interface.

[0223] In a configuration, the controller can be configured to detect a disconnection event at least in part based on whether the determined WOB metric or associated WOB data reaches zero or dips below a predetermined threshold (e.g., approaches zero) for a predetermined period of time.

[0224] In a configuration, the controller can further be configured to generate a warning, an alert, and / or a notification in response to detecting a disconnection event.

[0225] In a configuration, the controller can be configured to display or present the generated warning, alert, and / or notification of the disconnection event on a display of the breathing device.

[0226] In a configuration, the controller can be configured to send, transmit, or relay the generated warning, alert, and / or notification of the disconnection event to a remote system.

[0227] In a configuration, the generated warning, alert, and / or notification of the disconnection event can further include data indicating a suggested remedy or corrective action to address the disconnection event.

[0228] In a twenty-second aspect, the present disclosure includes a method of controlling a breathing device configured to provide a gas flow to a user for respiratory therapy, the device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of an average nasal pressure of the user at least in part based on the received flow parameter data; determining a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and processing the WOB metric or associated WOB data to detect a disconnection event.

[0229] The method of the twenty-second aspect can include any one or more of the features mentioned in connection with the twentieth or twenty-first aspect of the present disclosure as described in the above paragraphs.

[0230] In a twenty-third aspect, the present disclosure broadly includes a respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generate one or more warnings, alerts, and / or notifications at least in part based on comparing the determined WOB metric or associated WOB data with one or more configurable thresholds.

[0231] In a twenty-fourth aspect, the present disclosure includes a respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and generate one or more warnings, alerts, and / or notifications at least in part based on comparing the determined WOB metric or associated WOB data with one or more configurable thresholds.

[0232] The respiratory device of the twenty-third aspect or the respiratory therapy system of the twenty-fourth aspect may further have any one or more of the following aspects or features defined in the following paragraphs.

[0233] In a configuration, the controller is further operable to configure or adjust the one or more of the thresholds or any parameter associated with the one or more of the thresholds at least in part based on user input via a graphical user interface (GUI) of a display screen of the device.

[0234] In a configuration, the controller is configured to generate or provide a recommended threshold and / or parameter associated with the one or more thresholds at least in part based on the determined WOB metric or associated WOB data.

[0235] In a configuration, the one or more configurable thresholds may include any one or more of the following: a single threshold, a threshold range, an upper threshold and a lower threshold, and / or a threshold function based on one or more parameters and / or conditions.

[0236] In a configuration, the device or system provides a GUI on a display screen, the GUI being operable to adjust or configure the one or more thresholds associated with warnings, alerts, and / or notifications.

[0237] In a configuration, the GUI provides: a first GUI element that presents data indicating conditions of warnings, alerts, notifications, and / or thresholds or parameters, and / or thresholds being adjusted; and a second GUI element that is user-interactive or operable to adjust the one or more thresholds.

[0238] In a configuration, the second GUI element may include one or more user-interactive GUI elements for adjusting the one or more configurable thresholds via touch input or interaction with the display screen.

[0239] In a configuration, the one or more user-interactive GUI elements for adjusting the one or more configurable thresholds may include any one or more of the following: a bistable trigger element, a dial, a slider scale element, selectable discrete threshold elements, and / or numerical and / or categorical input fields for entering desired thresholds.

[0240] In a configuration, the one or more WOB warnings, alerts, and / or notifications may be configured with thresholds such that comparison of the determined WOB metric or WOB data with these thresholds effectively serves as an alternative warning, alert, and / or notification for other respiratory parameters.

[0241] In a configuration, the WOB warnings, alerts, and / or notifications may be configured as alternative warnings, alerts, and / or notifications for one or more of the following respiratory parameters: respiratory rate, minute ventilation, and / or tidal volume.

[0242] In a configuration, the controller may be configured to compare the determined WOB metric or associated WOB data with a plurality of configurable thresholds and may generate one or more different warnings, alerts, or notifications depending on the result of each respective comparison.

[0243] In a configuration, the configurable thresholds may be preconfigured with default or recommended values.

[0244] In a configuration, a user interface may be provided on a display of the device or system for accepting or adjusting default or recommended thresholds for one or more of the warnings, alerts, and / or notifications.

[0245] In a configuration, a user interface can be provided on a remote device or system that communicates data with a breathing device or system, and the user interface can be operable by a user to accept or adjust default or recommended thresholds for one or more of warnings, alerts, and / or notifications.

[0246] In a configuration, warnings, alerts, and / or notifications can be set with multiple or multiple upper bounds or threshold ceilings and lower bounds or threshold floors.

[0247] In a configuration, warnings, alerts, and / or notifications can be set with cascading or nested thresholds or threshold ranges, or inner and outer threshold ranges, or multiple or a series or progressive or stepwise increasing thresholds on a threshold scale. In such a configuration, the nature of the generated warnings, alerts, and / or notifications associated with each respective threshold can depend on the nature, location, priority, or extremity of the threshold on the overall threshold scale or be determined by the nature, location, priority, or extremity of the threshold on the overall threshold scale.

[0248] In a configuration, if a high-priority threshold is met, a high-priority warning, alert, or notification can be generated, and if a low-priority threshold is met, a low-priority warning, alert, and / or notification can be generated.

[0249] In a configuration, the default or recommended thresholds associated with any one or more of warnings, alerts, and / or thresholds can be at least partially recalibrated and / or dynamically changed by a controller based on changes in WOB metrics or associated WOB data (e.g., trend data) determined over one treatment period, multiple treatment periods, and / or some other configurable time period.

[0250] In a configuration, the one or more generated warnings, alerts, and / or notifications can be configured to be selectively presented on one or more devices or systems at least partially based on the nature of the warning, alert, or notification and / or the threshold(s) met.

[0251] In a configuration, higher-priority warnings, alerts, and / or notifications can be configured to be presented on a breathing device and one or more other remote devices or systems.

[0252] In a configuration, lower-priority warnings, alerts, and / or notifications can be configured to be presented only on the breathing device.

[0253] In a twenty-fifth aspect, the present disclosure includes a method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and includes the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the average nasal pressure of the user based at least in part on the received flow parameter data; determining a work of breathing (WOB) metric based at least in part on the determined nasal pressure change value; and generating one or more warnings, alerts, and / or notifications based at least in part on comparing the determined WOB metric or associated WOB data to one or more configurable thresholds.

[0254] The method of the twenty-fifth aspect may include any one or more of the features mentioned with respect to the twenty-third or twenty-fourth aspect of the present disclosure as described in the above paragraphs.

[0255] In another aspect, the present disclosure includes a respiratory device including: a flow generator configured to generate a gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of a characteristic or parameter of the gas flow; and a controller configured to: control the flow generator to deliver the gas flow for nasal high flow therapy; determine a work of breathing (WOB) metric based at least in part on the flow parameter data; and initiate one or more actions based at least in part on the determined WOB metric.

[0256] In a configuration, the flow parameter data includes pressure data indicative of or representative of the pressure of the gas flow.

[0257] In a configuration, the pressure data is sensed and generated by one or more pressure sensors in data communication with the controller.

[0258] In a configuration, the one or more pressure sensors are configured to sense and generate pressure data indicative of or representative of the pressure of the gas flow at the outlet of the blower of the flow generator.

[0259] In a configuration, the flow parameter data includes flow rate data indicative of or representative of the flow rate of the gas flow.

[0260] In a configuration, the flow rate data is sensed and generated by one or more flow rate sensors in data communication with the controller.

[0261] In a configuration, the one or more flow rate sensors are positioned at or near the outlet of the blower of the flow generator.

[0262] In the configuration, the WOB metric is determined at least in part based on flow parameter data that includes sensed pressure and / or flow rate data related to a gas flow.

[0263] In another aspect, the present disclosure includes a respiratory device that includes: a flow generator configured to generate a gas flow for a user; and a controller configured to: control the flow generator to deliver the gas flow for respiratory therapy or nasal high flow therapy; determine a work of breathing (WOB) metric at least in part based on pressure and / or flow rate measurements related to the gas flow; and initiate one or more actions at least in part based on the determined WOB metric.

[0264] In another aspect, the present disclosure includes a respiratory device that includes: a flow generator configured to generate a gas flow for a user; and a controller configured to: control the flow generator to deliver the gas flow for respiratory therapy or nasal high flow therapy; and determine a work of breathing (WOB) metric at least in part based on pressure and / or flow rate measurements related to the gas flow.

[0265] In another aspect, the present disclosure relates to an electronically implemented method that includes software code or encoded instructions that are executable or implementable by a computer, processor, or controller to implement any one or more of the methods or aspects described above.

[0266] In another aspect, the present disclosure broadly includes a non - transitory computer - readable medium having computer - executable instructions stored thereon that, when executed on one or more processing devices, cause the one or more processing devices to execute or implement any one or more of the methods or aspects described above.

[0267] Any one of the aspects of the present disclosure described in the above paragraphs may further have any one or more of the features described with respect to any one or more of the other aspects of the present disclosure described in the above paragraphs. BRIEF DESCRIPTION OF THE DRAWINGS

[0268] These and other features, aspects, and advantages of the present disclosure are described with reference to the drawings of certain embodiments, which are intended to schematically illustrate certain embodiments and not to limit the present disclosure.

[0269] Figure 1 Schematically shown is a respiratory system configured to provide respiratory therapy to a patient.

[0270] Figure 2 Is a front view of an exemplary respiratory device having a humidification chamber and a raised handle / rod in place.

[0271] Figure 3 is the top view corresponding to Figure 2 .

[0272] Figure 4 is the right side view corresponding to Figure 2 .

[0273] Figure 5 is the left side view corresponding to Figure 2 .

[0274] Figure 6 is the rear view corresponding to Figure 2 .

[0275] Figure 7 is the left front perspective view corresponding to Figure 2 .

[0276] Figure 8 is the right front perspective view corresponding to Figure 2 .

[0277] Figure 9 is the bottom view corresponding to Figure 2 .

[0278] Figure 10 shows an example configuration of the air and oxygen inlet arrangement structure of the breathing device.

[0279] Figure 11 shows another example configuration of the air and oxygen inlet arrangement structure of the breathing device.

[0280] Figure 12 is a transverse cross-sectional view showing further details of the air and oxygen inlet arrangement structure of Figure 11 .

[0281] Figure 13 is another transverse cross-sectional view showing further details of the air and oxygen inlet arrangement structure of Figure 11 .

[0282] Figure 14 is a longitudinal cross-sectional view showing further details of the air and oxygen inlet arrangement structure of Figure 11 .

[0283] Figure 15 is an exploded view of the upper housing part and the lower housing part of the main housing of the breathing device.

[0284] Figure 16 is a left front side perspective view of the lower housing of the main housing, which shows the housing for receiving the motor / sensor module sub-assembly.

[0285] Figure 17is a first bottom-side perspective view of the main housing of a breathing apparatus, which shows a recess for a motor / sensor module sub-assembly inside the housing.

[0286] Figure 18 is a second bottom-side perspective view of the main housing of a breathing apparatus, which shows a recess for a motor / sensor module sub-assembly.

[0287] Figure 19A Shows a block diagram of a control system that interacts with and / or provides control and indication to components of a respiratory system.

[0288] Figure 19B Shows a block diagram of an example controller.

[0289] Figure 20 Shows a block diagram of a motor and sensor module.

[0290] Figure 21 Shows a sensing chamber of an example motor and sensor module.

[0291] Figure 22A Shows an embodiment of a flowchart of a method for estimating the minute ventilation of a device.

[0292] Figure 22B Shows another embodiment of a flowchart of a method for estimating the minute ventilation of a device.

[0293] Figure 22C Shows another embodiment of a flowchart of a method for estimating the minute ventilation of a device.

[0294] Figure 22D Shows another embodiment of a flowchart of a method for estimating the minute ventilation of a device.

[0295] Figure 23 Shows another embodiment of a flowchart of a method for estimating the minute ventilation of a device.

[0296] Figure 24 Shows a schematic example of a graphical user interface (GUI) display screen of a breathing device, which shows an example configuration of a work of breathing monitoring screen.

[0297] Figure 25A - 25F Shows a schematic example of a GUI display screen of a breathing device, which shows examples of different work of breathing warning or notification screens.

[0298] Figure 26 Shows an embodiment of a flowchart of a method for estimating a work of breathing (WOB) metric and generating a recommendation for adjusting a treatment parameter setting based on the generated WOB data.

[0299] Figure 27A andFigure 27B Shows a schematic example of a GUI display screen of a breathing device, which shows various examples of disconnection warnings triggered in response to the calculated WOB data.

[0300] Figure 28A and Figure 28B Shows a schematic example of a GUI display screen for adjusting thresholds associated with notifications, warnings, and / or alerts triggered based on WOB metrics or data. Detailed Description

[0301] Although certain examples are described below, those skilled in the art will understand that the present disclosure extends beyond the specifically disclosed examples and / or uses and their obvious modifications and equivalents. Accordingly, it is intended that the scope of the present disclosure as disclosed herein should not be limited by any particular example described below.

[0302] 1. Overview of an exemplary breathing device

[0303] Examples of methods and / or processes for determining work of breathing (WOB) or metrics or parameters indicative of work of breathing will be described in the context of an example breathing device 10 that is configured or operable to provide nasal high - flow therapy via an unsealed patient interface. This is intended as a non - limiting example. It will be understood that these methods and processes can be applied to other breathing devices or systems and / or other operating modes and / or treatment modalities delivered by such devices.

[0304] Figure 1 A schematic representation of the example breathing device 10 is provided.

[0305] The breathing device 10 (or'respiratory system') includes a flow source 50 for providing a high - flow gas 31, which is, for example, air, oxygen, air blended with oxygen, or a mixture of air and / or oxygen with one or more other gases. Alternatively, the breathing assistance device may have a connector for coupling to a flow source. Thus, the flow source may be considered to form part of the device or be separate from the device (depending on the context), or even part of the flow source forms part of the device and part of the flow source does not belong to the device. In short, depending on the configuration (some components may be optional), the system may include a combination of components selected from:

[0306] · A flow source,

[0307] · A humidifier for humidifying the gas flow,

[0308] · A conduit (e.g., a dry line or a heated breathing tube),

[0309] · A patient interface,

[0310] · A check valve,

[0311] · Filter

[0312] The device or system will now be described in more detail.

[0313] The gas flow source can be a wall-mounted oxygen supply source, an oxygen cylinder 50A, other gas cylinders, and / or a high-flow device with a flow generator 50B. Figure 1 A gas flow source 50 is shown having a flow generator 50B, an optional air inlet 50C, and an optional connection to an O2 source (such as a cylinder or O2 generator) 50A via a shut-off valve and / or regulator and / or other gas flow control 50D, but this is just one option. The flow generator 50B can use one or more valves to control the flow delivered to the patient 56, or alternatively, the flow generator 50B can include a blower. As described, the gas flow source can be one or a combination of the flow generator 50B, the O2 source 50A, and the air source 50C. The gas flow source 50 is shown as part of the device 10, but in the case of an external oxygen cylinder or wall-mounted source, it can be considered a separate component, in which case the device has connection ports to connect to such a gas flow source. The gas flow source provides a gas flow (preferably, a high-flow gas) that can be delivered to the patient via the delivery conduit 16 and the patient interface 51.

[0314] The patient interface 51 can be an unsealed (non-sealed) interface (e.g., when used in high-flow therapy), such as an unsealed nasal cannula, or a sealed (sealed) interface (e.g., when used in CPAP), such as a nasal mask, a full face mask, or a nasal pillow. In some embodiments, the patient interface 51 is an unsealed patient interface, which will, for example, help prevent barotrauma (e.g., tissue damage to the lungs or other organs of the respiratory system caused by a pressure differential relative to the atmosphere). In some embodiments, the patient interface 51 is a sealed mask that seals with the patient's nose and / or mouth. The patient interface can be a nasal cannula with a manifold and nasal prongs, and / or a face mask, and / or a nasal pillow mask, and / or a nasal mask, and / or a tracheostomy interface, or any other suitable type of patient interface. The gas flow source can provide a base gas flow rate in the range, for example, between 0.5 liters per minute and 375 liters per minute, or any range within this range, or even a range with higher or lower limits. Details of the range and nature of the flow rate will be described later.

[0315] The humidifier 52 may optionally be provided between the gas source 50 and the patient to humidify the delivered gas. One or more sensors 53A, 53B, 53C, 53D (e.g., flow, oxygen fraction, pressure, humidity, temperature, or other sensors) may be placed throughout the system and / or at, on, or near the patient 56. Alternatively or additionally, sensors from which such parameters are derived may be used. Additionally or alternatively, the sensors 53A-53D may be one or more physiological sensors for sensing patient physiological parameters such as heart rate, oxygen saturation, partial pressure of oxygen in the blood, respiratory rate, partial pressure of CO2 in the blood. Alternatively or additionally, sensors from which such parameters are derived may be used. Other patient sensors may include EEG sensors, torso bands for detecting respiration, and other suitable sensors. In some configurations, the humidifier may be optional, or it may be preferred due to the advantage that humidifying the gas helps to maintain airway conditions. One or more of these sensors may form part of the device, or may be external to the device, where the device has an input for any external sensors. These sensors may be coupled to the controller 19 or send their output to the controller.

[0316] In some configurations, the respiratory system 10 may include a sensor 14 for measuring the oxygen fraction of the air inhaled by the patient. In some examples, the sensor 14 may be placed on the patient interface 51 to measure or otherwise determine the oxygen fraction very close to the patient's mouth and / or nose (at / near / adjacent to the patient's mouth and / or nose). In some configurations, the output of the sensor 14 is sent to the controller 19 to assist in controlling the respiratory system 10 to change its operation accordingly. The controller 19 is coupled to the gas source 50, the humidifier 52, and the sensor 14. In some configurations, the controller 19 controls these and other aspects of the respiratory system 10 as described herein. In some examples, the controller may operate the gas source 50 to provide a delivered gas flow at a desired flow rate that is high enough to meet or exceed the user's (i.e., the patient's) inspiratory demand. The provided flow rate is sufficient such that ambient gas is not entrained during user (i.e., patient) inspiration. In some configurations, the sensor 14 may communicate the measured value of the oxygen fraction at the patient's mouth and / or nose to the user, who may input the information into the respiratory system 10 / controller 19.

[0317] An optional check valve 23 may be provided in the breathing conduit 16. One or more filters may be provided at one and / or more air inlets 50C of the flow generator 50B to filter the incoming gases before they are pressurized into the high-flow gas 31 to the flow generator 50B.

[0318] The respiratory assistance device 10 can be an integrated or a component-based arrangement, which is generally shown in the dashed box 100 in Figure 1 In some configurations, the device or system can be a modular arrangement of components. Additionally, the device or system can include only some of the components shown, and not necessarily all of them are essential. Also, the conduit and the patient interface do not have to be part of the system, but can be considered separate. Hereinafter, it will be referred to as the respiratory assistance device or the respiratory system, but this should not be considered restrictive. The respiratory assistance device and the respiratory system will be broadly considered herein to include anything that provides a certain flow rate of gas to a patient. Some such devices and systems include a detection system that can be used to determine whether the gas flow rate meets the inspiratory demand.

[0319] The respiratory device 10 can include a main device housing 100. The main device housing 100 can contain a flow generator 50B that can be in the form of a motor / impeller arrangement, an optional humidifier or humidification chamber 52, a controller 19, and an input / output I / O user interface 54. The user interface 54 can include a display and an input device, and the input device can be, for example, buttons, a touch screen (e.g., an LCD screen), and a combination of a touch screen and buttons, etc. The controller 19 can include one or more hardware and / or software processors, and can be configured or programmed to control the components of the system, including but not limited to operating the flow generator 50B to generate a gas flow for delivery to the patient, operating the humidifier or humidification chamber 52 (if present) to humidify and / or heat the gas flow, receiving user input from the user interface 54 to reconfigure the respiratory device 10 and / or perform user-defined operations, and outputting information to the user (e.g., on the display). The user can be a patient, a healthcare professional, or others.

[0320] In one configuration, the user interface 54 of the respiratory device 10 can include a removable display or touch screen.

[0321] Continuing to refer to Figure 1 , the patient breathing conduit 16 can be coupled to a gas flow outlet (gas outlet or patient outlet port) 21 in the main device housing 100 of the respiratory device 10, and coupled to a patient interface 17 (such as a non-sealed interface like a nasal cannula with a manifold and nasal prongs). The patient breathing conduit 16 can also be a tracheostomy interface or other non-sealed interface.

[0322] A gas flow can be generated by a flow generator 50B and can be humidified and then delivered to a patient via a patient interface 51 through a patient breathing conduit 16. The controller 19 can control the flow generator 50B to generate a gas flow at a desired flow rate and / or control one or more valves to control the mixing of air and oxygen or other breathable gases. The controller 19 can control a heating element in or associated with the humidification chamber 52 (if present) to heat the gas to a desired temperature, which achieves a desired level of temperature and / or humidity for delivery to the patient. The patient breathing conduit 16 can have a heating element (such as a heating wire) to heat the gas flow traveling to the patient. The heating element can also be controlled by the controller 19.

