WO2001015602A1 - Systeme et procede de diagnostic de troubles respiratoires - Google Patents

Systeme et procede de diagnostic de troubles respiratoires Download PDF

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Publication number
WO2001015602A1
WO2001015602A1 PCT/US2000/024275 US0024275W WO0115602A1 WO 2001015602 A1 WO2001015602 A1 WO 2001015602A1 US 0024275 W US0024275 W US 0024275W WO 0115602 A1 WO0115602 A1 WO 0115602A1
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WO
WIPO (PCT)
Prior art keywords
respiratory
patient
related sounds
detected
sounds
Prior art date
Application number
PCT/US2000/024275
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English (en)
Inventor
Christopher M. Rembold
Paul Suratt
Original Assignee
University Of Virginia Patent Foundation
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 University Of Virginia Patent Foundation filed Critical University Of Virginia Patent Foundation
Priority to AU71114/00A priority Critical patent/AU7111400A/en
Publication of WO2001015602A1 publication Critical patent/WO2001015602A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/003—Detecting lung or respiration noise
    • 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
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A61B5/726—Details of waveform analysis characterised by using transforms using Wavelet transforms

Definitions

  • the invention relates to a method and apparatus for monitoring and diagnosing respiratory disorders, and more particularly to a method and apparatus for monitoring and diagnosing respiratory disorders by detecting and/or analyzing a patient's high frequency respiratory related sounds.
  • SDB Sleep Disordered Breathing
  • OSA Obstructive Sleep Apnea
  • SDB can occur in adults and children.
  • Sleep-related respiratory disorders, such as SDB are a significant cause of excessive daytime sleepiness, chronic fatigue, automobile accidents, hypertension, pulmonary hypertension, and even death.
  • SDB a disease that has been estimated to occur in approximately 4% of adults, the upper airway narrows or closes during sleep thereby increasing upper airway resistance and making it more difficult or impossible to breath.
  • SDB Sessions of SDB are frequently but not always terminated by arousal. Some of the physiological responses to SDB can include nocturnal awakening resulting in daytime sleepiness and fatigue, impaired neurocognitive function including difficulty concentrating, as well as activation of the sympathetic nervous system and increased risk of heart failure.
  • PSG laboratory based polysomnography
  • EEG electroencephalogy
  • EMG electromyography
  • EOG electoocculogram
  • ECG electrocardiogram
  • nasal and oral airflow oxyhemoglobin saturation
  • respiratory effort with one or more types of monitors including those that detect chest and abdominal movements, intercostal EMGs and esophageal pressure.
  • the data gathered leads to a calculation of the number of apneas per hour of sleep, the number of hypopneas per hour of sleep, the number of upper airway resistance events (elevated upper airway resistance leads to arousal) per hour of sleep, the number of arousals per hour of sleep, the number of arousals per hour of sleep related to apneas, hypopneas, and/or upper airway resistance events, as well as parameters describing sleep such as total sleep time, sleep efficiency, etc.
  • the Respiratory Disturbance Index (“RDI”) a term used by some to describe the average number of apneas and optionally hyponeas per hour, can also be determined.
  • RTI Respiratory Disturbance Index
  • U.S. Pat. No. 4,982,738 to Griebel discloses a diagnostic apnea monitor system that monitors and records snoring and respiration sounds made by a patient, as well as the patient's heart rate while the patient is sleeping. Signals indicative of snoring sounds and the time intervals therebetween are produced from the recorded respiration.
  • the system generates a first respiration disturbance index representing the number of intervals per hour between episodes of snoring.
  • An average heart rate is also generated in response to the patient's recorded second respiration disturbance index representing the number of episodes per hour in which the patient's heart rate remained at 90% to 109% of its average rate is calculated.
  • a physician can then evaluate the first and second disturbance indices to determine whether Obstructive Sleep Apnea is indicated.
