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WO2003055395A1 - Analyse de signaux medicaux acoustiques - Google Patents

Analyse de signaux medicaux acoustiques Download PDF

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Publication number
WO2003055395A1
WO2003055395A1 PCT/GB2002/005922 GB0205922W WO03055395A1 WO 2003055395 A1 WO2003055395 A1 WO 2003055395A1 GB 0205922 W GB0205922 W GB 0205922W WO 03055395 A1 WO03055395 A1 WO 03055395A1
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WO
WIPO (PCT)
Prior art keywords
signal
wavelet
respiration
wavelet transform
pulse
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.)
Ceased
Application number
PCT/GB2002/005922
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English (en)
Inventor
Paul Stanley Addison
James Nicholas Watson
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.)
CardioDigital Ltd
Original Assignee
CardioDigital Ltd
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 CardioDigital Ltd filed Critical CardioDigital Ltd
Priority to AU2002356324A priority Critical patent/AU2002356324A1/en
Publication of WO2003055395A1 publication Critical patent/WO2003055395A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/02—Stethoscopes
    • A61B7/04—Electric stethoscopes
    • 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

Definitions

  • the present invention relates to a method of analysis of medical signals, and in particular to a method of decomposition and analysis of signals used in phonocardiography. Specifically the invention relates to an improved method of denoising acoustic cardiac signals and in the extraction of clinically useful information from such signals including the location of relevant cardiac sounds in the signal and the monitoring and analysis of patient respiration including the determination of breathing rate.
  • the denoising of acoustic cardiac signals is essential in order to facilitate their clinical evaluation.
  • the removal of noise including movement artefact is the main goal of current signal analysis methods.
  • Our method allows for clinically relevant information to be extracted from acoustic cardiac waveforms even when a high level of noise is present in the signal .
  • Wavelet transforms allow a signal to be decomposed such that both the frequency characteristics and the temporal location of particular features in a time series may be highlighted simultaneously.
  • This feature localisation property overcomes the basic shortcoming of Fourier analysis, where the spectrum only contains globally averaged information which leads to location specific features in the signal being lost.
  • STFT short time Fourier transform
  • the wavelet-based method cannot resolve to an arbitrarily small scale due to the variable window width associated with the wavelet function.
  • the wavelet transform of a continuous time signal, x (t) is defined as:
  • a is the wavelet scale parameter
  • b is the wavelet location parameter
  • g (t) is the analysing wavelet function
  • g * (t) its complex conjugate.
  • the present invention provides a method of measuring physiological parameters, comprising processing a phonocardiogram signal using wavelet transform methods; and also provides a system suitable for carrying out the method.
  • the invention is a wavelet transform-based method for the elucidation of pertinent features from noisy acoustic cardiac waveforms associated with both cardiac and respiratory activity.
  • These techniques will be used within phonocardiographic signal acquisition and analysis devices (including remote devices used, for example, to monitor neonates) to monitor cardiac or respiratory activity, and preferably both, and provide information concerning these activities including pulse rate and respiration rate.
  • the methodology can facilitate the clinical interpretation of acoustic cardiac waveforms which suffer from excessive noise, including noise from movement artefact and poor coupling between microphone and patient. Poor coupling may arise from the lack of a rigid connection of the microphone and the patient skin or the placement of the microphone within the patient clothes. This document describes the methodology and its incorporation within a medical device.
  • Figure 2 (a) Wavelet Analysis of an Acoustic Cardiac Signal - Original Acoustic Cardiac Waveform.
  • Figure 2 (b) Wavelet Analysis of an Acoustic Cardiac Signal - the Wavelet Scalogram Corresponding to the signal in figure 2 (a)
  • Figure 2 (c) Wavelet Analysis of an Acoustic Cardiac Signal - The scalogram values from the selected band-pass centre frequency of the wavelet showing alternate large and small amplitude maxima (marked a and b in the figure) .
  • Figure 3 A detailed block diagram of a preferred embodiment of the wavelet-based pulse rate determination.
  • Figure 4 (b) Wavelet Transform Phase Plot corresponding to the Signal in Figure 4 (a)
  • Figure 5 (a) Wavelet Transform Modulus Plot of the signal shown in Figure 4 (a) .