[0323] The humidifier 52 of the device is configured to combine with or introduce humidity into the gas flow. Various humidifier 52 configurations can be employed. In one configuration, the humidifier 52 can include a removable humidification chamber. For example, the humidification chamber can be partially or completely removed from the flow path and / or the device or disconnected. For example, the humidification chamber can be removed, for example, for refilling, cleaning, replacement, and / or repair. In one configuration, the humidification chamber can be received and retained by or within a humidification compartment of the device or can otherwise be coupled to the housing of the device above or within it.

[0324] The humidification chamber of the humidifier 52 can include a gas inlet and a gas outlet to enable connection to the gas flow path of the device. For example, the gas flow from the flow generator 50B is received into the humidification chamber via its gas inlet after being heated and / or humidified and exits the chamber via its gas outlet.

[0325] The humidification chamber contains a volume of liquid, typically water or the like. In operation, the liquid in the humidification chamber is controllably heated by one or more heaters or heating elements associated with the chamber to generate water vapor or steam, thereby increasing the humidity of the gas flowing through the chamber.

[0326] In one configuration, the humidifier is a pass-over humidifier. In another configuration, the humidifier can be a non-pass-over humidifier.

[0327] In one configuration, the humidifier can include a heating plate, for example, associated with or within a humidification compartment on which the humidification chamber sits for heating. The chamber can be provided with a heat transfer surface (such as a metal insert, plate, or the like in the base surface or other surface of the chamber), which docks or engages with the heating plate of the humidifier.

[0328] In another configuration, the humidification chamber may include an internal heater or heater elements inside or within the chamber. The internal heater or these heater elements may be integrally mounted or disposed inside the chamber, or may be removable from the chamber.

[0329] The humidification chamber may be of any suitable shape and / or size. The location, number, size, and / or shape of the gas inlet and gas outlet of the chamber may vary as needed. In one configuration, the humidification chamber may have a base surface, one or more sidewalls extending upward from the base surface, and an upper surface or top surface. In one configuration, the gas inlet and gas outlet may be located on the same side of the chamber. In another configuration, the gas inlet and gas outlet may be on different surfaces of the chamber, such as on opposite sides or locations, or at other different locations.

[0330] In some configurations, the gas inlet and gas outlet may have parallel flow axes. In some configurations, the gas inlet and gas outlet may be located at the same height on the chamber.

[0331] Device 10 may use ultrasonic transducers, flow sensors (such as thermistor flow sensors), pressure sensors, temperature sensors, humidity sensors, or other sensors that communicate with controller 19 to monitor the characteristics of the gas flow and / or to operate system 10 in a manner that provides appropriate treatment. Gas flow characteristics may include gas concentration, flow rate, pressure, temperature, humidity, or other characteristics. Sensors 53A, 53B, 53C, 53D, 14 (such as pressure, temperature, humidity, and / or flow sensors) may be placed at various locations in main device housing 100, patient conduit 16, and / or patient interface 51. Controller 19 may receive outputs from the sensors to assist it in operating breathing device 10 in a manner that provides appropriate treatment, in order to determine suitable target temperatures, flow rates, and / or pressures of the gas flow. Providing appropriate treatment may include meeting or exceeding the patient's inspiratory demand. In the illustrated embodiment, sensors 53A, 53B, and 53C are located in the housing of the device, sensor 53D is located in patient conduit 16, and sensor 14 is located in patient interface 51.

[0332] Device 10 may include one or more communication modules to enable data communication or connection with one or more external devices or servers via a data or communication link or data network, whether wired, wireless, or a combination thereof. In one configuration, for example, device 10 may include a wireless data transmitter and / or receiver or transceiver 15 to enable controller 19 to receive data signals from operating sensors and / or control various components of system 10 wirelessly. Transceiver 15 or the data transmitter and / or receiver module may have antenna 15a as shown. In one example, the transceiver may include a Wi-Fi modem. Additionally or alternatively, data transmitter and / or receiver 15 may deliver data to a remote patient management system (i.e., a remote server) or enable remote control of system 10. System 10 may include a wired connection (e.g., using a cable or wire) to enable controller 19 to receive data signals from operating sensors and / or control various components of device 10. Device 10 may include one or more wireless communication modules. For example, the device may include a cellular communication module, such as, for example, a 3G, 4G, or 5G module. Module 15 may be or may include a modem that enables the device to communicate with a remote patient management system (not shown in the figure) using an appropriate communication network. The remote management system may include a single server or multiple servers or multiple computing devices implemented in a cloud computing network. The communication may be two-way communication between the device and the patient management system (e.g., a server) or other remote systems. Device 10 may also include other wireless communication modules, such as, for example, a Bluetooth module and / or a Wi-Fi module. The Bluetooth and / or Wi-Fi modules allow the device to wirelessly send information to another device (such as, for example, a smartphone or tablet) or operate via a LAN (local area network) or wireless LAN (WLAN). Additionally or alternatively, the device may include a near field communication (NFC) module to allow for data transfer and / or data communication.

[0333] For example, data representing a determined or calculated work of breathing (WOB) metric or value, or other associated WOB data (e.g., WOB trend data), or notification data generated in response to the WOB data (e.g., warnings, alerts, notifications) can be communicated to a remote patient management system (i.e., a remote server) and / or another remote electronic device (e.g., a personal electronic device such as a smartphone, tablet, computer, laptop, wearable device). The remote patient management system can be a single server or a network of servers or a cloud computing system or other suitable architecture for operating the remote patient management system. The remote patient management system (i.e., the remote server) further includes a memory for storing the received data and various software applications or services that are executed to perform various functions. Then, for example, the remote patient management system (i.e., the remote server) can communicate information or instructions to system 10 at least in part depending on the received data. For example, the nature of the received data can trigger the remote server (or a software application running on the remote server) to communicate a warning, alert, or notification to system 10. The remote patient management system can further store the received data for access by an authorized party (such as a clinician or a patient or another authorized party). The remote patient management system can further be configured to generate reports (e.g., report data, displayed reports, compiled reports, electronic reports, printable reports, numerical reports, graphical reports) in response to requests from an authorized party, and the work of breathing data or associated WOB data can be included in the generated reports. These reports can further include: other data or patient respiratory parameters such as respiratory rate or SpO2; and / or device parameters such as flow rate, oxygen concentration of the gas flow (e.g., sensed oxygen concentration and / or FiO2 and / or FdO2 parameter settings), humidity level, or other such device parameters.

[0334] Respiratory device 10 can include a high-flow therapy device. High-flow therapy as discussed herein is intended to be given its typical ordinary meaning as understood by those skilled in the art, which generally refers to the delivery of a humidified breathing gas at a flow rate that is typically intended to meet or exceed the user's inspiratory flow rate through a patient interface that is intentionally unsealed to the respiratory system. Typical patient interfaces include, but are not limited to, nasal or tracheal patient interfaces. The typical flow rate range for an adult is often, but not limited to, from about fifteen liters per minute to about sixty liters per minute or greater. The typical flow rate range for pediatric users (such as neonates, infants, and children) is often, but not limited to, from about one liter per kilogram of user body weight to about three liters per kilogram of user body weight or greater.

[0335] High-flow therapy can also optionally include gas mixture components that include supplemental oxygen and / or the administration of therapeutic drugs.

[0336] High flow therapy is often referred to as nasal high flow (NHF), humidified high flow nasal cannula (HHFNC), high flow nasal oxygen therapy (HFNO), high flow therapy (HFT), or trans-tracheal high flow (THF), among other common names. For example, in some configurations, for adult patients, 'high flow therapy' can refer to delivering gas to the patient at a flow rate greater than or equal to about 10 liters per minute (10 LPM), such as between about 10 LPM and about 100 LPM, or between about 15 LPM and about 95 LPM, or between about 20 LPM and about 90 LPM, or between about 25 LPM and about 85 LPM, or between about 30 LPM and about 80 LPM, or between about 35 LPM and about 75 LPM, or between about 40 LPM and about 70 LPM, or between about 45 LPM and about 65 LPM, or between about 50 LPM and about 60 LPM. In some configurations, for neonatal, infant, or pediatric patients, 'high flow therapy' can refer to delivering gas to the patient at a flow rate greater than 1 LPM, such as between about 1 LPM and about 25 LPM, or between about 2 LPM and about 25 LPM, or between about 2 LPM and about 5 LPM, or between about 5 LPM and about 25 LPM, or between about 5 LPM and about 10 LPM, or between about 10 LPM and about 25 LPM, or between about 10 LPM and about 20 LPM, or between about 10 LPM and 15 LPM, or between about 20 LPM and 25 LPM. High flow therapy devices for adult patients, neonates, infants, or pediatric patients can deliver gas to the patient at a flow rate between about 1 LPM and about 100 LPM or at a flow rate within any of the sub-ranges outlined above.

[0337] High flow therapy can effectively meet or exceed the patient's inspiratory demand, improve the patient's oxygenation, and / or reduce the work of breathing. Additionally, high flow therapy can create a flushing effect in the nasopharynx such that the anatomical dead space of the upper airway is flushed by the incoming high gas flow. The flushing effect can create a reservoir of available fresh gas with each breath while minimizing re-breathing of carbon dioxide, nitrogen, etc. Due to the pressure during exhalation, high flow therapy can also increase the patient's expiratory time. This in turn reduces the patient's respiratory rate.

[0338] The patient interface for high flow therapy can be a non-sealed interface to prevent barotrauma, which can include tissue damage to the lungs or other organs of the patient's respiratory system caused by a pressure differential relative to the atmosphere. The patient interface can be a nasal cannula with a manifold and nasal prongs, and / or an unsealed tracheostomy interface, or any other suitable type of patient interface.

[0339] Figures 2 to 18Shows an example breathing apparatus of a breathing device 10 having a main housing 100. The main housing 100 has a main housing upper casing 102 and a main housing lower casing 202. The main housing upper casing 102 has a peripheral wall arrangement 106 (see Figure 15 ). The peripheral wall arrangement defines a humidifier or humidification chamber compartment 108 for receiving a removable humidification chamber 300. The removable humidification chamber 300 contains a suitable liquid (such as, water) for humidifying the gas that can be delivered to a patient. The bottom plate portion of the humidification chamber compartment 108 may have a recess for receiving a heater arrangement (such as, a heating plate 140 or other suitable heating element) for heating the liquid in the humidification chamber 300 for use during the humidification process.

[0340] The humidification chamber 300 may be fluidly coupled to the device 10 as follows: The humidification chamber 300 enters the chamber compartment 108 in a linear sliding movement in the backward direction from a position at the front of the housing 100 in the direction towards the rear of the housing 100. The gas outlet port 322 may be in fluid communication with the motor.

[0341] As Figure 8 shown, the gas inlet port 340 (humidified gas return) may include a removable L-shaped elbow. The removable elbow may further include a patient outlet port 344 for coupling to a patient conduit 16 to deliver gas to a patient interface. The gas outlet port 322, the gas inlet port 340, and the patient outlet port 344 may each have a soft seal (such as, an O-ring seal or a T-seal) to provide a sealed gas path between the device 10, the humidification chamber 300, and the patient conduit 16.

[0342] The humidification chamber gas inlet port 306 may be complementary to the gas outlet port 322, and the humidification chamber gas outlet port 308 may be complementary to the gas inlet port 340. The axes of those ports may be parallel to each other such that the humidification chamber 300 can be inserted into the chamber compartment 108 in a linear movement.

[0343] The breathing apparatus may have an air and oxygen (or alternative auxiliary gas) inlet in fluid communication with the motor such that the motor can deliver air, oxygen (or alternative auxiliary gas), or a mixture thereof to the humidification chamber 300 and thus to the patient. As Figure 10As shown, the device can have a combined air / oxygen (or alternative auxiliary gas) inlet arrangement 350. Such an arrangement can include a combined air / oxygen port 352 entering the housing 100, a filter 354, and a lid 356 having a hinge 358. The gas tube can also optionally extend laterally or in another suitable direction and be in fluid communication with an oxygen (or alternative auxiliary gas) source. The port 352 can be fluidly coupled to the motor 402. For example, the port 352 can be coupled to the motor / sensor module 400 via a gas flow path between the port 352 and an inlet orifice or port in the motor and sensor module 400 that in turn leads to the motor.

[0344] The device can have Figures 11 to 14 the arrangement shown such that the blower can deliver air, oxygen (or alternative auxiliary gas), or a suitable mixture thereof to the humidification chamber 300 and thus to the patient. Such an arrangement can include an air inlet 356' in the rear wall 222 of the lower housing 202 of the housing 100. The air inlet 356' includes a rigid plate having a suitable grille arrangement formed by apertures and / or slots. Sound deadening foam can be disposed adjacent to the plate on the inner side thereof. An air filter box 354' can be positioned adjacent to the air inlet 356' inside the main housing 100 and includes an air outlet port 360 to deliver filtered air to the motor via an air inlet port 404 in the motor / sensor module 400. The air filter box 354' can include a filter configured to remove particulates (e.g., dust) and / or pathogens (e.g., viruses or bacteria) from the gas flow. A soft seal (such as an O-ring seal) can be provided between the air outlet port 360 and the air inlet port 404 to effect a seal between these components. The device can include a separate oxygen inlet port 358' positioned at the rear end of the housing adjacent to one side of the housing 100 for receiving oxygen from an oxygen source (such as a tank or source of piped oxygen). The oxygen inlet port 358' is in fluid communication with a valve 362. The valve 362 can suitably be a solenoid valve that enables control of the amount of oxygen added to the gas flow delivered to the humidification chamber 300. The oxygen port 358' and the valve 362 can be used with other auxiliary gases to control the addition of other auxiliary gases to the gas flow. The other auxiliary gases can include any one or more of several gases useful for gas therapy, including but not limited to heliox and nitric oxide.

[0345] As Figures 13 to 16As shown in, the lower housing 202 of the housing may include a suitable electronic device board, such as a sensing circuit board. The electronic device board may be positioned adjacent to the respective outer sidewalls 210, 216 of the lower housing 202. The electronic device board may contain or be in electrical communication with suitable electrical or electronic device components, such as but not limited to a microprocessor, a capacitor, a resistor, a diode, an operational amplifier, a comparator, and a switch. Sensors may be used with the electronic board. Components of the electronic device board (such as but not limited to, one or more microprocessors) may act as the controller 19 of the device.

[0346] One or more of the electronic device boards may be in electrical communication with the electrical components of the device 10, including the display unit and the user interface 54, the motor, the valve 362, and the heating plate 140, to operate the motor to provide a gas at a desired flow rate, to operate the humidification chamber 300 to humidify and heat the gas flow to an appropriate level, and to supply an appropriate amount of oxygen (or an appropriate amount of an alternative auxiliary gas) to the gas flow.

[0347] The electronic device board may be in electrical communication with a connector arrangement 274 that projects from the rear wall 122 of the upper housing 102 of the housing. The connector arrangement 274 may be coupled to an alarm, a pulse oximeter port, and / or other suitable accessories. The electronic device board may also be in electrical communication with an electrical connector 276 (which may also be provided in the rear wall 122 of the upper housing 102 of the housing) to provide mains power or battery power to the components of the device.

[0348] As mentioned above, operating sensors (such as, flow, temperature, humidity, and / or pressure sensors) may be placed at various locations in the breathing device, the patient breathing conduit 16, and / or the endotracheal tube 51 (such as, Figure 1 the locations shown in). The electronic device board may be in electrical communication with those sensors. The output from the sensors may be received by the controller 19 to assist the controller 19 in operating the breathing device 10 in a manner that provides optimal treatment (such as, controlling to a set flow rate). The set flow rate may be selected such that it provides irrigation of the patient's upper airway and / or meets or exceeds the patient's inspiratory demand and / or provides other advantages of the high-flow treatment described herein. In the illustrated embodiment, the sensors are positioned on the electronic boards, which are positioned within the housing. The sensors are encapsulated within the housing.

[0349] As outlined above, the electronic device board and other electrical and electronic components may be pneumatically isolated from the gas flow path to improve safety. The seal also prevents water from entering.

[0350] 1.1 Control System

[0351] Figure 19A An example control system 920 is shown (which may beFigure 1 Block diagram 900 of the controller 19) in which the exemplary control system can detect a patient's condition and control the operation of a respiratory system including a gas source. The control system 920 can manage the flow rate of the gas flowing through the respiratory system when delivering the gas to the patient. For example, the control system 920 can increase or decrease the flow rate by controlling the output of the motor speed of the blower (also referred to hereinafter as the "blower motor") 930 or the output of the valve 932 in the blender. The control system 920 can automatically determine a setpoint or personalized value for the flow rate for a particular patient, as discussed hereinafter. The flow rate can be optimized by the control system 920 to improve patient comfort and treatment.

[0352] The control system 920 can also generate audio and / or display / visual outputs 938, 939. For example, the flow therapy device can include a display and / or an audio output device (e.g., a speaker). The display can indicate to the doctor any warnings or alarms generated by the control system 920. The display can also indicate control parameters that the doctor can adjust. For example, the control system 920 can automatically recommend a flow rate for a particular patient. The control system 920 can also determine the patient's respiratory status (including but not limited to generating the patient's respiratory rate) and send it to the display, which will be described in more detail hereinafter.

[0353] The control system 920 can change the heater control output to control one or more of the heating elements (e.g., to maintain a temperature setpoint of the gas delivered to the patient). The control system 920 can also change the operation or duty cycle of the heating element. The heater control output can include a heated plate control output 934 and a heated breathing tube control output 936.

[0354] The control system 920 can determine the outputs 930 - 939 based on one or more received inputs 901 - 916. The inputs 901 - 916 can correspond to sensor measurements automatically received by the controller 600 (shown in Figure 19B . The control system 920 can receive sensor inputs including but not limited to the input 901 of a temperature sensor, the input 902 of a flow rate sensor, the motor speed input 903, the input 904 of a pressure sensor, the input 905 of a fractional sensor of a gas, the input 906 of a humidity sensor, the input 907 of a pulse oximeter (e.g., SpO2) sensor, stored or user parameters 908, the duty cycle or pulse width modulation (PWM) input 909, the input 910 of a voltage, the input 911 of a current, the input 912 of an acoustic sensor, the input 913 of a power, the input 914 of a resistance, the input 915 of a CO2 sensor, and / or the input 916 of a spirometer. The control system 920 can retrieve from the memory 624 (in Figure 19Breceives input from a user or stored parameter values (shown in

[0355] 1.2 Controller

[0356] Figure 19B shows a block diagram of an embodiment of a controller 600 (which may be the Figure 1 controller 19 in ). The controller 600 may include programming instructions for detecting input conditions and controlling output conditions. The programming instructions may be stored in the memory 624 of the controller 600. The programming instructions may correspond to the methods, procedures, and functions described herein. The programming instructions may be executed by one or more hardware processors 622 of the controller 600. The programming instructions may be implemented in C, C++, JAVA, or any other suitable programming language. Some or all parts of the programming instructions may be implemented in a dedicated circuit system 628 (such as an ASIC and an FPGA).

[0357] The controller 600 may further include a circuit 628 for receiving sensor signals. The controller 600 may further include a display 630 for transmitting the status of the patient and the respiratory assistance system. The display 630 may also show warnings and / or other alerts. The display 630 may be configured to display the characteristics of the sensed gas(es) in real time or otherwise. The controller 600 may also receive user input via a user interface (such as the display 630). The user interface may include buttons and / or dials. The user interface may include a touch screen.

[0358] 1.3 Motor and Sensor Module

[0359] Any feature of the respiratory system described herein (including but not limited to the humidification chamber, the flow generator, the user interface, the controller, and the patient breathing conduit configured to couple the gas outlet of the respiratory system to the patient interface) may be combined with any sensor module described herein.

[0360] Figure 20 shows a block diagram of a motor and sensor module 2000 (or'sensing block'), which may be received by a recess 250 in a breathing device (shown in Figure 17 and Figure 18 ). The motor and sensor module may include a blower 2001 that entrains room air for delivery to the patient. The blower 2001 may be a centrifugal blower.

[0361] One or more sensors (e.g., Hall effect sensors) can be used to measure the motor speed of the blower motor. The blower motor can include a brushless DC motor from which the motor speed can be measured without using a separate sensor. For example, during operation of the brushless DC motor, the back EMF can be measured from the unpowered windings of the motor, from which the motor position can be determined, which in turn can be used to calculate the motor speed. Additionally, a motor driver can be used to measure the motor current, which can be used with the measured motor speed to calculate the motor torque. The blower motor can include a low inertia motor.

[0362] Indoor air can enter the indoor air inlet 2002, which enters the blower 2001 through the inlet port 2003. The inlet port 2003 can include a valve 2004 through which pressurized gas can enter the blower 2001. The valve 2004 can control the oxygen flow into the blower 2001. The valve 2004 can be any type of valve, including a proportional valve or a two-way valve. In some embodiments, the inlet port does not include a valve.

[0363] The blower 2001 can operate at a motor speed greater than 1,000 RPM and less than 30,000 RPM, greater than 2,000 RPM and less than 21,000 RPM, or between any of the foregoing values. The operation of the blower 2001 mixes the gas entering the blower 2001 through the inlet port 2003. Using the blower 2001 as a mixer can reduce the pressure drop that would otherwise occur in a system with a separate mixer (e.g., a static mixer including baffles) because mixing requires energy.

