[go: up one dir, main page]

WO2018152675A1 - Système et procédé de dépistage précoce pour artériosclérose périphérique - Google Patents

Système et procédé de dépistage précoce pour artériosclérose périphérique Download PDF

Info

Publication number
WO2018152675A1
WO2018152675A1 PCT/CN2017/074250 CN2017074250W WO2018152675A1 WO 2018152675 A1 WO2018152675 A1 WO 2018152675A1 CN 2017074250 W CN2017074250 W CN 2017074250W WO 2018152675 A1 WO2018152675 A1 WO 2018152675A1
Authority
WO
WIPO (PCT)
Prior art keywords
pulse wave
wave signal
data
processing
dimensional
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/CN2017/074250
Other languages
English (en)
Chinese (zh)
Inventor
熊毅
刘成
陈仕欢
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.)
Shenzhen Hailife Technology Co Ltd
Original Assignee
Shenzhen Hailife Technology Co 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 Shenzhen Hailife Technology Co Ltd filed Critical Shenzhen Hailife Technology Co Ltd
Priority to PCT/CN2017/074250 priority Critical patent/WO2018152675A1/fr
Publication of WO2018152675A1 publication Critical patent/WO2018152675A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow

Definitions

  • the invention relates to the technical field of medical instruments, in particular to an early screening system and method for peripheral arteriosclerosis.
  • Arteriosclerosis is a primary disease that seriously affects human health. It is an effective, simple, low-risk, low-cost measure to improve human quality of life through early accurate, non-invasive screening and prevention.
  • the pulse wave signal is processed to obtain an index of arteriosclerosis.
  • both existing products and related theories are based on time domain processing technology.
  • the time domain treatment effectively solves the cases in the early screening of some peripheral arteriosclerosis in clinical applications, its clinical use is still limited and contingent. For example, the location of a thrombus cannot be accurately performed, the development trend of the disease cannot be accurately evaluated, and the early stage of thrombosis and the early degeneration of the arterial smooth muscle are difficult to find. Therefore, there is a need for an early screening system and method for arteriosclerosis that will provide clinicians with a reliable basis for disease assessment.
  • the present invention provides an early screening method for peripheral arteriosclerosis, the method comprising the steps of:
  • S2 performing data preprocessing on the pulse wave signal, where the data preprocessing comprises performing data preprocessing on the pulse wave signal by using FIR filtering;
  • S3 performing real-time frequency domain processing on the pulse wave signal preprocessed by the data, and obtaining a continuous three-dimensional waterfall spectrogram and/or a three-dimensional contour grayscale image, by using the three-dimensional waterfall spectrogram and/or three-dimensional
  • the contour grayscale map determines whether the patient has arteriosclerosis.
  • the method further comprises: S4: processing the pulse wave signal preprocessed by the data to obtain a thrombus in the artery of the patient by using a cross-correlation method position.
  • the present invention also provides an early screening system for peripheral arteriosclerosis, the system comprising: an infrared photoelectric data sensor for acquiring a pulse wave signal; a data preprocessing module for preprocessing the pulse wave signal, the data
  • the pre-processing module includes an FIR filtering module, configured to perform real-time frequency domain processing on the pulse wave signal preprocessed by the data, and obtain an amplitude spectrum for generating a three-dimensional waterfall spectrogram and a three-dimensional contour grayscale image.
  • An FFT processing module of the power spectrum optionally including a cross-correlation processing module for processing the pulse wave signal preprocessed by the data and acquiring a thrombus position in the artery of the patient by using a cross-correlation processing method; a main control unit for control and data calculation; and for displaying the three-dimensional waterfall spectrogram, the three-dimensional contour grayscale map, and the position of the thrombus a display module, wherein the infrared photoelectric data sensor is electrically connected to the data pre-processing module, and the data pre-processing module is electrically connected to an FFT processing module and a cross-correlation processing module, respectively, and the main control unit and the infrared photoelectric data respectively The sensor, the data pre-processing module, the FFT processing module, and the cross-correlation processing module are electrically connected.
