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WO2005074794A1 - Composant analyseur de bruit de coeur qui extrait les bruits de coeur du foetus des informations de bruit de coeur comprenant plusieurs bruits de coeur melanges de plusieurs foetus - Google Patents

Composant analyseur de bruit de coeur qui extrait les bruits de coeur du foetus des informations de bruit de coeur comprenant plusieurs bruits de coeur melanges de plusieurs foetus Download PDF

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Publication number
WO2005074794A1
WO2005074794A1 PCT/US2004/022738 US2004022738W WO2005074794A1 WO 2005074794 A1 WO2005074794 A1 WO 2005074794A1 US 2004022738 W US2004022738 W US 2004022738W WO 2005074794 A1 WO2005074794 A1 WO 2005074794A1
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WIPO (PCT)
Prior art keywords
heart sound
heart
fetuses
fetus
sound information
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Ceased
Application number
PCT/US2004/022738
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English (en)
Inventor
Roland Priemer
Vivek Nigam
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University of Illinois System
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University of Illinois System
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Publication of WO2005074794A1 publication Critical patent/WO2005074794A1/fr
Anticipated expiration legal-status Critical
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/02—Stethoscopes
    • A61B7/023—Stethoscopes for introduction into the body, e.g. into the oesophagus
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/02—Stethoscopes
    • A61B7/026—Stethoscopes comprising more than one sound collector
    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/22—Source localisation; Inverse modelling