  • U.S. Pat. No. 5,797,852 to Karakasoglu et al. discloses a sleep apnea detecting apparatus and method. It is comprised of a first microphone positioned in the vicinity of a patient's nose and mouth to pick up audible sounds created by breathing of the patient. A second microphone is provided which is positioned near the patient for picking up ambient noise in the vicinity of the patient to provide a baseline. The signals from the two microphones are then processed to provide a waveform that is closely correlated to the airflow of the patient. The waveform is then evaluated to determine the presence and magnitude of patient airflow. If patient airflow is determined to be decreased or absent, as reflected by the evaluated waveform, an apnea event is indicated.
  • cardio and respiratory functions such as nasal air flow, chest wall effort, oxygen saturation, heart rate and heart activity, can provide markers of sleep-related respiratory disorders. For instance, see U.S. Pat. No. 5,769,084 to Katz et al. and U.S. Pat. No. 6,091,973 to Colla et al.
  • the invention relates to a method and system for monitoring and diagnosing respiratory disorders, such as Sleep Disordered Breathing.
  • a method and system according to the invention involves detecting a patient's respiratory-related sounds and analyzing a patient's respiratory related sounds for the presence of high frequency respiratory-related sounds to thereby diagnose the occurrence of a respiratory disorder event. More particularly, it has been discovered that relatively high frequency respiratory sounds above 1250 Hz, and more particularly above about 3 kHz, are associated with disordered breathing, such as when upper airway resistance is high and the upper airway is narrowed.
  • a method includes the steps of detecting a patient's respiratory-related sounds and analyzing the patient's respiratory-related sounds for the presence of high frequency respiratory-related sounds to non-invasively monitor and diagnose disordered breathing such as increases in upper airway resistance and sleep-related respiratory disorders.
  • the method may further include the steps of measuring and analyzing other cardio- respiratory parameters such as heart rate, heart activity, airflow, oxygen saturation, and chest wall effort. The analyzed cardio-respiratory parameters can then be used in the diagnosis of upper airway resistance and sleep-related respiratory disorders.
  • a system according to the invention may include at least one respiratory- related sound detection module and a respiratory disorder diagnosis module.
  • the respiratory sounds can be detected using microphones or other devices which can detect high frequency sounds, either attached or unattached to the patient.
  • a system of the invention can be embodied in a hand-held, home-use instrument as well as in a instrument designed more particularly for use in a sleep laboratory or medical care facility, or in any proprietary or nonproprietary system for spectral analysis.
  • the system may further include at least one cardio- respiratory parameter measurement and analysis module.
  • a method or system of the invention can be used to predict the location, the geometry, and the approximate and/or relative size of the airway, anatomical location, or anatomical structure generating the detected respiratory sounds. Further, a method and system according to the invention can be used to monitor and diagnose other breathing disorders including obstructive lung diseases such as asthma, COPD, and emphysema.
  • Obstructive Sleep Apnea, Upper Airway Resistance Syndrome, and other sleep-related respiratory disorders can be used to monitor and diagnose any breathing disorder which involves the narrowing of any aspect of the respiratory pathway.
  • a method and system of the invention can be used to monitor and diagnose obstructive lung disorders such as asthma, COPD, and emphysema.
  • patients with sleep-related respiratory disorders have a spectrum of abnormal respiration including total apnea and breaths with increased airway resistance, these patients produce high frequency sounds during some of their abnormal breaths. Further, patients with other conditions may also exhibit increased upper airway resistance and high frequency sounds as an index of ventilatory distress.
