CN112998743A - Internal fistula stenosis degree evaluation method and evaluation system and wearable medical equipment - Google Patents
Internal fistula stenosis degree evaluation method and evaluation system and wearable medical equipment Download PDFInfo
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- CN112998743A CN112998743A CN202110192888.3A CN202110192888A CN112998743A CN 112998743 A CN112998743 A CN 112998743A CN 202110192888 A CN202110192888 A CN 202110192888A CN 112998743 A CN112998743 A CN 112998743A
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- 206010016717 Fistula Diseases 0.000 title claims abstract description 57
- 230000003890 fistula Effects 0.000 title claims abstract description 57
- 208000031481 Pathologic Constriction Diseases 0.000 title claims abstract description 33
- 230000036262 stenosis Effects 0.000 title claims abstract description 31
- 208000037804 stenosis Diseases 0.000 title claims abstract description 31
- 238000011156 evaluation Methods 0.000 title claims abstract description 27
- 230000003595 spectral effect Effects 0.000 claims abstract description 28
- 201000001881 impotence Diseases 0.000 claims abstract description 21
- 238000000034 method Methods 0.000 claims abstract description 20
- 230000004907 flux Effects 0.000 claims abstract description 14
- 230000002792 vascular Effects 0.000 claims abstract description 6
- 206010003694 Atrophy Diseases 0.000 claims abstract description 4
- 230000037444 atrophy Effects 0.000 claims abstract description 4
- 238000001631 haemodialysis Methods 0.000 claims description 12
- 230000000322 hemodialysis Effects 0.000 claims description 12
- 238000013135 deep learning Methods 0.000 claims description 7
- 238000013528 artificial neural network Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 5
- 230000005236 sound signal Effects 0.000 claims description 5
- 210000004204 blood vessel Anatomy 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 238000000502 dialysis Methods 0.000 abstract description 6
- 238000010586 diagram Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000002604 ultrasonography Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 206010035148 Plague Diseases 0.000 description 1
- 241000607479 Yersinia pestis Species 0.000 description 1
- 238000002583 angiography Methods 0.000 description 1
- 208000020832 chronic kidney disease Diseases 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010790 dilution Methods 0.000 description 1
- 239000012895 dilution Substances 0.000 description 1
- 208000028208 end stage renal disease Diseases 0.000 description 1
- 201000000523 end stage renal failure Diseases 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
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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
- A61B7/04—Electric stethoscopes
Abstract
The invention relates to an internal fistula stenosis degree evaluation method, an internal fistula stenosis degree evaluation system and wearable medical equipment, which comprise the following steps: collecting the vascular internal atrophy noise signals; extracting spectral centroid features and auditory spectral flux features from the intrinsic wilting noise signal; and classifying the intrinsic impotence noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics, and obtaining the DOS index of the intrinsic impotence noise signals. Its simple and easy degree is high, and is wearable, can alleviate medical personnel's burden at dialysis in-process real-time supervision.
Description
Technical Field
The invention relates to the technical field of internal fistula stenosis degree detection, in particular to an internal fistula stenosis degree evaluation method, an internal fistula stenosis degree evaluation system and wearable medical equipment.
Background
Maintenance Hemodialysis (MHD) is an effective alternative treatment for patients with end-stage renal failure, and establishing and maintaining a good vascular access is critical to ensure successful dialysis over a long period of time. Internal fistula blockage remains a primary problem that plagues physicians and patients during hemodialysis. Without a sufficiently effective vascular access, the efficiency of hemodialysis is reduced, thereby increasing the mortality rate of hemodialysis patients. Monitoring of fistula blockage is generally performed by monitoring the degree of stenosis of the vessel, with higher degrees indicating more severe blockage.
The commonly used internal fistula blockage detection methods at present comprise: ultrasound dilution, digital subtraction angiography, doppler ultrasound examination. However, these methods have the following disadvantages: the equipment is expensive, bulky and requires professional personnel to operate. In addition, partial researchers use single-side or double-side PPG signals to judge the stenosis degree, the accuracy rate is greatly improved, the volume of the equipment is reduced to a certain extent, but the acquisition circuit of the equipment is complex, and the simplicity in operation is not achieved.
Therefore, it is very necessary to provide a wearable internal fistula stenosis degree determination device based on internal fistula noise.
Disclosure of Invention
Therefore, the invention aims to solve the technical problems of inconvenience in detection of internal fistula blockage and complex operation in the prior art.