Definitions

  • TECHNICAL FIELD This invention relates generally to the medical arts and more particularly to sensing of heart sound information.
  • BACKGROUND A multiple gestation is a pregnancy in which a woman carries more than one fetus.
  • Multiple gestations are concerning because women who are expecting more than one baby are at increased risk of certain pregnancy complications, including preterm delivery. Some of the complications associated with multiple gestation can be minimized if they are detected and diagnosed early.
  • the embryonic heart starts beating twenty-two days after conception. The heart at this stage may be too small to hear.
  • the ninth or tenth week after the last menstrual period of the expecting mother one is more likely to be able to hear the heartbeat of the fetus.
  • the heartbeat can usually be heard consistently by using a Doppler instrument for amplification.
  • the human ear is unequalled in detecting sounds over a particular frequency range, the spectrum occupied by fetal heart sounds is on the threshold of audibility.
  • FPCG fetal phonocardiogram
  • the invention in one implementation encompasses an apparatus.
  • the apparatus comprises a heart sound analyzer component that extracts a heart sound of a fetus from heart sound information that comprises a plurality of mixtures of a plurality of heart sounds of a plurality of fetuses .
  • Another implementation of the invention encompasses a method.
  • Heart sound information is obtained that comprises a plurality of mixtures of a plurality of heart sounds of a plurality of fetuses.
  • a heart sound of a fetus extracted from the heart sound information.
  • FIG. 1 is a representation of one exemplary implementation of an apparatus that comprises a heart sound analyzer, a sensor array of a plurality of sensors, a plurality of signal paths, and one or more speaker components.
  • FIG. 2 is a representation of the heart sound analyzer of the apparatus of FIG. 1, and illustrates one or more analog to digital converters, one or more data buffer components, one or more software memory components, one or more processor components, one or more digital to analog converters, one or more filters, one or more amplifiers, one or more storage devices, one or more input devices, and one or more output devices.
  • FIG. 3 is a representation of a womb of a woman that carries a plurality of fetuses that each contributes a heart sound to heart sound information captured by the plurality of sensors of the apparatus of FIG. 1.
  • FIG. 4 is a representation of an exemplary neural network that extracts two statistically independent outputs from heart sound information captured by the plurality of sensors of the apparatus of FIG. 1.
  • FIG. 5 is a representation of an exemplary interaction between a neural network and a recursive parameter adjustment algorithm of the heart sound analyzer of the apparatus of FIG. 1.
  • FIG. 6 is a representation of one exemplary plot of two fetal phonocardiograms that comprise heart sounds of two fetal hearts.
  • FIG. 7 is a representation of another exemplary plot of heart sound information representing the output of two sensors of the plurality of sensors of the apparatus of FIG. 1.
  • Two fetal heart sounds are delayed by propagation delays between the fetal hearts and the plurality of sensors and then mixed by each of the plurality of sensors.
  • FIG. 8 is a representation of another exemplary plot of two fetal phonocardiograms extracted from heart sound information by the heart sound analyzer of the apparatus of FIG. 1.
  • an apparatus 100 in one example comprises a heart sound analyzer 102, a sensor array 103 of a plurality of sensors 104, 106, 108, and 110, a plurality of signal paths 112, 114, 116, and 118, and one or more speaker components 120.
  • the sensors 104, 106, 108, and 110 in one example obtain heart sound information 122 from a plurality of fetal hearts.
  • the heart sound information 122 comprises a plurality of mixtures of a plurality of heart sounds of a plurality of fetuses.
  • the sensors 104, 106, 108, and 110 each capture fetal phonocardiograms ("FPCGs") from the hearts of the plurality of fetuses within a womb of a woman.
  • the heart sound information 122 comprises mixtures of heart sounds from the plurality of fetuses.
  • the sensors 104, 106, 108, and 110 pass the heart sound information 122 through the signal paths 112, 114, 116, and 118 to the heart sound analyzer 102.
  • the heart sound analyzer 102 extracts a heart sound 124 of a fetus from the heart sound information 122 for aural examination by a doctor.
  • the heart sound 124 represents a heartbeat of a single fetal heart substantially without interference from heartbeats of the other fetal hearts within the womb.
  • the heart sound analyzer 102 separates the heart sound 124 from one or more other sounds of the heart sound information 122.
  • the heart sound analyzer 102 in one example comprises a fetal phonocardiogram analyzer.
  • the plurality of fetuses may comprise twins, triplets, quadruplets, quintuplets, or more.
  • the heart sound information 122 may comprise a mixture of two, three, four, five, or more fetal hearts.
  • the apparatus 100 comprises a number of the plurality of sensors 104, 106, 108, and 110 at least equal to a number of the plurality of fetuses.
  • the apparatus 100 comprises a number of the plurality of sensors 104, 106, 108, and 110 greater than a number of the plurality of fetuses.
  • the plurality of fetuses may comprise two fetuses and the apparatus 100 may comprise three sensors to allow separation of background noise, or the like, from the output of the heart sound 124 of one of the plurality of fetuses.
  • the sensors in one example comprise microphones. The microphones capture the heart sound information 122.
  • the heart sound analyzer 102 comprises one or more analog to digital converters 204, one or more data buffer components 206 and 212, one or more software memory components 208, one or more processor components 210, one or more digital to analog converters 214, one or more filters 216, one or more amplifiers 218, one or more storage devices 220, one or more input devices 222, and one or more output devices 224.