  • the spectral characteristics of the sounds made by patients may be detected to provide diagnostic information relating to the degree of upper airway resistance present. Since increased upper airway resistance occurs in SDB, such sleep-related respiratory disorders may be diagnosed by detecting and analyzing the respiratory-related sounds made by patients during sleep for the presence of high frequency respiratory-related sounds.
  • a method and system according to the can be used to predict the location, geometry, and approximate and/or relative size of the airway, anatomical location, or anatomical structure generating the detected respiratory-related sounds.
  • the frequency distribution and/or characteristics of the detected respiratory-related sounds can indicate the extent of apnea and/or narrowing of the upper airway and can be correlated with the dimensions of the narrowest point within the upper airway.
  • the frequency range of the high frequency sounds may be used to determine the location of any obstruction within the patient's airway to thereby aid in potential therapy.
  • the invention relates to a method for monitoring and diagnosing sleep-related respiratory disorders.
  • a method according to the invention includes the steps of detecting a patient's respiratory-related sounds during sleep; and analyzing the patient's respiratory-related sounds for the presence of high frequency respiratory-related sounds to thereby diagnosing the occurrence of sleep-related respiratory disorder events.
  • the presence of relatively high frequency sounds i.e., those above 1250 Hz and preferably above about 3 kHz, in the frequency distribution and/or characteristics of a patient's respiratory-related sounds is indicative of respiratory disorders, and thus can serve as a diagnostic indicator of the occurrence of respiratory disorders.
  • a method according to the invention can further include the steps of measuring and analyzing at least one additional cardio- respiratory parameter.
  • the analyzed cardio-respiratory parameter can then be used in the diagnosis of the occurrence of a respiratory disorder event in the patient.
  • the analyzed cardio-respiratory parameter can be used to detect the particular phase of breathing in which the high frequency sound occurs, to thereby verify the occurrence of respiratory disorder events during periods when high frequency respiratory sounds are detected.
  • the cardio- respiratory parameter measured can be any physiological parameter that is reflective of sleep-related respiratory disorders known in the art.
  • such cardio-respiratory parameters can include, but are not limited to, heart rate, heart activity, timing of heart rate and heart activity, airflow, oxygen saturation, chest wall effort, and abdominal movement.
  • a system of the invention includes at least one respiratory sound detection module for detecting the respiratory-related sounds of a patient during sleep; and a diagnostic module for analyzing the detected respiratory-related sounds for the presence of high frequency respiratory-related sounds to thereby diagnose the occurrence of sleep-related respiratory disorder events in the patient.
  • a system of the invention may also include at least one module to monitor and analyze at least one additional cardio-respiratory parameter reflective of the occurrence of sleep-related breathing disorder events, such as, but not limited to heart rate, heart activity, oxygen saturation, chest wall resistance, and/or airflow.
  • the analyzed cardio-respiratory parameters can then be used by the diagnostic module in the diagnosis of the occurrence of respiratory disorder events.
  • the cardio-respiratory parameters can be measured using any method known in the art for measuring such parameters, including, but not limited to the use of a nasal cannula, a pulse oximetor, an ECG, and/or a chest strain gauge.
  • the method and system of the invention may be used for monitoring and/or diagnosing sleep-related respiratory disorders or obstructive lung diseases.
  • the method and system may be used to screen patients at low to intermediate risk for sleep-related breathing disorders; to perform sleep studies in a medical care facility, to monitor the efficacy of treatment by measuring airway sounds during patient treatment; to monitor patients in acute care settings for abnormal respiration as a sign of cardiopulmonary distress; to monitor patients outside the hospital, such as infants, for abnormal respiration as a sign of cardiopulmonary distress; or any other monitoring system for disordered respiration in humans or animals.