  • the early screening method and system for peripheral arteriosclerosis provided by the present invention can be used by clinicians to evaluate human arterial lesions, especially for clinicians to have arteriosclerosis in the human body, and further The presence or absence of thrombus in the arteries provides a reliable basis for assessment.
  • FIG. 1 is a flow chart of an early screening method for peripheral arteriosclerosis according to a preferred embodiment of the present invention
  • FIG. 2 is a waveform diagram of a pulse wave signal collected by an early screening method for peripheral arteriosclerosis of the present invention
  • Figure 3 is a waveform diagram of another pulse wave signal collected by the early screening method of peripheral arteriosclerosis of the present invention.
  • 4a, 4b are three-dimensional waterfall spectrograms of Example 1 obtained by testing a normal person by the early screening method of peripheral arteriosclerosis of the present invention
  • 5a and 5b are three-dimensional waterfall spectrograms of Example 2 obtained by testing an arteriosclerotic patient by an early screening method for peripheral arteriosclerosis of the present invention
  • Figure 6 is an arteriosclerosis by an early screening method for peripheral arteriosclerosis of the present invention.
  • the three-dimensional contour line grayscale image of Example 3 obtained by the patient;
  • Figure 7 is a cross-correlation curve showing the presence of a thrombus in an artery obtained by testing an arteriosclerotic patient by an early screening method for peripheral arteriosclerosis of the present invention
  • Figure 8 is a cross-correlation curve when there is no thrombus in an artery obtained by testing a normal person by the early screening method of peripheral arteriosclerosis of the present invention
  • Figure 9 is a functional block diagram of an early arteriosclerosis screening system in accordance with a preferred embodiment of the present invention.
  • a preferred embodiment of the present invention provides an early screening method for peripheral arteriosclerosis comprising the following steps:
  • the pulse wave signal is collected on the limbs of the human body by infrared photoelectric sensing technology.
  • a plurality of infrared photoelectric data sensors are respectively fixed on the skin of the limbs of the human body, and infrared light is sent to the skin surface of the human body corresponding to the artery as the probe light through the infrared photoelectric data sensor, and the reflected light of the probe light is received, and the reflected light is transmitted through the reflected light.
  • the pulse wave signal is acquired to collect pulse signals of the arterial pulse around the human body.
  • the infrared photoelectric sensing technology may employ infrared photoelectric sensing technology known to those skilled in the art, and other prior art techniques capable of acquiring pulse wave signals may also be used in the present invention.
  • S2 Perform data preprocessing on the acquired pulse wave signal, where the data preprocessing includes performing noise reduction and filtering on the acquired pulse wave signal.
  • the obtained pulse wave signal is subjected to noise reduction processing by using a filtering method to obtain a signal with high signal to noise ratio and then digitally filtered, thereby retaining a pulse wave signal having a high signal to noise ratio in the frequency band for subsequent processing;
  • the data pre-processing can be performed using correlation filtering known to those skilled in the art, for example, using a filter.
  • other prior art techniques capable of optimizing the pulse wave signal can also be used in the present invention.
  • the data pre-processing further comprises: performing time domain data pre-processing on the pulse wave signal to obtain an associated vascular elasticity index, for example, PWV (pulse wave wave velocity), etc.
  • an associated vascular elasticity index for example, PWV (pulse wave wave velocity), etc.
  • PWV pulse wave wave velocity
  • the time domain data preprocessing may be Relevant time domain pretreatment methods known to those skilled in the art are used to obtain PWV and other related vascular elasticity indices for subsequent processing.
  • the minimum mean square error linear FIR filtering is performed on the pulse wave signal before the frequency domain processing, and the FIR adopts low-pass filtering, the pulse wave signal sampling frequency is 1 to 3 KHz, and the filter cutoff frequency is 0.5 to 1.5 KHz; In order to obtain a better pulse wave signal, that is, to clean the noise, to avoid affecting subsequent data processing.
  • the FIR adopts low-pass filtering
  • the pulse wave signal sampling frequency is 2 KHz
  • the filter cutoff frequency is 1 KHz.
  • the delayed digital pulse wave signal is used as a time sample value for linear prediction of the expected value.
  • N is the sequence length of the digital fetal pulse wave signal.
