System and method for sleep disorder diagnosis and treatment

• US 10,265,013 B2
• Filed: 08/23/2016
• Issued: 04/23/2019
• Est. Priority Date: 09/06/2013
• Status: Active Grant

• Current Assignee: Somnology, Inc.
• Original Assignee: Somnology, Inc.
• Inventors: Lim, Melissa Susann
• Primary Examiner(s): Tomaszewski, Michael
• Application Number:
  US15/244,999
• Publication Number:
  US 20160367184A1
• Time in Patent Office: 973 Days
• Field of Search: None
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• 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 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/087 Measuring breath flow
• 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 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61M 2021/0027 by the hearing sense
• CPC Class Codes: A61M 21/02 for inducing sleep or relaxation, e.g. by direct nerve stimulation, hypnosis, analgesia for massage A61H; electrotherapy A61N, e.g. applying alternating or intermittent electric currents for producing anaesthesia A61N1/36021
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• 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
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment

Abstract

A system and method for sleep disorder diagnosis and treatment are disclosed. A particular embodiment is configured to: establish a wireless data communication interface between a networked data processor and a sleep metering system, the sleep metering system being worn by a user and including a sensor array, wireless transceiver, and a processor; activate the sleep metering system to begin collection of sensor data from the user based on data signals from the sensor array of the sleep metering system; and detect a sleep-related condition in the user by use of the sleep metering system, the detection of the sleep-related condition including detecting anomalies in breathing patterns of the user by wirelessly receiving a plurality of sets of breathing pattern data from the sleep metering system at a plurality of pre-defined time intervals within a single sleep period, the breathing pattern data corresponding to variations in the degree of the user'"'"'s chest cavity movement in a series of breaths over a given time interval, the detection of the sleep-related condition further including using the plurality of sets of breathing pattern data to score any detected respiratory effort reduction or exaggeration condition for a level of severity over the plurality of pre-defined time intervals.

Claims

1. A computer-implemented method for improving detection of sleep-related conditions, the method comprising:

establishing, by use of a data processor, a wireless data communication interface between the data processor and a sleep metering system worn by a user, the sleep metering system including a sensor array, wireless transceiver, and a processor;

positioning the sleep metering system for data recording externally at the top of the user'"'"'s abdomen, the sleep metering system being removably attached to the user with an inductive belt being a chest expansion and respiratory effort measuring device to detect and measure airflow and respiratory effort in the user;

collecting, by use of the sleep metering system, sensor data from the user based on data signals from the sensor array of the sleep metering system;

receiving, by use of the data processor, a single abdominal effort channel waveform based on the collected sensor data from the sleep metering system, the single abdominal effort channel waveform representing breathing pattern data corresponding to variations in the degree of the user'"'"'s abdominal effort in a series of breaths over a given time interval;

detecting, by use of the data processor, a sleep-related condition in the user by use of the breathing pattern data from the sleep metering system, the sleep-related condition including anomalies in breathing patterns of the user based on the breathing pattern data from the sleep metering system at a plurality of pre-defined time intervals within a single sleep period;

identifying, by use of the data processor, a respiratory effort reduction or exaggeration condition for a level of severity over the plurality of pre-defined time intervals using the breathing pattern data from the sleep metering system and the detected sleep-related condition; and

performing a dynamic re-configuration of the sleep metering system based on the detected sleep-related condition.

2. The method of claim 1 including generating a user interface as a web application.

3. The method of claim 1 including generating a user interface as a mobile application.

4. The method of claim 1 including generating a value on an Epworth Sleepiness Scale (ESS).

5. The method of claim 1 including generating a sleep report containing information and datasets generated using the sensor data captured and processed for the user.

6. The method of claim 1 including generating a sleep log including information indicative of the time when the user got into bed, the time when the user got out of bed, the time when the user actually fell asleep, and the time when the user woke up.

7. The method of claim 1 wherein the sensor array includes sensors of a type from the group consisting of:

a motion detection device, a sound detection device, a pulse oximeter device, and a respiratory effort detection device.

8. The method of claim 1 including generating a sleep efficiency score based on the sensor data captured and processed for the user.