  • a system of the invention can be portable or stationary, depending on its intended use.
  • a method or system according to the invention may also be configured to log patient data regarding the spectral characteristics of respiratory-related sounds, as well as any additional measured cardio-respiratory parameters, for later diagnostic analysis.
  • a method or system of the invention can be configured to provide for real-time diagnosis of respiratory disorder events.
  • a real-time diagnostic method or system could also incorporate data logging if desired.
  • Patient respiratory-related sounds can be detected using any method known in the art.
  • a microphone can be placed in proximity to the patients nose and/or mouth to detect respiratory sounds.
  • a microphone can be placed in a nasal cannula.
  • more than one microphone can be used to detect respiratory sounds from both the nose and mouth individually, or as a background noise monitor.
  • the microphone can also optionally be interfaced with an audio recorder for data logging.
  • the microphone(s) can be either attached, or unattached to the patient.
  • the microphone can be incorporated into a nasal cannula as described in U.S. Pat. No. 5,671,733 to Raviv et al., the disclosure of which is hereby incorporated by reference in a manner consistent with this disclosure.
  • the microphone(s) may be placed and/or suspended, e.g., from the ceiling, in proximity to the nose and/or mouth of the patient.
  • the detected respiratory-related sounds can be analyzed for the presence of high frequency respiratory-related sounds using any frequency domain conversion processes known in the art, such as fast fourier transform ("FFT”) processes.
  • FFT fast fourier transform
  • FT Fourier Transform
  • STFT Short-Time FT
  • DCT Discrete Cosine Transforms
  • WT wavelet transforms
  • high pass filters can be used to isolate and detect the presence of high frequency respiratory-related sounds.
  • the patient's respiratory-related sounds can be analyzed for any the presence of any frequency above a certain frequency level, e.g., above 1250 Hz, preferably above 3 kHz.
  • the frequency distribution of the patient's respiratory-related sounds can be analyzed for the presence of respiratory-related sounds in particular frequency ranges, e.g., between about 4 and 6 kHz and between about 9 and 12 kHz. Such frequency distribution analysis can serve to more particularly identify and diagnose the respiratory disorder event.
  • Figure 1 illustrates a system 10 according to the invention.
  • a microphone 101 is connected to a box 11 containing a preamplifier 102 and a digital signal processor 103 that converts sound input into a frequency vs. amplitude measurement.
  • the box 11 serves as a container for the system, and may be designed, for example, to be hand-held for home or portable use.
  • the frequency vs. amplitude measurements are then stored in a data logger 115, optionally along with other cardio- respiratory parameter measurements as needed (e.g. oxygen saturation, nasal flow, ECG, and other measurements) which provide additional diagnostic information beyond the analysis of sound.
  • the optional cardio respiratory parameters can be measured using any methodologies and instrumentation known in the art.
  • a pulse oximetor 104 can be connected to box 11 and preamplifier 105 for measuring oxygen saturation.
  • a nasal cannula 106 can be connected to box 11 , transducer 107, and preamplifier 108 for measuring nasal airflow.
  • ECG (electrocardiogram) electrodes 109 can also be connected to box 11 and preamplifier 110 to provide measurement information regarding heart activity and heart rate.
  • a chest-encircling strain gauge 111 can be connected to box 11, pressure transducer 112, and preamplifier 113 to measure chest wall resistance.
  • the data logger 115 may be connected with an on-line analysis system if needed. In the embodiment shown, the data logger 115 interfaces through port 116 with computer 12 to download data for analysis and for programming the data collection box.
  • Figure 2 illustrates another embodiment of the invention that is configured as a real-time diagnostic system 20.
  • a microphone 101 is connected to a box 11 containing a preamplifier 102 and a digital signal processor 103 that converts sound input into a frequency vs. amplitude measurement.