  • the equation (a) is the sampling time series of the pulse wave signal; and the equation (b) is the delayed sampling time series.
  • the linear mean square error estimator that is, using the formula (c), is a method which is operability and easy to calculate mathematically.
  • c k (n) The value of c k (n) can be calculated by the positive definite matrix theory.
  • the output form of the FIR filter is determined by the following equation (h).
  • the coefficient h k (n) represents the impulse response of the FIR filter. It is solved by a second-order rectangular equation system to obtain the best coefficient c k (n). The specific process is to solve the linear equations; after solving, f(n) is the time domain complex data.
  • the adaptive filter is different from the traditional filter in that it needs to know the spectral distribution of the signal, but only needs to know the sample value of the sampled signal.
  • This adaptive filtering is based on the sample values of the sampled signal and is based on the optimization of the statistical properties of the sample values.
  • S3 Perform real-time frequency domain processing on the pulse wave signal preprocessed by the data to obtain a continuous three-dimensional waterfall spectrogram and/or a three-dimensional contour grayscale image, and pass the three-dimensional waterfall spectrogram and/or three-dimensional, etc. High-line grayscale map to determine whether the patient has arteriosclerosis.
  • the FFT of the real-time time extraction method is performed on the pulse wave signal preprocessed by the data, and the FFT (Fast Fourier Transform) complex operation process is performed according to the formula (1):
  • x(n) is time domain complex data
  • x(n) is preferably f(n) output through the FIR filter.
  • N can be adjusted according to the processing capability of the FFT processing module, for example, the value of N can be 512. 1024, 2048, etc. In this embodiment, the value of N is 512.
  • P(n) or A(n) can be logarithmically processed according to the requirements of the three-dimensional waterfall spectrogram and the three-dimensional contour grayscale image.
  • the pulse wave signal time domain signal
  • windowing processing is commonly used by those skilled in the art. Window processing methods, such as: triangular window, Hanning window, Hamming window, Gaussian window, and the like.
  • step S3 further, according to the calculated amplitude spectrum and power spectrum Line 3D dynamic processing.
  • the three-dimensional waterfall spectrum map is also called the spectrum array diagram. It is mainly applied to the three-dimensional spectrogram in which the signal power spectrum or the amplitude spectrum of the engineering vibration field is superposed with the vibration change, and the harmonic components in the vibration signal are changed with the vibration. Case.
  • This technique is used in early screening for arteriosclerosis because it truly reflects the vibration of the artery as it pulsates. The test proves that this vibration is closely related to the degree of hardening of the arterial wall.
  • the application of the three-dimensional waterfall spectrogram overcomes the follow-up caused by the human body's mental factors, resulting in instability and uncertainty in the time domain analysis; and, through the three-dimensional display, better depicts the arterial pulsation. With complete information on changes in blood pressure (systolic and diastolic), this is information that is difficult to detect in the time domain.
  • the three-dimensional contour line gray map is a contour line dynamic spectrum distribution 16-level gray scale three-dimensional display, it The information of the arterial pulsation as it changes with blood pressure (systolic and diastolic) is shown from another angle.
  • X 1 (n) R 1 (n)+jI 1 (n)
  • X 2 (n) R 2 (n)+jI 2 (n)
  • (n 0,1,2...255 )get on with Calculate and plot the 3D contour grayscale image.
  • 6 is a three-dimensional contour grayscale image of Example 3 obtained by testing a mild arteriosclerosis patient; as can be clearly seen from FIG. 6, the energy of the three-dimensional contour grayscale image of Embodiment 3 is at HZ50. There is a strip distribution between ⁇ 60 (the greater the energy, the darker the black). Under normal circumstances (testing for normal people), the energy distribution of the three-dimensional contour grayscale image is mainly concentrated in the lower part of the three-dimensional contour grayscale image.
  • the three-dimensional contour grayscale map reflects the energy characteristics of arteriosclerosis under time-frequency distribution. Because during the formation of arteriosclerosis, the elasticity of the arterial wall gradually decreases, along with the heart In addition to the increase in high-frequency components, the vibration of the tube wall during the pulsation also increases the energy generated by the tube wall during the vibration. When the arterial wall is elastic, it has an absorption effect on the energy generated by the vibration.
