Systems and methods for promoting a sleep stage of a user

1 . A method comprising:

determining a current sleep stage of a user during a sleep session, the user using a respiratory therapy system during the sleep session, wherein a desired sleep stage is selected from N1, N2, N3, and REM;

predicting an undesired sleep stage upcoming for the user during the sleep session based, at least in part, on (i) one or more user parameters, information from one or more previous sleep sessions, or a combination thereof, and (ii) the current sleep stage; and

adjusting one or more control parameters of the respiratory therapy system by sending control signals to the respiratory therapy system to change at least one of blower motor speed, pressure level, flow level, vent valve configuration, humidification level, or conduit temperature during the sleep session to promote the desired sleep stage of the user selected from N1, N2, N3, and REM, thereby optimizing sleep of the user.

2 . The method of claim 1 , wherein the information from the one or more previous sleep sessions includes one or more sleep profiles comprising one or more flow levels, one or more humidity levels, one or more temperature levels, one or more leak levels, one or more apnea-hypopnea indexes, a number of therapy sessions using a respiratory therapy system, a duration of therapy sessions using the respiratory therapy system, a change in location of the user, a change in position of the user, or a combination thereof, and the one or more user parameters include a number of apneas, a number of hypopneas, snoring levels, mask leak levels, duration of current usage of the respiratory therapy system, carbon dioxide levels in exhaled breath, sleep time, sleep stages, cardiac parameters, gross bodily movement levels, one or more micro-arousals, or a combination thereof during the sleep session.

3 . The method of claim 1 , wherein the predicting of the undesired sleep stage comprises:

estimating an expected progression of the user's sleep through a sleep architecture of the user during a remainder of the sleep session; and

comparing the expected progression of the user's sleep to a model of an expected sleep architecture for a normalized healthy sleeper to check if the expected progression of the user's sleep deviates from a normalized healthy sleeper.

4 . The method of claim 1 , further comprising:

conducting a plurality of simulations using one or more models of sleep architecture adjustment to estimate whether the adjusting of the one or more control parameters is likely to promote or maintain the desired sleep stage, prior to the adjusting of the one or more control parameters.

5 . The method of claim 4 , further comprising tracking an outcome of the adjusting of the one or more control parameters to validate an efficacy of the one or more models.

6 . The method of claim 5 , further comprising updating the one or more models based on the outcome of the adjusting of the one or more control parameters to improve the one or more models with respect to optimizing the sleep of the user.

7 . The method of claim 1 , further comprising monitoring the one or more user parameters, the respiratory therapy system, an environment of the user, or a combination thereof to determine whether one or more events occur that satisfy a sleep disturbance threshold.

8 . The method of claim 7 , further comprising disregarding the one or more user parameters, the one or more control parameters of the respiratory therapy system, the one or more control parameters of one or more devices in the environment of the user, or a combination thereof for a threshold period of time after the one or more events for training one or more models that determine the one or more control parameters.

9 . The method of claim 1 , wherein the predicting is performed, at least in part, by one or more pre-trained or dynamic models trained using one or more desired sleep architectures, the method further comprising updating the one or more pre-trained or dynamic models based, at least in part, on an outcome of the adjusting of the one or more control parameters.

10 . The method of claim 1 , further comprising adjusting one or more control parameters of one or more devices in an environment of the user, the one or more control parameters of the one or more devices in the environment of the user include a light level, a sound level, a room temperature level, a humidity level, an electrical stimulation, a sound masking or sound cancellation level, a bed level, a pillow inflation, a mattress inflation zone to cause the user to change position, a bed temperature, a scent, or a combination thereof of the environment of the user.

11 . A method comprising:

determining a current sleep stage of a user during a sleep session, the user using a respiratory therapy system during the sleep session, wherein a desired sleep stage is selected from N1, N2, N3, and REM; and

adjusting one or more control parameters of the respiratory therapy system by sending control signals to the respiratory therapy system to change at least one of blower motor speed, pressure level, flow level, vent valve configuration, humidification level, or conduit temperature during the sleep session to promote the desired sleep stage of the user selected from N1, N2, N3, and REM over the current sleep stage, thereby optimizing sleep of the user.

12 . The method of claim 11 , wherein the desired sleep stage is desired over the current sleep stage based on a desired progression of the user through an optimal sleep architecture during the sleep session.

13 . The method of claim 11 , further comprising determining a length of time a user has been within a current sleep cycle during the sleep session, wherein the adjusting of the one or more control parameters occurs based on the length of time.