  • the heart sound analyzer 102 Upon receipt of the heart sound information 122 from the sensor array 103, the heart sound analyzer 102 processes the heart sound information 122 and in one example outputs the heart sound 124.
  • the processor component 210 of the heart sound analyzer 102 extracts heartbeats of one or more of the plurality of fetuses from the heart sound information 122.
  • the heart sound 124 comprises a heartbeat of a first fetus of the plurality of fetuses within the womb.
  • the heart sound information 122 comprises a plurality of mixtures of a first heartbeat of a first fetus and a second heartbeat of a second fetus.
  • the heart sound analyzer 102 employs a blind source separation algorithm that accounts for propagation delays of the heart sound information 122 to create statistically independent outputs of one or more of the first heartbeat and the second heartbeat.
  • the heart sound analyzer 102 in one example employs an independent component analysis procedure to extract the heart sound 124 from the heart sound information 122.
  • the analog to digital converter 204 in one example obtains the heart sound information 122 from the sensor array 103.
  • the analog to digital converter 204 in one example digitizes the heart sound information 122.
  • the processor component 210 employs the analog to digital converter 204 to digitize the heart sound information 122.
  • the analog to digital converter 204 in one example outputs an MxK matrix of data of the heart sound information 122 to the data buffer component 206, where, for example, M is the number of sensors (e.g., the sensors 104, 106, 108, and 110) in the sensor array 103 and K is the number of times the analog to digital converter 204 samples the heart sound information 122.
  • the data buffer component 206 in one example comprises MxK point double buffered data memory.
  • the data buffer component 206 in one example provides the MxK matrix of data to the processor component 210.
  • the data buffer component 206 in one example comprises a demultiplexer, first and second data buffers, and a multiplexer.
  • the processor component 210 in one example controls the demultiplexer to steer the output of the analog to digital converter 204 to the first data buffer with an MxK matrix of data. While the first data buffer is filling with data, the processor component 210 in one example controls the multiplexer to steer data from the second data buffer to the processor component 210 until the processor component 210 has received an MxK matrix of data.
  • the processor component 210 processes the MxK matrix of data with software stored in the software memory component 208.
  • the processor component 210 controls the demultiplexer to steer data to the second data buffer with an MxK matrix of data. While the second data buffer is filling with data, the processor component 210 in one example controls the multiplexer to steer data from the first data buffer to the processor component 210 until the processor component 210 has received an MxK matrix of data.
  • the processor component 210 again employs the software stored in the software memory component 208 to process the MxK matrix of data. By continuously reversing the roles of the first and second data buffers, the heart sound analyzer 102 can work in real time.
  • the software memory component 208 in one example stores software for use by the processor component 210.
  • the processor component 210 employs the software to extract the heart sound 124 from the heart sound information 122.
  • the software memory component 208 in one example comprises an instance of the recordable data storage medium 146.
  • the software memory component 208 in one example stores a blind source separation algorithm that accounts for propagation delays within the heart sound information 122.
  • the processor component 210 employs the blind source separation algorithm to extract the heart sound 124 from the heart sound information 122.
  • the processor component 210 stores the heart sound 124.
  • the processor component 210 may store the heart sound 124 in the storage device 220. The processor component 210 may then access the heart sound 124 upon request from a user of the heart sound analyzer 102.
  • the user may employ the input device 222 to cause the processor 210 to output the heart sound 124 to the output device 224 and/or the speaker component 120.
  • the input device 222 in one example comprise one or more of a button, a dial, a mouse, a keyboard, and/or a touch-screen.
  • the output device 224 in one example comprise a liquid crystal display ("LCD").
  • LCD liquid crystal display
  • the user may also choose to filter, amplify, and/or shift a spectral content of the heart sound 124 from a first frequency range to a second frequency range with the processor component 210.
  • the processor component 210 employs digital filtering software to filter out one or more frequency ranges of the heart sound 124.
  • the processor component 210 amplifies one or more regions of the heart sound 124.
  • the processor component 210 may shift the spectral content of the heart sound 124 from a first frequency range to a second frequency range. For example, the user may hear better in the second frequency range than in the first frequency range.
  • the data buffer component 212 obtains data from the processor component 210.
  • the data buffer component 212 obtains the heart sound 124 from the processor component 210.
  • the data buffer component 212 obtains the heart sound 124 from the processor component 210.
  • the data buffer component 212 in one example comprises K point double buffered data memory.
  • the digital to analog converter 214 in one example converts a digital representation of the heart sound 124 into an analog representation of the heart sound 124.
  • the digital to analog converter 214 in one example outputs the heart sound 124 to one or more of the speaker component 120, the filter 216, and/or the amplifier 218.
  • the filter 216 in one example filters one or more frequency ranges of the analog representation of the heart sound 124.
