Systems, methods and apparatuses for the alleviation and outcome monitoring of sleep disordered breathing

• US 10,219,740 B2
• Filed: 03/13/2015
• Issued: 03/05/2019
• Est. Priority Date: 03/13/2014
• Status: Active Grant

• Current Assignee: Halare, Inc.
• Original Assignee: Halare, Inc.
• Inventors: Warren, Anthony C., Goldschmidt, Kyle H.
• Primary Examiner(s): Kahelin, Michael W
• Application Number:
  US15/124,418
• Publication Number:
  US 20170172494A1
• Time in Patent Office: 1,453 Days
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/4833 Assessment of subject's compliance to treatment
• CPC Class Codes: A61B 5/4848 Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation

Abstract

Systems and methods for determining the effectiveness of breath training regimens are disclosed. The systems include a sensor assembly configured to detect data indicative of at least one physiological parameter of a user during breath training sessions while the user is awake and while the user is asleep. The system also includes an electronic computing unit with a processor configured to analyze the data indicative of the at least one physiological parameter of the user detected by the sensor assembly, and determine effectiveness of the breath training sessions on the user by determining trends of the at least one physiological parameter of the user from the analyzed data, and determining changes in the at least one physiological parameter of the user while the user is asleep occurring during a period of time from the determined trends.

Claims

1. A system for monitoring sleep disordered breathing, the system comprising:

a sensor assembly configured to detect data indicative of at least one physiological parameter of a user during breath training sessions occurring while the user is awake, the breath training sessions including voluntary breath holding occurrences, and to detect data indicative of at least one physiological parameter obtained while the user is asleep,

an electronic computing unit comprising;

a processor configured to;

analyze the data indicative of the at least one physiological parameter obtained by the sensor assembly while the user is asleep and the at least one physiological parameter of a user during the breath training sessions occurring while the user is awake,

determine effectiveness of the breath training sessions occurring while the user is awake by;

determining trends of the at least one physiological parameter obtained while the user is asleep from the analyzed data and determining trends of the voluntary breath holding occurrences obtained during the breath training session, and

determining changes in the at least one physiological parameter obtained while the user is asleep during a period of time from the determined trends by determining a number of sleep disorder events occurring over the period of time and by determining if the frequency of the number of sleep disorder events is changing; and

an output unit configured to provide, to the user, information regarding the determined effectiveness of the breath training sessions.

2. The system of claim 1, wherein the sensor assembly further comprises:

a first sensor module configured to detect the data indicative of at least one physiological parameter of the user during breath training sessions while the user is awake; and

a second sensor module configured to detect the data indicative of at least one physiological parameter of the user while the user is asleep.

3. The system of claim 1, wherein the sleep disordered breathing includes at least one of apnea and hypopnea.

4. The system of claim 1, wherein the sensor assembly further comprises at least one of a pulse-rate sensor, a blood oxygen concentration sensor, and a motion sensor.

5. The system of claim 1, wherein the at least one physiological parameter of the user includes heart rate (HR), oxygen saturation (O₂Sat) of the user, and motion of the user'"'"'s body while the user is asleep.

6. The system of claim 1, further comprising a transmitter coupled to the sensor assembly and configured to communicate the data indicative of at least one physiological parameter of the user from the sensor assembly to the electronic computing unit.

7. The system of claim 1, wherein in the determined trends include trends of at least one of Heart Rate Variability (HRV), periods of movement during sleep, involuntary apnea occurrences and hypopnea occurrences, and O₂Sat of the user.

8. The system of claim 1, wherein the determined changes include changes in at least one of Heart Rate Variability (HRV), voluntary breath holding occurrences, periods of movement during sleep, involuntary apnea occurrences and hypopnea occurrences, and O₂Sat of the user.

9. The system of claim 1, wherein the processor is further configured to determine, from at least one of the determined trends and the determined changes, at least one of:

the user'"'"'s compliance with a prescribed regimen including the breath training sessions, existence of improvements for the user over time during the breath training sessions and while asleep in at least one of HRV, voluntary breath holding occurrences, periods of movement, involuntary apnea occurrences, involuntary hypopnea occurrences, and O₂Sat levels of the user, and

courses of action for reducing the user'"'"'s symptoms and the sleep disordered breathing experienced by the user.