  • the three-dimensional contour grayscale map it is very clear that different energy distributions occur during arteriosclerosis, and it can be concluded whether the subject has arteriosclerosis, and the pathological characteristics of arteriosclerosis can be accurately determined according to different energy distribution characteristics. For example, for the degenerative changes of the smooth muscle of the wall, the identification of atherosclerosis, etc., to determine the patient's future treatment plan.
  • S4 The pulse wave signal preprocessed by the data is processed by a cross-correlation processing method to obtain a position of a thrombus in the artery of the patient.
  • x(n), y(n) are pulse wave signals collected at different positions of the limb of the patient, for example: pulse wave signals at the left arm and the right arm, R xy (n) ) is a cross-correlation function that represents the degree of correlation between two different time series at a certain time.
  • N can be any positive integer, where 0 ⁇ n ⁇ N-1, 0 ⁇ m ⁇ N-1 . In this embodiment, the value of N is 512.
  • v PWV
  • K the correction coefficient of PWV
  • K is in the range of 1 to 10
  • d is the center line of the two infrared photoelectric data sensors at the position of the blood flow to the thrombus The distance from which the position of the thrombus can be determined.
  • the pulse wave signal is calculated by using formula (4) and the cross-correlation curve is output as shown in the figure. As shown in Figure 8, the cross-correlation curve has no distinct peak characteristics.
  • the pulse wave signal preprocessed by the data is processed by the method of cross-correlation processing, and it is possible to test whether there is a thrombus in the artery of the patient, and further obtain the position of the thrombus in the artery of the patient, and can accurately perform the thrombus
  • the positioning provides a reliable basis for clinicians to locate the location of the thrombus.
  • the present invention also provides an early screening system for peripheral arteriosclerosis, comprising an infrared photoelectric data sensor 11 for acquiring a pulse wave signal; and a data preprocessing module 12 for preprocessing the pulse wave signal.
  • An FFT processing module 13 for performing real-time frequency domain processing on the pulse wave signal and obtaining a continuous three-dimensional waterfall spectrogram and a three-dimensional contour grayscale image; preferably including pre-correlation processing
  • the processed pulse wave signal is processed, and a cross-correlation processing module 14 for acquiring the position of the thrombus in the artery of the patient; a main control unit 15 for control and data management of the entire system; and a display of the three-dimensional waterfall spectrogram, three-dimensional A display module 16 of the contour grayscale map and the location of the thrombus.
  • the infrared photoelectric data sensor 11 is electrically connected to the data preprocessing module 12, and the data preprocessing module 12 and the FFT processing module 13 are respectively.
  • the cross-correlation processing module 14 is electrically connected, and the main control unit 15 is electrically connected to the infrared photoelectric data sensor 11, the data pre-processing module 12, the FFT processing module 13, the cross-correlation processing module 14, and the display module 16, respectively.
  • the infrared photoelectric data sensor 11 is configured to acquire pulse wave signals at different positions of the patient's body. Specifically, a plurality of infrared photoelectric data sensors 11 are respectively fixed on the skin surface of the human limbs, and infrared light is sent to the skin surface of the human body corresponding to the artery as the probe light through the infrared photoelectric data sensor 11, and the reflected light of the probe light is received. The reflected light acquires a pulse wave signal to collect an arterial pulse wave signal around the human body.
  • the infrared photoelectric sensor may be an infrared photoelectric sensor known to those skilled in the art, and may be purchased or developed by itself.
  • the data preprocessing module 12 is configured to preprocess the pulse wave signal, and the infrared photoelectric data sensor 11 is electrically connected to the data preprocessing module 12 for using the pulse wave acquired by the infrared photoelectric data sensor 11.
  • the signal is pre-processed by the data pre-processing module 12.
  • the data pre-processing module 12 includes a filter for performing noise reduction and filtering processing on the acquired pulse wave signal, and a time domain data pre-processing of the acquired pulse wave signal to obtain an associated blood vessel elasticity index ( For example: PWV, pulse wave velocity) time domain data preprocessing module.
