WO2020135226A1 - 一种基于图像识别的引流监控系统及方法 - Google Patents

一种基于图像识别的引流监控系统及方法 Download PDF

Info

Publication number
WO2020135226A1
WO2020135226A1 PCT/CN2019/126662 CN2019126662W WO2020135226A1 WO 2020135226 A1 WO2020135226 A1 WO 2020135226A1 CN 2019126662 W CN2019126662 W CN 2019126662W WO 2020135226 A1 WO2020135226 A1 WO 2020135226A1
Authority
WO
WIPO (PCT)
Prior art keywords
drainage
data
monitoring
module
color
Prior art date
Application number
PCT/CN2019/126662
Other languages
English (en)
French (fr)
Chinese (zh)
Inventor
刘铁楠
吴春涛
艾梦池
Original Assignee
刘铁楠
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 刘铁楠 filed Critical 刘铁楠
Priority to JP2021538480A priority Critical patent/JP7211668B2/ja
Publication of WO2020135226A1 publication Critical patent/WO2020135226A1/zh
Priority to US17/304,841 priority patent/US20210316060A1/en

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
    • A61M1/71—Suction drainage systems
    • A61M1/73—Suction drainage systems comprising sensors or indicators for physical values
    • A61M1/734—Visual indicating means for flow
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content

Definitions

  • the present invention generally relates to the field of medical devices, and more particularly, to a drainage monitoring system and method based on image recognition.
  • the body fluid drainage device is one of the most common medical devices in the medical field and is widely used in major clinical departments.
  • the most commonly used drainage devices for existing medical devices are mainly drainage bottles or drainage bags.
  • drainage devices In the clinical application of diagnosis and treatment, drainage devices rely on gravity or negative pressure to drain, and are mostly placed at the bottom of the bed.
  • the indicators that characterize the changes in the drainage process include the drainage volume, color, and turbidity of the drainage fluid.
  • the amount of drainage volume reflects the accumulation and symptoms of water and blood pus in the body cavity of the patient.
  • the color and turbidity of the drainage fluid must be To a certain extent, it reflects the status of the drainage site tissue. Because the current medical drainage devices generally still rely on manual viewing for monitoring, automatic monitoring of the liquid in the drainage device cannot be achieved, and patients generally require long drainage treatment times, sometimes up to days or even weeks, so it will consume a lot of manpower It is especially inconvenient to observe and monitor the drainage volume, color and turbidity of the drainage fluid at night or when there is a shortage of personnel.
  • a drainage monitoring device that can simultaneously monitor drainage data including drainage flow rate, flow rate, drainage fluid color, etc., to minimize medical risks, and find, alarm, and record And treatment, thereby reducing the workload of medical staff, reducing the medical risks that may be caused by artificial monitoring of loopholes.
  • the present invention provides a medical drainage liquid monitoring system and method, which can realize the unified monitoring of important information data in the drainage process such as the drainage flow rate, flow rate, color, turbidity, etc. Collect and record the relevant data, and report to the police when an abnormality occurs.
  • a drainage monitoring system based on image recognition, comprising: at least one video acquisition device for acquiring video stream data of drainage fluid; an image processing module, which is connected to the at least one video acquisition device Connected for receiving the video stream data and processing the video stream data to obtain the drainage data of the drainage liquid; and a monitoring module connected to the image processing module for receiving and monitoring Describe the streaming data.
  • the video capture device includes a first video capture device aligned with the drainage container, and optionally, a second video capture device aligned with the drainage tube.
  • the drainage data includes the color, turbidity and drainage volume of the drainage fluid.
  • the monitoring module is further configured to calculate the flow rate of the drainage liquid flowing through the drainage tube based on the drainage flow data of the drainage liquid.
  • the monitoring module is further configured to determine a change in the properties of the drainage fluid based on the change in color and turbidity.
  • the image processing module includes: an image sampling module for extracting a key frame image from the video stream data; a color extraction module for performing image recognition on the key frame image and extracting the Color information of key frame image; turbidity detection module, used to process the key frame image to determine the turbidity information of the drainage fluid; drainage flow reading module, used to perform image recognition on the key frame image And enhanced processing, read the scale value information in the key frame image.