  • Figure 5 (b) Wavelet Transform Modulus Plot of the signal in Figure 4 (a) with possible routes of pulse and breathing ridges shown schematically.
  • Figure 6 A detailed block diagram of a preferred embodiment of the wavelet-based respiration and pulse rate determination.
  • Figure 1 shows an artefact free acoustic cardiac waveform.
  • the two adjacent wavetrain pulses corresponding to a single heartbeat (Si and S 2 sounds) are evident in the middle of the plot.
  • the time trace in Figure 2 (a) contains an acoustic cardiac waveform collected from a young baby where very poor coupling between the microphone and patient was present. As well as this poor coupling, the signal suffers from breathing and movement artefact, signal drop-outs and undersampling. (The difference in the quality from the trace in figure 1 is obvious.)
  • the wavelet scalogram derived from the signal in Figure 2(a) is shown in Figure 2b.
  • the bottom trace ( Figure 2 (c) ) contains the wavelet transform values across the scalogram corresponding to a selected band-pass frequency centre of the wavelet.
  • Figure 3 contains a block diagram of a preferred embodiment of the pulse detection and rate determination algorithm as incorporated within a medical device.
  • the digitised acoustic cardiac signal 10 is sent to a wavelet transformer 11.
  • a frequency level 12 is selected in wavelet space - either automatically or, as in this case, manually.
  • the wavelet transform values across this level are interrogated 13 and the occurrence of the alternate large and small peaks ( Figure 2(c)) used to determine the pulse frequency.
  • Figure 4 (a) contains a longer segment of the signal shown in Figure 2.
  • Figure 4(b) the wavelet transform phase is plotted, derived using a complex wavelet analysing function. At this resolution, new, regular structure can be observed at frequencies at, around, and below 1Hz . This corresponds to patient breathing.
  • Figure 5(a) contains a three dimensional, modulus plot of the (wavelet) transformed signal of Figure 4(a). Two ridges appear in the transform surface of Figure 5 (a) corresponding to the breathing and pulse signals. The pulse and breathing rate can be obtained directly from these ridges in the time frequency plane .
  • Figure 5 (b) shows the same scalogram as Figure 5 (a) .
  • a schematic of the loci of the breathing and respiration ridges is plotted as black broken lines above the wavelet transform surface.
  • the breathing and respiration ridges may be tracked across the wavelet transform surface using a suitable ridge following algorithm as is currently available. Using both phase and modulus information both breathing and pulse signals can be monitored to provide the clinically useful information (e.g. the breathing and/or pulse rate, significant changes in breathing and/or pulse pattern, etc.) hidden within signals containing high degrees of noise and artefact .
  • FIG. 6 contains a block diagram of a preferred embodiment of the pulse and respiration detection and rate determination algorithm.
  • the digitised acoustic cardiac signal 20 is sent to a wavelet transformer 21.
  • a representation of the transform is made in the time frequency domain as a surface 22. This can be, for example, the scalogram or rescaled scalogram as described above.
  • the dominant ridges associated with the manifestation of respiration in the signal are determined 23. This is used to provide a respiration frequency through time directly from the time-frequency representation 24.
  • the dominant ridges associated with the manifestation of pulse in the signal may also be determined 25. This is used to provide a pulse frequency through time directly from the time- frequency representation 26. This may also be used as a check of the pulse rate determination described above and in Figure 3.
  • the resulting breathing rate and pulse rate may then be displayed on the device.
  • the method may be similarly employed to analyse other acoustic medical signals and so determine pertinent clinical information.
  • the method may be further employed to detect and identify motion artefact within signals of medical relevance.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Acoustics & Sound (AREA)
  • Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Physics & Mathematics (AREA)
  • Pulmonology (AREA)
  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)

Abstract

On décompose un signal cardiaque acoustique par des techniques de transformée d'ondelettes et le signal ainsi décomposé est analysé pour fournir des informations physiologiquement utiles. Ces informations peuvent être la fréquence cardiaque et/ou respiratoire et des anomalies de celles-ci. L'utilisation de la décomposition des ondelettes offre un degré élevé d'élimination du bruit, des artefacts et des signaux transitoires.
PCT/GB2002/005922 2001-12-28 2002-12-24 Analyse de signaux medicaux acoustiques Ceased WO2003055395A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2002356324A AU2002356324A1 (en) 2001-12-28 2002-12-24 Analysis of acoustic medical signals