  • PWV blood vessel elasticity index
  • the obtained pulse wave signal is denoised by a filter to obtain a signal with high signal to noise ratio and then digitally filtered, thereby preserving the pulse wave signal with high signal to noise ratio in the frequency band for subsequent processing.
  • the time domain data preprocessing module performs time domain data preprocessing on the pulse wave signal to obtain an associated vascular elasticity index, such as PWV (pulse wave wave velocity), etc., and the time domain data preprocessing can be known by those skilled in the art. Correlated time domain preprocessing method to obtain PWV and other related vascular elasticity fingers Number for subsequent processing.
  • the FIR filtering is used to preserve the frequency characteristics of the pulse wave signal, and the random interference generated by the system is purified; and the optimal signal under the minimum mean square error is provided for the frequency domain data processing.
  • the FFT processing module 13 is configured to perform real-time frequency domain processing on the pulse wave signal, and obtain an amplitude spectrum and a power spectrum for generating a three-dimensional waterfall spectrogram and a three-dimensional contour grayscale image.
  • the data pre-processing module 12 is electrically connected to the FFT processing module 13 for sending the pulse wave signal processed by the data pre-processing module 12 to the FFT processing module 13, and the FFT processing module 13 and the main control unit 15
  • the electrical connection is used to send the amplitude spectrum and the power spectrum obtained by the FFT processing module 13 to the main control unit 15 to obtain a three-dimensional waterfall spectrogram, a three-dimensional contour grayscale image, and is electrically connected to the main control unit 15.
  • Display module 16 is displayed.
  • the FFT processing module 13 performs a real-time time extraction method FFT on the pulse wave signal preprocessed by the data, and performs an FFT (Fast Fourier Transform) complex operation process according to the formula (1):
  • X(n), X(n) are obtained.
  • R2(n) and I2(n) are real and imaginary parts corresponding to S2(n).
  • the main control unit 15 is electrically connected to the infrared photoelectric data sensor 11, the data preprocessing module 12, the FFT processing module 13, the cross correlation processing module 14, and the display module 16, respectively, for controlling the functions of these modules, and will pass the FFT.
  • the amplitude spectrum and the power spectrum obtained by the processing module 13 are drawn into a three-dimensional waterfall spectrum map and a three-dimensional contour gray scale image.
  • the main control unit 15 is used to implement control and data calculation of the entire system, and has functions such as a three-dimensional waterfall spectrogram and a three-dimensional contour gray scale drawing, and the device having the above functions can be used in the present invention, for example, it can be Digital signal processors, computer mainframes, and the like, which are commonly used in the field, and software programs, data operation programs, and drawing programs installed thereon can be implemented by those skilled in the art according to the prior art.
  • the three-dimensional waterfall spectrum map is also called the spectrum array diagram. It is mainly applied to the three-dimensional spectrogram in which the signal power spectrum or the amplitude spectrum of the engineering vibration field is superposed with the vibration change, and the harmonic components in the vibration signal are changed with the vibration. Case. This technique is used in early screening for arteriosclerosis because it truly reflects the vibration of the artery as it pulsates. The test proves that this vibration is closely related to the degree of hardening of the arterial wall.
  • the application of the three-dimensional waterfall spectrogram overcomes the follow-up caused by the mental factors of the human body, resulting in instability and uncertainty in the time domain analysis; it displays the information that is difficult to detect in the time domain through three-dimensional display. Better information on the arterial pulsation as it changes with blood pressure (systolic and diastolic).
  • the three-dimensional contour grayscale map is a 16-level grayscale three-dimensional display of the contour line dynamic spectrum distribution, which shows the information of the arterial pulsation as it changes with blood pressure (systolic and diastolic blood pressure) from another angle.