9. The method of claim 1 including attaching the sleep metering system at the top of the user'"'"'s abdomen with a strap.

10. A system for improving detection of sleep-related conditions, the system comprising:

a networked data processor;

a memory, in data communication with the networked data processor;

a sleep metering system in wireless data communication with the networked data processor, the sleep metering system being worn by the user and including a sensor array, wireless transceiver, and a processor, the sleep metering system being positioned for data recording externally at the top of the user'"'"'s abdomen, the sleep metering system being removably attached to the user with an inductive belt being a chest expansion and respiratory effort measuring device to detect and measure airflow and respiratory effort in the user; and

a sleep disorder diagnosis and treatment system, executable by the networked data processor, to;

establish a wireless data communication interface between the networked data processor and the sleep metering system;

activate the sleep metering system to collect sensor data from the user based on data signals from the sensor array of the sleep metering system;

receive, at the networked data processor, a single abdominal effort channel waveform based on the collected sensor data from the sleep metering system, the single abdominal effort channel waveform representing breathing pattern data corresponding to variations in the degree of the user'"'"'s abdominal effort in a series of breaths over a given time interval;

detect a sleep-related condition in the user by use of the breathing pattern data from the sleep metering system, the sleep-related condition including anomalies in breathing patterns of the user based on the breathing pattern data from the sleep metering system at a plurality of pre-defined time intervals within a single sleep period;

identify, by use of the networked data processor, a respiratory effort reduction or exaggeration condition for a level of severity over the plurality of pre-defined time intervals using the breathing pattern data from the sleep metering system and the detected sleep-related condition; and

perform a dynamic re-configuration of the sleep metering system based on the detected sleep-related condition.

11. The system of claim 10 being further configured to generate a user interface as a web application.

12. The system of claim 10 being further configured to generate a user interface as a mobile application.

13. The system of claim 10 being further configured to generate a value on an Epworth Sleepiness Scale (ESS).

14. The system of claim 10 being further configured to generate a sleep report containing information and datasets generated using the sensor data captured and processed for the user.

15. The system of claim 10 being further configured to generate a sleep log including information indicative of the time when the user got into bed, the time when the user got out of bed, the time when the user actually fell asleep, and the time when the user woke up.

16. The system of claim 10 wherein the sensor array includes sensors of a type from the group consisting of:

a motion detection device, a sound detection device, a pulse oximeter device, and a respiratory effort detection device.

17. The system of claim 10 being further configured to generate a sleep efficiency score based on the sensor data captured and processed for the user.

18. The system of claim 10 including the sleep metering system being attached at the top of the user'"'"'s abdomen with a strap.

19. A non-transitory machine-useable storage medium embodying instructions which, when executed by a machine, cause the machine to:

establish a wireless data communication interface between a networked data processor and a sleep metering system, the sleep metering system being worn by a user and including a sensor array, wireless transceiver, and a processor, the sleep metering system being positioned for data recording externally at the top of the user'"'"'s abdomen, the sleep metering system being removably attached to the user with an inductive belt being a chest expansion and respiratory effort measuring device to detect and measure airflow and respiratory effort in the user;

activate the sleep metering system to collect sensor data from the user based on data signals from the sensor array of the sleep metering system;

receive, at the networked data processor, a single abdominal effort channel waveform based on the collected sensor data from the sleep metering system, the single abdominal effort channel waveform representing breathing pattern data corresponding to variations in the degree of the user'"'"'s abdominal effort in a series of breaths over a given time interval;

detect a sleep-related condition in the user by use of the breathing pattern data from the sleep metering system, the sleep-related condition including anomalies in breathing patterns of the user based on the breathing pattern data from the sleep metering system at a plurality of pre-defined time intervals within a single sleep period;

identify a respiratory effort reduction or exaggeration condition for a level of severity over the plurality of pre-defined time intervals using the breathing pattern data from the sleep metering system and the detected sleep-related condition; and

perform a dynamic re-configuration of the sleep metering system based on the detected sleep-related condition.

20. The machine-useable storage medium of claim 19 wherein the sensor array includes sensors of a type from the group consisting of:

a motion detection device, a sound detection device, a pulse oximeter device, and a respiratory effort detection device.