IP Library Granted Patent US 12,721,567
Granted Patent B2
US 12,721,567 · App. 17/915,779 · Granted Sep 1, 2026

Systems and methods for detecting REM behavior disorder

Inventors: Roxana Tiron (Dublin, IE); Ehsan Chah (Dublin, IE); Hannah Meriel Kilroy (Dublin, IE); Marta Perez Denia (Dublin, IE); Kieran Conway (Dublin, IE)
Assignee: ResMed Sensor Technologies Limited
A61B5/4812A61B5/0816A61B5/1114A61B5/4803A61B5/4815A61B5/7246A61B5/7267G16H10/60G16H40/67
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,721,567
App. No.
17/915,779
Granted
Sep 1, 2026
Kind
B2
Abstract

A method for monitoring a sleep session of an individual comprises receiving data associated with a current sleep session of the individual; analyzing at least a portion of the received data to identify one or more sleep stages experienced by the individual during the current sleep session, the one or more sleep stages including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stage, a wake stage, or any combination thereof; and generating a summary of the current sleep session, the summary including (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).

Claims (75)

1 . A method for monitoring a sleep session of an individual, the method comprising:

receiving data associated with a current sleep session of the individual, the data including temporal data associated with the current sleep session;

analyzing at least a portion of the received data to identify one or more sleep stages experienced by the individual during the current sleep session, the one or more sleep stages including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stage, a wake stage, or any combination thereof, the analyzing including distinguishing between one or more atypical REM sleep stages and one or more wake stages based at least in part on the temporal data; and

generating a summary of the current sleep session, the summary including (i) a number of the one or more atypical REM sleep stages experienced by the individual during the current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).

2 . The method of claim 1 , wherein the received data further includes (i) respiration data, (ii) motion data indicative of motion of the individual during the current sleep session, (iii) audio data indicative of sound detected during the current sleep session, (iv) optical data indicative of light in an area where the individual is located during the sleep session, or (v) any combination thereof.

3 . The method of claim 2 , wherein distinguishing between the one or more atypical REM sleep stages and the one or more wake stages includes:

tracking a time elapsed since a beginning of the current sleep session based at least in part on the temporal data;

analyzing the motion data to detect if the individual is currently moving;

in response to a first amount of time having elapsed since the beginning of the current sleep session and detecting the individual is currently moving, determining that the individual is currently in the wake stage; and/or

in response to a second amount of time having elapsed since the beginning of the current sleep session and detecting the individual is currently moving, determining that the individual is currently in the atypical REM sleep stage, the second amount of time being greater than the first amount of time.

4 . The method of claim 2 , further comprising:

determining an amount of movement of the individual during the sleep session based on the motion data;

determining a respiration rate or a respiration rate variability of the individual during the sleep session based on the respiration data;

in response to determining that the amount of movement of the individual is less than a threshold amount of movement and that the respiration rate or the respiration rate variability of the individual is greater than a threshold respiration rate or a threshold respiration rate variability, determining that the individual is not in a typical REM sleep stage; and/or

in response to determining that the amount of movement of the individual is greater than the threshold amount of movement and that the respiration rate or the respiration rate variability of the individual is greater than the threshold respiration rate or the threshold respiration rate variability, determining that the individual is in an atypical REM sleep stage.

5 . The method of claim 2 , wherein distinguishing between the one or more atypical REM sleep stages and the one or more wake stages includes:

determining an amount of movement of the individual during the sleep session based on the motion data;

determining a light level of the area where the individual is located during the sleep session based on the optical data;

in response to determining that the amount of movement of the individual is greater than a threshold amount of movement and that the light level of the area where the individual is located is greater than a threshold light level, determining that the individual is in a wake stage; and/or

in response to determining that the amount of movement of the individual is greater than the threshold amount of movement and that the light level of the area where the individual is located is less than the threshold light level, determining that the individual is in an atypical REM sleep stage.

6 . The method of claim 2 , wherein distinguishing between the one or more atypical REM sleep stages and the one or more wake stages includes:

determining whether the sound detected during the current sleep session is speech made by the individual;

determining a light level of the area where the individual is located during the sleep session based on the optical data;

in response to determining that the detected sound is speech made by the individual and that the light level of the area where the individual is located is greater than a threshold light level, determining that the individual is in a wake stage; and/or

in response to determining that the detected sound is speech made by the individual and that the light level of the area where the individual is located is less than the threshold light level, determining that the individual is in an atypical REM sleep stage.

7 . The method of claim 2 , wherein distinguishing between the one or more atypical REM sleep stages and the one or more wake stages includes:

determining whether the sound detected during the current sleep session is speech made by the individual;

determining a time elapsed during the current sleep session based at least in part on the temporal data;

in response to determining that the detected sound is speech made by the individual and that the time elapsed during the current sleep session is less than a threshold time, determining that the individual is in a wake stage; and/or

in response to determining that the detected sound is speech made by the individual and that the time elapsed during the current sleep session is greater than the threshold time, determining that the individual is in an atypical REM sleep stage.