  • the filter 216 in one example comprises one or more low pass filters.
  • the amplifier 218 in one example amplifies an output of the filter 216 to drive the speaker component 120.
  • the user may employ one or more of the speaker component 120 and/or the output device 224 to listen to and/or view the heart sound 124 and/or a representation of the heart sound 124.
  • the user may employ the speaker component 120 and/or the output device 224 for examination of the heart sound 124.
  • the user may employ the heart sound analyzer 102 to automatically diagnose one or more fetal heart dysfunctions.
  • the processor component 210 compares one or more features (e.g., signatures) of the heart sound 124 to a normal range of the features (e.g., signatures) of the heart sound 124. If the heart sound 124 is outside of the normal range, then the heart sound 124 may indicate one or more dysfunctions.
  • the heart sound 124 in one example is a mixture of a plurality of discrete heart sounds from a plurality of corresponding distinct heart sound sources (e.g., a heart valve) of a single fetal heart.
  • the heart sound analyzer 102 may extract from the heart sound 124 one or more discrete heart sounds of the corresponding distinct heart sound sources, as described in "EXTRACTION OF ONE OR MORE DISCRETE HEART SOUNDS FROM HEART SOUND INFORMATION," by Priemer, co-filed herewith.
  • the heart sound 124 may comprise a first discrete heart sound from a first distinct sound source of the single fetal heart.
  • the heart sound 124 may also comprise a second discrete heart sound from a second distinct sound source of the single fetal heart.
  • the first and second discrete heart sounds in one example occur contemporaneously in the heart sound 124.
  • the heart sound analyzer 102 in one example creates statistically independent outputs of one or more of the first discrete heart sound and the second discrete heart sound to allow aural examination of the individual first and second discrete heart sounds by a doctor.
  • a womb 302 of a woman may carry a plurality of fetuses 304 and 306.
  • Each of the fetuses 304 and 306 contribute heart sounds to the heart sound information 122 captured by the sensors 104, 106, 108, and 110.
  • the sensors 104, 106, 108, and 110 in one example are organized into a plurality of sensor pods 308 and 310.
  • each of the sensor pods 308 and 310 comprise a single sensor or microphone.
  • the sensor pod 308 comprises a plurality of sensors (e.g., the sensors 104 and 106) and the sensor pod 310 comprises a plurality of sensors (e.g., the sensors 108 and 110).
  • the sensor pods 308 and 310 are independently movable over an abdomen 312 of the woman to capture the heart sound information 122 of the fetuses 304 and 306 within the womb 302. For example, a doctor may move the sensor pod 308 over the abdomen 312 to a location that is near the fetus 304 and the doctor may move the sensor pod 310 over the abdomen 312 to a location that is near the fetus 306.
  • the heart sound information 122 comprises a mixture of first heart sounds from a heart 314 of the fetus 304 and second heart sounds from a heart 316 of the fetus 306.
  • the first heart sounds from the fetus 304 experience a propagation delay (d 22 ) 318 traveling to the sensor pod 308 and a propagation delay (d ⁇ 2 ) 320 traveling to the sensor pod 310.
  • the second heart sounds from the fetus 306 experience a propagation delay (d 21 ) 322 traveling to the sensor pod 308 and a propagation delay (d ⁇ ) 324 traveling to the sensor pod 310.
  • a neural network 402 illustrates an exemplary extraction of two statistically independent outputs from the heart sound information 122 captured by two sensors (e.g., the sensors 104 and 106).
  • the processor component 210 passes the heart sound information 122 through a plurality of external nodes of the neural network 402 in number at least equal to the number of the plurality of fetuses 304 and 306.
  • the processor component 210 passes the heart sound information 122 through a plurality of internal nodes of the neural network 402 equal to the number of external nodes to determine one or more weights and one or more delays of each of the heart sounds from the plurality of fetuses 304 and 306.
  • the neural network 406 outputs an MxK matrix of data that represents the heart sounds of the plurality of fetuses 304 and 306.
  • the heart sounds of the plurality of fetuses 304 and 306 in one example are statistically independent.
  • the heart sound information 122 comprises a plurality of composite heart sounds.
  • the plurality of composite heart sounds comprise a composite heart sound signal (xi) 404 captured by the sensor 104 and a composite heart sound signal (x 2 ) 406 captured by the sensor 104.
  • the outputs of the sensors 104 and 106 are sampled at discrete time points t.
  • the sampling rate is 1/T samples/sec, and n is called the discrete time index.
  • the composite heart sound signals ( i and x 2 ) 404 and 406 in one example comprise delayed mixtures of fetal phonocardiogram (si) produced by the fetus 306 and fetal phonocardiogram (s 2 ) produced by the fetus 304.
  • d 22 , d 12 , d 21 , and d ⁇ represent the propagation delays 318, 320, 322, and 324 of the first and second heart sounds.
  • a 12 , a 21 , and a 22 represent attenuations of the first and second heart sounds due to signal strength losses traveling through the abdomen 312 of the woman to the sensors (e.g., the sensors 104 and 106).
  • the neural network 402 serves to separate the composite heart sound signals (xi and x 2 ) 404 and 406 to obtain estimates (ui and u 2 ) 408 and 410 of the fetal phonocardiograms si and s 2 .
  • b ⁇ 2 and b 2 ⁇ represent delay differences 414 and 412 between the propagation delays 318, 320, 322, and 324.
  • w 0 ⁇ , w l l9 w 12 , w 02 , w 22 and w 1 represent weights 416, 420, 424, 418, 422, and 426 of the neural network 402.
  • the blocks 428 and 430 that convert the estimates (ui and u 2 ) 408 and 410 to signals (yi and y 2 ) 432 and 434 represent nonlinearities described by the equations below.