In order to solve the technical problem, the invention provides an internal fistula stenosis degree evaluation method, which comprises the following steps:
s1, collecting the vascular internal withering noise signals;
s2, extracting spectral centroid characteristics and auditory spectral flux characteristics from the intrinsic impotence noise signals;
and S3, classifying the intrinsic impotence noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics, and obtaining the DOS index of the intrinsic impotence noise signals.
In another embodiment of the present invention, between S1 and S2, further comprising: and filtering the intrinsic impotence noise signal to obtain a filtered sound signal.
In another embodiment of the present invention, the collected intrinsic impotence noise signals are classified by SVM in the S3.
In another embodiment of the present invention, in S3, the collected intrinsic wilting noise signals are classified by means of deep learning of the neural network.
In another embodiment of the present invention, the step S3 further includes: and S4, evaluating the internal fistula stenosis degree of the classified internal withered noise signals.
In another embodiment of the present invention, the S4 specifically includes: when the DOS index of the internal wilting noise signal is 0-30%, the narrow degree of the output internal fistula is low, when the DOS index of the internal wilting noise signal is 30-60%, the narrow degree of the output internal fistula is medium, and when the DOS index of the internal wilting noise signal is 60-100%, the narrow degree of the output internal fistula is high.
In another embodiment of the present invention, in S1, the signal of the intrinsic safety noise is collected by a microphone.
The invention discloses a system for evaluating the internal fistula stenosis degree of a hemodialysis patient, which comprises:
the data acquisition module is used for acquiring an internal withering noise signal of a blood vessel;
a feature extraction module for extracting spectral centroid features and auditory spectral flux features from the intrinsic wilting noise signal;
and the classification module classifies the intrinsic impotence noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics and obtains the DOS index of the intrinsic impotence noise signals.
In another embodiment of the present invention, the method further comprises an evaluation module, wherein the evaluation module performs internal fistula stenosis degree evaluation on the classified internal withered noise signals: when the DOS index of the internal withered noise signal is 0-30%, the narrow degree of the internal fistula output by the evaluation module is low, when the DOS index of the internal withered noise signal is 30-60%, the narrow degree of the internal fistula output by the evaluation module is medium, and when the DOS index of the internal withered noise signal is 60-100%, the narrow degree of the internal fistula output by the evaluation module is high.
In another embodiment of the present invention, the classification module classifies the collected intrinsic wilting noise signals by means of deep learning of SVM or neural network.
The invention discloses wearable medical equipment which comprises the system for evaluating the internal fistula stenosis degree of a hemodialysis patient.
Compared with the prior art, the technical scheme of the invention has the following advantages:
1. the invention provides a method for evaluating the stenosis degree of a blood vessel aiming at an internal fistula part, which is used for judging the stenosis degree of the blood vessel by acquiring a sound signal of the internal fistula part.
2. The system provided by the invention is simple in composition, convenient to realize, free of influence on a hemodialysis process, simple to operate and wearable, and can be used for monitoring medical staff in real time in the dialysis process only by connecting the medical staff with a terminal, so that the burden of the medical staff can be reduced.
3. In the prior art, the hemodialysis time is long, the conventional medical equipment mostly adopts Doppler ultrasound to randomly check in the dialysis process, the operation is complex, and medical staff are required to be around all the time, so that the burden of the medical staff is increased.
4. The invention is oriented to the actual medical care scene, is simple and effective to realize, and simultaneously effectively keeps balance between reliability and complexity.
Drawings
FIG. 1 is a schematic flow chart of the method for evaluating the stenosis degree of an internal fistula according to the present invention;
fig. 2 is a schematic flow chart of classification by SVM or deep learning.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
Referring to fig. 1-2, the invention discloses a method for evaluating the stenosis degree of an internal fistula, which comprises the following steps:
step one, collecting an intrinsic atrophy noise signal through a microphone.
And step two, extracting spectral centroid characteristics and auditory spectral flux characteristics from the intrinsic impotence noise signals.
And step three, classifying the intrinsic impotence noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics, and obtaining the DOS index of the intrinsic impotence noise signals. In the third step, the collected intrinsic wilting noise signals can be classified through an SVM, and can also be classified through a neural network deep learning mode.
The method also comprises the following steps between the first step and the second step: and filtering the intrinsic impotence noise signal to obtain a filtered sound signal. The invention can also carry out normalization processing on the filtered sound signal, thereby being convenient for feature extraction in the step two.