[0364] The mixed air can leave the blower 2001 through the conduit 2005 and enter the flow path 2006 in the sensor chamber 2007. A sensing circuit board with sensors 2008 can be positioned in the sensor chamber 2007 such that the sensing circuit board is at least partially immersed in the gas flow. At least some of the sensors 2008 on the sensing circuit board can be positioned within the gas flow to measure the gas properties within the flow. After passing through the flow path 2006 in the sensor chamber 2007, the gas can leave 2009 and reach the humidification chamber.

[0365] Positioning the sensor 2008 downstream of the combined blower and mixer 2001 can improve the accuracy of measurements (e.g., measurements of gas fraction concentrations, including oxygen concentration), thus outperforming systems that position the sensor upstream of the blower and / or mixer. Such positioning can give a repeatable flow profile. Further, positioning the sensor downstream of the combined blower and mixer avoids the pressure drop that would otherwise occur, because in the case where sensing occurs before the blower, a separate mixer (e.g., a static mixer with baffles) is required between the inlet and the sensing system. The mixer introduces a pressure drop across the mixer. Positioning the sensing element after the blower can allow the blower to act as a mixer, while a static mixer would reduce pressure, whereas the blower increases pressure. Also, immersing at least a portion of the sensing circuit board and the sensor 2008 in the flow path can improve the accuracy of measurements, because immersing the sensors in the flow means they are more likely to experience the same conditions (e.g., temperature and pressure) while the gas is flowing and thus provide a better representation of the characteristics of the gas flow.

[0366] Reference Figure 21 , the gas leaving the blower can enter the flow path 402 in the sensor chamber 400, which can be positioned within the motor and sensor module and can be Figure 20 the sensor chamber 2007. The flow path 402 can have a curved shape. The flow path 402 can be configured to have a curved shape without sharp turns. The flow path 402 can have curved ends with a more straight section therebetween. The curved flow path shape can reduce the pressure drop in the gas flow without reducing the sensitivity of the flow rate measurement by partially aligning the measurement region with the flow path to form a measurement portion of the flow path.

[0367] A sensing circuit board 404 having sensors (e.g., acoustic transmitters and / or receivers, humidity sensors, temperature sensors, thermistors, etc.) can be positioned in the sensor chamber 400 such that the sensing circuit board 404 is at least partially immersed in the flow path 402. Immersing at least a portion of the sensing circuit board and the sensors in the flow path can improve the accuracy of measurements, because sensors immersed in the flow are more likely to experience the same conditions (e.g., temperature and pressure) while the gas is flowing and thus provide a better representation of the characteristics of the gas flow. After passing through the flow path 402 in the sensor chamber 400, the gas can leave and reach the humidification chamber.

[0368] At least two different types of sensors can be used to measure gas flow rate. The first type of sensor can include a thermistor, so that the flow rate can be determined by monitoring the heat transfer between the gas flow and the thermistor. When the gas flows around the thermistor and passes by the thermistor, the thermistor flow sensor can operate the thermistor at a constant target temperature within the flow. The sensor can measure the amount of electricity required to maintain the thermistor at the target temperature. The target temperature can be configured to be higher than the temperature of the gas flow, such that at higher flow rates, more power is required to maintain the thermistor at the target temperature.

[0369] The thermistor flow sensor can also maintain multiple (e.g., two, three, or more) constant temperatures on the thermistor to avoid the difference between the target temperature and the gas flow temperature being too small or too large. The multiple different target temperatures can allow the thermistor flow sensor to be accurate across a large temperature range of the gas. For example, the thermistor circuit can be configured to be able to switch between two different target temperatures such that the temperature of the gas flow will always fall within a certain range (e.g., not too close but not too far) relative to one of the two target temperatures. The thermistor circuit can be configured to operate at a first target temperature of about 50°C to about 70°C or about 66°C. The first target temperature can be associated with a desired flow temperature range between about 0°C to about 60°C or between about 0°C and about 40°C. The thermistor circuit can be configured to operate at a second target temperature of about 90°C to about 110°C or about 100°C. The second target temperature can be associated with a desired flow temperature range between about 20°C to about 100°C or between about 30°C and about 70°C.

[0370] The controller can be configured to adjust the thermistor circuit to change between at least a first target temperature mode and a second target temperature mode by connecting or bypassing a resistor within the thermistor circuit. The thermistor circuit can be arranged in a Wheatstone bridge configuration including a first voltage divider arm and a second voltage divider arm. The thermistor can be located on one of the voltage divider arms. More details of the thermistor flow sensor are described in PCT Application Publication No. WO 2018 / 052320, filed on September 3, 2017, which is incorporated herein by reference in its entirety.

[0371] The second type of sensor may include an acoustic sensor assembly. Acoustic sensors, including acoustic transmitters and / or receivers, can be used to measure the time of flight of an acoustic signal to determine gas velocity and / or composition, and these acoustic sensors can be used in a flow therapy device. In one ultrasonic sensing (including ultrasonic transmitter and / or receiver) topology, a driver causes a first sensor (e.g., an ultrasonic transducer) to generate an ultrasonic pulse in a first direction. A second sensor (e.g., a second ultrasonic transducer) receives this pulse and provides a measurement of the time of flight of the pulse between the first ultrasonic transducer and the second ultrasonic transducer. Using this time of flight measurement, the speed of sound of the gas flow between the ultrasonic transducers can be calculated by a processor or controller of the respiratory system. The second sensor can emit a pulse in a second direction opposite to the first direction and the first sensor can receive this pulse to provide a second measurement of the time of flight, thereby allowing determination of characteristics of the gas flow (e.g., flow rate or flow velocity). In another acoustic sensing topology, an acoustic pulse emitted by an acoustic transmitter (e.g., an ultrasonic transducer) can be received by an acoustic receiver (e.g., a microphone). More details of the acoustic flow sensor are described in PCT application publication number WO 2017 / 095241, filed on December 2, 2016, which application publication is incorporated herein by reference in its entirety.

[0372] The one or more flow sensors or the sensor assembly including one or more flow sensors can be located at various positions in and / or along the gas flow path in the breathing device. In one configuration, the one or more flow sensors or the sensing assembly can be located or arranged behind the flow generator 50B, i.e., the sensor is configured or arranged to sense or measure the flow velocity of the gas in the flow path behind the flow generator 50B. In this configuration, the flow velocity signal or flow velocity data generated by the one or more flow sensors can represent the flow velocity signal or data output by the flow generator, i.e., the flow velocity of the gas flow output from the flow generator 50B.

[0373] In one example configuration, one or more flow rate sensors or sensor assemblies may be located within the main device housing 100, in front of or behind the humidifier 52 (if present). For example, a flow rate sensor may be arranged or configured within the main device housing 100 to sense the flow rate of gas in the flow path at a location between the flow generator 50B and the humidifier 52 or at a location in the flow path behind the humidifier. In another example configuration, one or more flow rate sensors or sensor assemblies may be located within and / or along the breathing conduit 16 and / or the patient interface 51. In this configuration, the sensor or sensor assembly is configured to sense or measure the flow rate of the gas flow in the flow path including and / or formed by the breathing conduit 16 and / or the patient interface (i.e., the flow path following the gas outlet 21 of the main device housing 100). In another example configuration, the device may include any combination of the one or more flow rate sensors or sensor assemblies mentioned in terms of their configuration or location. For example, the device may include any combination of one or more flow rate sensors or sensor assemblies at any one or more locations along the gas flow path, whether within the main device housing 100 or within the breathing conduit 16 and / or the patient interface 51).

[0374] In some configurations, readings from both a first type of sensor and a second type of sensor may be combined to determine a more accurate flow rate measurement. For example, a previously determined flow rate and one or more outputs from a sensor of one of these types may be used to determine a predicted current flow rate. Then, one or more outputs from a sensor of the other of the first type and the second type may be used to update the predicted current flow rate in order to calculate a final flow rate.

[0375] 2. Exemplary embodiment of a work of breathing determination process

[0376] The methods and processes for determining data indicative of or representing the work of breathing will be described in the context of the example breathing device 10 described above, which is configured or operable to provide nasal high flow therapy via an unsealed patient interface. As previously explained, these methods and processes may also be applied to other breathing devices and / or other operating modes and / or treatment modes delivered by such devices.

[0377] 2.1 Overview of the work of breathing (WOB) determination process

[0378] Work of breathing (WOB) is a clinical metric that provides a valuable indicator of the efficacy of respiratory therapy. Determining an estimate or metric of WOB can be used to improve patient outcomes when using a respiratory device. For example, in some configurations, a WOB metric can be used to evaluate whether current respiratory device and / or therapy settings need to be adjusted, which parameters to adjust, and / or how much to adjust those settings.

[0379] As those skilled in the art will appreciate, WOB has a generally accepted definition that relates to the energy or work required or exerted for a person to breathe. One way to determine true WOB is to use a chest strap that measures the force and depth of chest movement during a person's breathing, but these are not always convenient or practical for some patients. In some scenarios, respiratory rate can be used as an indicator of WOB. This disclosure provides methods and processes for determining one or more alternative analogs, surrogates, or metrics of a patient's WOB when the patient is undergoing high-flow therapy delivered by a respiratory device. Alternative WOB metrics can be used to enhance clinical decision-making, patient outcomes, and / or the operation of respiratory devices to deliver improved high-flow therapy.

[0380] The embodiments described below are intended to provide a method for reliably estimating a patient WOB metric using sensor data obtainable from a respiratory device and / or algorithms implemented thereon.

[0381] This disclosure relates to methods and / or algorithms for determining one or more patient or user WOB metrics or estimates based at least in part on sensed flow parameter data indicative of or representative of the gas flow in a respiratory device during patient or user use. By way of example, methods for determining three different user WOB metrics or estimates will be described below. Each of these three example methods involves an estimate of ΔP 鼻 which represents the nasal pressure change value that indicates the average nasal pressure of a user when the user is undergoing respiratory therapy with a respiratory device.

[0382] In the example methods, the various WOB metrics are determined or calculated based at least in part on flow parameter data indicative of or representative of the gas flow in the flow path of the respiratory device.

[0383] In an example configuration, the flow parameter data includes flow rate data indicative of or representative of the flow rate of the gas flow provided by the breathing device during a respiratory therapy. In one example, the flow rate data can be a flow signal generated by one or more flow sensors disposed or positioned in the flow path of the breathing device. The one or more flow sensors can be disposed in the flow path downstream of the flow generator of the breathing device. When a patient uses the breathing device during a respiratory therapy, fluctuations around the typical human breathing frequency will be observed in the flow rate signal. The flow rate signal can be very noisy, and in the example configuration, algorithms and / or signal preprocessing can be applied to the raw flow signal generated by the flow sensors to minimize the effect of the noise. By analyzing the fluctuations in the preprocessed flow rate signal, various useful WOB parameters or metrics associated with the patient can be extracted while the patient is undergoing respiratory therapy with the breathing device.

[0384] In some example configurations, the flow parameter data used to generate the WOB metric can additionally or alternatively include pressure data indicative of or representative of the gas flow provided by the flow generator (e.g., the pressure at the blower outlet in the breathing device).

[0385] As will be seen, in these example configurations, there are some common steps for determining all three example WOB metrics, which will be outlined below.

[0386] The method and / or algorithm for generating the WOB metric can be executed or implemented on any suitable controller or processor. In an example configuration, the method and / or algorithm for generating the WOB metric can be executed or implemented on the main controller or primary controller of the breathing device. As explained above, the main controller of the breathing device communicates electrically or data-wise with the flow sensors and / or pressure sensors located in the main housing of the breathing device, the breathing conduit, and / or the patient interface. In some example configurations, pressure sensing lines can feed pressure samples from the patient interface to one or more pressure sensors located in the main housing of the breathing device.

[0387] 2.2 First example WOB metric - ΔP 鼻 Estimate

[0388] Now, a first example WOB metric method or algorithm for generating the first example WOB metric will be described. The first example WOB metric is based on determining or calculating the nasal pressure change value, i.e., ΔP 鼻 Estimate, as will be explained below.

[0389] Generally, the flow rate (Q 管 ) through the breathing conduit can be determined by applying known hydrodynamic relationships. The result is the following equation:

[0390]

[0391] Wherein:

[0392] C 管 is the conductance of the breathing tube - a measure of how easily / unimpeded gas can flow through the tube,

[0393] Q 管 is the gas flow rate through the breathing tube,

[0394] P 鼓风机 is the pressure at the output of the blower of the breathing device,

[0395] P 鼻 is the pressure at or within the patient's nostrils ('nasal pressure').

[0396] In this example configuration, without accessing direct nasal pressure measurements, some approximations and trial values can be used to find the tube conductance value C 管 . In other configurations, the tube conductance can be derived or determined based on sensor data representing direct nasal pressure measurements.

[0397] In the context of NHF therapy delivered by a breathing device, it has typically been found that:

[0398] P 鼓风机 ≥10P 鼻 (2)

[0399] This expression allows determination of an approximation of the tube conductance C according to the following equation 管 :

[0400]

[0401] Where P 鼻,猜测 is a preliminary trial value of P 鼻 . In this example, P 鼻,猜测 can be an initial estimate or guess of the nasal pressure. In one example, the initial estimate or guess can be at least partially based on a preliminary estimate of the measured blower pressure and / or flow rate and / or flow conductance. In one example, the initial estimate or guess can be a guess in the mathematical sense, i.e., not a completely arbitrary choice of value, but an educated choice of a suitable initial value that may be relatively close to the true value. In an example configuration, the P 鼻,猜测 value can be derived or determined from one or more stored functions, previous relationships, equations, models, or look-up tables based on one or more input parameters (such as but not limited to, a preliminary estimate of the blower pressure, flow rate, and / or flow conductance). In one example, based on previous knowledge of the expected or estimated pressure drop between the blower and the patient interface (e.g., nasal cannula), P 鼻,猜测The value can depend on the blower output pressure P 鼓风机 and, in some configurations, for example, most of the pressure drop is caused by the breathing conduit.

[0402] In such an example configuration, P 鼓风机 can be measured or sensed by one or more pressure sensors or pressure sensing configurations in the breathing device. In one example, P 鼓风机 the pressure data can be based on or depend on pressure data generated by one or more pressure sensors located at or near the outlet of the blower of the breathing device or in the flow path downstream of the blower in the main housing of the breathing device.

[0403] In one example configuration, the pressure sensor can be a gauge pressure sensor that includes a port to the ambient environment and is configured to sense and generate pressure data representative of the difference between the pressure at or near the blower outlet and the pressure in the ambient environment. In such a configuration, P 鼓风机 the pressure data can include, be represented by, or depend on the sensed gauge pressure data generated by the gauge pressure sensor.

[0404] In another example configuration, the pressure sensor can be an absolute pressure sensor that is configured to sense and generate pressure data representative of the absolute pressure at or near the blower outlet in the flow path. In such a configuration, P 鼓风机 the pressure data can include, be represented by, or depend on the sensed absolute pressure data generated by the absolute pressure sensor.

[0405] In another example configuration, the device can include: an absolute pressure sensor configured to sense the absolute pressure at or near the blower outlet; and an ambient pressure sensor configured to sense the ambient pressure of the environment. In such a configuration, P 鼓风机 the pressure data can include pressure data representative of the difference between the absolute pressure data from the absolute pressure sensor and the ambient pressure data from the ambient pressure sensor.

[0406] In such an example configuration, Q 管 can be based on the flow rate at the outlet of the blower of the breathing device (as sensed by a flow sensor of the device). This assumes no faults or unexpected behavior, such as, for example, a tube leak due to an improper connection between the gas outlet of the main housing of the breathing device and the tube inlet. For example, assuming no significant leak along the flow path from the blower to the patient interface connected to the end of a breathing conduit (e.g., a tube), the flow rate Q 管 should be very close to the flow rate at the blower outlet.

[0407] As explained above, the tube flow rate Q 管 can be based on the flow rate signal or data from a flow rate sensor in the flow path downstream of the blower in the main housing of the breathing device. In such an example configuration, Q 管 values are based on the preprocessed flow rate signal. For example, the raw flow rate signal or data from the flow rate sensor can be processed to remove and / or minimize the effects of noise in the signal. Examples of the preprocessing of the raw flow rate signal will be explained later in Section 2.5.

[0408] In one example configuration, the selection or calculation of P 鼻,猜测 (the preliminary trial value of P 鼻 ) can be pre-programmed and / or based on known relationships between the gas flow parameters. In one example, the controller can be pre-programmed with a look-up table or other suitable data structure or function that contains a series of approximate corresponding values of the blower pressure P 鼓风机 , the blower flow rate (equivalent to Q 管 as described above), and the P 鼻 values, such that the trial P 鼻 value (P 鼻,猜测 ) can be selected using or based on the measures or sensor data representing the blower output pressure and flow rate. In one example configuration, the look-up table, function, or data structure representing the relationship for selecting the trial P 鼻 value can be stored in a memory (such as but not limited to, the non-volatile memory of the device) associated with or accessible to the controller of the breathing device.

[0409] Once the nasal pressure trial P 鼻,猜测 value is selected or picked, the respiratory conduit conductance C 管 can be estimated according to the equation for C 管 provided above.

[0410] The C 管 equation can be rearranged into an equation to estimate the nasal pressure P 鼻 :

[0411] Q 管 2 = C 管 2 (P 鼓风机 - P 鼻 ) (4)

[0412]

[0413] As shown above, in this example, the estimated value of the nasal pressure P 鼻 depends on the blower output pressure P 鼓风机 , the tube flow rate Q管 and the tube conductance C 管 and is determined or calculated based thereon.

[0414] In this example, the absolute value of the nasal pressure P 鼻 may be unreliable under some conditions due to multiple noise sources in the flow and pressure measurements that can be largely but not fully accounted for by the preprocessing steps (e.g., blower motor noise, patient breathing, electronic noise, etc.). In view of this, in such a configuration, the WOB metric algorithm may rely on a variable or parameter derived from the absolute value of the estimate of the nasal pressure P 鼻 to generate or represent the WOB metric rather than relying on the absolute value itself.

[0415] In such an example configuration, the WOB metric may be based on the magnitude of the fluctuations (i.e., ‘delta’) in the nasal pressure estimate, which is represented as ΔP 鼻 . This value of the change in nasal pressure ΔP 鼻 is related to the patient's respiratory effort and can be observed as the WOB metric because it depends only weakly on the noise sources mentioned.

[0416] In such an example configuration, the WOB metric algorithm may be configured to use the following equation to determine the magnitude of the fluctuations in nasal pressure (ΔP 鼻 ) at a certain point in time:

[0417]

[0418] Mathematically, this equation is essentially the derivative of the equation for P 鼻 shown above. The variable MV 装置 term represents or indicates the minute ventilation of the device (MV 装置 ). In this example, MV 装置 estimates the average volume of air / gas mixture output by the respiratory device per minute. Although MV 装置 is related to the gas flow output of the respiratory device, it is very closely related to the patient's respiration because the patient's inspiratory and expiratory volumes are encoded in the MV 装置 signal. Examples of methods for determining the MV 装置 signal or data that indicates or represents MV 装置 are further described below under section 2.6.

[0419] Because C 管 and Q 管 are approximately constant, the changes in MV 鼻 are reflected in the ΔP 装置 value. MV 装置The variation occurs due to a change in the patient's breathing effort (i.e., how much energy is expended when the patient breathes). In this example configuration, an increase in ΔP 鼻 indicates an increase in WOB, and conversely, a decrease in ΔP 鼻 indicates a decrease in WOB.

[0420] The nasal pressure change signal or value ΔP 鼻 can be calculated periodically or on an arbitrary or specific basis. In one example configuration, the nasal pressure change signal or value ΔP 鼻 can be calculated periodically at any suitable frequency by a WOB metric algorithm. In one example, the ΔP 鼻 value is calculated as a WOB metric at a frequency selected from the range of approximately 1 Hz to approximately 20 Hz (i.e., between approximately every 1 second and approximately every 5 ms). It will be appreciated that any suitable frequency can be selected depending on the application of the WOB metric and / or the characteristics of the incoming data stream used by the WOB metric algorithm to calculate ΔP 鼻 WOB metric.

[0421] Any one or more of the following aspects related to ΔP 鼻 WOB metric can be applied in an example configuration of the WOB metric algorithm:

[0422] · In some configurations, compared to other disclosed WOB metrics, the ΔP 鼻 WOB metric can be beneficial due to fewer potential sources of error. For example, in one configuration, the ΔP 鼻 WOB metric only requires or only depends on flow rate and pressure sensor data or signals from a breathing device.

[0423] · The tube conductivity C 管 is approximately constant, but in some example configurations, a filter can be used to update at the same rate as ΔP 鼻 This is because, in some scenarios or applications, the tube conductivity may change if / when the position of the breathing conduit (e.g., the tube) changes during delivery of a breathing treatment to a patient using a breathing device. For example, if the tube becomes more bent or coiled, the conductivity will decrease (since the impedance increases in these cases), or vice versa if the tube straightens during use.