  • a cross-correlation processing module 14 is further included, and the patient's artery can be further located by the cross-correlation processing module 14 on the basis of testing the patient's presence of arteriosclerosis by the FFT processing module 14 and the main control unit 15. Whether there is a thrombus or a location of a thrombus.
  • the cross-correlation processing module 14 is configured to process the pulse wave signal preprocessed by the data and acquire the position of the thrombus in the artery of the patient.
  • the data pre-processing module 12 is electrically connected to the cross-correlation processing module 14 for sending the pulse wave signal processed by the data pre-processing module 12 to the cross-correlation processing module 14, the cross-correlation processing module 14 and the main
  • the control unit 15 is electrically coupled for controlling the operation of the cross-correlation processing module 14 by the main control unit 15 and displaying the position of the thrombus in the patient's artery through the display module 16 electrically coupled to the main control unit 15.
  • x(n), y(n) are pulse wave signals collected at different positions of the patient's body, for example, pulse wave signals at the left arm and the right arm
  • R xy (n) ) is a cross-correlation function that represents the degree of correlation between two different time series at a certain time
  • N can be any integer.
  • the value of N is 512, where 0 ⁇ n ⁇ N-1, and 0 ⁇ m ⁇ N-1.
  • v PWV
  • K is the correction coefficient of PWV
  • K is in the range of 1 to 10
  • d is the distance from the center line of the two infrared photoelectric data sensors to the direction of blood flow to the thrombus.
  • the display module 14 can be a display screen, such as a liquid crystal touch screen or the like, for displaying the three-dimensional waterfall spectrogram, the three-dimensional contour grayscale image, and the position of the thrombus, so that As seen by the clinician, an intuitive display of the condition of the arteriosclerosis and the location of the thrombus is provided.
  • the early screening system and method for peripheral arteriosclerosis have at least the following beneficial effects: the FFT complex module performs FFT complex operation on the pulse wave signal to obtain a corresponding amplitude spectrum and power spectrum, and then The three-dimensional waterfall spectrogram and/or three-dimensional contour grayscale map obtained by the main control unit can provide the clinician with the possible pathological mechanism, degree and development trend of early arteriosclerosis, and can clearly reflect the blood with the change of blood pressure. Flow velocity in the arteries, reflux, and response to thrombosis provide an effective basis for physicians' clinical risk assessment and future treatment options.
  • Cross-correlation processing can accurately determine the position and size of the embolus in the artery, especially in the early stage of emboli formation. When it is difficult to find through imaging medical equipment, it can provide the doctor with the basis for early effective treatment.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Physiology (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Cardiology (AREA)
  • Physics & Mathematics (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 système et un procédé de dépistage précoce pour l'artériosclérose périphérique. Le procédé comprend les étapes suivantes : S1 : acquérir des signaux d'onde pulsatile à partir de différents emplacements sur le corps d'un patient ; S2 : effectuer un prétraitement de données sur un signal d'onde pulsatile ; S3 : effectuer un traitement de domaine de fréquence en temps réel sur le signal d'onde pulsatile qui a subi le prétraitement de données et obtenir un spectrogramme en cascade tridimensionnel continu et/ou une carte tridimensionnelle en niveaux de gris de contour et déterminer si l'artériosclérose est présente chez le patient au moyen du spectrogramme en cascade tridimensionnel et/ou de la carte tridimensionnelle en niveaux de gris de contour. Le signal d'onde pulsatile qui a subi le prétraitement de données est traité au moyen d'un procédé de traitement de corrélation croisée pour obtenir l'emplacement d'un thrombus dans une artère de membre du patient. Le procédé et le système de dépistage précoce pour l'artériosclérose périphérique peuvent être utilisés par les cliniciens pour évaluer des lésions artérielles dans le corps humain et peuvent être utilisés en particulier par les cliniciens pour obtenir une base fiable pour évaluer si des lésions précoces de l'artériosclérose sont présentes dans le corps humain et si un thrombus est présent dans une artère.
PCT/CN2017/074250 2017-02-21 2017-02-21 Système et procédé de dépistage précoce pour artériosclérose périphérique Ceased WO2018152675A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/074250 WO2018152675A1 (fr) 2017-02-21 2017-02-21 Système et procédé de dépistage précoce pour artériosclérose périphérique