  • a logistic function relates the estimate (ui) 408 to the signal (yi) 432 and the estimate (u 2 ) 410 to the signal (y 2 ) 434.
  • a monotonically increasing nonlinear function converts the estimate (ui) 408 to the signal (yi) 432 and the estimate (u 2 ) 410 to the signal (y 2 ) 434.
  • the parameters e.g., the weights (wrji, w ⁇ , w 12 , wo 2 , w 22 and w 21 ) 416, 420, 424, 418, 422, and 426, and the delay differences (b ⁇ 2 and b 2 ⁇ ) 414 and 412) of the neural network 402 are calculated to make the signals (yi and y 2 ) 432 and 434 statistically independent. Then, the estimates (ui and u 2 ) 408 and 410 must also be statistically independent.
  • the estimate (ui) 408 becomes proportional to the fetal phonocardiogram (s ) and the estimate (u 2 ) 410 becomes proportional to the fetal phonocardiogram (s 2 ), delayed by the propagation delays (d ⁇ and d 22 ) 324 and 318, respectively, which means that the estimates (ui andu 2 ) 408 and 410 are statistically independent, resulting in: u 2 (t) ⁇ a 22 w 22 s 2 (t-d 22 ) oc s 2 (t-d 22 ) Determining the weights (w 0 ⁇ , w ⁇ , w 12 , w 02 , w 22 and w 2 ⁇ ) 416, 420, 424, 418, 422, and 426, and the delay differences (b ⁇ 2 and b 2 ⁇ ) 412 and 414 that will make the signals (yi and y 2 ) 432 and 434 statistically independent is the goal of the phonocardiogram separator depicted in FIG
  • the formulas above give the gradients of entropy of the signals H(y ls y 2 ) with respect to each of the parameters of the neural network 402.
  • a parameter of the neural network 402 such as the weight (w ⁇ ) 420.
  • the gradient of H with respect to the weight (w ⁇ ) 420 is denoted by ⁇ w ⁇ .
  • ⁇ w ⁇ can be calculated for each input sample X ⁇ (t) and x 2 (t)
  • y ⁇ (t) and y 2 (t) and u ⁇ (t) and u 2 (t) can be calculated and then ⁇ w ⁇ (t) can also be calculated.
  • ⁇ w ⁇ can be calculated for many (e.g.,
  • the blind source separation algorithm that accounts for the propagation delays of the heart sound information 122 comprises a number of steps.
  • the first step is for the heart sound analyzer 102 to collect a fixed number (e.g., K) of incoming mixture samples in a single frame.
  • the second step is for the heart sound analyzer 102 to calculate the updates to be made to the weights (w 0 ⁇ , w ⁇ , w 12 , w 02 , w 22 and w 21 ) 416, 420, 424, 418, 422, and 426, and propagation delay differences (b ⁇ 2 and b 2 ⁇ ) 414 and 412 by iterating over the frame once.
  • This is equivalent to averaging K gradients and updating the weights (woi, w ⁇ , w ⁇ 2 , W 02 , w 22 and w 21 ) 416, 420, 424, 418, 422, and 426, and propagation delay differences (b ⁇ 2 and b 21 ) 414 and 412.
  • the third step is for the heart sound analyzer 102 to repeat the first and second steps until a predetermined number of iterations over a frame have been completed, or the updates to weights (w 0 ⁇ , w ⁇ , w 12 , w 02 , w 22 and w 21 ) 416, 420, 424, 418, 422, and 426, and propagation delay differences (b 12 and b 2 ⁇ ) 414 and 412 have become smaller than a predetermined threshold.
  • the fourth step is for the heart sound analyzer 102 to input the next frame, which comprises new incoming data, and discard the last frame.
  • the fifth step is for the heart sound analyzer 102 to repeat the first, second, third, and fourth steps until the weights (w 0 ⁇ , w ⁇ , w ⁇ 2 , w 02 , w 22 and w 21 ) 416, 420, 424, 418, 422, and 426, and propagation delay differences (b 12 and b 2 ⁇ ) 414 and 412 have converged to constants.
  • the neural network 402 receives the composite heart sound signals (xi and x 2 ) 404 and 406 as inputs.
  • a recursive parameter adjustment algorithm 502 also receives the heart sound signals (xi and x 2 ) 404 and 406 as inputs.
  • the neural network 402 produces the estimates (ui and u 2 ) 408 and 410 and the signals (yi and y 2 ) 432 and 434.
  • the recursive parameter adjustment algorithm 502 receives the estimates (ui and u 2 ) 408 and 410 and the signals (yi and y 2 ) 432 and 434 as inputs.
  • the recursive parameter adjustment algorithm 502 serves to determine the parameters (e.g., the weights and delay differences) of the neural network 402. Referring to FIGS. 1 and 6-8, fetal phonocardiograms 602 and 604 illustrate heart sounds of two fetal hearts. FIG.
  • FIG. 7 depicts heart sound information 702 and 704 comprised of mixtures of heart sounds of the two fetal hearts delayed by propagation delays between the fetal hearts and the sensors.
  • Fetal phonocardiograms 802 and 804 illustrate a separation of the heart sounds of the two fetal hearts from the mixed phonocardiograms 702 and 704.
  • the heart sound information 122 comprises the two phonocardiogram mixtures 702 and 704.
  • the heart sound analyzer 102 extracts the heart sound of each of the two fetuses into statistically independent outputs.
  • the apparatus 100 in one example comprises a plurality of components such as one or more of electronic components, hardware components, and computer software components. A number of such components can be combined or divided in the apparatus 100.
  • An exemplary component of the apparatus 100 employs and/or comprises a set and/or series of computer instructions written in or implemented with any of a number of programming languages, as will be appreciated by those skilled in the art.
  • the apparatus 100 in one example employs one or more computer-readable signal-bearing media.
  • Examples of a computer-readable signal-bearing medium for the apparatus 100 comprise the recordable data storage medium 146 of the heart sound analyzer 102.
  • the computer-readable signal-bearing medium for the apparatus 100 comprises one or more of a magnetic, electrical, optical, biological, and atomic data storage medium.
  • the computer-readable signal-bearing medium comprises a modulated carrier signal transmitted over a network comprising or coupled with the apparatus 100, for instance, one or more of a telephone network, a local area network ("LAN"), the internet, and a wireless network.
  • a network comprising or coupled with the apparatus 100, for instance, one or more of a telephone network, a local area network ("LAN"), the internet, and a wireless network.