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB0131024.2 2001-12-28
GB0131024A GB0131024D0 (en) 2001-12-28 2001-12-28 Analysis of acoustic medical signals

Publications (1)

Publication Number Publication Date
WO2003055395A1 true WO2003055395A1 (fr) 2003-07-10

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/GB2002/005922 Ceased WO2003055395A1 (fr) 2001-12-28 2002-12-24 Analyse de signaux medicaux acoustiques

Country Status (3)

Country Link
AU (1) AU2002356324A1 (fr)
GB (1) GB0131024D0 (fr)
WO (1) WO2003055395A1 (fr)

Cited By (50)

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GB2408124A (en) * 2003-11-14 2005-05-18 Siemens Med Solutions Health A biomedical data signal processing system
EP1769737A1 (fr) * 2005-09-29 2007-04-04 Siemens Aktiengesellschaft Procédé et dispositif d'affaiblissement des artéfacts respiratoires dans des données de tension arterielle
WO2009106691A1 (fr) * 2008-02-26 2009-09-03 Finsor Oy Procédé, appareil et ensemble de programmes informatiques permettant de détecter la fréquence cardiaque
WO2010007489A1 (fr) * 2008-07-15 2010-01-21 Nellcor Puritan Bennett Ireland Procédés et systèmes de traitement d’un signal de faible irrigation
US7944551B2 (en) 2008-06-30 2011-05-17 Nellcor Puritan Bennett Ireland Systems and methods for a wavelet transform viewer
US8226568B2 (en) 2008-07-15 2012-07-24 Nellcor Puritan Bennett Llc Signal processing systems and methods using basis functions and wavelet transforms
US8235911B2 (en) 2008-07-15 2012-08-07 Nellcor Puritan Bennett Ireland Methods and systems for filtering a signal according to a signal model and continuous wavelet transform techniques
US8285352B2 (en) 2008-07-15 2012-10-09 Nellcor Puritan Bennett Llc Systems and methods for identifying pulse rates
US8346333B2 (en) 2009-07-30 2013-01-01 Nellcor Puritan Bennett Ireland Systems and methods for estimating values of a continuous wavelet transform
US8358213B2 (en) 2008-07-15 2013-01-22 Covidien Lp Systems and methods for evaluating a physiological condition using a wavelet transform and identifying a band within a generated scalogram
US8364225B2 (en) 2009-05-20 2013-01-29 Nellcor Puritan Bennett Ireland Estimating transform values using signal estimates
US8385675B2 (en) 2008-07-15 2013-02-26 Nellcor Puritan Bennett Ireland Systems and methods for filtering a signal using a continuous wavelet transform
US8400149B2 (en) 2009-09-25 2013-03-19 Nellcor Puritan Bennett Ireland Systems and methods for gating an imaging device
US8478376B2 (en) 2009-07-30 2013-07-02 Nellcor Puritan Bennett Ireland Systems and methods for determining physiological information using selective transform data
US8515513B2 (en) 2008-11-05 2013-08-20 Covidien Lp System and method for facilitating observation of monitored physiologic data
US8594759B2 (en) 2009-07-30 2013-11-26 Nellcor Puritan Bennett Ireland Systems and methods for resolving the continuous wavelet transform of a signal
US8660625B2 (en) 2008-07-15 2014-02-25 Covidien Lp Signal processing systems and methods for analyzing multiparameter spaces to determine physiological states
US8679027B2 (en) 2008-07-15 2014-03-25 Nellcor Puritan Bennett Ireland Systems and methods for pulse processing
US8755871B2 (en) 2011-11-30 2014-06-17 Covidien Lp Systems and methods for detecting arrhythmia from a physiological signal
US8761855B2 (en) 2008-07-15 2014-06-24 Nellcor Puritan Bennett Ireland Systems and methods for determining oxygen saturation
US8834378B2 (en) 2010-07-30 2014-09-16 Nellcor Puritan Bennett Ireland Systems and methods for determining respiratory effort
US8855749B2 (en) 2009-09-24 2014-10-07 Covidien Lp Determination of a physiological parameter
US8870791B2 (en) 2006-03-23 2014-10-28 Michael E. Sabatino Apparatus for acquiring, processing and transmitting physiological sounds