[0424] · In some example configurations, the flow rate Q of the gas through the breathing conduit 管 ideally should be approximately constant to achieve the generated ΔP 鼻Maximum accuracy / reliability of the WOB metric. This is typically the case over a period of 1 minute or longer. Nevertheless, in some configurations, the WOB metric algorithm can be configured to take into account variations / changes in gas flow rate. For example, in some configurations, the WOB metric algorithm can be configured to take into account variations in gas flow rate by the following steps: discarding spurious readings associated with transient flow rate variations and / or applying an averaging filter (e.g., an exponential filter) to smooth the data.

[0425] · In some example configurations, ΔP 鼻 The value of the WOB metric can depend on the size and fit of the patient interface used by the patient (e.g., the size and fit of a nasal cannula or other patient interface used by the patient). Additionally or alternatively, ΔP 鼻 The value of the WOB metric can depend on the physiological characteristics of the patient, such as but not limited to their respiratory effort.

[0426] 2.3 Second example WOB metric - ΔP 鼻 *Q 呼吸 Estimated value

[0427] A second example WOB metric method or algorithm for generating the second example WOB metric will now be described. The second example WOB metric is based on the nasal pressure change value ΔP 鼻 of the first example WOB metric, and a variable representative of or indicative of changes in respiratory volume or the user's respiratory flow rate, or depending on both. In this example, the change in respiratory volume or the user's respiratory flow rate is represented by Q 呼吸 as shown.

[0428] In one example configuration, the second WOB metric algorithm can be a variant of the first WOB metric algorithm. For example, the second WOB metric algorithm can include additional steps or calculations in addition to calculating the ΔP 鼻 WOB metric, as will be further explained below.

[0429] In a volume change system, the work done can be expressed as:

[0430] Work = Pressure * Volume (7)

[0431] In this second example, if the nasal pressure change value ΔP 鼻 is substituted for pressure, then the actual work value of WOB can be estimated by substituting a measure or value of the volume change for the volume term. In this example, the result of these substitutions provides an estimated value of the actual work value of WOB, rather than a metric of WOB. For example, the estimated value of the actual work provides a value in joules.

[0432] In this second example WOB metric algorithm, a measure or value representing the change in respiratory volume or the user's respiratory flow rate is represented as Q 呼吸 . In this example, the user's respiratory flow rate Q can be roughly estimated via the following equation 呼吸 :

[0433]

[0434] where all terms have the same physical meaning as previously described. C 鼻 represents the conductance of the patient's nostrils (nostrils / nares) and can depend at least on the size of the patient's nostrils as well as the nasal cannula size and fit. Although C can be easily and roughly estimated 管 (as previously discussed), in this example configuration, the parameters on which C depends may require the implementation of a calibration or learning process to obtain an accurate estimate 鼻 .

[0435] In this example configuration, the user's respiratory flow rate Q 呼吸 can physically be similar to the patient's nasal minute volume, which is represented by MV 鼻 . The nasal minute volume MV 鼻 is a measure for estimating the minute volume of the patient's nasal cavity and is explained in detail in PCT patent application publication WO 2022 / 167960, filed on February 3, 2022, which is incorporated herein by reference in its entirety. However, unlike the MV 鼻 metric, the user's respiratory flow rate Q 呼吸 can better account for the flow conductance components in a high-flow therapy system (e.g., a respiratory device configured to deliver NHF therapy) and can thus be a more general metric of the average amount of air entering / leaving the patient's nasal cavity per minute. In this example configuration, MV 鼻 can be similar to MV 装置 , apart from being transformed by a certain factor, which incorporates information and / or depends on the patient interface (e.g., size, type, etc.) and the fit of the patient interface (e.g., the degree of blockage of the nostrils in the context of a nasal cannula).

[0436] In this example configuration, the user's respiratory flow rate Q 呼吸 equation or function is derived by applying the flow-pressure equation to a suitable patient nostril model: Conductance * Pressure = Flow 2 . Alternatively, Pressure = Resistance * Flow 2. In one example, the patient nostril model is at least partially based on three key flows, namely: the flow entering the nostril via the nasopharynx due to the patient's breathing and the flow exiting the nostril, and the leakage flow exiting / around the nasal cannula. This results in three simultaneous equations (9)-(11), which can be rearranged and solved for the patient's respiratory flow. In this example, the resulting expression for Q 呼吸 can then be integrated (e.g., to find its average value). Thus, the above equations (for determining the average value of Q 呼吸 ) are obtained.

[0437] For example, these three simultaneous equations can be:

[0438] C 管 *(P 装置 -P 鼻 ) = Q 管 2 (9)

[0439] C 鼻 *P 鼻 = Q 鼻 2 (10)

[0440] Q 呼吸 +Q 管 = Q 鼻 (11)

[0441] The above three simultaneous equations (9)-(11) are some examples of possible equations that can be used and solved for the patient's respiratory flow. In alternative configurations, if more accurate modeling is desired or required for a particular application or situation, one or more different and / or more complex equations including more parameters can be used.

[0442] In one example configuration, the calibration process for obtaining an estimate or value of C 鼻 may require inserting a suitable nasal cannula into the patient's nostril, followed by the respiratory device testing a series of predetermined flow rates while measuring or estimating the nasal pressure at each discrete flow rate. Additionally or alternatively, in another example configuration, the calibration process can be non-discrete, involving providing a flow rate sweep while continuously measuring or estimating the nasal pressure.

[0443] In another alternative example configuration, using manual input from a user or clinician, the value of C 鼻 can be estimated at least partially based on one or more patient physiological factors or characteristics. For example, it can be estimated based on parameters or estimates related to patient size (e.g., their body length) and / or cannula-nostril blockage (e.g., the estimated percentage blockage of the cannula prong in the nostril), and / or one or more other suitable parameters.鼻 value

[0444] By further explanation, regarding patient size, it can be expected that longer (larger) patients have larger nostrils (e.g., adult patients compared to pediatric or even infant patients). The size (e.g., the cross-sectional area of the entrance of the nostril) will contribute to C 鼻 . Ignoring whether the nasal cannula fits optimally, larger patients will generally wear larger cannulas than smaller patients (e.g., pediatric), and the larger cannulas will have a Y-piece with a wider bore that provides less flow resistance.

[0445] By further explanation, regarding cannula-nostril blockage (or 'nostril blockage'), a higher percentage of blockage means a tighter fit between the inside of the nostril and the wall of the Y-piece of the cannula, and conversely, a lower percentage of blockage means there is more space between the Y-piece of the cannula and the inside of the nostril. Depending on the degree of blockage, the amount / rate of the exhaled gas flow through the Y-piece or the Y-piece-nostril 'gap' will vary and thus affect the conductance.

[0446] In this example, the C 鼻 estimate can be based on relationships determined from previous experience testing.

[0447] This second example WOB metric algorithm generates a WOB metric representing an estimate of ΔP 鼻 *Q 呼吸 which can be regarded as the actual estimate of WOB as described above. In this example configuration, this ΔP 鼻 *Q 呼吸 WOB metric may involve more calculation steps than the first example ΔP 鼻 WOB metric. In this example, the additional calculation steps may mainly result from the need to estimate or derive the conductance C 鼻 of the patient's nostrils. This second example ΔP 鼻 *Q 呼吸 WOB metric can provide an actual estimate of WOB that clinicians may be more familiar with. In this example, the accuracy and reliability of the second example ΔP 鼻 *Q 呼吸 WOB metric can depend at least in part on the accuracy of the C 鼻 value. In some configurations, the accuracy of the C 鼻 value can depend at least in part on or be determined by additional input or parameters about the patient provided by the clinician as described above.

[0448] 2.4 Third example WOB metric - ΔP 鼻 * Breathing smoothness estimate

[0449] Now, a third example WOB metric method or algorithm for generating a third example WOB metric will be described. The third example WOB metric is based on the nasal pressure change value ΔP of the first example WOB metric 鼻 and a variable representing or indicating a breathing smoothness factor, or depending on both of these. In this example, the breathing smoothness factor is represented by σ.

[0450] In one example configuration, the third WOB metric algorithm can be a variant of the first WOB metric algorithm. For example, the third WOB metric algorithm can include additional steps or calculations in addition to calculating ΔP 鼻 WOB metric, as will be further explained below.

[0451] In this third example, the WOB metric algorithm is configured to apply the breathing smoothness factor σ to the ΔP 鼻 estimate, thereby generating the ΔP 鼻 *σ WOB metric. In this example, breathing smoothness is a mathematical concept based on the number of possible continuous derivatives of a quantization function over a domain. In the case of ΔP 鼻 data, breathing smoothness physically involves the rate of change of nasal pressure fluctuations.

[0452] This breathing smoothness measure σ is useful because it can indicate the patient's breathing rate (or be strongly correlated with it). For example, a higher breathing rate will be evident as a steeper rate of change in the nasal pressure fluctuation signal or data, which will be measured by the breathing smoothness value σ (i.e., a value representing decreased breathing smoothness), and vice versa (i.e., an increased breathing smoothness value can represent a lower breathing rate).

[0453] In one example configuration, the third WOB metric algorithm can determine or calculate the breathing smoothness factor σ at least partially based on an estimate or value of the patient's minute ventilation (e.g., the device minute ventilation). For example, the WOB metric algorithm can be configured to estimate the device minute ventilation according to any one of the methods outlined in section 2.6 below or any other suitable method. In this example, the calculated device minute ventilation estimate can then be normalized. For example, the device minute ventilation can be normalized according to or based on the number of available data points and then passed to a function that outputs a frequency-independent breathing smoothness measure or factor σ. In this example, the function can be pre-determined by a mixture of analytical and numerical analysis.

[0454] Then, the third WOB metric algorithm is configured to apply the calculated breathing smoothness factor σ to the ΔP 鼻 WOB metric (e.g., of the first example WOB metric) to generate the third example WOB metric ΔP 鼻*σ. In this example, compared to the first example ΔP 鼻 WOB metric, ΔP 鼻 *σ WOB metric can be more mathematically dependent on the respiratory rate. In this configuration, the third example WOB metric can be more similar to the confirmed pressure-time product metric, which is another known WOB metric.

[0455] 2.5 Preprocessing of the flow rate signal

[0456] As explained above, the example WOB metric methods or algorithms and their respective output WOB metrics are at least partially based on flow parameter data. In an example, the flow parameter data can at least include flow rate data from one or more flow rate sensors, which represents or indicates the flow rate of gas in the flow path. As further explained, typically, the WOB metric algorithm receives and utilizes the preprocessed flow rate signal or data, i.e., the raw flow rate data or signal from the flow sensor is preprocessed to remove or minimize the effect of noise in the signal. In an alternative configuration, it will be appreciated that the WOB metric algorithm can receive the raw flow rate signal or data and perform preprocessing steps or stages as part of the WOB metric algorithm.

[0457] Examples of some forms of preprocessing that can be applied to the raw flow rate signal or data will now be described below, which is then further processed and / or used as an input to generate a WOB metric.

[0458] As discussed above, it may be difficult to determine flow data (e.g., flow rate data) in an unsealed system (such as a nasal high flow system). The open nature of the system results in a very low signal-to-noise ratio. For example, an unsealed interface (nasal cannula) tends to generate a large amount of leakage flow and swirling flow around the patient's nostrils, which contributes to a substantial amount of noise in the sensed flow rate signal (e.g., raw flow rate data). Any measured flow data may include various irregularities and noises that obscure the flow data and must be addressed to accurately determine the desired measurement. The flow data is important because it can inform about the unsealed system, the patient's respiratory flow, and / or other device or patient metrics and / or parameters.

[0459] In this example, to remove noise and other irregularities from any acquired flow data, the flow signal can be fed through a preprocessing step or stage. The preprocessing can allow the controller to remove certain distortions from the flow parameters such that the flow parameter signal used to determine the device output and / or patient respiratory parameters (e.g., the WOB metric) can better reflect the impact of the gas flow parameters used in the patient's treatment on the patient's respiration. More details of the preprocessing of the flow signal are described in PCT application publication WO / 2020 / 178746, filed Mar. 4, 2020, which is incorporated herein by reference in its entirety.

[0460] If a patient is attached to a respiratory system and breathing through a patient interface, the fluctuations in the preprocessed flow rate or other flow parameter data obtained in an open system (i.e., an unsealed system that delivers a gas flow to the patient via an unsealed interface such as a nasal cannula) consist of randomly uncorrelated noise and correlated respiratory signals generated from various sources. In particular, the fluctuations in the flow parameter data can include noise (random and uncorrelated with the patient's respiration) and the patient respiratory signal (which is correlated with the patient's respiration). The preprocessing of the data can begin with the controller receiving the flow parameter data (e.g., unprocessed or raw data). The controller can then perform a preprocessing step, such as by determining whether the flow parameter data is good or suitable for use. If the data is not suitable for use, the controller can discard the data.

[0461] When determining the suitability of the data, the controller can receive second flow parameter data of a different type than the first flow parameter data. The second flow parameter data is assumed to have some correlation with the first parameter. The second flow parameter data can include, for example, motor speed, pressure, and / or oxygen flow rate or concentration or any other parameter that may affect the gas flow rate or provide an indication of the gas flow rate, the effect being separate from the effect of the patient's respiration on the gas flow rate. The controller can be configured to determine whether the second flow parameter data can be used as a correlation parameter with the first flow parameter data. For example, if the second flow parameter data meets a threshold level, the second flow parameter data can be a useful correlation metric. If the second flow parameter data does not meet the threshold level, it is assumed that the second flow parameter data is not correlated with the first flow parameter data. Thus, the second flow parameter data can be ignored or discarded (i.e., deleted or not utilized by the controller). If there is insufficient second flow parameter data, the controller can determine that it does not have enough data to use the first flow parameter data and can discard the first parameter data. If the second flow parameter data meets a minimum threshold level, the controller can determine that the first parameter data is suitable for use.

[0462] As an example, the second flow parameter data can represent the motor speed. In order to identify the patient's respiration in the first flow parameter data, the motor needs to operate at a sufficient speed. If the motor speed is too low, it may not be possible to accurately predict the effect or correlation of the motor speed on the flow data (e.g., flow rate). Therefore, after the controller has received the motor speed data, the controller can compare the motor speed with a minimum motor speed threshold. If the motor speed is below the threshold, the controller can consider the first flow parameter data inappropriate and can discard some or all of the first flow parameter data. However, if the motor speed is above the threshold, the controller can calculate the most recent change in the motor speed. A change in the motor speed may cause a change in the first flow parameter data, which makes it more difficult to identify the patient's respiration in the first flow parameter data. Although the effect of the motor speed can be removed from the first flow parameter data to some extent, a large change in the motor speed may make the data too unreliable for identifying the patient's respiration. Therefore, the controller can apply a running filter to the relative change in the motor speed in order to generate a first value representing the most recent relative change in the motor speed. The controller can then compare the first value with a first threshold. If the first value is above the first threshold, the controller can consider the flow parameter data inappropriate and can discard the flow data points. If the first value is below the first threshold, the controller can consider the flow parameter data suitable for use.

[0463] As another example, the second flow parameter data can represent the concentration of supplemental gas from a supplemental gas source. The first flow parameter data (e.g., flow rate) may be affected by the flow rate or concentration of the supplemental gas from the supplemental gas source. The controller can receive oxygen flow rate data or oxygen concentration data. The controller can calculate the most recent change in the oxygen flow rate or oxygen concentration. If the flow rate or concentration of oxygen changes, the resulting change in the total flow rate may make it more difficult to identify the patient's respiration in the flow rate signal or other flow parameter signals. Therefore, the controller can apply a running filter to the change in the oxygen concentration or oxygen flow rate of the gas in order to generate a second value representing the most recent change in the oxygen concentration or flow rate. The controller can compare the second value with a second threshold. If the second value is above the second threshold, the controller can determine that the first flow parameter data is inappropriate and can discard the first flow parameter data points. However, if the second flow parameter data is below the threshold, the controller can consider the flow parameter data to be suitable.

[0464] As described above, if the controller determines that the data is appropriate, the first flow parameter data (or any other flow parameter data) can also be modified to remove the effect of the motor (or other factors such as oxygen concentration or flow rate). Modifying the first flow parameter data can involve removing the assumed effect of other variables from the first flow parameter data (e.g., motor speed). This assumed effect is only valid if the gas flow parameter data meets certain criteria. As described above, if these criteria are not met, the data can be discarded.

[0465] The process can modify the first flow parameter data to remove the effect of the motor speed. The effect of the motor can be estimated using the motor speed and the flow conductance. The controller can measure the instantaneous flow conductance. The flow conductance can be calculated as provided below:

[0466]

[0467] In the equation provided above, C is the flow conductance, filt() is the filtering function, Q is the flow parameter data, and ω 马达 is the motor speed. In some configurations, the filtering function is a low-pass filter. In some examples, the flow parameter data is a flow rate signal generated by a flow rate sensor of a breathing device. The flow conductance is approximately constant over time and can therefore be estimated using a low-pass filter. The controller measures the instantaneous flow conductance at each iteration using the current motor speed and the measured flow rate. The controller can filter the instantaneous flow conductance to determine the filtered flow conductance.

[0468] The controller can compare the instantaneous flow conductance with the filtered flow conductance to see if the difference is significantly different. If the difference is significant, something may have changed the physical system, such as an endotracheal tube being attached or detached. The instantaneous flow conductance can be compared with the filtered flow conductance by taking the difference between the two variables and comparing it to a minimum or maximum threshold. If the difference exceeds or falls below the threshold, the difference is considered significant and the controller can reset the filtered flow conductance. The controller can also change the filter coefficient of the filtering function in the filtered flow conductance calculation based on the difference between the instantaneous flow conductance and the filtered flow conductance. This allows the filtered flow conductance to change more quickly when the variance of the flow conductance is high (e.g., when the endotracheal tube is first attached).

[0469] If the difference between the instantaneous flow conductance and the filtered flow conductance does not exceed the threshold, the difference is considered insignificant and the controller can estimate the effect of the motor on the flow rate. The controller can use the filtered flow conductance and the motor speed to output the value of this effect. This value can be subtracted from or otherwise removed from the flow rate data to obtain preprocessed flow rate data. The preprocessed flow rate data can more accurately indicate the patient's respiratory flow (although the preprocessed flow rate data may still include signal noise).

[0470] The controller can also track recent changes in the conductance. Changes can be tracked by adding the difference between the last two instantaneous conductance values to a running total, which then decays over time. The decaying running total is filtered to obtain a filtered recent change in the conductance capacity. The filtered recent change in the conductance capacity can be used, along with the preprocessed flow rate data, in a further part of the frequency analysis algorithm.

[0471] 2.6 Determine the device minute volume MV 装置

[0472] As explained above, some of the example WOB metric algorithms and their respective WOB metrics are at least partially based on the device minute volume MV of the breathing device 装置 or are dependent on the device minute volume.

[0473] Reference Figures 22A - 23 is made, and examples of various methods for determining or calculating an estimated value of the device minute volume MV 装置 will be described below. It will be appreciated, however, that alternative methods can be used. In some configurations, the WOB metric algorithm can implement such methods for determining an estimated value or data of the device minute volume. In other configurations, the estimated value or data of the device minute volume can be calculated separately in the controller and then fed to the WOB metric algorithm executed on the controller.

[0474] While it is relatively easy to measure inhalation and exhalation in a sealed system, it is much more difficult to measure respiratory parameters in an unsealed system. In an unsealed system (such as, for example, a nasal high-flow system), the open nature of the system (due to the use of an unsealed patient interface) makes it significantly more difficult to determine patient respiratory parameters because the desired signals are often weak and / or masked by noise.

[0475] The present disclosure provides reliable methods for estimating key patient respiratory parameters (such as, for example, the WOB metric) in an unsealed system (e.g., an unsealed nasal cannula used in a high-flow system).

[0476] The controller can include a process configured to calculate an estimated value of the device minute volume (MV 装置 ). The device minute volume (MV 装置 ) represents the device minute volume, which is a measure of the average volume of air that is pushed in and out of the breathing device (i.e., the device) per minute. In some configurations, the device minute volume (MV 装置 ) can be a discrete value or a series of discrete values (e.g., a succession of previous estimated values). In some examples, the series of discrete values can be obtained from the device minute volume (MV 装置starting from the first estimate of (), and continuing until the end of the respiratory device usage (treatment) period. Alternatively, a series of discrete values of the device minute ventilation (MV 装置 ) estimate can represent a specific time window and be continuously rewritten when estimating a new value. For example, a series of discrete values of the device minute ventilation (MV 装置 ) estimate can represent their values over a recent period of time. In some configurations, the period of time can be 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes, 60 minutes, 65 minutes, 70 minutes, between 15 and 20 minutes, between 20 and 25 minutes, between 25 and 30 minutes, between 30 and 35 minutes, between 35 and 40 minutes, between 40 and 45 minutes, between 45 and 50 minutes, between 50 and 55 minutes, between 55 and 60 minutes, between 60 and 65 minutes, between 65 and 70 minutes, between 15 and 30 minutes, between 30 and 45 minutes, between 45 and 60 minutes, and any value (including the endpoints) between the listed ranges.