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/074250 WO2018152675A1 (fr) 2017-02-21 2017-02-21 Système et procédé de dépistage précoce pour artériosclérose périphérique

Publications (1)

Publication Number Publication Date
WO2018152675A1 true WO2018152675A1 (fr) 2018-08-30

Family

ID=63253392

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/074250 Ceased WO2018152675A1 (fr) 2017-02-21 2017-02-21 Système et procédé de dépistage précoce pour artériosclérose périphérique

Country Status (1)

Country Link
WO (1) WO2018152675A1 (fr)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100292590A1 (en) * 2007-11-20 2010-11-18 The Doshisha Arteriosclerosis diagnostic device
US20110208073A1 (en) * 2008-09-01 2011-08-25 The Doshisha Arteriosclerosis evaluating apparatus
CN102488499A (zh) * 2011-10-28 2012-06-13 中国人民解放军第四军医大学 一种基于脉搏波的心血管弹性测试及动脉硬化早期预警系统
CN205041379U (zh) * 2015-10-14 2016-02-24 天津普仁万合信息技术有限公司 一种测量踝-桡动脉脉搏波速度的全身动脉硬化监测设备
CN105725983A (zh) * 2016-01-07 2016-07-06 深圳市和来科技有限公司 一种周围动脉硬化的早期筛查方法及系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100292590A1 (en) * 2007-11-20 2010-11-18 The Doshisha Arteriosclerosis diagnostic device
US20110208073A1 (en) * 2008-09-01 2011-08-25 The Doshisha Arteriosclerosis evaluating apparatus
CN102488499A (zh) * 2011-10-28 2012-06-13 中国人民解放军第四军医大学 一种基于脉搏波的心血管弹性测试及动脉硬化早期预警系统
CN205041379U (zh) * 2015-10-14 2016-02-24 天津普仁万合信息技术有限公司 一种测量踝-桡动脉脉搏波速度的全身动脉硬化监测设备
CN105725983A (zh) * 2016-01-07 2016-07-06 深圳市和来科技有限公司 一种周围动脉硬化的早期筛查方法及系统

Similar Documents

Publication Publication Date Title
CN106037694B (zh) 一种基于脉搏波的连续血压测量装置
Fan et al. Robust blood pressure estimation using an RGB camera
Yan et al. The moment segmentation analysis of heart sound pattern
US20140316292A1 (en) Circulation Monitoring System
JP2004329550A (ja) 超音波診断装置
Sahoo et al. Wavelet based pulse rate and Blood pressure estimation system from ECG and PPG signals
CN111012319A (zh) 皮肤血流和血管的监测成像方法、系统及存储介质
Ruffo et al. An algorithm for FHR estimation from foetal phonocardiographic signals
Kumar et al. Oscillometric waveform evaluation for blood pressure devices
CN107115103A (zh) 一种基于阵列传感器设计的脉象宽度检测及3d脉图构建方法
CN115251866A (zh) 一种采用毫米波雷达的连续血压检测方法、检测系统及可穿戴装置
CN106264505A (zh) 一种基于支持向量机的心率谱峰选择方法
CN105725983B (zh) 一种周围动脉硬化的早期筛查方法及系统
Al–Fahoum et al. A multiple signal classification approach for photoplethysmography signals in healthy and athletic subjects
CN105105734A (zh) 一种基于心音信号的无创连续血压测量方法、装置及系统
EP3236858B1 (fr) Système et procédé de mesure de paramètres artériels
Zhang et al. Using rear smartphone cameras as sensors for measuring heart rate variability
CN118628501A (zh) 基于欧拉视频放大的压疮检测方法、系统、设备及介质
Paliakaitė et al. Blood pressure estimation based on photoplethysmography: finger versus wrist
Shalom et al. Systolic blood pressure measurement by detecting the photoplethysmographic pulses and electronic Korotkoff-sounds during cuff deflation
Torbati et al. Image-based gating of intravascular ultrasound sequences using the phase information of dual-tree complex wavelet transform coefficients
CN113729653A (zh) 一种人体脉搏波信号采集方法
Joseph et al. A virtual instrument for automated measurement of arterial compliance
Sakalauskas et al. Investigation of radiofrequency ultrasound‐based fibrotic tissue strain imaging method employing endogenous motion
Gupta et al. Denoising and analysis of PPG acquired from different body sites using Savitzky Golay filter

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17897990

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205 DATED 19.12.2019)

122 Ep: pct application non-entry in european phase

Ref document number: 17897990

Country of ref document: EP

Kind code of ref document: A1