14 . The method of claim 13 , wherein the desired sleep stage is determined based, at least in part, on the length of time the user has been within the current sleep cycle, a number of previous sleep cycles of the user during the sleep session, or a combination thereof.

15 . The method of claim 13 , wherein the desired sleep stage is determined based on, at least in part, a number of previous sleep cycles of the user during the sleep session.

16 . A system comprising:

a memory storing machine-readable instructions; and

a control system including one or more processors configured to execute the machine-readable instructions to:

determine a current sleep stage of a user during a sleep session, the user using a respiratory therapy system during the sleep session, wherein a desired sleep stage is selected from N1, N2, N3, and REM;

predict an undesired sleep stage upcoming for the user during the sleep session based, at least in part, on one or more user parameters, information from one or more previous sleep sessions, or a combination thereof, and the current sleep stage; and

adjust one or more control parameters of the respiratory therapy system by sending control signals to the respiratory therapy system to change at least one of blower motor speed, pressure level, flow level, vent valve configuration, humidification level, or conduit temperature during the sleep session to promote the desired sleep stage of the user selected from N1, N2, N3, and REM, thereby optimizing sleep of the user.

17 . The system of claim 16 , wherein the information from the one or more previous sleep sessions includes one or more sleep profiles comprising one or more flow levels, one or more humidity levels, one or more temperature levels, one or more leak levels, one or more apnea-hypopnea indexes, a number of therapy sessions using a respiratory therapy system, a duration of therapy sessions using the respiratory therapy system, a change in location of the user, a position of the user, or a combination thereof, and the one or more user parameters include a number of apneas, a number of hypopneas, snoring levels, mask leak levels, duration of current usage of a respiratory therapy system, carbon dioxide levels in exhaled breath, sleep time, sleep stages, cardiac parameters, gross bodily movement levels, one or more micro-arousals, or a combination thereof during the sleep session.

18 . The system of claim 16 , wherein, for the predicting of the undesired sleep stage, the control system further is configured to execute the machine-readable instructions to:

estimate an expected progression of the user's sleep through a sleep architecture of the user during a remainder of the sleep session; and

compare the expected progression of the user's sleep to a model of an expected sleep architecture for a normalized healthy sleeper to check if the expected progression of the user's sleep deviates from a normalized healthy sleeper.

19 . The system of claim 16 , wherein the control system further is configured to execute the machine-readable instructions to conduct a plurality of simulations using one or more models of sleep architecture adjustment to estimate whether the adjusting of the one or more control parameters is likely to promote or maintain the desired sleep stage, prior to the adjusting of the one or more control parameters.

20 . The system of claim 19 , wherein the control system further is configured to execute the machine-readable instructions to track an outcome of the adjusting of the one or more control parameters to validate an efficacy of the one or more models.

21 . The system of claim 20 , wherein the control system further is configured to execute the machine-readable instructions to update the one or more models based on the outcome of the adjusting of the one or more control parameters to improve the one or more models with respect to optimizing the sleep of the user.

22 . The system of claim 16 , wherein the control system further is configured to execute the machine-readable instructions to monitor the one or more user parameters, the respiratory therapy system, an environment of the user, or a combination thereof to determine whether one or more events occur that satisfy a sleep disturbance threshold.

23 . The system of claim 22 , wherein the control system further is configured to execute the machine-readable instructions to disregard the one or more user parameters, the one or more control parameters of the respiratory therapy system, the one or more control parameters of one or more devices in the environment of the user, or a combination thereof for a threshold period of time after the one or more events for training one or more models that determine the one or more control parameters.

24 . The system of claim 16 , wherein the machine-readable instructions configure the control system to predict based, at least in part, on one or more pre-trained or dynamic models trained using one or more desired sleep architectures, and the control system further is configured to execute the machine-readable instructions to update the one or more pre-trained or dynamic models based, at least in part, on an outcome of the adjusting of the one or more control parameters.

25 . The system of claim 16 , wherein the control system including the one or more processors is further configured to adjust one or more control parameters of one or more devices in an environment of the user, the one or more control parameters of the one or more devices in the environment of the user include a light level, a sound level, a room temperature level, a humidity level, a sound level, an electrical stimulation, a sound masking or sound cancellation level, a bed level, a pillow inflation, a mattress inflation zone to cause the user to change position, a bed temperature, a scent, or a combination thereof of the environment of the user.