  • the image sampling module is configured to adjust the sampling rate based on changes in the color information.
  • the turbidity detection module includes: a brightness extraction module to extract the brightness value of the image from the key frame image; a turbidity determination module to characterize the turbidity of the drainage fluid based on the brightness value Degrees information.
  • the image processing module includes: an image sampling module for extracting key frame images from the video stream data; and an image feature extraction module for extracting color features and turbidity from the key frame images Degree features, wherein the image feature extraction module is a model obtained based on neural network training.
  • the image sampling module is configured to adjust the sampling rate based on changes in the color characteristics.
  • the monitoring module includes: a first data receiving unit for receiving color, turbidity and drainage flow data of the drainage liquid; a data processing unit for calculating flow through based on the drainage flow data The flow rate of the drainage liquid of the drainage tube, and determining the property change of the drainage liquid based on the change of the color data and the turbidity data; the first display unit is used to change the color, turbidity, drainage flow rate, flow rate and properties At least one of them is displayed in real time; and a first alarm unit is used to issue an alarm signal when at least one of the drainage volume, color, turbidity, drainage volume, flow rate, and property changes exceeds a predetermined threshold.
  • the drainage monitoring system further includes a central monitoring module for monitoring the monitoring data of a plurality of the monitoring modules in real time.
  • the central monitoring module includes: a second data receiving unit configured to receive monitoring data sent by a plurality of the monitoring modules in a wired or wireless manner, the monitoring data including the color, turbidity, At least one of the drainage volume, the flow rate, and the change in the properties; the storage unit for storing the monitoring data; and the second display unit for simultaneously displaying the monitoring data of a plurality of the monitoring modules.
  • the central monitoring module further includes: a second alarm unit, configured to issue an alarm signal when the monitoring data of any one of the plurality of monitoring modules exceeds a predetermined threshold.
  • the central monitoring module further includes: a threshold setting unit for setting a predetermined threshold of the monitoring data of each monitoring module.
  • Another aspect of the present invention provides a drainage monitoring method based on image recognition, including: acquiring video stream data of drainage fluid; processing the video stream data to obtain drainage data of the drainage fluid; and receiving and Monitoring the drainage data, wherein the drainage data includes the color, turbidity and drainage volume of the drainage liquid.
  • the drainage monitoring system can accurately monitor the color and change of the drainage liquid, and realizes a variety of drainage data such as the flow rate, drainage volume, and turbidity of the drainage liquid based on image processing Monitoring, to achieve the processing, recording and alarming of the above drainage data, reducing the workload of medical staff and greatly reducing medical risks; the monitoring system does not require the liquid nature of the drainage fluid, and all body fluids are It has better response and higher accuracy; and the monitoring system has a simple structure, is easy to install and deploy, and can be applied to various clinical occasions.
  • FIG. 1 is a block schematic diagram of a drainage monitoring system according to an embodiment of the invention.
  • FIG. 2 is a block diagram of an image processing module according to an embodiment of the invention.
  • FIG. 3 is a block diagram of an image processing module according to another embodiment of the present invention.
  • FIG. 4 is a structural block diagram of a monitoring module according to an embodiment of the present invention.
  • FIG. 5 is a structural block diagram of a central monitoring module according to an embodiment of the present invention.
  • FIG. 6 is a flowchart of a method for monitoring drainage according to an embodiment of the present invention.
  • the monitoring system of the present invention is suitable for various medical procedures involving drainage.
  • body fluids such as abdominal fluid and pleural fluid generally flow out of the drainage chamber through the medical drainage catheter, and are finally contained by the drainage container.
  • the drainage container can It is all the drainage containers in the medical process, such as drainage bottles, drainage bags, negative pressure drainage devices or intraoperative suction devices, which are generally placed under the chamber to form a hydraulic pressure difference to achieve the drainage of body fluids.
  • the existing drainage devices generally manually monitor the drainage flow, color and other data of the drainage liquid, which is easy to cause risks due to the lack of monitoring. Therefore, the present invention proposes to be able to detect and perform the drainage data during the drainage process Monitoring device.