[0477] Figure 22A , Figure 22B , Figure 22C and Figure 22D show four flowcharts of methods for estimating the device minute ventilation (MV 装置 ). Figure 22A shows a simplified method 1000 for estimating the device minute ventilation (MV 装置 ) of 1000. Figure 22B , Figure 22C and Figure 22D show examples of more detailed methods 1100, 1200, 1300 for estimating the device minute ventilation (MV 装置 ).

[0478] As Figure 22A shown, the method 1000 for estimating the device minute ventilation (MV 装置 ) starts by obtaining raw flow rate data at step 1002. The raw flow rate data can be obtained from a flow rate sensor (such as an ultrasonic flow sensor). Estimating the device minute ventilation (MV 装置) The method may include: at step 1004, preprocessing the raw flow rate data to remove unwanted signal components. The removal of unwanted signal components has been described in more detail above. There may be unwanted signal components from the flow generator motor. In some configurations, the unwanted signal components may be generated from other sources (e.g., noise), and the unwanted signal components may mainly come from the flow generator motor. For example, the preprocessed flow data may be a flow rate signal including components associated with the patient's respiratory activity. For example, the components associated with the patient's respiratory activity may be included in the flow rate signal as a magnitude of the flow rate change (e.g., as fluctuations). Once preprocessed, the flow data can represent the patient respiratory data. Method 1000 may include step 1006, at which, assuming the data has sufficient quality, the preprocessed data can be passed to the device minute volume algorithm to calculate the device minute volume (MV 装置 ).

[0479] Reference Figure 22B , a more detailed flowchart of method 1100 for estimating the device minute volume (MV 装置 ) will be described. Like method 1000, method 1100 begins by obtaining raw flow rate data at step 1102. The raw flow rate data can be obtained from a flow rate sensor (such as an ultrasonic flow sensor). Method 1100 may include: at step 1104, preprocessing the raw flow rate data to remove unwanted signal components. The removal of unwanted signal components has been described in more detail above. There may be unwanted signal components from the flow generator motor. Once preprocessed, the flow data can represent the patient respiratory data. Then, the processed flow rate data can be analyzed at step 1106 to determine whether the data quality is good enough. If not, the flow data is discarded, and method 1100 returns to step 1102 and waits to receive the raw flow data.

[0480] However, if the data is determined to have sufficient quality, the data can proceed to step 1112, in which method 1100 uses the processed data to calculate the device minute volume (MV 装置 ). If the data does not include large transient peaks (possibly due to interface adjustment), the data can be considered to have sufficient quality. The device minute volume (MV 装置 ) measures the average volume of air pushed in and out of the device per minute. As shown in step 1112, the formula for calculating the device minute volume (MV 装置) The process can be accomplished by first fitting a spline to the flow data using a least squares criterion. The flow data can be, for example, the most recent pre-filtered flow velocity data points. In some configurations, the least squares criterion first approximates the pre-processed flow data (e.g., the respiratory signal) and then integrates along the spline to estimate the ventilation volume.

[0481] Method 1100 can include step 1116, in which a spline is used to calculate the instantaneous estimate of the device minute ventilation (MV 装置 ) In some examples, the use of a spline may be more useful than alternative methods (e.g., a series of filters configured to generate statistical measures of the data) because it can perform better (i.e., fit / interpolate the data more accurately) over a wider range of sampling frequencies. This is described in more detail below. Method 1100 can include three different methods for calculating the instantaneous estimate of the device minute ventilation (MV 装置 ) The estimate of the device minute ventilation (MV 装置 ) represents the integral of the absolute value of the first term of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., a zero-order spline). The estimate of the device minute ventilation (MV 装置 ) is represented by: the integral of the absolute value of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., a first-order spline). To calculate the instantaneous estimate of the device minute ventilation (MV 装置 ), the estimate can be obtained within 1 second, or 20 estimates can be obtained within 1 second (i.e., a sampling frequency of 20 Hz). The time period used to calculate the estimate can be any one of the following ranges: between at least 1 and 120 seconds, between 1 and 60 seconds, between 60 and 120 seconds, between 1 and 10 seconds, between 10 and 20 seconds, between 20 and 30 seconds, between 30 and 40 seconds, between 40 and 50 seconds, between 50 and 60 seconds, between 60 and 70 seconds, between 70 and 80 seconds, between 80 and 90 seconds, between 90 and 100 seconds, between 100 and 110 seconds, between 110 and 120 seconds, or can be at least one of the following: 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 60 seconds, 70 seconds, 80 seconds, 90 seconds, 100 seconds, 110 seconds, and 120 seconds.

[0482] The device minute ventilation (MV 装置) The estimated value represents the average of the absolute values of the curve fitted to the gas flow parameter data (i.e., calculated without using splines for data interpolation). Any of the aforementioned estimated values can be used as an input in method 1100, although each estimated value has advantages and disadvantages depending on the random errors in the sensor data and the patient's respiratory rate. Method 1100 can use the estimated value of the device minute ventilation (MV 装置 ) which represents the integral of the absolute value of the first term of the line fitted to the signal. This estimated value may be the most resilient to random errors and least affected by them, while being most affected by the respiratory rate.

[0483] Reference Figure 22C , a more detailed flowchart of method 1200 for estimating the device minute ventilation (MV 装置 ) will be described. Like method 1000 and method 1100, method 1200 begins by obtaining raw flow rate data at step 1202. The raw flow rate data can be obtained from a flow rate sensor (such as an ultrasonic flow sensor). In some configurations, at step 1204, the raw flow rate data is first analyzed to determine if the data quality is good enough. If the raw flow rate data is determined to have sufficient quality, the data can be preprocessed to remove unwanted signal components. If the raw flow rate data quality is insufficient, the flow rate data is discarded and method 1200 returns to step 1202 and waits to receive additional raw flow data. In some examples, method 1200 can include: at step 1206, preprocessing the raw flow rate data to remove unwanted signal components. The removal of unwanted signal components was described in more detail above. There may be unwanted signal components from the flow generator motor. Once preprocessed, the flow data can represent patient respiratory data. In some configurations, once the flow data has been preprocessed, the data can proceed to step 1212 where method 1200 fits a curve to the flow data. If the data does not include large transient peaks (possibly due to interface adjustment), the data can be considered to have sufficient quality. The device minute ventilation (MV 装置 ) measures the average volume of air pushed in and out of the device per minute. The process for fitting a curve to the flow data can be done by first fitting a spline to the flow data using the least squares criterion. In some configurations, the fitted line can be (approximately) represented by the following formula:

[0484]

[0485] In the equations provided above, m is a fitting parameter corresponding to the mean value of the flow data, s is the slope (i.e., the gradient), and t* is the linear range of the normalized time parameter. In some configurations, t* is the linear range of the normalized time parameter, where the "earliest" time point in the flow data equals -1 and the "most recent" time point in the flow data equals 1.

[0486] In some configurations, other function approximation methods may also be used. The flow data can be, for example, the most recent pre-filtered flow velocity data points. In some examples, the least squares method can be used to approximate the pre-processed flow data (e.g., the respiratory signal) and then integrate along the spline to estimate the ventilation volume. In some configurations, the controller can perform a variety of line and / or curve fitting techniques to fit the one or more functions to a selected portion of the flow parameter variation data. This can include, for example, regression analysis, interpolation, extrapolation, linear least squares, non-linear least squares, total least squares, simple linear regression, robust simple linear regression, polynomial regression, orthogonal regression, Deming regression, linear piecewise regression, regression dilution, and / or other non-limiting example techniques. In some configurations, the one or more functions (which at least include those described above) can generate a curve. In some configurations, the curve can be a line. The lines or curves described herein can include multiple curves, vertices, and / or other features. The lines described herein can be straight, angled, and / or horizontal. In some examples, the lines described herein can be the best fit lines.

[0487] Method 1200 may include step 1214, in which an instantaneous estimate of the minute ventilation (MV 装置 ) of the device is calculated using data from a curve constructed by fitting a spline. Method 1200 may include three different methods for calculating an instantaneous estimate of the minute ventilation (MV 装置 ) of the device. The estimate of the minute ventilation (MV 装置 ) of the device is represented by: the integral of the absolute value of the first term of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., the zero-order spline). The estimate of the minute ventilation (MV 装置 ) of the device is represented by: the integral of the absolute value of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., the first-order spline). To calculate the minute ventilation (MV 装置) The instantaneous estimated value can be obtained within 1 second, or 20 estimated values can be obtained within 1 second (i.e., the sampling frequency is 20 Hz). The time period used to calculate the estimated value can be any one of the following ranges: between at least 1 and 120 seconds, between 1 and 60 seconds, between 60 and 120 seconds, between 1 and 10 seconds, between 10 and 20 seconds, between 20 and 30 seconds, between 30 and 40 seconds, between 40 and 50 seconds, between 50 and 60 seconds, between 60 and 70 seconds, between 70 and 80 seconds, between 80 and 90 seconds, between 90 and 100 seconds, between 100 and 110 seconds, between 110 and 120 seconds, or can be at least one of the following: 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 60 seconds, 70 seconds, 80 seconds, 90 seconds, 100 seconds, 110 seconds, and 120 seconds.

[0488] The estimated value of the minute ventilation (MV) of the device 装置 ) represents the average value of the absolute value of the curve fitted to the gas flow parameter data (i.e., calculated without using splines for data interpolation). Any of the foregoing estimated values can be used as an input in method 1200, but each estimated value has advantages and disadvantages, depending on the random errors in the sensor data and the patient's respiratory rate. Method 1200 can use the estimated value of the minute ventilation (MV) of the device 装置 ) which represents the integral of the absolute value of the first term of the line fitted to the signal. This estimated value may be the most resilient to random errors and least affected by random errors, while also being most affected by the respiratory rate. In some embodiments, method 1200 can skip step 1212, and the preprocessed flow data can proceed directly to step 1214, in which method 1200 can directly calculate the average value of the selected preprocessed flow velocity data points.

[0489] In one example configuration, method 1200 can also be configured to apply a filter at step 1216 to average the instantaneous minute ventilation (MV) of the device 装置 ) In some configurations, a filter (e.g., an exponential filter) can be used to average or "smooth" each estimated value or sequence of estimated values captured by multiple repetitions of the previously described steps. In some examples, this step can occur after the initial estimate but before any additional processing steps.

[0490] In some configurations, the minute ventilation (MV) of the device 装置) The estimated value is determined by obtaining an estimated value, which involves obtaining the integral of the absolute value of the first term of a line fitted to the flow rate signal (e.g., a zero-order spline). In some examples, all three methods discussed above are used to estimate the minute ventilation (MV 装置 ) for each of the data points. As previously mentioned, these three methods include: (1) where the estimated value of the minute ventilation (MV 装置 ) is represented by: the integral of the absolute value of the first term of a line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow rate data points (i.e., a zero-order spline); (2) where the estimated value of the minute ventilation (MV 装置 ) is represented by: the integral of the absolute value of a line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow rate data points (i.e., a first-order spline); and (3) where the estimated value of the minute ventilation (MV 装置 ) is represented by the average of the absolute values of a curve fitted to the gas flow parameter data (i.e., calculated without using a spline for data interpolation).

[0491] Reference Figure 22D , another flowchart of a method 1300 for estimating the minute ventilation (MV 装置 ) 1300 will be described. In this method 1300, all three methods discussed above are used to estimate the minute ventilation (MV 装置)。Similar to methods 1000, 1100, and 1200, method 1300 begins by obtaining raw flow rate data at step 1302. The raw flow rate data can be obtained from a flow rate sensor (such as an ultrasonic flow sensor). In some configurations, at step 1304, the raw flow rate data is first analyzed to determine whether the data quality is good enough. If the raw flow data is determined to have sufficient quality, the data can be preprocessed to remove unwanted signal components. If the raw flow data quality is insufficient, the flow data is deprecated, and method 1300 returns to step 1302 and waits to receive additional raw flow rate data. In some examples, method 1300 can include: at step 1306, preprocessing the raw flow data to remove unwanted signal components. The removal of unwanted signal components is described in more detail above. There may be unwanted signal components from the flow generator motor. Once preprocessed, the flow rate data can represent patient breathing data. In some configurations, once the flow rate data has been preprocessed, the data can proceed to step 1312, where method 1300 fits a curve to the flow rate data. If the data does not include large transient peaks (possibly due to interface adjustment), the data can be considered to have sufficient quality. The minute volume (MV) of the device 装置 ) measures the average volume of air pushed in and out of the device per minute. The process for fitting a curve to the flow data can be done by first fitting a spline to the flow data using the least squares criterion. In some configurations, the fitted line can be (approximately) represented by the following equation:

[0492]

[0493] In the equation provided above, m is a fitting parameter corresponding to the average value of the flow data, s is the slope (i.e., gradient), and t* is the linear range of the normalized time parameter. In some configurations, t* is the linear range of the normalized time parameter, where the "earliest" time point in the flow data is equal to -1 and the "latest" time point in the flow data is equal to 1.

[0494] In some configurations, other function approximation methods may also be used. The flow data can be, for example, the most recent pre-filtered flow velocity data points. In some examples, the least squares method can be used to approximate the pre-processed flow data (e.g., respiratory signal) and then integrate along the spline to estimate the ventilation volume. In some configurations, the controller can perform a variety of line and / or curve fitting techniques to fit the one or more functions to a selected portion of the flow parameter variation data. This can include, for example, regression analysis, interpolation, extrapolation, linear least squares, non-linear least squares, total least squares, simple linear regression, robust simple linear regression, polynomial regression, orthogonal regression, Deming regression, linear piecewise regression, regression dilution, and / or other non-limiting example techniques. In some configurations, the one or more functions (which at least include those functions above) can generate a curve. In some configurations, the curve can be a line. The lines or curves described herein can include multiple curves, vertices, and / or other features. The lines described herein can be straight, angled, and / or horizontal. In some examples, the lines described herein can be best fit lines.

[0495] Method 1300 may include step 1314, in which an instantaneous estimate of the minute ventilation (MV 装置 ) of the device is calculated using data from a curve constructed by fitting a spline. Method 1300 may include three different methods for calculating an instantaneous estimate of the minute ventilation (MV 装置 ) of the device. In some configurations, one of the three estimates is an estimate of the minute ventilation (MV 装置 ) of the device represented by: the integral of the absolute value of the first term of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., zero-order spline). In some examples, another of the three estimates is an estimate of the minute ventilation (MV 装置 ) of the device represented by: the integral of the absolute value of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., first-order spline). To calculate the minute ventilation (MV 装置)'s instantaneous estimate value, this estimate value can be obtained within 1 second, or 20 estimate values can be obtained within 1 second (i.e., the sampling frequency is 20 Hz). The time period used to calculate the estimate value can be any one of the following ranges: between at least 1 and 120 seconds, between 1 and 60 seconds, between 60 and 120 seconds, between 1 and 10 seconds, between 10 and 20 seconds, between 20 and 30 seconds, between 30 and 40 seconds, between 40 and 50 seconds, between 50 and 60 seconds, between 60 and 70 seconds, between 70 and 80 seconds, between 80 and 90 seconds, between 90 and 100 seconds, between 100 and 110 seconds, between 110 and 120 seconds, or can be at least one of the following: 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 60 seconds, 70 seconds, 80 seconds, 90 seconds, 100 seconds, 110 seconds, and 120 seconds. In some configurations, another of the three estimate values is the minute ventilation (MV 装置 )'s estimate value: the average value of the absolute value of the curve fitted to the gas flow parameter data (i.e., calculated without using splines for data interpolation). In some configurations, the first MV 装置 estimate value (i.e., zero-order spline) is the most resilient to noise / least dependent on noise, and is most affected by the patient's breathing rate. In some examples, the second MV 装置 estimate value (i.e., first-order spline) is significantly dependent on noise, but less dependent on the breathing rate. In some configurations, the third MV 装置 estimate value (i.e., where there are no splines / interpolations, and the estimate value is a direct average of a series of instantaneous absolute values) is significantly affected by noise and independent of the breathing rate. It should be further noted that all three estimate values vary with the flow rate, which means they will vary according to the blower flow rate output.

[0496] In some configurations, method 1300 can skip step 1312, and the preprocessed flow data can go directly to step 1314, in which method 1300 can directly calculate the average value of the selected preprocessed flow velocity data points.

[0497] Once method 1300 obtains the three estimate values of the minute ventilation (MV 装置 ) at step 1314, a filter can be applied to the minute ventilation (MV 装置 ) at step 1316 to obtain the instantaneous minute ventilation (MV 装置)Calculate the average value. In some configurations, a filter (e.g., an exponential filter) can be used to average or "smooth" each estimate or sequence of estimates captured through multiple repetitions of the previously described steps. In some examples, this step can occur after the initial estimate but before any additional processing steps.

[0498] In method 1300, there are three measurements (i.e., the first MV 装置 estimate, the second MV 装置 estimate, and the third MV 装置 estimate) and three unknown values or signal components, which can form and / or contribute to the estimated minute ventilation signal of the device. These unknown values and signal components can include, for example, noise, respiratory rate (e.g., the speed of flow changes induced by the patient), and the potential minute ventilation signal of the device. Thus, there is a set of three analytical expressions or equations that can be solved simultaneously to derive the expressions for noise, respiratory rate, and minute ventilation of the device. In some configurations, solving these three analytical expressions or equations simultaneously can be computationally very expensive and thus require high processing hardware requirements in embedded device applications, such as in medical devices. In some configurations, in method 1300, the algorithm of method 1300 first proceeds to step 1318 to normalize the three MV 装置 estimates according to the number of data points used in each estimate. In some examples, method 1300 can include step 1320, in which a noise correction factor can be calculated, where the noise correction factor is related to the signal-to-noise ratio. The calculation of the noise correction factor in step 1320 can be similar to any noise correction factor disclosed in PCT application publication WO / 2020 / 178746 filed on March 4, 2020, which is incorporated herein by reference in its entirety. In some configurations, a noise correction factor related to one or more of the normalized MV 装置 estimates can be calculated.

[0499] In some configurations, method 1300 can include step 1322, in which the algorithm can use a predefined fitting curve that relates the normalized minute ventilation estimate and the noise correction factor to one of the minute ventilation (MV 装置 ) estimates. In some configurations, the fitting function can at least partially include some numerically derived terms. In some configurations, this correction curve can approximate the output of the analytical expression of the minute ventilation (MV 装置 ). This can provide a minute ventilation (MV 装置 ) with minimal noise and respiratory rate dependence.

[0500] In some configurations of method 1300, a filter (e.g., an exponential filter) can be used to average or "smooth" each minute ventilation (MV 装置 ) estimate or sequence of estimates captured through multiple repetitions of the previously described steps. In some examples, this step can occur after the initial estimate but before any additional processing steps.

[0501] Reference Figure 23 , a flowchart of method 1400 for estimating a normalized minute ventilation of a device will be described. Different from the method shown in Figures 22B - 22D , the breathing device obtains a corrected minute ventilation of the device and normalizes it using the breathing device flow rate. In some configurations, this can present an estimate of the minute ventilation of the device that is independent of flow rate and independent of the device flow rate. In some examples, the estimated minute ventilation of the device is also independent of nasal cannula fit and can provide a general metric of the patient's minute ventilation.

[0502] Method 1400 begins by obtaining raw flow rate data at step 1402. The raw flow rate data can be obtained from a flow rate sensor (such as an ultrasonic flow sensor). In some configurations, at step 1404, the raw flow rate data is first analyzed to determine if the data quality is good enough. If the raw flow rate data is determined to have sufficient quality, the data can be preprocessed to remove unwanted signal components. If the raw flow rate data quality is insufficient, the flow rate data is discarded and method 1400 returns to step 1402 and waits to receive additional raw flow rate data. In some examples, method 1400 can include: at step 1406, preprocessing the raw flow rate data to remove unwanted signal components. The removal of unwanted signal components is described in more detail above. There may be unwanted signal components from the flow generator motor.

[0503] In some configurations, once the flow data has been preprocessed, the data can proceed to step 1408, in which method 1400 fits a curve to the flow data. If the data does not include large transient peaks (possibly due to interface adjustment), the data can be considered to have sufficient quality. Minute ventilation (MV 装置 ) measures the average volume of air pushed in and out of the device per minute. The process for fitting a curve to the flow data can be done by first fitting a spline to the flow data using the least squares criterion. In some configurations, the fitted line can be (approximately) represented by the following formula:

[0504]

[0505] In the equations provided above, m is a fitting parameter corresponding to the average value of the flow data, s is the slope (i.e., the gradient), and t* is the linear range of the normalized time parameter. In some configurations, t* is the linear range of the normalized time parameter, where the "earliest" time point in the flow data equals -1 and the "latest" time point in the flow data equals 1.

[0506] In some configurations, other function approximation methods can also be used. The flow data can be, for example, the most recent pre-filtered flow velocity data points. In some examples, the least squares method can be used to approximate the pre-processed flow data (e.g., a respiratory signal) and then integrate along the spline to estimate the ventilation volume. In some configurations, the controller can perform a variety of line and / or curve fitting techniques to fit the one or more functions to a selected portion of the flow parameter variation data. This can include, for example, regression analysis, interpolation, extrapolation, linear least squares, non-linear least squares, total least squares, simple linear regression, robust simple linear regression, polynomial regression, orthogonal regression, Deming regression, linear piecewise regression, regression dilution, and / or other non-limiting example techniques. In some configurations, the one or more functions (which at least include those functions described above) can generate a curve. In some configurations, the curve can be a line. The lines or curves described herein can include multiple curves, vertices, and / or other features. The lines described herein can be straight, angled, and / or horizontal. In some examples, the lines described herein can be the best fit lines.

