WO2012057406A1 - Dispositif et procédé non invasifs de mesure de la motilité intestinale à l'aide d'une analyse des sons émis par les intestins - Google Patents

Dispositif et procédé non invasifs de mesure de la motilité intestinale à l'aide d'une analyse des sons émis par les intestins Download PDF

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WO2012057406A1
WO2012057406A1 PCT/KR2010/009614 KR2010009614W WO2012057406A1 WO 2012057406 A1 WO2012057406 A1 WO 2012057406A1 KR 2010009614 W KR2010009614 W KR 2010009614W WO 2012057406 A1 WO2012057406 A1 WO 2012057406A1
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signal
long sound
bowel
noise
invasive
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PCT/KR2010/009614
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English (en)
Korean (ko)
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송철규
서정환
김거식
유상훈
김민호
서자영
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전북대학교산학협력단
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Publication of WO2012057406A1 publication Critical patent/WO2012057406A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/008—Detecting noise of gastric tract, e.g. caused by voiding
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
    • A61B5/4222—Evaluating particular parts, e.g. particular organs
    • A61B5/4255—Intestines, colon or appendix
    • 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

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  • the present invention relates to an apparatus and method for measuring intestinal motility, and more particularly, to an apparatus and method for non-invasive diagnosis of intestinal motility using bowel sound signals generated by the movement of intestinal digestive substances and gases. will be.
  • the intestinal motility is diagnosed using Barr index, Blethyn index, colon transit time (CTT), and the most widely used method of diagnosing intestinal motility using CTT.
  • the method of diagnosing intestinal motility using CTT is performed by a subject swallowing a capsule containing a radiopaque marker, and then radiating the large intestine through X-ray or MRI after 1, 3, or 7 days. It is a method of diagnosing intestinal motility by checking the number of markers remaining.
  • the present invention is to solve the above problems, by using the characteristic parameters derived by analyzing the long-sound signal that is generated in the intestine using a feature variable to estimate the transit time (CTT) based on the quantitative motility It is an object of the present invention to provide an apparatus and method for measuring non-invasive bowel motility through diagnosing bowel sound.
  • another object of the present invention is to provide an apparatus and method for measuring non-invasive bowel motility through bowel analysis, which can reduce noise inevitably introduced to collect sound generated in the intestine.
  • the intestinal motility measuring apparatus in the non-invasive intestinal motility measurement device through the long sound analysis, the signal collection unit for measuring and outputting the long sound signal that is the sound generated in the intestine; A noise removing unit for removing noise from the long sound signal output from the signal collecting unit and outputting the noise; A variable extraction unit for extracting feature variables from the noise-removed long sound signal; A relation expression derivation unit for deriving a relation between the extracted feature variables and a previously measured colon transit time (CTT); And an intestinal motility diagnosis unit for diagnosing the exercise state of the intestine based on the derived relational expression.
  • CTT colon transit time
  • the method for measuring intestinal motility in the non-invasive method of diagnosing intestinal motility through the sound analysis of the bowel, comprising the steps of: measuring a long sound signal which is a sound generated in the intestine; Removing noise from the measured long sound signal; Extracting feature variables from the noise-free long sound signal; Deriving a relationship between the extracted feature variable and the colon transit time through a regression analysis; And diagnosing bowel motility using the derived relational expression.
  • the apparatus for removing noise from a long sound signal calculates a kurtosis vector of a long sound signal, which is a sound generated in a field, and sets the standard deviation of the vector as a critical point, Eliminating the signal is characterized in that to remove the time invariant signal.
  • the present invention has the effect of measuring the intestinal motility non-invasive and quantitatively by measuring and analyzing a long sound signal, which is a sound generated in the intestine, from the outside of the subject.
  • the present invention can measure the motility of the intestine in a short period of time through the long sound signal, there is an effect that helps in the early diagnosis and prognosis of the disease.
  • the present invention can measure the motility of the intestine within a short period of time without exposure to the radiation, there is an effect that can replace the use of conventional radiation equipment.