8 . The method of claim 2 , wherein distinguishing between the one or more atypical REM sleep stages and the one or more wake stages includes:

determining an amount of movement of the individual during the sleep session based on the motion data;

determining a time elapsed during the current sleep session based at least in part on the temporal data;

in response to determining that the amount of movement of the individual is greater than a threshold amount of movement and that the time elapsed during the current sleep session is less than a threshold time, determining that the individual is in a wake stage; and/or

in response to determining that the amount of movement of the individual is greater than a threshold amount of movement and that the time elapsed during the current sleep session is greater than the threshold time, determining that the individual is in an atypical REM sleep stage.

9 . The method of claim 2 , further comprising (i) determining an amount of movement of the individual during the sleep session based on the motion data, the amount of movement of the individual being above a threshold amount of movement indicating that the individual is in an atypical REM sleep stage, (ii) determining whether the detected sound is speech made by the individual, the detected sound being speech by the individual indicating that the individual is in an atypical REM sleep stage, (iii) determining a light level of the area where the individual is located during the sleep session, the determined light level being greater than a threshold light level indicating that the individual is in a wake stage, or (iv) any combination of (i)-(iii).

10 . The method of claim 1 , further comprising:

determining a time elapsed during the current sleep session based at least in part on the temporal data; and

based on one or more previous sleep stages already experienced by the individual during the sleep session and the time elapsed during the current sleep session, identifying a current sleep stage.

11 . The method of claim 1 , further comprising:

receiving historical data associated with one or more prior sleep sessions of the individual;

generating a historical summary of the one or more prior sleep sessions of the individual, the historical summary including a number of atypical REM sleep stages experienced by the individual during the one or more prior sleep sessions, and a time spent in atypical REM sleep stages during the one or more prior sleep sessions; and

comparing the historical summary of the one or more prior sleep sessions to the summary of the current sleep session, to aid in confirming the number of atypical REM sleep stages experienced by the individual during the current sleep session, and the time spent in atypical REM sleep stages during the current sleep session.

12 . The method of claim 1 , further comprising:

analyzing, using a trained dream enactment behavior (DEB) algorithm, at least the portion of the received data to determine whether the individual is undergoing DEB during the current sleep session; and

in response to a determination that the individual is undergoing DEB, causing an action to be performed, the action being configured to (i) aid in ending the DEB, (ii) aid in mitigating an impact of the DEB on the individual, (iii) aid in mitigating an impact of the DEB on a bed partner of the individual, or (iv) any combination thereof.

13 . The method of claim 12 , further comprising:

receiving historical data associated with one or more prior sleep sessions of the individual, the historical data including data related to confirmed instances of the individual undergoing DEB during at least one of the one or more prior sleep sessions; and

comparing the historical data associated with one or more prior sleep sessions to the data associated with the current sleep session, to aid in determining whether the individual is undergoing DEB during the current sleep session.

14 . The method of claim 12 , wherein the action includes activating a light source, activating an audible alarm, causing a bed on which the individual is lying to move, or causing the individual to be physically moved.

15 . The method of claim 1 , further comprising causing an action to be performed in response to the summary indicating that (i) the number of atypical REM sleep stages experienced by the individual during the current sleep session satisfies a threshold number, (ii) a time spent in atypical REM sleep stages during the current sleep session is greater than a threshold time, or (iii) both (i) and (ii).

16 . The method of claim 1 , wherein the analyzing includes:

selecting one or more unidentified sleep stages by determining, based on non-temporal data, that each respective unidentified sleep stage is either a wake stage or an atypical REM sleep stage;

for each respective unidentified sleep stage, determining a time elapsed within the sleep session based on a portion of the temporal data associated with the respective unidentified sleep stage; and

determining whether each respective unidentified sleep stage is a wake stage or an atypical REM sleep stage based on the time elapsed within the sleep session for the respective unidentified sleep stage.

17 . The method of claim 1 , wherein the data associated with the current sleep session of the individual further includes motion data, and wherein the analyzing includes:

determining that one or more unidentified sleep stages are either a wake stage or an atypical REM sleep stage by analyzing at least the motion data; and

determining a time elapsed within the sleep session for each respective unidentified sleep stage based on a portion of the temporal data associated with the respective unidentified sleep stage to determine whether each respective unidentified sleep stage is a wake stage or an atypical REM sleep stage.

18 . The method of claim 1 , wherein the data associated with the current sleep session of the individual further includes audio data, and wherein the analyzing includes:

determining that one or more unidentified sleep stages are either a wake stage or an atypical REM sleep stage by analyzing at least the audio data; and

determining a time elapsed within the sleep session for each respective unidentified sleep stage based on a portion of the temporal data associated with the respective unidentified sleep stage to determine whether each respective unidentified sleep stage is a wake stage or an atypical REM sleep stage.

