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WO2025169092A1 - Systèmes et procédés d'identification d'états de sommeil d'un patient sur la base de l'activation du muscle de l'oreille moyenne - Google Patents

Systèmes et procédés d'identification d'états de sommeil d'un patient sur la base de l'activation du muscle de l'oreille moyenne

Info

Publication number
WO2025169092A1
WO2025169092A1 PCT/IB2025/051232 IB2025051232W WO2025169092A1 WO 2025169092 A1 WO2025169092 A1 WO 2025169092A1 IB 2025051232 W IB2025051232 W IB 2025051232W WO 2025169092 A1 WO2025169092 A1 WO 2025169092A1
Authority
WO
WIPO (PCT)
Prior art keywords
mema
events
signals
patient
controller
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/IB2025/051232
Other languages
English (en)
Inventor
Robin Guillard
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Robin Guillard Eirl
Original Assignee
Robin Guillard Eirl
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Robin Guillard Eirl filed Critical Robin Guillard Eirl
Publication of WO2025169092A1 publication Critical patent/WO2025169092A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A61B5/4812—Detecting sleep stages or cycles
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1107—Measuring contraction of parts of the body, e.g. organ or muscle
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A61B5/1114—Tracking parts of the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb using a particular sensing technique
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/12—Audiometering
    • A61B5/121—Audiometering evaluating hearing capacity
    • A61B5/125—Audiometering evaluating hearing capacity objective methods
    • A61B5/126—Audiometering evaluating hearing capacity objective methods measuring compliance or mechanical impedance of the tympanic membrane
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/389—Electromyography [EMG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A61B5/4809—Sleep detection, i.e. determining whether a subject is asleep or not
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A61B5/4815—Sleep quality
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A61B5/4818—Sleep apnoea
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6814—Head
    • A61B5/6815—Ear
    • A61B5/6817—Ear canal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches

