Detecting sleeping disorders

• US 10,105,092 B2
• Filed: 06/09/2016
• Issued: 10/23/2018
• Est. Priority Date: 11/16/2015
• Status: Active Grant

• Current Assignee: Eight Sleep, Inc
• Original Assignee: Eight Sleep, Inc
• Inventors: Franceschetti, Matteo, Bassi, Massimo Andreasi
• Primary Examiner(s): Kurilla, Eric J
• Application Number:
  US15/178,117
• Publication Number:
  US 20170135632A1
• Time in Patent Office: 866 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 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• 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 5/117 Identification of persons methods or arrangements for recognising patterns, e.g. fingerprints, G06F18/00, G06V40/00; identification of persons by analysing their voice or speech G10L17/00
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/6892 Mats
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7271 Specific aspects of physiological measurement analysis A61B5/316, A61B5/349 and A61B5/374 take precedence
• 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: A61B 5/74 Details of notification to user or communication with user or patient indicating measured values G01D7/00; user input means input or output arrangements for computers G06F3/00
• CPC Class Codes: A61G 2210/70 for cooling
• CPC Class Codes: A61G 2210/90 for heating
• CPC Class Codes: A61G 7/002 having adjustable mattress frame
• CPC Class Codes: A61G 7/015 divided into different adjustable sections, e.g. for Gatch position
• CPC Class Codes: A61G 7/018 Control or drive mechanisms
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Introduced are methods and systems for monitoring a person'"'"'s sleeping patterns, and detecting episodes of sleeping disorders such as snoring and sleep apnea. In one embodiment, a sensor strip attached to the mattress monitors the user'"'"'s breathing, and detects signature frequencies corresponding to snoring and sleep apnea. Once a sleeping disorder is detected, a notification can be sent to a device associated with the user, or the user'"'"'s bed can be automatically adjusted to alleviate the sleeping disorder.

Claims

1. A method to detect when a user is experiencing a sleeping disorder, the method comprising:

obtaining a breathing rate from a sensor disposed proximate to the user, the breathing rate comprising an inhale portion and an exhale portion;

identifying an inhale breathing rate of the user by removing the exhale portion from the breathing rate to obtain the inhale portion as the inhale breathing rate of the user;

based on the inhale breathing rate of the user, determining that the user is experiencing the sleeping disorder, wherein determining that the user is experiencing the sleeping disorder includes;

determining frequencies corresponding with the inhale breathing rate,

determining that the frequencies include a first frequency range around a first peak frequency and a second frequency range around a second peak frequency, the first frequency range being different than the second frequency range, and

determining that the first frequency range is within a frequency range corresponding to the sleeping disorder, and that the second frequency range is not within the frequency range corresponding to the sleeping disorder, wherein determining that the user is experiencing the sleeping disorder is based on the first peak frequency and the first frequency range; and

upon said determining that the user is experiencing the sleeping disorder, sending a signal to a device associated with the user, the signal comprising an indication that the user is experiencing the sleeping disorder.

2. The method of claim 1, said determining that the user is experiencing the sleeping disorder comprising:

receiving a first plurality of breathing rates associated with at least one person and a second plurality of breathing rates associated with the at least one person, wherein each breathing rate in the first plurality of breathing rates comprises normal breathing and further each breathing rate in the first plurality of breathing rates comprises the inhale portion and the exhale portion, and wherein each breathing rate in the second plurality of breathing rates comprises snoring and further each breathing rate in the second plurality of breathing rates comprises the inhale portion and the exhale portion;

removing the exhale portion from each breathing rate in the first plurality of breathing rates and the second plurality of breathing rates to obtain a first plurality of inhale breathing rates and a second plurality of inhale breathing rates;

based on the first plurality of inhale breathing rates and the second plurality of inhale breathing rates, creating a training model; and

based on the training model, and the inhale breathing rate associated with the user, determining that the user is snoring.

3. The method of claim 1, said determining that the user is experiencing the sleeping disorder comprising:

receiving a first plurality of breathing rates associated with at least one person and a second plurality of breathing rates associated with the at least one person, wherein each breathing rate in the first plurality of breathing rates comprises normal breathing and further each breathing rate in the first plurality of breathing rates comprises the inhale portion and the exhale portion, and wherein each breathing rate in the second plurality of breathing rates comprises breathing indicative of sleep apnea and further each breathing rate in the second plurality of breathing rates comprises the inhale portion and the exhale portion;

removing the exhale portion from each breathing rate in the first plurality of breathing rates and the second plurality of breathing rates to obtain a first plurality of inhale breathing rates and a second plurality of inhale breathing rates;

based on the first plurality of inhale breathing rates and the second plurality of inhale breathing rates, creating a training model; and

based on the training model, and the inhale breathing rate associated with the user, determining that the user is experiencing sleep apnea.

4. The method of claim 1, said determining that the user is experiencing the sleeping disorder comprising:

transforming the inhale breathing rate to obtain a transformed breathing rate comprising a plurality of frequencies and a plurality of intensities associated with the plurality of frequencies; and

detecting a peak frequency in the plurality of frequencies associated with the transformed breathing rate, wherein the peak frequency is indicative of the sleeping disorder.

5. The method of claim 4, said detecting the peak frequency indicative of the sleeping disorder comprising:

detecting an intensity peak in the plurality of intensities, wherein the intensity peak is associated with the peak frequency; and

when the peak frequency associated with the intensity peak is within a snoring frequency range, determining that the peak frequency is indicative of snoring, the snoring frequency range comprising frequencies within 0 Hz to 150 Hz.

6. The method of claim 4, said detecting the peak frequency indicative of the sleeping disorder comprising:

smoothing the transformed breathing rate to obtain a smooth transformed breathing rate, the smooth transformed breathing rate comprising a plurality of smooth frequencies, and a plurality of smooth intensities associated with the plurality of smooth frequencies; and

detecting an intensity peak in the plurality of smooth intensities, wherein the intensity peak is associated with the peak frequency; and

when the peak frequency associated with the intensity peak is within a snoring frequency range, determining that the peak frequency is indicative of snoring, the snoring frequency range comprising frequencies within 0 Hz to 150 Hz.

7. The method of claim 4, further comprising:

determining a frequency band around the peak frequency, wherein the frequency band comprises a continuous frequency region around the peak frequency, the continuous frequency region comprising frequencies whose corresponding intensities differ less than 3 dB from an intensity associated with the peak frequency;

selecting the peak frequency and the frequency band, wherein the frequency band is greater than 1 Hz; and

based on the peak frequency and the frequency band, detecting sleep apnea.

8. The method of claim 1, further comprising:

determining a number of snoring episodes experienced by the user, said determining the number of snoring episodes comprising;

identifying a time period associated with the breathing rate, wherein the time period lasts at least 1 minute, and wherein the time period is free of snoring; and

incrementing an indication of the number of snoring episodes experienced by the user.

9. The method of claim 8, said sending the signal to the device associated with the user comprising:

sending a notification comprising the number of snoring episodes.

10. The method of claim 1, said sending the signal to the device associated with the user comprising:

sending a notification to a mobile device associated with the user that the user has been snoring.

11. The method of claim 1, said sending the signal to the device associated with the user comprising:

sending the signal to an adjustable bed frame, the adjustable bed frame comprising an adjustable section, the signal comprising an identification associated with the adjustable section, and a position associated with the adjustable section, the position configured to prevent snoring.