[0507] Method 1400 can include step 1410, in which an instantaneous estimate of the minute ventilation (MV 装置 ) of the device is calculated using data of a curve constructed by fitting a spline. Method 1400 can include three different methods for calculating an instantaneous estimate of the minute ventilation (MV 装置 ) of the device. In some configurations, one of the three estimates is the estimate of the minute ventilation (MV 装置 ) of the device represented by: the integral of the absolute value of the first term of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., a zero-order spline). In some examples, another of the three estimates is the estimate of the minute ventilation (MV 装置 ) of the device represented by: the integral of the absolute value of the line fitted to the gas flow parameter data divided by the time range covered by the selected filtered flow velocity data points (i.e., a first-order spline). To calculate the minute ventilation (MV 装置)'s instantaneous estimate value, and this estimate value can be obtained within 1 second, or 20 estimate values can be obtained within 1 second (i.e., the sampling frequency is 20 Hz). The time period used to calculate the estimate value can be any one of the following ranges: between at least 1 and 120 seconds, between 1 and 60 seconds, between 60 and 120 seconds, between 1 and 10 seconds, between 10 and 20 seconds, between 20 and 30 seconds, between 30 and 40 seconds, between 40 and 50 seconds, between 50 and 60 seconds, between 60 and 70 seconds, between 70 and 80 seconds, between 80 and 90 seconds, between 90 and 100 seconds, between 100 and 110 seconds, between 110 and 120 seconds, or can be at least one of the following: 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 60 seconds, 70 seconds, 80 seconds, 90 seconds, 100 seconds, 110 seconds, and 120 seconds. In some configurations, another one of the three estimate values is the minute ventilation (MV 装置 )'s estimate value: the average value of the absolute value of the curve fitted to the gas flow parameter data (i.e., calculated without using splines for data interpolation). In some configurations, the first MV 装置 estimate value (i.e., zero-order spline) is the most resilient to noise / has the least dependence on noise, and is most affected by the patient's breathing rate. In some examples, the second MV 装置 estimate value (i.e., first-order spline) significantly depends on noise, but less on the breathing rate. In some configurations, the third MV 装置 estimate value (i.e., where there is no spline / interpolation, and the estimate value is the direct averaging of a series of instantaneous absolute values) is significantly affected by noise and independent of the breathing rate. It should be further noted that all three estimate values vary with the flow rate, which means they will vary according to the blower flow rate output.

[0508] In some configurations, method 1400 can skip step 1408, and the preprocessed flow data can directly proceed to step 1410, in which method 1400 can directly calculate the average value of the selected preprocessed flow rate data points.

[0509] Once method 1400 obtains the three estimate values of the minute ventilation (MV 装置 ) at step 1410, a filter can be applied to the minute ventilation (MV 装置 ) at step 1412 to obtain the instantaneous minute ventilation (MV 装置)Calculate the average value. In some configurations, a filter (e.g., an exponential filter) can be used to average or "smooth" each estimate or sequence of estimates captured through multiple repetitions of the previously described steps. In some examples, this step can occur after the initial estimate but before any additional processing steps.

[0510] In method 1400, there are three measurements (i.e., the first MV 装置 estimate, the second MV 装置 estimate, and the third MV 装置 estimate), and three unknown values or signal components, which can form and / or contribute to the estimated minute ventilation signal of the device. These unknown values and signal components can include, for example, noise, respiratory rate (e.g., the speed of flow changes induced by the patient), and the potential minute ventilation signal of the device. Thus, there is a set of three analytical expressions or equations that can be solved simultaneously to derive expressions for noise, respiratory rate, and minute ventilation of the device. In some configurations, solving these three analytical expressions or equations simultaneously can be computationally very expensive and thus require high processing hardware in embedded device applications, such as in medical devices. In some configurations, in method 1400, the algorithm of method 1400 first proceeds to step 1414 to normalize the three MV 装置 estimates according to the number of data points used in each estimate. In some examples, method 1400 can include step 1416, in which a noise correction factor can be calculated, where the noise correction factor is related to the signal-to-noise ratio. The calculation of the noise correction factor in step 1416 can be similar to any noise correction factor disclosed in PCT application publication WO / 2020 / 178746 filed on March 4, 2020, which is incorporated herein by reference in its entirety. In some configurations, a noise correction factor related to one or more of the normalized MV 装置 estimates can be calculated.

[0511] In some configurations, method 1400 can include step 1418, in which the algorithm can use a predefined fitting curve that relates the normalized minute ventilation estimate and the noise correction factor to one of the minute ventilation (MV 装置 ) estimates of the device. In some configurations, the fitting function can at least partially include some numerically derived terms. In some configurations, this correction curve can approximate the output of the analytical expression of the corrected minute ventilation (MV 装置 ) of the device. This can provide a corrected minute ventilation (MV 装置 ) with minimal noise and respiratory rate dependence.

[0512] In some configurations, method 1400 may include step 1420, in which the corrected device minute volume (MV 装置 ) is normalized using the device flow rate. In some examples, the same data previously used in a previous step (i.e., good quality, pre-processed flow rate data) is used to arrive at the corrected device minute volume (MV 装置 ) and provide an estimate of the device minute volume that is flow rate independent and independent of the device flow rate. As previously mentioned, the corrected device minute volume (MV 装置 ) can be independent of nasal cannula fit and provides a general metric of patient minute volume.

[0513] 2.7 WOB metric - depending on or relative to the measure of a healthy person

[0514] In some configurations, any of the WOB metrics or measures described above can be converted to a measure or metric depending on the measure of a nominally healthy person, or presented or expressed as a measure or metric relative to the measure of such a healthy person. In such configurations, the controller of the breathing device or other processing device implementing or executing the WOB metric algorithm can take additional steps to convert, transform, or otherwise represent the WOB metric or measure depending on or relative to the measure of a healthy person based on stored (e.g., stored in the device's memory) or otherwise accessible comparison data regarding healthy persons.

[0515] In one configuration, any of the example WOB metrics can be presented or expressed as a ratio or percentage expected from an 'average healthy person'. For example, the WOB metric data can be transformed, converted, or presented so that the patient's breathing performance is represented as a ratio of an ideal healthy value. In some configurations, this representation of the disclosed WOB metrics can have the advantage of being familiar to clinicians, which can make them more intuitive.

[0516] In some configurations, one or more of the WOB metrics described above involving a nominal 'average healthy person' can be calculated from a nominal person (or a series of different sized nominal persons) with an average cannula in a controlled environment and pre-programmed or otherwise stored in the memory of the breathing device or in a memory accessible to the breathing device.

[0517] In an alternative configuration, a hybrid of estimated, detected, and / or manually input parameters can be used to estimate the WOB metric for a specific patient size. For example, measurable flow and pressure parameters (e.g., Q 管 , P 鼓风机)It can be used in combination with the measurements or estimates of the patient's size manually entered by the clinician and the approximate percentage of nasal obstruction. Alternatively or additionally, in another example, the device can estimate the patient's size based on the flow rate setting, and the knowledge of the cannula size (e.g., which can be manually entered) and the patient's size can be used to estimate or roughly estimate the nasal obstruction.

[0518] In another example configuration, a table (or other suitable data structure) of patient parameters and corresponding WOB measurements (if they are healthy) can also be stored in the memory of the breathing device and accessed when needed to allow the generation of WOB metrics or measurements depending on or relative to the measurements of healthy individuals.

[0519] In one example configuration, the breathing device or the controller of the breathing device can be configured to periodically or continuously calculate or account for the ratio or percentage of the patient's WOB measurement value to the nominal healthy WOB measurement value. Any of the applications described in the following sections can apply to this ratio or percentage, not just the individual WOB measurement.

[0520] 2.8 Applications of WOB Metrics

[0521] Overview

[0522] Any of the patient WOB metrics, data, or trend data disclosed herein (including patient WOB metrics expressed as a ratio or percentage relative to data of healthy individuals) can be generated and used by the breathing device in one or more various applications or functions, examples of which are further discussed below. In some configurations, these WOB metrics are generated and used by one or more applications or functions during the respiratory therapy period when the patient is using the breathing device. In some configurations, the application or function can utilize and / or process the WOB metric data generated and stored during the respiratory therapy period for post-treatment processing and / or storage, such as sending or transmitting the WOB metric data and / or related treatment data to a remote or cloud computing system, such as a patient and / or device management platform.

[0523] Examples of various applications and / or functions that can utilize and / or process the WOB metrics discussed above and / or generated by the algorithms disclosed above will now be further explained in detail. In some examples further explained below, the one or more WOB metrics or associated data can be used for any one or more of the following actions:

[0524] · Display the WOB metric data and / or WOB trend data on the respiratory device or an associated device (e.g., on the device's display screen and / or GUI, or transmitted for display on an associated device or a device that communicates data with the device).

[0525] · Trigger or generate an alarm or notification or recommendation (visual, auditory, and / or tactile) on the respiratory device or an associated device that communicates data with the device.

[0526] · Trigger or generate one or more warnings, alarms, and / or notifications at least in part based on the determined WOB metric data and / or WOB trend data, and one or more thresholds. The warnings, alarms, and / or notifications can be auditory, visual, and / or tactile.

[0527] · Trigger or generate one or more warnings, alarms, and / or notifications at least in part based on the WOB metric data and / or WOB trend data, and one or more thresholds, where the one or more warnings, alarms, and / or notifications include data indicating a recommended adjustment or change to the treatment settings and / or device settings.

[0528] · Generate a report based on the WOB metric data and / or WOB trend data.

[0529] Any one or more of the example applications and / or functions discussed above or below can be used in combination by the respiratory device.

[0530] First exemplary application – Displaying WOB data

[0531] In this example, the WOB metric data generated by the respiratory device can be displayed on the respiratory device's display screen or user interface (e.g., graphical user interface - GUI), or can be transmitted for display on an associated remote device or system that communicates data with the device. As discussed above, the raw or absolute patient WOB metric can be displayed, and / or the patient WOB ratio or percentage metric relative to healthy WOB data can be displayed. Additionally or alternatively, one or more WOB trends or trend data related to the WOB data (e.g., 'WOB increasing', 'WOB decreasing', 'WOB stable') can be displayed in isolation or simultaneously with the WOB metric data.

[0532] Reference Figure 24, an example GUI 2100 including a WOB monitoring screen is shown. In this example, the WOB monitoring screen includes a first GUI element 2102 configured to display WOB metric data. In this example, the WOB metric data can be a patient WOB ratio or percentage metric relative to nominal healthy WOB data, but alternatively can be raw or absolute WOB metric data. In this example, the WOB monitoring screen further includes a second GUI element 2104 displayed simultaneously, which is configured to display corresponding WOB trend data related to the WOB data displayed in the first GUI element 2102. The GUI elements 2102, 2014 can display their respective data in any suitable format or combination of formats, such as including but not limited to numerically, graphically, textually, iconically, colorfully, and / or animatedly.

[0533] In a configuration, the respiratory device can be configured to display WOB data (e.g., WOB metric data and / or WOB trend data) on the display or user interface of the respiratory device at the end of each treatment period or at some other configurable or predetermined time.

[0534] In a configuration, the respiratory device can be configured to process WOB data across multiple treatment periods or time periods of a patient, and can generate comparison data and / or aggregation data and / or statistical data representing or indicating statistics, changes, and / or trends in the patient's WOB data over multiple treatment periods and / or other desired time periods (e.g., days or weeks) regarding the captured data. The comparison data, aggregation data, and / or statistical data can be stored on the respiratory device and / or transmitted to a remote device or server for storage and / or further processing. Additionally or alternatively, the comparison data, aggregation data, and / or statistical data can be displayed or presented on the display of the respiratory device at the end of a treatment period and / or at some other configurable or predetermined time and / or based on a condition or event.

[0535] Second exemplary application – Displaying notifications and / or suggestions

[0536] In this example, the WOB data and / or related notifications and / or suggestions generated or triggered based on the WOB data can be displayed for a user, patient, and / or clinician or clinical staff (e.g., respiratory therapist, nurse, etc.). The WOB data, notifications, and / or suggestions can be displayed on the display screen or user interface (e.g., GUI) of the respiratory device and / or transmitted for display on a remote device or system (e.g., patient and / or device management system, and / or portable electronic device, such as a smartphone, tablet, laptop computer, wearable smart device, etc.) that communicates data with the device.

[0537] In one configuration, the GUI of the breathing device can be configured to display or present one or more live or real-time generated WOB metrics based on any of those disclosed above. This can also prompt the user to see if the treatment settings of the breathing device or changes to the treatment settings (e.g., flow rate settings and / or gas flow oxygen concentration related settings such as, for example, FiO2 and / or FdO2 settings) are beneficially changing the patient's WOB in real time (e.g., resulting in a low, lower, or reduced WOB). Such a configuration can enable the user or clinician to fine-tune the treatment settings of the breathing device for the patient to achieve the purpose of reducing the WOB.

[0538] In another configuration, one or more auditory and / or visual warnings, advisories, notifications, prompts, or the like can be presented or displayed on the display screen or GUI simultaneously with the WOB metrics or data. Audible warnings, alarms, and / or notifications can be provided via the audio output device of the device. For example, if the patient's WOB has increased / has increased with a new flow rate setting, an appropriate warning can be presented or delivered. Refer to Figures 25A - 25F , various GUI examples of such configurations and / or notifications and / or warnings will be described.

[0539] Figure 25A A first example GUI 2110 is shown, in which the WOB data has triggered a message 2112 that indicates that high work of breathing has been detected and the patient should be checked.

[0540] Figure 25B A second example GUI 2120 is shown, in which the WOB data has triggered: a first GUI element 2122 for displaying a trend notification indicating that the patient's work of breathing is increasing; and a second GUI element 2124 including notification or advisory data for adjusting the treatment settings. For example, the notification data can include data indicating how to adjust one or more of the treatment settings of the breathing device to reduce the work of breathing.

[0541] Figure 25C A third example GUI 2130 is shown, in which the WOB data has triggered: a first GUI element 2132 for displaying a message indicating that high work of breathing has been detected; and a second GUI element 2134 including a notification or remedial advice to increase the flow rate setting of the breathing device to the user or clinician. In this example, the GUI displays a WOB warning and corresponding remedial data or advisory data that provides information on how to resolve or remedy the warning. For example, increasing the flow rate setting can assist in reducing the patient's current work of breathing as represented by the calculated WOB data.

[0542] Figure 25DShows a fourth example GUI 2140, where the WOB data has triggered a message or trend notification 2142 that indicates a trend of increasing work of breathing has been detected and the patient should be examined.

[0543] Figure 25E Shows a fifth example GUI 2150, where the WOB data has triggered: a first GUI element 2152 for displaying a notification or message indicating low work of breathing has been detected; and a second GUI element 2154 including a notification or remedial advice for adjusting the treatment settings. The notification data can include data indicating one or more of how to adjust the treatment settings of the breathing device in response to the detected low work of breathing.

[0544] Figure 25F Shows a sixth example GUI 2160, where the WOB data has triggered: a first GUI element 2162 for displaying a trend notification indicating that the patient's work of breathing is increasing; and a second GUI element 2164 including a notification or remedial advice to increase the flow rate setting of the breathing device to the user or clinician. In this example, the GUI displays a WOB warning and corresponding remedial data or advice data that provides information on how to resolve or remedy the warning. For example, increasing the flow rate setting can assist in stopping and / or reversing the current trend of the patient's increasing work of breathing.

[0545] As discussed above, the notification data or information provided in the WOB notification, warning, and / or advice display screen can be provided or presented in any suitable form or combination of visual forms, including but not limited to, for example, numerical values, text information, graphical forms or formats, continuous trend lines, data plotted over time or represented in a chart, icons, animations, and / or color-coded information. Additionally or alternatively, for example, the notification data can be provided audibly and / or using audible cues or voice commands.

[0546] Third exemplary application – Reporting WOB data or notification data and generating a report

[0547] In some configurations, the generated WOB data (e.g., WOB metric data and / or WOB trend data) and / or notification data (e.g., warnings, alerts, notifications triggered based on a comparison of the WOB data with one or more thresholds) can be reported or transmitted by the breathing device to one or more remote devices or systems (e.g., patient and / or device management systems, and / or other personal or portable electronic devices such as smartphones, tablets, laptops, wearable devices). In one configuration, the breathing device can be configured to report or transmit the WOB data and / or notification data immediately, in real-time, periodically, on demand, or upon request, at configurable intervals, or automatically in response to a specific event or action.

[0548] In one example configuration, the breathing device is configured to report or transmit WOB data and / or notification data at or after the end of each treatment period. In one example, the breathing device is configured to report or transmit WOB data and / or notification data when the device is operating in a dry mode at any other suitable time after or when the treatment period has ended. In one configuration, the dry mode of the breathing device refers to a mode of the device in which, after a treatment period, the breathing device dries, for example, by the controller operating a blower or a flow generator instead of a humidifier.

[0549] In one example configuration, the breathing device is configured to report or transmit WOB data and / or notification data from a previous treatment period during a preheat mode of a subsequent treatment period. For example, during a preheat mode of a new treatment period, the breathing device may be configured to report or transmit WOB data and / or notification data generated from a previous treatment period or multiple previous periods. In one configuration, the preheat mode of the breathing device refers to a mode of the device in which, before the start of a treatment period, the controller raises the humidifier (if present) of the device to an operating temperature.

[0550] Any of the above notification data (e.g., warnings, notifications, recommendations, etc.) triggered in response to the calculated or determined WOB data may additionally or alternatively be transmitted for display or presentation on a remote device or system that communicates data directly or indirectly with the breathing device. Additionally or alternatively, the WOB data generated by the breathing device may trigger the presentation of such notification data on a remote device or system, e.g., the remote device or system may trigger the display or presentation of the notification data in response to receiving and processing the WOB data from the breathing device. By way of example, the remote device or system may be any suitable electronic device or system having visual (e.g., a display screen), auditory, and / or tactile user interfaces, including but not limited to mobile phones, smartphones, tablets, laptop computers, pagers, personal computers, wearable devices, or any other suitable electronic device.

[0551] In some configurations, WOB data and / or associated triggered notification data can be transmitted by a respiratory device to a remote device or system for presentation. In some configurations, WOB data and / or associated triggered notification data can be transmitted to a remote cloud- or server-based patient and / or device management system, which can process the incoming data and then relay or push the WOB and / or notification data to one or more other electronic devices or systems (e.g., a clinician electronic device or system such as a smartphone, tablet, laptop computer, computer, wearable device, etc.). In some configurations, the patient and / or device management system can be configured to receive WOB data from the respiratory device, process the WOB data, and cause (e.g., push, trigger, or generate) notification data to be presented on one or more remote electronic devices or systems (e.g., a clinician electronic device or system).

[0552] In some configurations, a remote server or device (e.g., a patient and / or device management system) that receives WOB data and / or notification data from a respiratory device can be configured to generate one or more patient reports based on the received WOB data (e.g., WOB metric data and / or trend data). The generated reports can be of any suitable type and / or format, including but not limited to reported data, displayed reports, compiled reports, electronic reports, printable reports, numerical reports, graphical reports. The reports can include data representing WOB data and / or notification data for a single treatment period and / or across multiple treatment periods and / or across a selectable or configurable time period (e.g., days or weeks).

[0553] In some configurations, the generated reports can include comparative data and / or aggregated data and / or statistical data related to WOB data and / or notification data received for a patient based on one or more treatment periods and / or within a desired time period (e.g., days or weeks).

[0554] Fourth exemplary application – Adjusting suggestions in response to a treatment parameter setting of a WOB metric

[0555] Reference Figure 26 , an example method 2200 for calculating a WOB metric implemented by a respiratory device (e.g., a controller of the respiratory device) will be described according to the previous disclosure above, and the method results in the respiratory device generating a recommendation for adjusting a treatment parameter setting in response to the calculated WOB metric. The order of the steps described is not critical in all configurations, and some steps can occur in parallel rather than sequentially. Details and alternatives associated with each of these steps have been described above and will not be repeated for the sake of brevity.

[0556] In this example method 2200, the process begins at step 2202, where the controller of the breathing device receives pressure data, e.g., from one or more pressure sensors of the device, at step 2204. In this configuration, the pressure data indicates the pressure P at the output of the blower. 鼓风机 The controller then receives flow rate data indicative of the device output flow rate, e.g., from one or more flow rate sensors in the flow path of the device, as shown at step 2206. The controller is then configured to calculate or estimate the conduit or tube flow rate Q, at least in part, based on the received device output flow rate data, 管 as shown at step 2208. In this example, the controller is also configured to generate an estimate of the minute ventilation MV of the device, at least in part, based on the device output flow rate data, 装置 as shown at step 2210.