Definitions

  • the set-up may be loaded onto the individual to be tested, with expert installation taking 15 to 30 minutes.
  • This examination also may include respiratory measurements, e.g., measurement of respiratory flow by nasal cannula, plethysmography straps, etc., and/or blood oxygenation (SpO2) with a view to diagnosing sleep apnea.
  • the central deliverable obtained at the end of a polysomnography examination is a hypnogram, as shown in FIG. 1, which consists of a chronological temporal representation of the individual’s sleep stages during the night.
  • sleep trackers such as smart watches (e.g., ScanWatch made available by Withings, Issy-les-Moulineaux, France; Apple Watch made available by Apple, Cupertino, California; Google Pixel Watch made available by Google, Menlo Park, California; Galaxy Watch made available by Samsung, Suwon, South Korea), rings (e.g., Oura Ring made available by Oura Health Ltd., Oulu, Finland; Circular Ring made available by Circular Paris, Ile-de-France, France), devices to be integrated into mattresses (Sleep made available by Withings, Issy-les- Moulineaux, France), lightweight EEG measurement headsets (Dreem headband made available by Beacon Biosignals, Boston, Massachusetts; Muse S headband made available by InteraXon Inc., Toronto, Ontario, Canada), etc.
  • sleep trackers generally manage to detect sleep reliably, but have known and criticized difficulties in reliably detecting the different sleep stages (Nl, N2, N3, REM). For example, Withings smart watches only distinguish between “light” sleep (a mixture of N2 and REM sleep) and “deep” sleep with no clarity as to whether this is N3 sleep.
  • the present disclosure overcomes the drawbacks of previously-known systems and methods by providing an apparatus for identifying a sleep state of a patient.
  • the apparatus may include an earpiece sized and shaped to be disposed adjacent an ear canal of the patient, the earpiece comprising one or more sensors configured to measure physiological information indicative of middle ear muscle activation (MEMA) events of the patient and generate one or more signals indicative of the measured physiological information, and a controller operatively coupled to the one or more sensors.
  • the controller may have instructions that, when executed by a processor of the controller, cause the controller to: detect an occurrence of one or more MEMA events in the one or more signals received from the one or more sensors; and identify the sleep state of the patient based on the occurrence of one or more MEMA events.
  • the one or more MEMA events may comprise muscle contractions of at least one of a tensor tympani muscle, a tensor veli palatine muscle, or a stapedian muscle.
  • the one or more sensors comprise an otoscope camera configured to generate video data of an eardrum of the patient, the video data indicative of MEMA events of the patient.
  • the controller may be programmed to: preprocess the one or more signals to isolate the one or more MEMA events in the one or more signals; generate one or more preprocessed signals comprising the one or more isolated MEMA events; and detect the occurrence of one or more MEMA events in the one or more preprocessed signals.
  • the controller may be programmed to filter the one or more signals based on one or more specific signal characteristics of the one or more signals to preprocess the one or more signals to isolate the one or more MEMA events in the one or more signals.
  • the one or more additional sensors may comprise an accelerometer configured to measure acceleration and generate accelerometer data, such that the controller may be programmed to use the accelerometer data to preprocess the one or more signals and distinguish non-MEMA events to facilitate isolation of the one or more MEMA events in the one or more signals.
  • the measured additional physiological information may be indicative of at least one of activation of a jaw of the patient, movement of an eye of the patient, or a bruxism event.
  • the controller may be programmed to use the physiological information indicative of activation of the jaw of the patient to preprocess the one or more signals and distinguish combined MEMA events from pure MEMA events to facilitate isolation of the one or more MEMA events in the one or more signals.
  • Detecting the occurrence of one or more MEMA events in the one or more signals and identifying the sleep state of the patient based on the occurrence of one or more MEMA events may comprise executing, via the controller, a machine learning algorithm to detect the occurrence of one or more MEMA events in the one or more signals and to identify the sleep state of the patient based on the occurrence of one or more MEMA events, the machine learning algorithm trained on a temporal record of MEMA events.
  • the method may include generating, via the controller, a hypnogram illustrating a plurality of sleep states of the patient over time, and/or identifying, via the controller, a sleep pathology of the patient based on the occurrence of one or more MEMA events.
  • FIG. 4 is a graph illustrating various sensor signals over time including a MEMA event in accordance with the principles of the present disclosure.
  • the sleep state of the individual may be any one of the four sleep stages, e.g., Nl, N2, N3, REM sleep, or an awake state, as well as “sleep with mentation state” and “sleep without mentation state.”
  • Wearable 200 may be worn by an individual such that at least a portion of wearable 200 is disposed adjacent the individual’s ear canal, e.g., at least partially within and/or around the ear canal.
  • wearable 200 may comprise a viscoelastic material, e.g., foam, configured to transition between a compressed state and an expanded state where wearable 200 conforms to the anatomy of the individual’s ear where wearable 200 is located, such that wearable 200 may be comfortably worn by the individual.
  • sensor 202 may include one or more electrodes configured to measure an electric and/or magnetic field propagated by muscle contractions of middle ear muscles, and to generate signals indicative of the electric and/or magnetic field such that MEMA events, if any, are observable from readings of the signals.
  • the electrode may be a piece of conductor material (e.g., metal or conductive polymer) sized and shaped to non- invasively contact the individual’s skin, e.g., within the ear canal, to measure the electrical potential of a biological activity, e.g., micro-movements of the skin due to muscle contractions of middle ear muscles.
  • sensor 202 may include one or more impedancemetry sensors configured to measure reverberation of sound by a tympanic membrane of the individual, and to generate signals indicative of the measured sound reverberation such that MEMA events, if any, are observable from readings of the signals, as described in the Pessah article. Additionally, or alternatively, sensor 202 may include one or more otoscope cameras configured to generate video data of an eardrum of the individual, such that MEMA events, if any, are observable from readings of the video data.