Step four, carrying out internal fistula stenosis degree evaluation on the classified internal atrophy noise signals, wherein the evaluation comprises the following steps: when the DOS index of the internal wilting noise signal is 0-30%, the narrow degree of the output internal fistula is low, when the DOS index of the internal wilting noise signal is 30-60%, the narrow degree of the output internal fistula is medium, and when the DOS index of the internal wilting noise signal is 60-100%, the narrow degree of the output internal fistula is high.
The invention also discloses a system for evaluating the internal fistula stenosis degree of the hemodialysis patient, which comprises a data acquisition module, a feature extraction module and a classification module.
The data acquisition module is used for acquiring the vascular internal withering noise signals.
The feature extraction module is used for extracting spectral centroid features and auditory spectral flux features from the intrinsic impotence noise signals.
The classification module classifies the intrinsic wilting noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics and obtains the DOS index of the intrinsic wilting noise signals. The classification module classifies the collected intrinsic wilting noise signals in a mode of SVM or neural network deep learning.
The invention also comprises an evaluation module, and the evaluation module carries out internal fistula stenosis degree evaluation on the classified internal withered noise signals: when the DOS index of the internal withered noise signal is 0-30%, the internal fistula narrow degree output by the evaluation module is low, when the DOS index of the internal withered noise signal is 30-60%, the internal fistula narrow degree output by the evaluation module is medium, and when the DOS index of the internal withered noise signal is 60-100%, the internal fistula narrow degree output by the evaluation module is high.
The invention discloses wearable medical equipment which comprises the system for evaluating the internal fistula stenosis degree of a hemodialysis patient. It has small volume and convenient operation. According to the invention, a proper MEMS microphone can be selected for collecting the internal fistula noise, a resonance cavity can be designed, and the amplitude of the required noise signal is increased. A buzzer alarm device can also be added to give an alarm when the level rises. During the dialysis process, the device is placed at the internal fistula, so that real-time monitoring can be achieved. The time of each dialysis is about 4 hours, and the use time can be met due to the low power consumption design. And when the terminal detects that the DOS grade is increased, the medical staff carries out corresponding measures to help the patient.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A method for evaluating the stenosis degree of an internal fistula is characterized by comprising the following steps:
s1, collecting the vascular internal withering noise signals;
s2, extracting spectral centroid characteristics and auditory spectral flux characteristics from the intrinsic impotence noise signals;
and S3, classifying the intrinsic impotence noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics, and obtaining the DOS index of the intrinsic impotence noise signals.
2. The method for assessing the stenosis degree of an internal fistula according to claim 1, further comprising, between S1 and S2:
and filtering the intrinsic impotence noise signal to obtain a filtered sound signal.
3. The method for assessing stricture of internal fistula according to claim 1, wherein the collected internal fistula noise signals are classified by SVM in S3.
4. The method for assessing the stenosis degree of an internal fistula according to claim 1, wherein the classification of the collected internal impotence noise signals is performed by deep learning through a neural network in S3.
5. The method for assessing the stenosis degree of an internal fistula according to claim 1, further comprising, after the step S3:
s4, evaluating the internal fistula stenosis degree of the classified internal withered noise signals, and specifically comprises the following steps:
when the DOS index of the internal wilting noise signal is 0-30%, the narrow degree of the output internal fistula is low, when the DOS index of the internal wilting noise signal is 30-60%, the narrow degree of the output internal fistula is medium, and when the DOS index of the internal wilting noise signal is 60-100%, the narrow degree of the output internal fistula is high.
6. The method for assessing stricture of internal fistula according to claim 1, wherein in S1 the signal of internal fistula noise is collected by a microphone.
7. A system for assessing a stenosis level of an internal fistula of a hemodialysis patient, comprising:
the data acquisition module is used for acquiring an internal withering noise signal of a blood vessel;
a feature extraction module for extracting spectral centroid features and auditory spectral flux features from the intrinsic wilting noise signal;
and the classification module classifies the intrinsic impotence noise signals according to the spectral centroid characteristics and the auditory spectral flux characteristics and obtains the DOS index of the intrinsic impotence noise signals.
8. The system of claim 7, further comprising an evaluation module for evaluating the internal fistula stenosis degree of the classified internal syphon signals: when the DOS index of the internal withered noise signal is 0-30%, the narrow degree of the internal fistula output by the evaluation module is low, when the DOS index of the internal withered noise signal is 30-60%, the narrow degree of the internal fistula output by the evaluation module is medium, and when the DOS index of the internal withered noise signal is 60-100%, the narrow degree of the internal fistula output by the evaluation module is high.
9. The system of claim 7, wherein the classification module classifies the collected intrinsic atrophy noise signals by means of deep learning of an SVM or neural network.