[0557] In this example, the controller then determines or calculates an estimated value of the nasal pressure test value P, 鼻,猜测 as shown at step 2212. Then, based at least in part on Q, 管 P, 鼓风机 and P, 鼻,猜测 the estimated value of the tube conductance C is determined, as shown at step 2214. After this, the controller is configured to calculate the nasal pressure fluctuation WOB metric ΔP, at least in part, based on the values of Q, 管 C, 管 and MV, 管 as shown at step 2216, and as previously described. Additionally or alternatively, the controller may proceed with further processing steps to generate one or more of the other WOB metrics described above in Sections 2.3 and 2.4. 装置 鼻 In this example method 2200, the controller is then configured to optionally process the ΔP

[0558] WOB metric or other calculated WOB data and may generate a treatment parameter setting change or adjustment recommendation. The generated treatment parameter setting change or adjustment recommendation may be based at least in part on or responsive to the generated WOB data or based on further processing of the WOB data relative to one or more thresholds or the like, as shown at step 2218. For example, if the WOB data is outside configurable limits or is demonstrating an adverse trend, the controller may generate a change or adjustment recommendation, as described above. 鼻

[0559] If a change in a treatment parameter setting is recommended or triggered at step 2218, the controller can optionally be configured to display or present those recommended treatment parameter setting changes on the display of the breathing device and / or can transmit them for display on one or more remote devices or systems, as discussed above, as shown at step 2220. In one configuration, the breathing device can be configured with the following additional optional step: enabling a user or clinician to approve and confirm or reject the recommended treatment parameter setting changes depending on whether they want the recommended setting changes to be applied by the controller. For example, the user or clinician can confirm or reject the recommended setting changes via a user interaction with the user interface of the breathing device and / or the remote device or system.

[0560] In a configuration, the controller can be configured to process WOB data (e.g., WOB metric data and / or WOB trend data), and then can generate a notification, warning, or alert recommending an adjustment to a treatment parameter setting based on comparing the WOB data to one or more thresholds. The controller can recommend a change to any one or more treatment settings or device settings, such as but not limited to a flow rate setting and a gas flow oxygen concentration setting (e.g., FiO2 and / or FdO2 settings, e.g., these settings control the oxygen concentration in the gas flow provided to the patient). The treatment parameter setting adjustment recommendation can include, for example, an indication of the response or remedial change required depending on the comparison of the WOB data to the one or more thresholds, such as 'increase flow rate' or 'decrease flow rate' or 'increase oxygen concentration' or 'decrease oxygen concentration'. As discussed above, the recommended treatment setting adjustment can be presented or displayed on the breathing device and / or transmitted to a remote device or system for processing and / or display.

[0561] Fifth exemplary application – Disconnecting an alarm or notification

[0562] In another example, the controller can be configured to process any one of the one or more calculated WOB metrics described above to detect a disconnection of any part of the flow path (e.g., the patient breathing circuit and / or the patient interface) and / or a disconnection or detachment of the patient from the patient interface (e.g., a nasal cannula).

[0563] For example, in one configuration, if ΔP 鼻 WOB metric (and by extension, ΔP 鼻 *Q 呼吸 WOB metric or ΔP 鼻*σWOB index, etc.) reaches zero or crosses a predetermined threshold (e.g., close to zero) for a sufficient period of time (i.e., the patient's breathing is not detected), a disconnection may have occurred. If such a disconnection is detected based on the WOB data, any appropriate response can be initiated or triggered. For example, the controller can trigger the presentation of an audio and / or visual alarm and / or display a notification (e.g., text and / or animation) on the display screen to suggest a corrective action. Alternatively or additionally, an alarm (visual, auditory, and / or tactile) can be triggered on a remote device or system, such as but not limited to a mobile phone, tablet computer, laptop computer, pager, or other suitable device (further examples of which have been previously described).

[0564] Reference Figure 27A and Figure 27B , which shows some examples of possible GUI screen disconnection warning notifications for display on the display screen of a breathing device or a remote device.

[0565] Figure 27A Shows a first example GUI 2300, where the WOB data has triggered a disconnection warning notification screen, which includes information indicating that a potential disconnection event has been detected and prompts the user or clinician to check the patient circuit (e.g., breathing tube and / or patient interface) connections along the air circuit and / or check for the patient's detachment from the patient interface.

[0566] Figure 27B Shows a second example GUI 2310, where the WOB data has triggered a disconnection warning notification screen, which includes a first GUI element 2312 that includes text information indicating that a potential disconnection event has been detected and prompts the user or clinician to check the patient circuit (as in Figure 27A the example). Additionally, a second GUI element 2314 that includes an animation or other image can be displayed next to or simultaneously with the first GUI element, which can prompt the user to check the patient breathing circuit or otherwise visually warn them of the potential disconnection event.

[0567] Sixth exemplary application – Configurable alarm settings

[0568] In another example, the controller of the breathing device can be configured with one or more configurable alarms or trigger thresholds, the generated WOB data can be compared with the one or more configurable alarms or trigger thresholds, and then actions can be taken depending on those comparisons.

[0569] For example, any one of the WOB metrics or data can be compared to one or more thresholds associated with one or more corresponding notification, warning, and / or alert events. For example, the controller can be configured with one or more specific notification, warning, or alert events that are triggered if the WOB data meets or complies with the threshold requirements or threshold rules. The threshold rules or requirements for each notification, warning, and / or alert event can be based on a single threshold, a threshold range, an upper threshold limit and a lower threshold limit, or a threshold function based on one or more parameters and / or conditions (e.g., if the WOB data exceeds the upper limit for a specific period of time, or if the WOB data exceeds the upper limit more than x times within a specific period of time, then an alert / alert / notification is triggered). Whether a notification, warning, and / or alert event is triggered can depend on whether the threshold rules or functions are met after comparing the WOB data or metric to the threshold rules or functions and the associated threshold limits.

[0570] In some configurations or for some notification, warning, or alert events, one or more of the threshold limits or threshold function parameters can be pre-programmed or pre-configured. In other configurations or for some notification, warning, or alert events, one or more of the threshold limits or threshold function parameters can be user or clinician configurable. In such a configuration, the threshold limits or threshold function parameters can be configurable and / or adjustable via a user interface (e.g., a GUI) presented on the display screen of the breathing device.

[0571] Reference Figure 28A and Figure 28B , shows some examples of possible GUI screens operable to adjust threshold parameters for specific notification, warning, and / or alert events.

[0572] Figure 28AShows a first example GUI 2400 presenting a parameter warning threshold configuration or adjustment screen. In this example GUI 2400, a first GUI element 2402 provides a notification or information about the parameter warning or notification threshold being adjusted. For example, the parameter warning or notification or alert may be selected from examples including but not limited to the following: 'High WOB', 'Low WOB', and / or 'Possible disconnection'. In this example GUI 2400, a second GUI element 2404 is also provided, and the second GUI element may be a user-interactive or operable GUI element or interface that enables adjustment of the one or more thresholds associated with the parameter warning. In this example, the GUI may be presented on a touchscreen user interface, and the user can interact with the GUI elements to configure the thresholds via touch input or interactivity. The user-interactive GUI elements for adjusting the one or more configurable thresholds may include any suitable form of adjustment, including but not limited to: a bistable trigger element for increasing or decreasing the threshold limit, a dial or slider scale element for adjusting the threshold, a selectable discrete threshold element for selecting from a series of discrete threshold levels, a numerical or categorical input field for entering the desired threshold.

[0573] In Figure 28A the example shown, the threshold is adjusted via a user-interactive GUI 2404 having positive ('+') and negative ('-') GUI elements or buttons, and these GUI elements or buttons can be interacted with to incrementally increase and decrease the warning parameter threshold, respectively. In this example, the upper slider element 2406 may represent the upper limit parameter threshold, and the lower slider element 2408 may represent the lower limit parameter threshold. In one configuration, the user can tap, select, or touch either the upper slider element 2406 or the lower slider element 2408, and then can move the selected slider element to adjust the selected threshold by interacting with the positive ('+') and negative ('-') GUI elements or buttons. Additionally or alternatively, the user can directly interact with the upper slider element 2406 and / or the lower slider element 2408 by sliding and / or dragging the slider element along the slider bar / range to adjust the corresponding upper limit parameter threshold and / or lower limit parameter threshold.

[0574] Figure 28B The second example GUI 2400a shown in Figure 28A is the same as that shown and described in Figure 28AAs in the example described, the user can select either the upper slider element 2406a and / or the lower slider element 2408a and then interact with the 'higher' or 'lower' GUI element to adjust the selected parameter threshold, or the user can directly interact with either of the slider elements 2406a, 2408a by sliding and / or dragging the slider element along the slider bar / range to adjust the associated parameter threshold.

[0575] In other example configurations, it will be appreciated that Figure 28A and Figure 28B the GUI in may alternatively be provided with a single interactive slider bar on the slider scale for adjusting a single upper limit parameter warning threshold or a lower limit parameter warning threshold.

[0576] In one example configuration, the WOB metric or data can act as a background parameter that is used to set or serve as input to guide the setting of one or more general respiratory device alert thresholds (e.g., respiratory rate alert, minute ventilation alert, tidal volume alert, and / or etc.). In other example configurations, the WOB alert can be configured based on the WOB metric or data, and the WOB alert can serve as an alternative alert for other parameters (such as but not limited to, respiratory rate, minute ventilation, tidal volume, and / or etc.). For example, in some configurations, the WOB metric can be closely related to some of these other parameters. For example, if the patient's respiratory rate or minute ventilation increases, the WOB metric should generally also increase accordingly. Similarly, if the patient's respiratory rate or minute ventilation decreases, the WOB metric will generally also decrease. This can be advantageous in some configurations because it can be quite difficult to detect some respiratory parameters in an unsealed respiratory system (such as, a nasal high flow system). In some cases, the described WOB metrics can be calculated more reliably, but they still depend on the underlying (multiple) patient respiratory parameters, thus enabling them to be used as alternative or surrogate metrics that can be used to trigger one or more respiratory parameter alerts, as further explained later.

[0577] In one example configuration, after the respiratory device is started and operating during a respiratory treatment period for a patient, an initial WOB metric or data can be calculated or accounted for. The respiratory device can then display or visualize the WOB metric or data or another related parameter (e.g., minute ventilation) on its display and provide recommendations for upper bounds or threshold upper limits and lower bounds or threshold lower limits based at least in part on the WOB metric or data.

[0578] In one example, an alert can be provided that is triggered based on comparing the ΔP 鼻 WOB metric or data to an associated threshold. This ΔP 鼻The WOB metric alarm can be considered to act as a surrogate for a patient minute ventilation alarm (actual patient minute ventilation compared to a device or nasal minute ventilation measurement as previously described) or a respiratory rate alarm. In some configurations, such an alarm threshold can have the advantage that the alarm threshold is based on ΔP 鼻 WOB metric and acts as a surrogate for a patient minute ventilation or respiratory rate alarm. The estimation of the ΔP 鼻 WOB metric may potentially be more accurate and / or more informative about changes in a patient's respiration.

[0579] In one example, the ΔP 鼻 WOB metric used as an alarm can be similar to a minute ventilation alarm. In this example, the ΔP 鼻 WOB metric is proportional to and closely related to the patient's minute ventilation (MV) (and where V T is the tidal volume). Thus, the device can be configured such that certain alarm thresholds for the ΔP 鼻 WOB metric value act as an alarm system for high or low MV. In this case, a larger ΔP 鼻 WOB metric magnitude corresponds to a higher MV, and vice versa.

[0580] In another example, because the ΔP 鼻 is proportional to and closely related to MV, the ΔP 鼻 WOB metric alarm can be configured to act as a respiratory rate (RR) alarm. For example, because it can be said that if the tidal volume is assumed to be relatively constant during the provision of respiratory therapy, then Therefore, a decreasing ΔP 鼻 (magnitude) may indicate an increasing RR, and vice versa. As the patient pants shorter and more frequently, their RR will increase while the MV (proportional to the ΔP 鼻 ) will decrease.

[0581] In other examples, the previously discussed WOB metric examples (e.g., ΔP 鼻 、ΔP 鼻 *Q 呼吸 and / or ΔP 鼻Any one or more of *)σ) may be used as an alternative alert for the patient's minute ventilation or respiratory rate. For example, any one or more of the WOB metric examples may be compared to one or more thresholds configured or calibrated for the patient minute ventilation alert and / or respiratory rate alert. In some such configurations, the WOB metric may be compared to a threshold without any time aspect (e.g., if the WOB metric crosses the threshold at any point, an alert will be triggered). In other such configurations, the WOB metric may be compared to a threshold with one or more associated additional trigger conditions, such as time or trend or other conditions. For example, the alert thresholds may be configured such that they trigger only if the WOB metric is above or below the threshold for a predetermined or configurable period of time, or if the WOB metric crosses the threshold a certain number of times within a predetermined or configurable period of time, or under other such conditions.

[0582] In some configurations, with respect to the WOB metric alert, the upper bound or threshold upper limit may (at least in part) correspond to an undesirably high WOB that requires a change in treatment parameters. The lower bound or threshold lower limit may similarly (at least in part) correspond to an undesirably low WOB, but may also be used as a disconnect alert trigger as previously described. Thus, the one or more WOB metrics or data may be compared to one or more thresholds, and the one or more WOB metrics or data may trigger different alerts, warnings, or notifications depending on whether the WOB metric is above or below these thresholds (depending on the threshold function or criteria).

[0583] In one example configuration, the clinician may choose to accept the default or respiratory device-recommended notification, warning, and / or alert thresholds, ignore them completely, use them in concert with their own preferred thresholds or other warning triggers (e.g., SpO2 alert), or adjust the default or recommended thresholds before accepting them. In this example, the clinician may perform these alert threshold setting adjustments or threshold configurations or confirmations via the user interface of the respiratory device (e.g., GUI) or remotely via the user interface of another electronic device or system that communicates data with the respiratory device.

[0584] In some configurations, the WOB metric alerts, warnings, or notifications can be configured with multiple or multiple upper bounds or threshold ceilings and lower bounds or threshold floors. For example, the alerts, warnings, or notifications can be configured with cascading or nested thresholds or threshold ranges, or inner and outer threshold ranges, or multiple or a series of progressive or escalating thresholds, where the nature of the triggered alert, warning, or notification associated with each respective threshold depends on the nature, location, priority, or extremity of that threshold on the overall threshold scale or is dependent on the nature, location, priority, or extremity of that threshold on the overall threshold scale. In one example configuration, for instance, a first upper bound or threshold ceiling can simply trigger a notification or recommendation to adjust a therapy parameter, while a second, higher upper bound or threshold ceiling can trigger a high-priority warning, as the value of this higher upper bound or threshold ceiling can correspond to a WOB metric magnitude indicative of severe hyperventilation or other serious medical events.

[0585] In one example configuration, the default or recommended upper bound or threshold ceiling / lower bound or threshold floor of the breathing device can be recalibrated or dynamically changed for each therapy session, after a certain time period has elapsed, or after a number of therapy sessions have passed. In other words, the threshold recommendations can be changed daily, weekly, monthly, or within any other suitable time period (which can also be configurable). In one example, the recalibration of the recommended thresholds can be at least partially based on one or more calculated WOB metrics or data and / or changes in WOB trend data. For example, the controller can be configured such that a persistent downward trend in one or more of the WOB metrics or data over one or more therapy sessions can cause the recommended upper bound or threshold ceiling / lower bound or threshold floor to narrow (i.e., a narrower acceptable range can be tolerated), shift downward, shift upward, or otherwise change according to any combination thereof.

[0586] In some example scenarios, the default values of the upper bound or threshold ceiling / lower bound or threshold floor can be set or configured across a fleet of breathing devices according to hospital, health system, or clinician protocols. In one configuration, the default thresholds can be pre-programmed during manufacturing or configured remotely (e.g., via a cloud- or server-based patient and / or device management system or platform).

[0587] In one configuration, the default values of the upper bound or threshold ceiling / lower bound or threshold floor can be stored in the breathing device memory or in the memory of a remote device or system used to configure the breathing device.

[0588] In some example configurations, warnings, notifications, and / or alerts can be configured to selectively present on different devices or systems based on thresholds being crossed. For example, as mentioned, a first upper bound or threshold ceiling can trigger a notification to adjust a therapy parameter and can be displayed only on the display of a breathing device. A second upper bound or threshold ceiling corresponding to a more stringent threshold can trigger an alert or notification to be presented on more than one device or system in addition to being displayed on the breathing device, such as, for example, on one or more remote devices.

[0589] Above, although the upper bound or threshold ceiling and the lower bound or threshold floor have been discussed together, in some configurations, they can be configured individually or selectively. For example, a clinician or user can selectively configure the lower bound or threshold floor for disconnect alarms but may not adjust the higher bound or threshold associated with other alerts or notifications (e.g., high WOB).

[0590] 3. Terms and definitions

[0591] Unless the context otherwise indicates, as used in this specification and the claims, the phrase 'computer-readable medium' or'machine-readable medium' shall be understood to include a single medium or multiple media. Examples of multiple media include centralized or distributed databases and / or associated caches. These multiple media store the one or more sets of computer-executable instructions. The phrase 'computer-readable medium' or'machine-readable medium' shall also be understood to include any medium that is capable of storing, encoding, or carrying a set of instructions for execution by a processor of a computing device and that causes the processor to execute any one or more of the methods described herein. A computer-readable medium is also capable of storing, encoding, or carrying data structures used by or associated with these sets of instructions. The phrases 'computer-readable medium' and'machine-readable medium' include, but are not limited to, portable to fixed storage devices, solid state memories, optical media or optical storage devices, magnetic media, and / or various other media capable of storing, containing, or carrying instructions and / or data. 'Computer-readable medium' or'machine-readable medium' can be non-transitory.

[0592] As used in this specification and the claims, the term 'comprising' means 'comprising at least in part' or 'including but not limited to', such that it is to be interpreted in an inclusive sense rather than an exclusive or exhaustive sense. When interpreting each statement in this specification and the claims that includes the term 'comprising', there can also be features other than the feature or features that begin with that term. Related terms (such as, 'comprise' and 'comprises') will be interpreted in the same manner.

[0593] It is intended that references to numerical ranges disclosed herein (e.g., 1 to 10) also incorporate references to all rational numbers within that range (e.g., 1, 1.1, 2, 3, 3.9, 4, 5, 6, 6.5, 7, 8, 9, and 10) and also any range of rational numbers within that range (e.g., 2 to 8, 1.5 to 5.5, and 3.1 to 4.7), and thus, all sub-ranges of all ranges expressly disclosed herein are hereby expressly disclosed. These are merely examples of specific intended disclosures, and all possible combinations of numerical values between the recited lowest value and the highest value will be considered to be expressly stated in this application in a similar manner.

[0594] The term ‘and / or’ means ‘and’ or ‘or’, or both.

[0595] The use of ‘(s)’ following a noun means the plural and / or singular form of that noun.

[0596] Unless expressly stated otherwise, or otherwise understood within the context in which it is used, conditional language (such as “can”, “may”, “might”, or “could”) generally is intended to convey that certain embodiments include while other embodiments do not include certain features, elements, and / or steps. Thus, such conditional language generally is not intended to imply that the features, elements, and / or steps are required in one or more embodiments in any way, or that one or more embodiments necessarily include logic for deciding whether these features, elements, and / or steps are included in or will be implemented in any particular embodiment, with or without user input or prompting.

[0597] Degree language used herein (such as the terms “about”, “approximately”, “substantially”, and “essentially” as used herein) represents a value, quantity, or characteristic that is close to the stated value, quantity, or characteristic and that still performs the desired function or achieves the desired result. For example, the terms “about”, “approximately”, “substantially”, and “essentially” may refer to a quantity within less than 10%, less than 5%, less than 1%, less than 0.1%, and less than 0.01% of the stated quantity.

[0598] In this specification, patent specifications, other external documents, or other information sources have been referenced, typically for the purpose of providing background for discussing the features of the invention. Unless expressly stated otherwise, references to such external documents will not be construed as an admission that such documents or such information sources are prior art in any jurisdiction or form part of the common general knowledge in the art.

[0599] In the above description, specific details are given to provide a thorough understanding of the embodiments. However, those of ordinary skill in the art will understand that the embodiments may be practiced without these specific details. For example, software modules, functions, circuits, etc. may be shown in block diagrams so as not to obscure the embodiments with unnecessary details. In other instances, well-known modules, structures, and techniques may not be shown in detail so as not to obscure the embodiments.

[0600] Moreover, it should be noted that an embodiment may be described as a process, which is depicted as a flowchart, a flow diagram, a structural diagram, or a block diagram. Although a flowchart may describe operations as a sequential process, many operations may be performed in parallel or concurrently. Additionally, the order of the operations may be rearranged. When the operations of a process are completed, the process terminates. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. in a computer program. When a process corresponds to a function, its termination corresponds to the function returning to the calling function or the main function.

[0601] Aspects of the systems and methods described above may be operable on any type of general-purpose computer system or computing device, including but not limited to desktop computers, laptop computers, notebooks, tablet computers, smart TVs, gaming consoles, or mobile devices. The term "mobile device" includes but is not limited to wireless devices, mobile phones, smartphones, mobile communication devices, user communication devices, personal digital assistants, mobile handheld computers, laptop computers, wearable electronic devices (such as smartwatches and head-mounted devices), e-book readers and reading devices capable of reading electronic content, and / or other types of mobile devices typically carried by an individual and / or having some form of communication capability (e.g., wireless, infrared, short-range radio, cellular, etc.).