10. The system of claim 1, wherein the information provided to the user includes at least one of information about:

the user'"'"'s compliance with a prescribed regimen including the breath training sessions, existence of improvements for the user over time during the breath training sessions and while asleep in at least one of HRV, voluntary breath holding occurrences, periods of movement, involuntary apnea occurrences, involuntary hypopnea occurrences, and O₂Sat levels of the user, and

courses of action for reducing the user'"'"'s symptoms and the sleep disordered breathing experienced by the user.

11. The system of claim 2, wherein the second sensor module includes a motion sensor for detecting motion of the user'"'"'s body while the user is asleep.

12. A method for monitoring sleep disordered breathing in a user, the method comprising the steps of:

detecting, with a sensor assembly, data indicative of at least one physiological parameter of a user during breath training sessions occurring while the user is awake, the breath training sessions including voluntary breath holding occurrences, and data indicative of at least one physiological parameter obtained while the user is asleep,

analyzing, with a processor in an electronic computing unit, the data indicative of the at least one physiological parameter obtained by the sensor assembly while the user is asleep and the at least one physiological parameter of a user during the breath training sessions occurring while the user is awake,

determining, with the processor, effectiveness of the breath training sessions occurring while the user is awake by;

determining trends of the at least one physiological parameter obtained while the user is asleep from the analyzed data and determining trends of the voluntary breath holding occurrences obtained during the breath training session, and

determining changes in the at least one physiological parameter obtained while the user is asleep during a period of time from the determined trends by determining a number of sleep disorder events occurring over the period of time and by determining if the frequency of the number of sleep disorder events is changing; and

providing, with an output unit, information to the user regarding the determined effectiveness of the breath training sessions.

13. The method of claim 12, wherein the method further comprises the step of determining from at least one of the determined trends and the determined changes, with the processor, at least one of:

the user'"'"'s compliance with a prescribed regimen including the breath training sessions, existence of improvements for the user over time during the breath training sessions and while asleep in at least one of HRV, voluntary breath holding occurrences, periods of movement, involuntary apnea occurrences, involuntary hypopnea occurrences, and O₂Sat levels of the user, and

courses of action for reducing the user'"'"'s symptoms and the sleep disordered breathing experienced by the user.

14. The method of claim 12, wherein the method further comprises the step of detecting, with the processor, occurrences and severity of at least one of involuntary apnea events and involuntary hypopnea events, by combining two or more measurements derived from the data indicative of the at least one physiological parameter of the user.

15. The method of claim 12, wherein the method further comprises the step of detecting, with the processor, occurrences and severity of at least one of voluntary apnea events and voluntary hypopnea events, by combining two or more measurements derived from the data indicative of the at least one physiological parameter of the user.

16. The method of claim 12, wherein the information provided to the user includes at least one of information about:

the user'"'"'s compliance with a prescribed regimen including the breath training sessions, existence of improvements for the user over time during the breath training sessions and while asleep in at least one of HRV, voluntary breath holding occurrences, periods of movement, involuntary apnea occurrences, involuntary hypopnea occurrences, and O₂Sat levels of the user, and

courses of action for reducing the user'"'"'s symptoms and the sleep disordered breathing experienced by the user.

17. The method of claim 12, wherein the method further comprises the step of storing, with a memory unit, at least one of the data indicative of the at least one physiological parameter of the user detected by the sensor assembly, the analyzed data, and the determined effectiveness of the breath training sessions.

18. The method of claim 12, wherein the method further comprises the steps of:

detecting, at a first sensor module incorporated into the sensor assembly, the data indicative of at least one physiological parameter of a user during breath training sessions while the user is awake; and

detecting, at a second sensor module incorporated into the sensor assembly, the data indicative of at least one physiological parameter of a user while the user is asleep.

19. The method of claim 12, wherein the determining the effectiveness of the breath training regimen further comprises determining changes in sleep patterns in a person that sleeps in the vicinity of the user.