19 . A system comprising:

an electronic interface configured to receive data associated with a current sleep session of an individual, the data including temporal data associated with the current sleep session;

a memory storing machine-readable instructions; and

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

analyze at least a portion of the received data to identify one or more sleep stages experienced by the individual during the current sleep session, the one or more sleep stages including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stage, a wake stage, or any combination thereof, the analyzing including distinguishing between one or more atypical REM sleep stages and one or more wake stages based at least in part on the temporal data; and

generate a summary of the current sleep session, the summary including (i) a number of the one or more atypical REM sleep stages experienced by the individual during the current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).

20 . A method for monitoring a sleep session of an individual, the method comprising:

receiving data associated with a current sleep session of the individual, the data including at least temporal data associated with the current sleep session and motion data indicative of motion of the individual during the current sleep session;

analyzing at least a portion of the received data to identify one or more sleep stages experienced by the individual during the current sleep session, the one or more sleep stages including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stage, a wake stage, or any combination thereof, the analyzing including:

tracking a time elapsed since a beginning of the current sleep session based at least in part on the temporal data;

analyzing the motion data to detect if the individual is currently moving;

in response to a first amount of time having elapsed since the beginning of the current sleep session and detecting the individual is currently moving, determining that the individual is currently in the wake stage; and/or

in response to a second amount of time having elapsed since the beginning of the current sleep session and detecting the individual is currently moving, determining that the individual is currently in the atypical REM sleep stage, the second amount of time being greater than the first amount of time; and

generating a summary of the current sleep session, the summary including (i) a number of atypical REM sleep stages experienced by the individual during the current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 30, 2022
From: TIRON, ROXANA; CHAH, EHSAN; KILROY, HANNAH MERIEL; PEREZ DENIA, MARTA; CONWAY, KIERAN
To: RESMED SENSOR TECHNOLOGIES LIMITED
Reel/Frame 061276/0817 →
Continuity (2)
Provisional Application 63003240 · Mar 31, 2020
Related Publication 20230240595A1 · Aug 3, 2023
References Cited (39)
US 10964195B1 · Huang · 2021 [cited by examiner]
US 11147505B1 · Shoeb · 2021 [cited by examiner]
US 11883188B1 · Kahn · 2024 [cited by examiner]
US 12016698B2 · Garcia Molina · 2024 [cited by examiner]
US 20080262373A1 · Burns et al. · 2008 [cited by applicant]
US 20110160603A1 · Langston et al. · 2011 [cited by applicant]
US 20120053508A1 · Wu et al. · 2012 [cited by applicant]
US 20140088373A1 · Phillips · 2014 [cited by examiner]
US 20150119741A1 · Zigel · 2015 [cited by examiner]
US 20150126821A1 · Kempfner et al. · 2015 [cited by applicant]
US 20170086732A1 · Tribble et al. · 2017 [cited by applicant]
US 20170273617A1 · Kaji · 2017 [cited by examiner]
US 20180242902A1 · Martinmäki · 2018 [cited by examiner]
US 20190069839A1 · Park et al. · 2019 [cited by applicant]
US 20190223781A1 · Arrington · 2019 [cited by examiner]
US 20200397365A1 · Zhang · 2020 [cited by examiner]
US 20230148956A1 · Narayanan · 2023 [cited by examiner]
CN 104812300A · 2015 [cited by applicant]
CN 106510663A · 2017 [cited by applicant]
CN 106691686A · 2017 [cited by applicant]
CN 107875496A · 2018 [cited by applicant]
CN 110366387A · 2019 [cited by applicant]
CN 110558946A · 2019 [cited by applicant]
EP 0773504A1 · 1997 [cited by examiner]
JP 201622310A · 2016 [cited by applicant]
JP 2019195469A · 2019 [cited by applicant]
JP 202022732B1 · 2020 [cited by applicant]
WO 2014047310A1 · 2014 [cited by applicant]
WO 2016061629A1 · 2016 [cited by applicant]
WO 2017132726A1 · 2017 [cited by applicant]
WO 2018050913A1 · 2018 [cited by applicant]
WO 2019122413A1 · 2019 [cited by applicant]
WO 2019122414A1 · 2019 [cited by applicant]
WO 2019212901A1 · 2019 [cited by applicant]
WO 2020104465A2 · 2020 [cited by applicant]
Howelll et al., “A Novel Therapy for REM Sleep Behavior Disorder (RBD)”, Journal of Clinical Sleep Medicine, 2011, vol. 7, No. 6, 639-644A. [cited by applicant]
International Search Report in International Patent Application No. PCT/IB2021/052669 mailed Jul. 2, 2021 (6 pp.). [cited by applicant]
Written Opinion in International Patent Application No. PCT/IB2021/052669 mailed Jul. 2, 2021 (8 pp.). [cited by applicant]
Cooray N. et al., “Detection of REM sleep behaviour disorder by automated polysomnography analysis”, Clinical Neurophysiology, vol. 130, No. 4; Feb. 6, 2019 (Feb. 6, 2019), pp. 505-514. [cited by applicant]