  • system 100 may include one or more additional sensors 210 configured to measure additional physiological information and generate one or more signals indicative of the measured additional physiological information, e.g., during the same sleep session of the individual sensed by sensors 202, to facilitate removal of artifacts to isolate combined and/or pure MEMA events from the signals generated by sensor 202, as described in further detail below.
  • An artifact is a non-MEMA event that may be a signature on the sensor signals that looks like a MEMA event, but that is actually random noise, e.g., non- negligible movement of the individual during sleep.
  • MEMA events may include combined MEMA events, e.g., activations of the middle ear muscles with simultaneous activations of the individual’s jaw muscles (e.g., masseter, suprahyoid, pterygoidian, etc.) as measured by sensor 210, as well as pure MEMA events, e.g., only activations of the middle ear muscles without activations of the individual’s jaw muscles.
  • system 100 may be used to determine an individual’s sleep state by observing combined and/or pure MEMA events.
  • Device interface module 310 may be executed by processor 302 for interfacing with an application installed on device 120, e.g., a mobile application installed on a smart phone. For example, device interface module 308 may determine if device 120 is paired with sleep state determination platform 300, e.g., via communication system 304, and further may transmit data to device 120 when paired. Moreover, device interface module 308 may pause the transmission of data to device 120 when it is determined that device 120 is outside a predetermined range from wearable 200, and may cause the remaining data to be stored, e.g., either on memory 306 or on cloud storage 160, until device 120 is determined to be within the predetermined range.
  • an application installed on device 120 e.g., a mobile application installed on a smart phone.
  • device interface module 308 may determine if device 120 is paired with sleep state determination platform 300, e.g., via communication system 304, and further may transmit data to device 120 when paired. Moreover, device interface module 308 may pause the transmission of data to device
  • device interface module 308 may interface with device 120 to receive the one or more signals from device 120 indicative of a command by the user to, e.g., start or stop a sleep sensing session, and/or pair device 120 with sleep state determination platform 300, and further to transmit data to device 120 including, for example, a hypnogram as described above, an alert when the power source level of wearable 200 is low and/or depleted, and/or if the user is determined to be in a sleep stage close to awake, etc.
  • Sensor data processing module 312 may be executed by processor 302 for processing data received by sensor interface module 310 from sensors 202 to automatically identify MEMA events in the signals generated by sensors 202, and optionally, for processing data received by sensor interface module 310 from additional sensors 210 to remove artifacts and isolate MEMA events in the signals received from sensors 202. Particularly, physiological events (e.g., activation of the jaws, bruxism, movements, etc.) observed in the signals from sensors 202 may be mistaken as MEMA events.
  • physiological events e.g., activation of the jaws, bruxism, movements, etc.
  • sensor data processing module 312 may determine if a signature of the signal from sensors 202, which may have been identified as a candidate MEMA event as described above, is an artifact or not. For example, if signals received from sensors 210, e.g., an accelerometer and/or a strain gauge, indicate the synchronous occurrence of non-negligible activity with a candidate MEMA event in the signal received from sensors 202, sensor data processing module 312 may determine that the candidate MEMA event is an artifact, and accordingly, remove/disregard the artifact from the signal received from sensors 202.
  • sensors 210 e.g., an accelerometer and/or a strain gauge
  • sensor data processing module 312 may determine that the candidate MEMA event is a MEMA event, e.g., an actual contraction of the individual’s middle ear muscles.
  • a combined MEMA event includes an activation of the individual’s middle ear muscles with simultaneous activation of the individual’s jaw muscles. Accordingly, to determine whether an identified MEMA event is a combined MEMA event or a pure MEMA event, if the EMG signal received from sensor 210, e.g., an electrode disposed on the individual’s jaw, indicates the synchronous occurrence of activation of the individual’s jaw muscles with the identified MEMA event, sensor data processing module 312 may determine that the MEMA event is a combined MEMA event.
  • sensor data processing module 312 may determine that the identified MEMA event is a pure MEMA event. As described above, system 100 may determine an individual’s sleep state based on MEMA events identified in the signals received from sensors 202 without distinguishing between combined MEMA events and pure MEMA events.
  • sensor data processing module 312 upon identification of one or more MEMA events in the signal from sensors 202, sensor data processing module 312 further may generate a plot of the signal as a function of density of the one or more MEMA events over time, e.g., the duration of the sleep sensing session, as shown in FIG. 5 described in further detail below.
  • the density function of MEMA events may be plotted as the number of MEMA events per minute.
  • sensor data processing module 312 further may distinguish whether the detected MEMA events are unilateral (e.g., occurring in only one ear of the individual, which only occurs about 15% of the time) or bilateral (e.g., occurring in both ears of the individual), such as when the individual uses two wearables 200 (one in each ear).
  • FIG. 5 is a graph illustrating a density function of MEMA events over time, e.g., number of MEMA events in a predefined unit of time, overlaid with time spent in REM sleep.
  • the graph may be a plot of the moving average of the number of MEMA events over an average of, e.g., ten seconds, one minute, etc.
  • the time during which the individual was in REM sleep is accurately predicted according to precise signal matching with the identified MEMA events.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • General Health & Medical Sciences (AREA)
  • Physiology (AREA)
  • Dentistry (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Otolaryngology (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Artificial Intelligence (AREA)
  • Psychiatry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Mathematical Physics (AREA)
  • Signal Processing (AREA)
  • Fuzzy Systems (AREA)
  • Evolutionary Computation (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Anesthesiology (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