  • FIG. 1 is a block diagram showing the configuration of a non-invasive bowel motility measurement device through the sound analysis according to an embodiment of the present invention.
  • FIG 2 is an exemplary view showing a position for collecting a long sound signal according to an embodiment of the present invention.
  • FIG. 3 is an example of a graph showing a long sound signal measured in the present invention.
  • FIG. 4 is a flowchart illustrating a method for measuring non-invasive bowel motility through bowel analysis according to an embodiment of the present invention.
  • FIG. 5 is a flowchart specifically showing noise removing from a long sound signal in the flowchart of FIG. 4.
  • FIG. 1 is a block diagram showing the configuration of a non-invasive bowel motility measurement device through the sound analysis according to an embodiment of the present invention
  • Figure 2 is an illustration showing a position for collecting the long sound signal according to an embodiment of the present invention
  • 3 is an example of a graph showing a long sound signal measured in the present invention
  • FIG. 4 is a flowchart illustrating a method for measuring non-invasive field motility through long sound analysis according to an embodiment of the present invention
  • FIG. 5 is a flowchart illustrating the steps of removing noise from the long sound signal in the flowchart of FIG. 4.
  • the non-invasive bowel motility measurement device (A) through the long sound analysis in the non-invasive bowel motility measurement device through the long sound analysis, the sound generated in the intestine
  • a noise removing unit 200 which removes and outputs noise from the long sound signal output from the signal collecting unit 100
  • a relational expression deriving unit 400 for deriving a relational expression between the extracted feature variables and a previously measured colon transit time (CTT);
  • CTT colon transit time
  • an intestinal motility diagnosis unit 500 for diagnosing the exercise state of the intestine based on the derived relational expression.
  • the non-invasive bowel motility measurement method through the long sound analysis the step of collecting and measuring the long sound signal which is a sound generated in the intestine (S100); Removing invariant signals such as noise, especially heart sounds or respiratory sounds, from the collected and measured long sound (S200); Extracting feature variables from the noise-free long sound signal (S300); Deriving a relationship between the extracted feature variable and colon transit time (CTT) through regression analysis (S400); A method of diagnosing intestinal motility is performed by converting the extracted feature variable into an intestinal motility index, for example, a large intestine transit time, using the derived relational expression (S500).
  • the signal collection unit 100 collects and measures a long sound signal through at least one or more electronic stethoscopes or microphones (S100).
  • the signal collection unit 100 in a state in which the subject maintains an empty stomach for at least 8 hours or more, after ingesting a predetermined amount of food, for 10 minutes every 10 hours after 1 hour, 4 hours, and 8 hours Measure
  • the signal collector 100 may measure the long sound at a specific position of the abdomen as shown in FIG. 2 using three electronic stethoscopes (or microphones).
  • the signal collection unit 100 includes an ascending colon (CH1), a descending colon (CH2), and a sigmoid colon (CH3) located in the abdomen of the subject. It is desirable to measure the long sound signal in place.
  • CH1 ascending colon
  • CH2 descending colon
  • CH3 sigmoid colon
  • the signal collector 100 includes the measured long sound signal analog / digital converter 110, and converts the measured long sound signal, which is the measured analog signal, into a digital signal.
  • the analog / digital converter 110 preferably converts the digital signal to a sampling frequency of 8 KHz in consideration of the frequency band of the long sound signal.
  • the signal collection unit 100 includes a fourth Butterworth bandpass filter 120 to remove or minimize signal fluctuation noise caused by breathing noise or unnecessary movement caused by the subject's breathing.
  • the frequency band of the fourth-order Butterworth bandpass filter 120 is preferably 5 ⁇ 600 Hz.
  • the sampling frequency, the type of filter, the order and the frequency band of the signal collector 100 can be adjusted according to the characteristics of the device used when measuring the long sound.
  • the noise removing unit 200 removes noise of the long sound signal output from the signal collecting unit 100 by using an kurtosis-based noise detection method (IKD) (S200).
  • IKD kurtosis-based noise detection method
  • the noise removing unit 200 calculates the kurtosis vector of the long sound signal, removes the time-invariant signal by removing a signal in the time domain corresponding to a point below the threshold, using the standard deviation of the vector as a critical point. This removes the noise from the long sound signal.