US8880576B2 (en) 2011-09-23 2014-11-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US8923945B2 (en) 2009-09-24 2014-12-30 Covidien Lp Determination of a physiological parameter
US9011347B2 (en) 2008-10-03 2015-04-21 Nellcor Puritan Bennett Ireland Methods and apparatus for determining breathing effort characteristics measures
US9050043B2 (en) 2010-05-04 2015-06-09 Nellcor Puritan Bennett Ireland Systems and methods for wavelet transform scale-dependent multiple-archetyping
US9113830B2 (en) 2011-05-31 2015-08-25 Nellcor Puritan Bennett Ireland Systems and methods for detecting and monitoring arrhythmias using the PPG
US9113815B2 (en) 2008-06-30 2015-08-25 Nellcor Puritan Bennett Ireland Systems and methods for ridge selection in scalograms of signals
US9119597B2 (en) 2011-09-23 2015-09-01 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9155493B2 (en) 2008-10-03 2015-10-13 Nellcor Puritan Bennett Ireland Methods and apparatus for calibrating respiratory effort from photoplethysmograph signals
US9179876B2 (en) 2012-04-30 2015-11-10 Nellcor Puritan Bennett Ireland Systems and methods for identifying portions of a physiological signal usable for determining physiological information
US9192336B2 (en) 2003-02-27 2015-11-24 Nellcor Puritan Bennett Ireland Method of analyzing and processing signals
US9247896B2 (en) 2012-01-04 2016-02-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using phase locked loop
US9378332B2 (en) 2008-06-30 2016-06-28 Nellcor Puritan Bennett Ireland Processing and detecting baseline changes in signals
US9402554B2 (en) 2011-09-23 2016-08-02 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9554712B2 (en) 2013-02-27 2017-01-31 Covidien Lp Systems and methods for generating an artificial photoplethysmograph signal
US9560978B2 (en) 2013-02-05 2017-02-07 Covidien Lp Systems and methods for determining respiration information from a physiological signal using amplitude demodulation
US9597022B2 (en) 2011-09-09 2017-03-21 Nellcor Puritan Bennett Ireland Venous oxygen saturation systems and methods
US9675274B2 (en) 2011-09-23 2017-06-13 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9687159B2 (en) 2013-02-27 2017-06-27 Covidien Lp Systems and methods for determining physiological information by identifying fiducial points in a physiological signal
US9693736B2 (en) 2011-11-30 2017-07-04 Nellcor Puritan Bennett Ireland Systems and methods for determining respiration information using historical distribution
US9693709B2 (en) 2011-09-23 2017-07-04 Nellcot Puritan Bennett Ireland Systems and methods for determining respiration information from a photoplethysmograph
US9848820B2 (en) 2014-01-07 2017-12-26 Covidien Lp Apnea analysis system and method
US9901308B2 (en) 2014-02-20 2018-02-27 Covidien Lp Systems and methods for filtering autocorrelation peaks and detecting harmonics
US9955894B2 (en) 2014-01-28 2018-05-01 Covidien Lp Non-stationary feature relationship parameters for awareness monitoring
US9974468B2 (en) 2013-03-15 2018-05-22 Covidien Lp Systems and methods for identifying a medically monitored patient
US10022068B2 (en) 2013-10-28 2018-07-17 Covidien Lp Systems and methods for detecting held breath events
CN109567856A (zh) * 2018-11-23 2019-04-05 四川长虹电器股份有限公司 一种基于智能平台的听诊位置智能提醒方法
US11284827B2 (en) 2017-10-21 2022-03-29 Ausculsciences, Inc. Medical decision support system

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US7887490B2 (en) 2005-09-29 2011-02-15 Siemens Aktiengesellscahft Method and device for removing respiratory artefacts from measured blood pressure data
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US11357471B2 (en) 2006-03-23 2022-06-14 Michael E. Sabatino Acquiring and processing acoustic energy emitted by at least one organ in a biological system
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