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

Abstract

L'invention concerne un composant analyseur de bruits de coeur (102) d'un appareil (100) qui extrait, par un exemple, un bruit de coeur (124) d'un foetus parmi les informations de bruit de coeur (122) de plusieurs bruits de coeur mélangés de plusieurs foetus (304, 306).
PCT/US2004/022738 2004-01-21 2004-07-16 Composant analyseur de bruit de coeur qui extrait les bruits de coeur du foetus des informations de bruit de coeur comprenant plusieurs bruits de coeur melanges de plusieurs foetus Ceased WO2005074794A1 (fr)

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US60/537,941 2004-01-21

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PCT/US2004/023049 Ceased WO2005076148A1 (fr) 2004-01-21 2004-07-16 Identification d'une ou plusieurs sources de bruits cardiaques distinctes produisant un ou plusieurs bruits cardiaques discrets
PCT/US2004/022738 Ceased WO2005074794A1 (fr) 2004-01-21 2004-07-16 Composant analyseur de bruit de coeur qui extrait les bruits de coeur du foetus des informations de bruit de coeur comprenant plusieurs bruits de coeur melanges de plusieurs foetus

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2162644A (en) * 1984-06-29 1986-02-05 Walter Campbell Peaston Separating heartbeat sources
WO2003003905A2 (fr) * 2001-07-05 2003-01-16 Softmax, Inc. Systeme et procede de separation de signaux cardiaques

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GB2162644A (en) * 1984-06-29 1986-02-05 Walter Campbell Peaston Separating heartbeat sources
WO2003003905A2 (fr) * 2001-07-05 2003-01-16 Softmax, Inc. Systeme et procede de separation de signaux cardiaques

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MOGHAVVEMI M ET AL: "A non-invasive PC-based measurement of fetal phonocardiography", SENSORS AND ACTUATORS A, ELSEVIER SEQUOIA S.A., LAUSANNE, CH, vol. 107, no. 1, 1 October 2003 (2003-10-01), pages 96 - 103, XP004452856, ISSN: 0924-4247 *
VARADY P; WILDT L; BENYO Z; HEIN A: "An advanced method in fetal phonocardiography", COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol. 71, no. 3, July 2003 (2003-07-01), pages 283 - 296, XP008037413 *

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