Systems and methods for positioning a patient's mandible in response to sleep apnea status

Patent metadata

Field	Value
Publication number	US-2016199215-A1
Application number	US-201614992175-A
Country	US
Kind code	A1
Filing date	Jan 11, 2016
Priority date	Jan 13, 2015
Publication date	Jul 14, 2016
Grant date	—

Abstract

Systems, methods, devices, and apparatus for positioning a patient's mandible in response to sleep apnea status are provided herein. In one aspect, a system for monitoring and treating sleep apnea in a patient comprises one or more sensors configured to monitor the patient for symptoms associated with sleep apnea; an intraoral appliance worn by the patient, one or more processors, and memory comprising instructions executable by the one or more processors to cause the one or more processors to: receive a set of sensor data from the one or more sensors, detect, using a machine learning algorithm, onset of a sleep apnea event based on the set of sensor data, and transmit a control signal to the intraoral appliance to cause the intraoral appliance to displace a lower jaw of the patient from a first position to a second position in order to treat the sleep apnea event.

First claim

What is claimed is:

1 . A system for monitoring and treating sleep apnea in a patient, the system comprising:
one or more sensors configured to monitor the patient for symptoms associated with sleep apnea; an intraoral appliance wearable by the patient; one or more processors; and memory comprising instructions executable by the one or more processors to cause the one or more processors to:
receive a set of sensor data from the one or more sensors,
detect, using a machine learning algorithm, onset of a sleep apnea event based on the set of sensor data, and
transmit a control signal to the intraoral appliance to cause the intraoral appliance to displace a lower jaw of the patient from a first position to a second position in order to treat the sleep apnea event.

2 . The system of claim 1 , wherein the one or more sensors are configured to measure one or more of breathing sounds, snoring sounds, breathing rate, respiratory air flow, chest expansion, oxygen level, cardiac data, or sleeping position, or combinations thereof.

3 . The system of claim 1 , wherein the machine learning algorithm is customized to the patient using data of previous sleep patterns of the patient.

4 . The system of claim 3 , wherein the instructions further cause the system to:
identify a discrepancy between a current sleeping pattern of the patient and the previous sleep patterns of the patient; and generate an alert indicative of the discrepancy.

5 . The system of claim 1 , wherein the first position is a habitual jaw position and the second position is an advanced jaw position.

6 . The system of claim 5 , wherein the instructions further cause the system to:
receive a second set of sensor data from the one or more sensors; detect, using the machine learning algorithm, termination of the sleep apnea event based on the second set of sensor data; and transmit a second control signal to the intraoral appliance to cause the intraoral appliance to displace the lower jaw of the patient from the second position to the first position.

7 . The system of claim 1 , wherein the instructions further cause the system to determine the second position for the lower jaw using the machine learning algorithm.

8 . The system of claim 7 , wherein the instructions further cause the system to:
receive a third set of sensor data from the one or more sensors while the lower jaw is in the second position; and determine effectiveness of the second position of the lower jaw in treating the sleep apnea event based on the third set of sensor data.

9 . The system of claim 8 , wherein the instructions further cause the system to update the machine learning algorithm based on the determined effectiveness.

10 . The system of claim 8 , wherein the instructions further cause the system to:
determine, using the machine learning algorithm, a modified position of the lower jaw to improve the effectiveness of treating the sleep apnea event; and transmit a third control signal to the intraoral appliance to displace the lower jaw to the modified position.

11 . A method for monitoring and treating sleep apnea in a patient, the method comprising:
receiving a set of sensor data from one or more sensors configured to monitor the patient for symptoms associated with sleep apnea; detecting, using a machine learning algorithm executed by one or more processors, onset of a sleep apnea event based on the set of sensor data; and transmitting a control signal to an intraoral appliance worn by the patient to cause the intraoral appliance to displace a lower jaw of the patient from a first position to a second position in order to treat the sleep apnea event.

12 . The method of claim 11 , wherein the one or more sensors are configured to measure one or more of breathing sounds, snoring sounds, breathing rate, respiratory air flow, chest expansion, oxygen level, cardiac data, or sleeping position, or combinations thereof.

13 . The method of claim 11 , wherein the machine learning algorithm is customized to the patient using data of previous sleep patterns of the patient.

14 . The method of claim 13 , further comprising:
identifying a discrepancy between a current sleeping pattern of the patient and the previous sleep patterns of the patient; and generating an alert indicative of the discrepancy.

15 . The method of claim 11 wherein the first position is a habitual jaw position and the second position is an advanced jaw position.

16 . The method of claim 15 , further comprising:
receiving a second set of sensor data from the one or more sensors; detecting, using the machine learning algorithm, termination of the sleep apnea event based on the second set of sensor data; and transmitting a second control signal to the intraoral appliance to cause the intraoral appliance to displace the lower jaw of the patient from the second position to the first position.

17 . The method of claim 11 , further comprising determining the second position for the lower jaw using the machine learning algorithm.

18 . The method of claim 17 , further comprising:
receiving a third set of sensor data from the one or more sensors while the lower jaw is in the second position; and determining effectiveness of the second position of the lower jaw in treating the sleep apnea event based on the third set of sensor data.

19 . The method of claim 18 , further comprising updating the machine learning algorithm based on the determined effectiveness.

20 . The method of claim 18 , further comprising:
determining, using the machine learning algorithm, a modified position of the lower jaw to improve the effectiveness of treating the sleep apnea event; and transmitting a third control signal to the intraoral appliance to displace the lower jaw to the modified position.

Assignees

• Align Technology Inc

Inventors

• Kopelman Avi

Classifications

• A61F5/566 Primary

  Intra-oral devices · CPC title