[0602] Aspects of the systems and methods described above may be operable or implemented on any type of special-purpose or particular computer or any machine or computer or server or electronic device (having a microprocessor, a processor, a microcontroller, a programmable controller, etc.), or a cloud-based platform or other network of processors and / or servers (whether local or remote), or any combination of such devices.

[0603] In addition, embodiments may be implemented by hardware, software, firmware, middleware, microcode, or any combination thereof. When implemented in software, firmware, middleware, or microcode, the program code or code segments for performing the necessary tasks may be stored in a machine-readable medium (such as a storage medium or other storage device). The processor may perform the necessary tasks. A code segment may represent any combination of procedures, functions, subroutines, programs, routines, subroutines, modules, software packages, classes, or instructions, data structures, or program statements. A code segment may be coupled to another code segment or hardware circuit by passing and / or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means (including memory sharing, message passing, token passing, network transmission, etc.).

[0604] In the above description, the storage medium may represent one or more devices for storing data, including read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, and / or other machine or computer-readable media for storing information.

[0605] The various illustrative logical blocks, modules, circuits, elements, and / or components described in connection with the examples disclosed herein may be implemented or performed with the following, which are designed to perform the functions described herein: a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic component, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, circuit, and / or state machine. The processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, several microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0606] The methods or algorithms described in connection with the examples disclosed herein may be embodied directly in hardware, in a software module executable by a processor, or in a combination of both, in the form of processing units, programming instructions, or other indications, and may be contained within a single device or distributed across multiple devices. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. The storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral with the processor.

[0607] Without departing from the scope of the present disclosure, one or more of the components and functions shown in the figures may be rearranged and / or combined into a single component or embodied in several components. Without departing from the scope of the present disclosure, additional elements or components may also be added. Additionally, the features described herein may be implemented in software, hardware, as a business method, and / or any combination thereof.

[0608] In various aspects, embodiments of the present disclosure may be embodied in a computer-implemented process, a machine (such as an electronic device or a general-purpose computer or other device that provides a platform on which a computer program may be executed), a process executed by these machines, or an article of manufacture. Such an article of manufacture may include a computer program product or a digital information product (wherein a computer-readable storage medium contains computer program instructions or computer-readable data stored thereon), as well as the processes and machines that produce and use these articles of manufacture.

[0609] Although the present disclosure has been described in the context of certain embodiments and examples, those skilled in the art will understand that the present disclosure extends beyond the specifically disclosed embodiments to other alternative embodiments and / or uses and obvious modifications and their equivalents. Additionally, although several variations of the embodiments of the present disclosure have been shown and described in detail, other modifications within the scope of the present disclosure will be readily apparent to those skilled in the art. It is also contemplated that various combinations or sub-combinations of the specific features and aspects of the embodiments may be made, and such combinations or sub-combinations are still within the scope of the present disclosure. For example, the features described above in connection with one embodiment may be used with different embodiments described herein, and such a combination is still within the scope of the present disclosure. It should be understood that the various features and aspects of the disclosed embodiments may be combined with or substituted for one another to form various patterns of variations of the embodiments of the present disclosure. Therefore, it is intended that the scope of the disclosure herein should not be limited by the specific embodiments described above. Thus, unless otherwise stated or unless clearly incompatible, each embodiment of the present disclosure may include, in addition to its basic features described herein, one or more features as described herein from each other embodiment of the present invention disclosed herein.

[0610] The present disclosure may also be broadly said to include the parts, elements, and features individually or jointly referred to or indicated in the present disclosure, and any combination or all combinations of any two or more of the said parts, elements, or features, and, where specific integers having known equivalents in the art to which the present disclosure pertains are mentioned herein, such known equivalents are considered to be incorporated herein as if individually set forth.

[0611] Features, materials, characteristics or groups described in connection with a particular aspect, embodiment or example will be understood to be applicable to any other aspect, embodiment or example described elsewhere in this section or in this specification, unless incompatible therewith. All features disclosed in this specification (including any appended claims, abstract and drawings), and / or all steps of any method or process so disclosed, may be combined in any combination, except combinations in which at least some of such features and / or steps are mutually exclusive. The scope of protection is not limited to the details of any of the foregoing embodiments. The scope of protection extends to any novel feature or any novel combination of features disclosed in this specification (including any appended claims, abstract and drawings), or to any novel step or any novel combination of steps of any method or process so disclosed.

[0612] In addition, certain features described in the context of separate embodiments in this disclosure may also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment may also be implemented separately or in any suitable sub-combination in multiple embodiments. Further, although features may be described above as acting in certain combinations, in some cases, one or more features from a claimed combination may be removed from that combination, and the combination may be claimed as a sub-combination or a variation of a sub-combination.

[0613] Moreover, while operations may be depicted in the drawings or described in the specification in a particular order, such operations need not be performed in the particular order shown or in sequential order, or all operations need not be performed, to achieve the desired result. Other operations not depicted or described may be incorporated into the example methods and processes. For example, one or more additional operations may be performed before, after, simultaneously with or between any of the described operations. Further, the operations may be rearranged or reordered in other embodiments. Those skilled in the art will appreciate that in some embodiments, the actual steps taken in the processes shown and / or disclosed may differ from those shown in the figures. Depending on the embodiment, certain steps described above may be removed, and other steps may be added. In addition, the features and attributes of the particular embodiments disclosed above may be combined in different ways to form additional embodiments, all of which are within the scope of this disclosure. Also, the separation of the various system components in the embodiments described above should not be understood to be required in all embodiments, and it should be understood that the described components and systems may generally be integrated together in a single product or packaged into multiple products.

[0614] For purposes of this disclosure, certain aspects, advantages, and novel features are described herein. Not all such advantages may be achieved in accordance with any particular embodiment. Thus, for example, those skilled in the art will recognize that the disclosure may be embodied or implemented in a manner that achieves one advantage or a group of advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein.

[0615] The scope of the disclosure is not intended to be limited by the specific disclosure of the embodiments in this section or elsewhere in this specification, and may be defined by the claims as presented in this section or elsewhere in this specification or as will be presented in the future. The language of the claims will be interpreted broadly based on the language employed in the claims, and not limited to the examples described in this specification or during the prosecution of this application, which examples will be construed as non-exclusive.

Claims

1. A respiratory device configured to provide a gas flow to a user for respiratory therapy, the respiratory device comprising: a flow generator configured to generate the gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and initiate one or more actions at least in part based on the determined WOB metric.

2. The breathing device according to claim 1, wherein, The flow parameter data includes flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator.

3. The breathing device according to claim 2, wherein, The device includes one or more flow rate sensors configured to sense and generate the flow rate data.

4. The breathing device according to claim 3, wherein The one or more flow rate sensors are positioned in or along the flow path of the gas flow.

5. The breathing device according to claim 3 or claim 4, wherein, The one or more flow rate sensors are positioned at or near the outlet of the blower of the flow generator.

6. The breathing device according to any one of claims 3 to 5, wherein, The one or more flow rate sensors are in electrical communication with the controller.

7. The breathing device according to any one of claims 3 to 6, wherein, The controller is further configured to process the flow rate data to remove noise and / or signal components associated with the flow generator.

8. The breathing device according to claim 7, wherein, The controller is configured to remove noise related to the influence of the motor on the flow rate data.

9. The breathing device according to claim 7 or claim 8, wherein, The controller is configured to receive data regarding the motor speed and, if the motor speed is below a preset threshold, discard the flow rate data of the gas flow.

10. The breathing device according to any one of claims 7 to 9, wherein, The controller is configured to: if the controller determines that the quality of the flow rate data parameters of the gas flow is insufficient, discard the flow rate data.

11. The breathing device according to claim 10, wherein, If the flow rate data includes large transient peaks, the flow rate data is determined to be of insufficient quality.

12. The breathing device according to any one of claims 1 to 11, wherein, The flow parameter data includes pressure data indicative of or representative of the pressure of the gas flow at the outlet of the blower of the flow generator.

13. The breathing device according to claim 12, wherein, The device further includes one or more pressure sensors configured to sense and generate the pressure data.

14. The breathing device according to claim 13, wherein, The one or more pressure sensors are positioned in or along the flow path of the gas flow.

15. The breathing device according to claim 13 or claim 14, wherein, The one or more pressure sensors are positioned at or near the outlet of the blower of the flow generator.

16. The breathing device according to any one of claims 13 to 15, wherein, The one or more pressure sensors are in electrical communication with the controller.

17. The breathing device according to any one of claims 12 to 16, wherein, The controller is further configured to determine an initial nasal pressure estimate indicative of or representative of an estimate of the nasal pressure of the user at least in part based on the pressure data.

18. The breathing device according to any one of claims 1 to 17, wherein, The controller is further configured to determine a flow path conductance estimate indicative of or representative of an estimate of the conductance of the flow path of the gas flow between the flow generator and the patient interface.

19. The breathing device according to claim 18, wherein, The controller is configured to determine the flow path conductance estimate at least in part based on the initial nasal pressure estimate indicative of or representative of an estimate of the nasal pressure of the user.

20. The breathing device according to claim 18 or claim 19, wherein, The controller is configured to determine the flow path conductivity estimate at least in part based on flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator.

21. The breathing device according to any one of claims 18 to 20, wherein, The controller is configured to determine the flow path conductivity estimate at least in part based on pressure data indicative of or representative of the pressure of the gas flow at the outlet of the blower of the flow generator.

22. The breathing device according to claim 18, wherein, The controller is configured to determine the flow path conductivity estimate at least in part based on flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator and the motor speed representing the motor speed of the blower of the flow generator.

23. The breathing device according to claim 18, wherein, The controller is configured to determine the flow path conductivity estimate at least in part based on flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator and pressure data indicative of or representative of the pressure of the gas flow at the outlet of the blower of the flow generator.

24. The breathing device according to any one of claims 18 to 23, wherein, The controller is configured to determine the nasal pressure change value at least in part based on the flow path conductivity estimate.

25. The breathing device according to any one of claims 18 to 24, wherein, The controller is configured to determine the nasal pressure change value at least in part based on flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator.

26. The breathing device according to any one of claims 18 to 25, wherein, The controller is configured to determine the nasal pressure change value at least in part based on minute ventilation data indicative of or representative of the average gas volume provided by the flow generator per minute.

27. The breathing device according to claim 26, wherein, The controller is configured to determine the minute ventilation data by fitting a plurality of splines to the flow parameter data of the gas flow, wherein the plurality of splines are fitted using a least squares criterion and the minute ventilation data is determined by integrating along the plurality of splines.

28. The breathing device according to claim 26, wherein, The controller is configured to determine the minute ventilation data by determining the integral of the absolute value of the first term of the line fitted to the flow parameter data of the gas flow.

29. The breathing apparatus according to claim 26, wherein, The controller is configured to determine the device minute ventilation data by determining the integral of the absolute value of the data of the line fitted to the flow parameter data of the gas flow divided by the time range.

30. The breathing device according to claim 26, wherein, The controller is configured to determine the device minute ventilation data by determining the average value of the absolute value of the line fitted to the flow parameter data of the gas flow across a series of time points within a time range.

31. The breathing device according to any one of claims 1 to 30, wherein, The nasal pressure change value is determined at a frequency selected in the range of 1 Hz to 20 Hz.

32. The breathing device according to any one of claims 1 to 30, wherein, The nasal pressure change value is continuously determined as a rolling average.

33. The breathing device according to any one of claims 1 to 32, wherein, The device further includes a non-transitory computer-readable medium accessible to or in data communication with the controller, and preferably wherein the non-transitory computer-readable medium includes non-volatile memory, and preferably wherein the device further includes a patient nostril model stored in the non-volatile memory.

34. The breathing device according to claim 33, wherein, The controller is further configured to determine a user respiratory flow rate estimate indicative of or representative of the respiratory flow rate of the user at least in part based on flow rate data indicative of or representative of the flow rate of the gas flow provided by the flow generator and the patient nostril model.

35. The breathing device according to claim 34, wherein, The controller is configured to determine the user respiratory flow rate estimate at least in part based on an estimate of the flow path conductance, which indicates or represents an estimate of the conductance of the gas flow path between the flow generator and the patient interface.

36. The breathing device according to claim 34 or claim 35, wherein, The controller is configured to determine the user respiratory flow rate estimate at least in part based on minute ventilation data indicating or representing the average gas volume provided per minute by the flow generator.

37. The breathing device according to any one of claims 34 to 36, wherein, The controller is configured to determine a nasal conductance estimate at least in part based on data indicating the patient interface size and an estimate of nasal obstruction of the patient interface, the nasal conductance estimate indicating or representing an estimate of the conductance of the gas flow path between the patient interface and the user's nostrils.

38. The breathing apparatus according to claim 37, wherein, The controller is configured to determine the user respiratory flow rate estimate at least in part based on the determined or calculated nasal conductance estimate.

39. The breathing device according to any one of claims 34 to 38, wherein, The controller is configured to determine the work of breathing metric at least in part based on the nasal pressure change value and the user respiratory flow rate estimate signal.

40. The breathing device according to any one of claims 1 to 39, wherein, The controller is configured to determine a smoothness value indicating or representing the smoothness of the minute ventilation data, the minute ventilation data indicating or representing the average gas volume provided per minute by the flow generator.

41. The breathing device according to claim 40, wherein, The controller is configured to determine the work of breathing metric at least in part based on the nasal pressure change value and the smoothness value.

42. The breathing device according to any one of claims 1 to 41, wherein, The device further includes a display screen, and preferably wherein the display screen displays a graphical user interface, and / or preferably wherein the display screen is in electrical communication with the controller.

43. The breathing apparatus according to claim 42, wherein, The display screen is removable from the device or the housing of the device.

44. The breathing device according to claim 42 or claim 43, wherein, The controller is configured to display a graphical metric representing the determined work of breathing metric on the display screen.

45. The breathing device according to claim 44, wherein, The graphical metric includes any one or more of the following: a numerical value, text, a waveform, an illustration, or an animation.

46. The breathing apparatus according to claim 44 or claim 45, wherein, The graphical metric indicates or represents whether the determined work of breathing metric is increasing or decreasing.

47. The breathing device according to any one of claims 1 to 46, wherein, The controller is configured to trigger or generate a warning, an alarm, and / or a notification at least in part based on the determined work of breathing metric and one or more thresholds.

48. The breathing device according to claim 47, wherein, The warning, the alarm, and / or the notification is triggered or generated at least in part based on determining that the work of breathing metric has increased above a threshold.

49. The breathing apparatus according to claim 47 or claim 48, wherein, The warning, the alarm, and / or the notification is triggered or generated at least in part based on determining that the work of breathing metric has decreased below a threshold.

50. The breathing device according to claim 49, wherein, The threshold is a disconnection detection threshold.

51. The breathing device according to claim 50, wherein, The warning, the alarm, and / or the notification is triggered or generated at least in part based on determining that the work of breathing metric has continuously decreased below the threshold for an associated predetermined duration condition.

52. The breathing device according to any one of claims 47 to 51, wherein, The controller is configured to generate the warning, the alarm, and / or the notification in a form selected from any one or more of the following: auditory, visual, and / or tactile.

53. The breathing device according to claim 52, wherein, The device further includes an audio output device in electrical communication with the controller, and wherein the controller is configured to audibly generate the warning, the alarm, and / or the notification via the audio output device.

54. The breathing device according to claim 52 or claim 53, wherein, The controller is configured to visually generate the warnings, alerts, and / or notifications via a display screen of the device.

55. The breathing device according to any one of claims 52 to 54, wherein, The controller is configured to send or transmit data representative of the warnings, alerts, and / or notifications to a remote device or system that communicates data with the device.

56. The breathing device according to any one of claims 47 to 55, wherein, The controller is operable to configure or adjust any parameter of or associated with the one or more thresholds at least in part based on user input via a graphical user interface of the display screen of the device.

57. The breathing device according to any one of claims 47 to 56, wherein, The controller is configured to generate or provide a recommended threshold and / or parameter associated with the one or more thresholds at least in part based on the work of breathing metric.

58. The breathing device according to any one of claims 1 to 57, wherein, The controller is further configured to determine a ratio or percentage of a work of breathing metric of the user relative to a nominal equivalent work of breathing metric of a nominal average healthy person.

59. The breathing apparatus according to claim 58, wherein, The nominal equivalent work of breathing metric is determined at least in part based on a magnitude of a nominal nasal pressure change of the nominal average healthy person.

60. The breathing apparatus according to claim 59, wherein, The magnitude of the nominal nasal pressure change of the nominal average healthy person is determined at least in part based on predetermined physiological parameters of the nominal average healthy person.

61. The breathing device according to claim 59 or claim 60, wherein, The magnitude of the nominal nasal pressure change of the nominal average healthy person is determined at least in part based on manually input physiological parameters associated with the user.

62. The breathing device according to any one of claims 59 to 61, wherein, The magnitude of the nominal nasal pressure change of the nominal average healthy person is determined at least in part based on a nominal measure of nostril occlusion by a nominal nasal cannula prong of a patient interface.

63. The breathing device according to any one of claims 59 to 62, wherein, The magnitude of the nominal nasal pressure change of the nominal average healthy person is determined at least in part based on a manually input measure of nostril occlusion by a nasal cannula prong of a patient interface.

64. The breathing device according to any one of claims 58 to 63, wherein, The controller is configured to generate one or more warnings, alerts, and / or notifications at least in part based on: a value of a ratio or percentage of a work of breathing metric of the user relative to a nominal equivalent work of breathing metric of a nominal average healthy person or associated trend data of the ratio or percentage, and one or more thresholds.

65. The breathing device according to any one of claims 58 to 64, wherein, The controller is configured to visually display on a display screen of the device the value of the ratio or percentage and / or trend data relating to the ratio or percentage.

66. The breathing device according to any one of claims 58 to 65, wherein, The controller is configured to generate warnings, alerts, and / or notifications including data indicative of a recommended adjustment to one or more treatment settings and / or device settings at least in part based on: a value of a ratio or percentage of a work of breathing metric of the user relative to a nominal equivalent work of breathing metric of a nominal average healthy person or associated trend data of the ratio or percentage, and one or more thresholds.

67. The breathing device according to claim 66, wherein, The treatment settings and / or device settings include a flow rate setting and / or an oxygen concentration setting of a gas flow.

68. The breathing device according to any one of claims 1 to 67, wherein, The device further includes a housing, and wherein the housing includes or incorporates the following: The flow generator; A humidifier configured to heat and humidify the gas flow; A sensing block or sensor module including the one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and The controller.

69. The breathing device according to claim 68, wherein, The sensing block or sensor module includes a flow rate sensor and a pressure sensor.

70. A method of controlling a respiratory device configured to provide a gas flow to a user for respiratory therapy, the device comprising: a flow generator configured to generate the gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; and a controller, wherein the method is performed or implemented by the controller and comprises the steps of: receiving the flow parameter data; determining a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determining a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and initiating one or more actions at least in part based on the determined WOB metric.

71. A respiratory therapy system configured to provide a gas flow to a user for respiratory therapy, the respiratory therapy system comprising: a flow generator configured to generate the gas flow for the user; one or more sensors configured to generate flow parameter data indicative of or representative of the gas flow; a breathing conduit operatively coupled to the flow generator and configured to convey the gas flow from the flow generator to the user; a patient interface operatively coupled to the breathing conduit; and a controller, wherein the controller is configured to: receive the flow parameter data; determine a nasal pressure change value indicative of the average nasal pressure of the user at least in part based on the received flow parameter data; determine a work of breathing (WOB) metric at least in part based on the determined nasal pressure change value; and initiating one or more actions at least in part based on the determined WOB metric.

72. A respiratory device comprising: a flow generator configured to generate a gas flow for a user; one or more sensors configured to generate flow parameter data indicative of or representative of a characteristic or parameter of the gas flow; and a controller configured to: control the flow generator to deliver the gas flow for high flow nasal therapy; determine a work of breathing (WOB) metric at least in part based on the flow parameter data; and initiating one or more actions at least in part based on the determined WOB metric.

73. The breathing device according to claim 72, wherein, The flow parameter data includes pressure data indicative of or representative of the pressure of the gas flow.

74. The breathing device according to claim 73, wherein, The pressure data is sensed and generated by one or more pressure sensors in data communication with the controller.

75. The breathing device according to claim 74, wherein, The one or more pressure sensors are configured to sense and generate pressure data indicative of or representative of the pressure of the gas flow at the outlet of the blower of the flow generator.

76. The breathing device according to any one of claims 72 to 75, wherein, The flow parameter data includes flow rate data indicative of or representative of the flow rate of the gas flow.

77. The breathing apparatus according to claim 76, wherein, The flow rate data is sensed and generated by one or more flow rate sensors in data communication with the controller.

78. The breathing device according to claim 77, wherein, The one or more flow rate sensors are located at or near the outlet of the blower of the flow generator.

79. The breathing device according to any one of claims 72 to 78, wherein, The WOB metric is determined based at least in part on flow parameter data, the flow parameter data including sensed pressure and / or flow rate data related to the gas flow.

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