  • the IKD algorithm is for selectively extracting only non-stationary signals from the entire signal, and is calculated by calculating the kurtosis of the signals.
  • the kurtosis of a time-varying signal has a larger characteristic than the kurtosis of a stationary signal. Since the long sound signal corresponds to a time-varying signal, this algorithm can effectively remove the respiratory sound and the heart sound, which are a kind of time invariant signal mixed with the long sound.
  • the noise removing unit 200 includes removing the noise by calculating a kurtosis vector of the long sound signal (S210); Calculating a standard deviation (SD) of the calculated kurtosis vector (S220); Removing only a long sound signal of a region in which a value less than the standard deviation (SD) exists among the calculated kurtosis vectors (S230); Calculating a sum of squares of noise which is the removed long sound signal (S240); And repeating the above step until the calculated sum of squares is smaller than a preset reference value (S250).
  • SD standard deviation
  • S220 Removing only a long sound signal of a region in which a value less than the standard deviation (SD) exists among the calculated kurtosis vectors
  • S230 Calculating a sum of squares of noise which is the removed long sound signal
  • S240 Calculating a sum of squares of noise which is the removed long sound signal
  • S250 a preset reference value
  • m j and ⁇ j are mean and standard deviation, respectively, measured in long sound.
  • the noise removing unit 200 calculates the standard deviation of the derived K in a second step (S220), so that a signal within the j th sliding window region in which a value less than the calculated standard deviation exists among the derived K is present. Only remove (S230).
  • the noise removing unit 200 calculates a sum of squares of the total noise, which is a signal in a j-th sliding window region in which a value less than the calculated standard deviation is present, in operation S240. If the sum of squares is larger than the preset reference value, it is determined that extra noise is mixed in the long sound signal, and the steps 1 and 2 are repeated. If the sum is smaller than the preset reference value, the noise is almost eliminated to determine that the noise is almost eliminated.
  • the process of removing ends (S250).
  • the preset reference value is a value set arbitrarily by the user as a single kurtosis value such as 10 and 20, for example. At this time, the smaller the predetermined reference value, the more noise is removed, but the long sound signal may also be inevitably removed.
  • the variable extractor 300 extracts a feature variable from the long sound signal from which the noise is removed (S300).
  • the characteristic variable is jitter (J ch, t ) , which is the period variation rate between pitches of the long sound signal, shimmer (S ch, t ), which is the magnitude variation rate, and trace (T ch ), which is the change amount of the jitter and shimmer. Equation 2] to [Equation 4].
  • Pi, Ai, and N are the periods between the pitches of the long sound signals, the magnitudes between the peaks of the pitches, and the total number of pitches, respectively.
  • ch and t represent channels (CH1, CH2, CH3) and time (after 1, 4, 8 hours) for measuring long sound, respectively.
  • the Pi, Ai, N are obtained through the long sound signal graph as shown in FIG.
  • FIG. 3 is an example of a graph showing a long sound signal measured in the present invention.
  • the period and amplitude between pitches of the long sound signal according to the present invention can be obtained through a graph.
  • Feature variable which is obtained by the above method is, for a period of a degree of variability in the collected prolonged sound pitch (jitter), the size change rate (shimmer) and measuring time represents the amount of change (trace) of the two variables, total of 21 (J ch, t 9 gae , S ch, t 9 and 3 T ch ).
  • the relational expression deriving unit 400 derives a relational expression for quantitatively diagnosing intestinal motility using the feature variable extracted through the variable extracting unit 300 (S400).
  • the relational expression obtains the colon pass time as an output value using the extracted feature variable as an input value.
  • the intestinal motility diagnosis unit 500 converts a feature variable into an intestinal motility index, for example, a large intestine transit time (CTT), based on the derived relationship to diagnose the intestinal motility. That is, the motility of the intestine of the subject is diagnosed based on the estimated CTT value. For example, if the CTT value is in the normal range (in the paper, it is generally known that the normal range of CTT is about 20 to 40 hours), it is judged as normal intestinal motility, and outside this range, it is diagnosed as fast or delayed motility. .
  • CTT large intestine transit time
  • the present invention estimates colonic transit time (CTT) using characteristic variables derived by analyzing long-term signals, which are sounds generated in the intestine, and based on this, non-invasive field through long-term analysis that can quantitatively diagnose intestinal motility.
  • CTT colonic transit time