  • the frequency vs. amplitude measurement is analyzed by a built-in diagnostic system 114 in real time in combination with other easily obtained measurements (e.g. oxygen saturation, nasal flow, ECG, and other measurements). If the real-time diagnostic system 114 detects the occurrence of a sleep-related respiratory disorder event, an alarm system 117 is activated and patient data is passed to data logger 115 for future download to computer 12 through interface port 116 for analysis. Interface port 116 also allows for programming of the diagnostic system 114.
  • Figure 1 is a block diagram of one embodiment of the portable sleep related breathing disorder diagnostic system of the invention.
  • Figure 2 is a block diagram of one embodiment of the portable sleep related breathing disorder alarm system of the invention.
  • Figure 3 shows a representative tracing of the association between airway flow, esophageal pressure (an estimate of effort), and the spectral characteristics of the sound during six inspirations.
  • the bottom tracing shows esophageal pressure ("PES") measured with a catheter and the second from bottom tracing shows airway flow measured with nasal prongs attached to a pressure transducer.
  • the spectral characteristics were measured during six inspirations labeled A-F and are displayed as intensity (loudness) on the Y-axis and frequency in kHz on the X-axis.
  • Figure 4 shows another representative tracing of the association between airway flow, esophageal pressure (an estimate of effort), and the spectral characteristics of the sound during three inspirations.
  • the bottom right tracing shows PES measured with a catheter and the top right tracing shows airway flow.
  • the spectral characteristics were measured during three inspirations labeled A-C as in Fig. 3.
  • Figure 5 shows a third representative tracing of the association between airway flow, esophageal pressure (an estimate of effort), and the spectral characteristics of the sound during three inspirations.
  • the bottom right tracing shows PES measured with a catheter and the top right tracing shows airway flow.
  • the spectral characteristics were measured during three inspirations labeled A-C as in Fig. 3.
  • the University of Virginia has four such diagnostic rooms for sleep studies. Each is soundproofed from the other rooms.
  • the sleep studies were standard studies, and data was collected with Sandman software (Toronto, Canada). All patients had esophageal pressure measured with a catheter made from PI 00 tubing and a 10 cm latex balloon at the distal end.
  • Figures 3-5 demonstrate, in three separate patients, the association between airway (nasal) flow, esophageal pressure (an estimate of effort), and the spectral characteristics of the sound made during several inspirations.
  • Fig. 3 shows 40 sec of a sleep study in a patient with obstructive sleep apnea. Flow remained similar during all the breaths shown, therefore, increases in resistance correlate with the degree of negative deflection in esophageal pressure ("PES").
  • PES esophageal pressure
  • Fig. 4 shows three successive breaths of a sleep study in a second patient with obstructive sleep apnea. Each successive inspiration was associated with increasing effort (more negative PES). Inspiration A, with low effort, was associated with sound predominantly less than 3 kHz (there was no artifactual fan sound). Inspirations B was associated with increased sound at 8-9 kHz. Inspiration C, with the highest effort, was associated with increased sound, both below 3 kHz and at 8-11 kHz.
  • Fig. 5 shows three successive breaths of a sleep study in a third patient with obstructive sleep apnea.
  • each successive inspiration was associated with less effort (less negative PES) and increasing flow, indicating decreasing airway resistance with each breath.
  • Inspiration A with high resistance, was associated with sound at 0-3 kHz, 4-5 kHz, and 8-11 kHz.
  • Inspirations B was associated with less sound at 8-11 kHz.
  • Inspiration C with the least resistance, was associated with substantially less sound at 8-11 kHz and less sound at 4-5 kHz.
  • the invention is applicable to the monitoring and diagnosis of respiratory disorders, such as Sleep Disordered Breathing and Obstructive Lung Diseases.
  • the invention allows for simple, non-invasive monitoring and diagnosis of respiratory disorders through the detection and analysis of high frequency respiratory-related sounds.