L'invention concerne des systèmes et des procédés pour détecter l'apparition d'événements d'activation du muscle de l'oreille moyenne (MEMA) dans des signaux physiologiques obtenus à partir d'un ou de plusieurs capteurs portables, par exemple, des capteurs intra-auriculaires, portés par un individu, et identifier un ou plusieurs états de sommeil de l'individu, par exemple, le sommeil REM, sur la base des événements MEMA détectés. Des informations physiologiques supplémentaires mesurées par l'intermédiaire d'un ou de plusieurs capteurs supplémentaires peuvent être utilisées conjointement avec les signaux obtenus à partir d'un ou de plusieurs capteurs portables pour identifier et éliminer des événements non MEMA, par exemple, des artéfacts, pour identifier plus précisément des événements MEMA. Les états de sommeil identifiés de l'individu peuvent être présentés graphiquement à un utilisateur par l'intermédiaire d'un dispositif mobile couplé de manière fonctionnelle au ou aux capteurs portables.
PCT/IB2025/051232 2024-02-06 2025-02-05 Systèmes et procédés d'identification d'états de sommeil d'un patient sur la base de l'activation du muscle de l'oreille moyenne Pending WO2025169092A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP24305203.2 2024-02-06
EP24305203 2024-02-06

Publications (1)

Publication Number Publication Date
WO2025169092A1 true WO2025169092A1 (fr) 2025-08-14

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2025/051232 Pending WO2025169092A1 (fr) 2024-02-06 2025-02-05 Systèmes et procédés d'identification d'états de sommeil d'un patient sur la base de l'activation du muscle de l'oreille moyenne

Country Status (1)

Country Link
WO (1) WO2025169092A1 (fr)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180049690A1 (en) * 2016-08-19 2018-02-22 Matthew Walker Sleep tracking systems, methods, and devices
WO2020187109A1 (fr) * 2019-03-15 2020-09-24 华为技术有限公司 Procédé et système de détection du sommeil d'un utilisateur
WO2020257372A1 (fr) * 2019-06-19 2020-12-24 Bose Corporation Stadification du sommeil à l'aide d'une photopléthysmographie (ppg) intra-auriculaire
EP4085835A1 (fr) * 2021-05-03 2022-11-09 Karlsruher Institut für Technologie Saisie discrète dans les mains et les yeux par contraction volontaire du muscle tenseur du tympan

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180049690A1 (en) * 2016-08-19 2018-02-22 Matthew Walker Sleep tracking systems, methods, and devices
WO2020187109A1 (fr) * 2019-03-15 2020-09-24 华为技术有限公司 Procédé et système de détection du sommeil d'un utilisateur
WO2020257372A1 (fr) * 2019-06-19 2020-12-24 Bose Corporation Stadification du sommeil à l'aide d'une photopléthysmographie (ppg) intra-auriculaire
EP4085835A1 (fr) * 2021-05-03 2022-11-09 Karlsruher Institut für Technologie Saisie discrète dans les mains et les yeux par contraction volontaire du muscle tenseur du tympan

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
BENSON, KV P ZARCONE JR: "Phasic Events of REM Sleep: Phenomenology of Middle Ear Muscle Activity and Periorbital Integrated Potentials in the Same Normal Population", SLEEP, vol. 2, no. 2, 1979, pages 199 - 213
D. OUDIETTE ET AL.: "Dreaming without REM sleep", CONSCIOUSNESS AND COGNITION, vol. 21, no. 3, 2012, pages 1129 - 1140
D. SLEGEL ET AL.: "An Inexpensive Alternative for Recording Middle Ear Muscle Activity (MEMA) During Sleep", SLEEP, vol. 15, no. 6, 1992, pages 567 - 70
DUANE E. SLEGEL ET AL.: "Middle-Ear Muscle Activity (MEMA) and Its Association with Motor Activity in the Extremities and Head in Sleep", SLEEP, vol. 14, no. 5, 1991, pages 454 - 459
PESSAH, M AH P ROFFWARG: "Spontaneous Middle Ear Muscle Activity in Man: A Rapid Eye Movement Sleep Phenomenon", SCIENCE (NEW YORK, N.Y., vol. 178, no. 4062, 1972, pages 773 - 6

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