  • the term "drainage device” is used in the present invention, and its meaning includes both a drainage container for containing drainage fluid, a drainage tube connected to the drainage site of the patient and the drainage container, and a negative pressure device connected to the drainage container.
  • the drainage tube and the drainage container are preferably made of sampling transparent materials, such as glass or transparent silica gel.
  • FIG. 1 is a schematic diagram of a drainage monitoring system according to a first embodiment of the present invention.
  • the drainage monitoring device includes: a video collection device 10, which can shoot the drainage liquid to obtain the video stream data of the drainage liquid; and an image processing module 20, which is connected to the video collection device 10 and can receive The video stream data, and process the video stream data to obtain the drainage data of the drainage liquid; and a monitoring module 30, which is connected to the image processing module 20, is used to receive and monitor the drainage data.
  • the video capture device 10 may use optical sensor devices such as a camera, and the camera continuously collects image data sequences to form video stream data. Compared with pure image data, the present invention uses video data to achieve dynamic real-time monitoring of the drainage process.
  • the video capture device 10 is aimed at the drainage device 40 to shoot the drainage process.
  • At least one video acquisition device is provided.
  • only one first camera aligned with the drainage container may be provided, so as to implement monitoring of the drainage liquid in the drainage container.
  • the side of the drainage container is provided with Volume scale.
  • volume scale lines can be printed on each side of the drainage container.
  • the volume scale lines are printed in black and are wear-resistant and corrosion-resistant.
  • the video data collected from this contains information such as flow rate and color.
  • a second camera aligned with the drainage tube may be additionally provided for acquiring color information of the drainage liquid flowing through the drainage tube. If there is a dangerous situation such as blood vessel rupture during the postoperative drainage process, the color change of the drainage liquid in the drainage container is not as obvious as the color change of the drainage liquid in the drainage tube, so the collected data through the second camera can monitor such danger more sensitively.
  • the video acquisition device 10 is detachably mounted on the drainage container or negative pressure device, and can also be installed on the IV rack together with the drainage container, which ensures that the drainage container is located below the drainage chamber of the patient, and the video acquisition device and the drainage container are positioned opposite Fixed, to ensure the consistency of the format of the video acquisition data.
  • a light source can be set to ensure the clarity of the shooting at night during the drainage process, and the light source may not be used according to the specific situation.
  • the image processing module 20 receives the video data captured by the camera, and obtains the drainage data such as the color, turbidity, and drainage volume of the drainage liquid through the image processing method.
  • the image processing module includes an image sampling module 21, a color extraction module 22, a turbidity detection module 23 and a drainage flow reading module 24.
  • the video stream data can be regarded as a sequence of images discharged in a certain order.
  • the image sampling module 21 is used to extract key frame images from the video stream data collected by the camera. This article uses "key frame images" to denote images from which drainage data can be obtained.
  • the image acquisition module 21 can extract the key frame image in the video stream data at a fixed sampling frequency, for example, extract one frame image per second, or adjust the sampling rate of the key frame image according to the change of the drainage data as described below, so as to achieve The dynamic and accurate monitoring of a certain period of time during the drainage process.
  • the color extraction module 22 is used to perform image recognition on the key frame image and extract color information of the key frame image.
  • the key frame images of the first camera or the second camera may be used for image recognition to extract color information
  • the key frame images of the first camera and the second camera may be used for image recognition to extract color information. It can be compared and analyzed to obtain the patient's drainage situation. Since the color information of the image of the second camera aligned with the drainage tube can better characterize the real-time color of the drainage liquid, the color extraction module 22 preferably extracts the color in the key frame image of the second camera information.
  • the color extraction module 22 may collect the RGB values of multiple sampling points of the key frame image according to a preset sampling rule, and then estimate the color information of the key frame image according to the color values of the multiple sampling points.
  • the color of the drainage area of the same key frame image is basically the same, so the color value of a few pixels in this area can represent most of the pixels in the image, and the collection bottle or drainage tube is used as the sampling area. Select multiple sampling points in the sampling area and collect their color values, so that the color information of the image can be extracted.