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
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  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

La présente invention concerne un dispositif non invasif et un procédé non invasif de mesure de la motilité intestinale à l'aide d'une analyse des sons émis par les intestins. Le dispositif non invasif destiné à mesurer la motilité intestinale à l'aide d'une analyse des sons émis par les intestins comprend : une unité de collecte du signal qui mesure et affiche un son émis par les intestins, en d'autres termes un son intestinal ; une unité de suppression du bruit qui supprime le bruit du signal intestinal affiché par l'unité de collecte des signaux et qui affiche le signal ; une unité d'extraction de paramètres qui extrait les paramètres caractéristiques du son intestinal duquel le bruit a été supprimé ; une unité de définition d'une relation qui définit une relation entre les paramètres caractéristiques et le temps de transit colique (TTC) mesuré à l'avance ; et une unité de diagnostic de la motilité intestinale qui établit un diagnostic relatif à l'état de motilité de l'intestin en se basant sur la relation définie.
PCT/KR2010/009614 2010-10-26 2010-12-31 Dispositif et procédé non invasifs de mesure de la motilité intestinale à l'aide d'une analyse des sons émis par les intestins WO2012057406A1 (fr)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104305961A (zh) * 2014-10-20 2015-01-28 清华大学 肠鸣音监测识别系统
WO2015117035A1 (fr) * 2014-01-30 2015-08-06 University Of Florida Research Foundation, Inc. Procédés et systèmes de diagnostic de capacité d'alimentation
US9179887B2 (en) 2010-04-16 2015-11-10 University Of Tennessee Research Foundation Systems and methods for predicting gastrointestinal impairment
CN111407307A (zh) * 2020-04-17 2020-07-14 华中科技大学同济医学院附属协和医院 肠蠕动电刺激按摩装置及电刺激按摩方法
US11918408B2 (en) 2019-04-16 2024-03-05 Entac Medical, Inc. Enhanced detection and analysis of biological acoustic signals

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US5301679A (en) * 1991-05-31 1994-04-12 Taylor Microtechnology, Inc. Method and system for analysis of body sounds
US6228040B1 (en) * 1998-08-04 2001-05-08 Western Research Company, Inc. Method and apparatus for diagnosis of irritable bowel syndrome
US6776766B2 (en) * 1996-04-03 2004-08-17 Rush-Presbyterian-St. Luke's Medical Center Method and apparatus for characterizing gastrointestinal sounds
US20080306355A1 (en) * 2006-11-20 2008-12-11 Smithkline Beecham Corporation Method and System for Monitoring Gastrointestinal Function and Physiological Characteristics

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5301679A (en) * 1991-05-31 1994-04-12 Taylor Microtechnology, Inc. Method and system for analysis of body sounds
US6776766B2 (en) * 1996-04-03 2004-08-17 Rush-Presbyterian-St. Luke's Medical Center Method and apparatus for characterizing gastrointestinal sounds
US6228040B1 (en) * 1998-08-04 2001-05-08 Western Research Company, Inc. Method and apparatus for diagnosis of irritable bowel syndrome
US20080306355A1 (en) * 2006-11-20 2008-12-11 Smithkline Beecham Corporation Method and System for Monitoring Gastrointestinal Function and Physiological Characteristics

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9179887B2 (en) 2010-04-16 2015-11-10 University Of Tennessee Research Foundation Systems and methods for predicting gastrointestinal impairment
US10603006B2 (en) 2010-04-16 2020-03-31 University Of Tennessee Research Foundation Systems and methods for predicting gastrointestinal impairment
US11801030B2 (en) 2010-04-16 2023-10-31 University Of Tennessee Research Foundation Systems and methods for predicting gastrointestinal impairment
WO2015117035A1 (fr) * 2014-01-30 2015-08-06 University Of Florida Research Foundation, Inc. Procédés et systèmes de diagnostic de capacité d'alimentation
US10478116B2 (en) 2014-01-30 2019-11-19 University Of Florida Research Foundation, Inc. Methods and systems for feeding readiness diagnosis
CN104305961A (zh) * 2014-10-20 2015-01-28 清华大学 肠鸣音监测识别系统
US11918408B2 (en) 2019-04-16 2024-03-05 Entac Medical, Inc. Enhanced detection and analysis of biological acoustic signals
CN111407307A (zh) * 2020-04-17 2020-07-14 华中科技大学同济医学院附属协和医院 肠蠕动电刺激按摩装置及电刺激按摩方法

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