10. A wearable medical device comprising the system for evaluating a degree of stenosis in a hemodialysis patient according to any one of claims 7 to 9.
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| CN202110192888.3A CN112998743A (en) | 2021-02-20 | 2021-02-20 | Internal fistula stenosis degree evaluation method and evaluation system and wearable medical equipment |
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110054352A1 (en) * | 2009-08-25 | 2011-03-03 | Po-Jen Ko | Portable Dialysis Access Monitor Device |
| TW201400087A (en) * | 2012-06-18 | 2014-01-01 | Nat Cheng Kung University Hospital | Estimating method for vascular access function of dialysis fistula |
| TW201613526A (en) * | 2014-10-01 | 2016-04-16 | Nat Cheng Kung University Hospital | Apparatus, computer program product and computer readable medium using audio signal for detection and determination of narrowing condition of fluid pipe |
| TW201740369A (en) * | 2016-05-12 | 2017-11-16 | National Cheng Kung Univ Hospital | Computer program product and computer readable medium for determination of narrowing condition of fistula by detection of audio signals |
| US20180070841A1 (en) * | 2016-09-12 | 2018-03-15 | GrafWorx, Inc. | Wearable device with multimodal diagnostics |
| US20180326142A1 (en) * | 2017-05-12 | 2018-11-15 | Nexcom International Co., Ltd. | Portable device for monitoring vascular access status |
| US20190320912A1 (en) * | 2018-04-21 | 2019-10-24 | Above Care Inc. | Arteriovenous fistula stenosis detection system and method thereof and sensing device |
| CN110720899A (en) * | 2019-10-14 | 2020-01-24 | 浙江大学 | AVA (Audio video coding) stenosis positioning and stenosis degree multi-stage classification system based on MPSF (Multi-Point Multi-function template) extraction |
| CN111134652A (en) * | 2020-03-11 | 2020-05-12 | 四川大学华西医院 | Multifunctional monitoring wrist guard for internal arteriovenous fistula of hemodialysis patient |
| CN111449637A (en) * | 2020-04-07 | 2020-07-28 | 上海市第十人民医院 | Evaluation system and method for arteriovenous internal fistula blood vessel |
| RU2738071C1 (en) * | 2020-05-14 | 2020-12-07 | Общество с ограниченной ответственностью "МЕДБРАЗЕ" | Method for assessment of arteriovenous fistula condition |
-
2021
- 2021-02-20 CN CN202110192888.3A patent/CN112998743A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110054352A1 (en) * | 2009-08-25 | 2011-03-03 | Po-Jen Ko | Portable Dialysis Access Monitor Device |
| TW201400087A (en) * | 2012-06-18 | 2014-01-01 | Nat Cheng Kung University Hospital | Estimating method for vascular access function of dialysis fistula |
| TW201613526A (en) * | 2014-10-01 | 2016-04-16 | Nat Cheng Kung University Hospital | Apparatus, computer program product and computer readable medium using audio signal for detection and determination of narrowing condition of fluid pipe |
| TW201740369A (en) * | 2016-05-12 | 2017-11-16 | National Cheng Kung Univ Hospital | Computer program product and computer readable medium for determination of narrowing condition of fistula by detection of audio signals |
| US20180070841A1 (en) * | 2016-09-12 | 2018-03-15 | GrafWorx, Inc. | Wearable device with multimodal diagnostics |
| US20180326142A1 (en) * | 2017-05-12 | 2018-11-15 | Nexcom International Co., Ltd. | Portable device for monitoring vascular access status |
| US20190320912A1 (en) * | 2018-04-21 | 2019-10-24 | Above Care Inc. | Arteriovenous fistula stenosis detection system and method thereof and sensing device |
| CN110720899A (en) * | 2019-10-14 | 2020-01-24 | 浙江大学 | AVA (Audio video coding) stenosis positioning and stenosis degree multi-stage classification system based on MPSF (Multi-Point Multi-function template) extraction |
| CN111134652A (en) * | 2020-03-11 | 2020-05-12 | 四川大学华西医院 | Multifunctional monitoring wrist guard for internal arteriovenous fistula of hemodialysis patient |
| CN111449637A (en) * | 2020-04-07 | 2020-07-28 | 上海市第十人民医院 | Evaluation system and method for arteriovenous internal fistula blood vessel |
| RU2738071C1 (en) * | 2020-05-14 | 2020-12-07 | Общество с ограниченной ответственностью "МЕДБРАЗЕ" | Method for assessment of arteriovenous fistula condition |
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Application publication date: 20210622 |