Abstract

L'invention concerne un procédé et un système (10) de surveillance et de diagnostic de troubles respiratoires, tels que les troubles respiratoires du sommeil et les troubles ventilatoires obstructifs. Un procédé et système (10) de l'invention consistent à détecter et analyser les sons émis par un patient et associés à sa respiration, de manière à pouvoir diagnostiquer la survenue d'événements du type troubles respiratoires, ces sons étant obtenus par l'intermédiaire d'un microphone (101). On a notamment découvert que des sons respiratoires possédant une fréquence relativement élevée, se situant au-dessus de 1250 Hz, et plus particulièrement au-dessus de 3 kHz, étaient associés à une résistance accrue à l'écoulement gazeux dans les voies aériennes et indiquaient des événements du type troubles respiratoires.
PCT/US2000/024275 1999-09-02 2000-09-05 Systeme et procede de diagnostic de troubles respiratoires WO2001015602A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU71114/00A AU7111400A (en) 1999-09-02 2000-09-05 System and method for the diagnosis of respiratory disorders

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US15215799P 1999-09-02 1999-09-02
US60/152,157 1999-09-02

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WO2001015602A1 true WO2001015602A1 (fr) 2001-03-08

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010054481A1 (fr) * 2008-11-17 2010-05-20 Toronto Rehabilitation Institute Procédé et appareil de surveillance du cycle respiratoire par analyse de fréquence d’un flux de données acoustiques
WO2015181140A1 (fr) * 2014-05-26 2015-12-03 Spiro Medical As Système de surveillance d'effort respiratoire
US9649087B2 (en) 2011-05-17 2017-05-16 University Health Network Method and device for apnea and hypopnea detection
US9801590B2 (en) 2011-05-17 2017-10-31 University Health Network Breathing disorder identification, characterization and diagnosis methods, devices and systems
CN107569231A (zh) * 2017-08-07 2018-01-12 于立萍 呼吸科疾病检查治疗装置
US9949667B2 (en) 2008-11-17 2018-04-24 University Health Network Mask and method for use in respiratory monitoring and diagnostics
US10269228B2 (en) 2008-06-17 2019-04-23 Koninklijke Philips N.V. Acoustical patient monitoring using a sound classifier and a microphone
US10506969B2 (en) 2015-11-03 2019-12-17 University Health Network Acoustic upper airway assessment system and method, and sleep apnea assessment system and method relying thereon
CN113854969A (zh) * 2021-10-29 2021-12-31 海信视像科技股份有限公司 一种智能终端及睡眠监测方法

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5203343A (en) * 1991-06-14 1993-04-20 Board Of Regents, The University Of Texas System Method and apparatus for controlling sleep disorder breathing
US5505199A (en) * 1994-12-01 1996-04-09 Kim; Bill H. Sudden infant death syndrome monitor

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5203343A (en) * 1991-06-14 1993-04-20 Board Of Regents, The University Of Texas System Method and apparatus for controlling sleep disorder breathing
US5505199A (en) * 1994-12-01 1996-04-09 Kim; Bill H. Sudden infant death syndrome monitor

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10269228B2 (en) 2008-06-17 2019-04-23 Koninklijke Philips N.V. Acoustical patient monitoring using a sound classifier and a microphone
WO2010054481A1 (fr) * 2008-11-17 2010-05-20 Toronto Rehabilitation Institute Procédé et appareil de surveillance du cycle respiratoire par analyse de fréquence d’un flux de données acoustiques
US9232910B2 (en) 2008-11-17 2016-01-12 University Health Network Method and apparatus for monitoring breathing cycle by frequency analysis of an acoustic data stream
US9949667B2 (en) 2008-11-17 2018-04-24 University Health Network Mask and method for use in respiratory monitoring and diagnostics
US9649087B2 (en) 2011-05-17 2017-05-16 University Health Network Method and device for apnea and hypopnea detection
US9801590B2 (en) 2011-05-17 2017-10-31 University Health Network Breathing disorder identification, characterization and diagnosis methods, devices and systems
WO2015181140A1 (fr) * 2014-05-26 2015-12-03 Spiro Medical As Système de surveillance d'effort respiratoire
US10506969B2 (en) 2015-11-03 2019-12-17 University Health Network Acoustic upper airway assessment system and method, and sleep apnea assessment system and method relying thereon
CN107569231A (zh) * 2017-08-07 2018-01-12 于立萍 呼吸科疾病检查治疗装置
CN113854969A (zh) * 2021-10-29 2021-12-31 海信视像科技股份有限公司 一种智能终端及睡眠监测方法

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