  • the acquired color information can be corrected, for example, the camera takes an image of the standard color card and extracts its color, and compares it with the standard color to obtain the deviation between the two as a correction factor, and uses The correction factor corrects the color of the drainage fluid extracted from the key frame image.
  • the image sampling module 21 is configured to adjust the sampling rate based on the change of the color information.
  • the change of the color information can be based on the RGB values of the three channels to calculate the change value of the color of the drainage liquid over time, which can be either the amount of change in the overall color of the drainage liquid or the amount of change in the color value of a single channel.
  • the sampling rate of the key frame image extracted from the video stream data should be increased, such as by the second One frame image is adjusted to extract 5 frames per second, which makes the monitoring of the drainage process more accurate.
  • the turbidity detection module 23 is used to process the key frame image to determine the turbidity information of the drainage fluid.
  • the brightness information of the image is used to characterize the turbidity of the drainage fluid.
  • the turbidity detection module includes: a brightness extraction module that extracts the brightness value of the image from the key frame image; a turbidity determination module that characterizes the turbidity information of the drainage fluid based on the brightness value.
  • the brightness value of the key frame image can be extracted in various ways.
  • the key frame image can be converted from RGB space to a YUV format image, and the Y value is used as the turbidity information of the drainage fluid.
  • the key frame image may be converted from RGB space to another color mode image, for example, the L component of LAB and the I component of HSI may be used as the brightness value of the pixel.
  • the turbidity information of the drainage fluid can be characterized by calculating its average or mean square value. If the value is greater than a threshold, it indicates that the drainage fluid is normal and clear Status, and if the value is lower than a threshold, it indicates that there may be blood clots in the drainage fluid, causing it to appear cloudy.
  • the drainage flow reading module 24 is used to perform image recognition and enhancement processing on the key frame image, and read the scale value information in the key frame image.
  • the scale value information represents the volume of the drainage liquid contained in the drainage container.
  • the scale value information may be determined based on the level of the drainage fluid. Specifically, first convert the key frame image to grayscale mode, and then perform median filtering on the image to enhance the liquid level information in the image, and the processed image is subjected to edge enhancement processing to extract the liquid level in the drainage container Line, based on the pixel coordinates of the liquid level line, the volume of drainage fluid can be calculated.
  • the first camera is set in a direction that can be aligned with the volume scale lines on the two sides of the drainage container, so that there are two liquid level lines in the key frame image, which can be based on the average of the two liquid level lines
  • Pixel coordinates calculate the volume of the drainage fluid to balance the possible angle difference between the camera and the liquid level line.
  • the present invention can also use machine learning to extract color features and turbidity features in the drainage data.
  • the image processing module includes: an image sampling module 21', an image feature extraction module 22' and a drainage flow reading module 24', in which the image acquisition module 21' and the drainage flow reading module 24' function
  • the configuration is the same as that of the image acquisition module 21 and the drainage reading module 24 described above, which will not be repeated here.
  • the image feature extraction module 22' is a model obtained based on neural network training and is used to extract color features and turbidity features from key frame images.
  • the neural network may use a CNN model of a convolutional neural network, while using the YUV color space as the input feature of the model, which independently reflects the brightness and chrominance information of the image.
  • a neural network By training a neural network to obtain a detection model, and using the input of a certain layer in the model as a descriptor of color features and turbidity features, any actual captured image can be input into the model to obtain the representation of the image Drainage data description. Specifically, in the area to be recognized of the drainage tube, a certain number of pixels are extracted and their color values are converted into the color values of the YUV color space, and then the data is input into the trained CNN model for color and turbidity recognition.
  • the image sampling module 21' may be configured to adjust the sampling rate based on the change in the color characteristics. Its function and principle are the same as the previous image acquisition module 21, and will not be repeated here.
  • the image processing module 20 is connected to the monitoring module 30 through a data line, which receives drainage data such as the color, turbidity, and drainage volume of the drainage fluid. Meanwhile, as described below, the monitoring module 30 may compare the received drainage data with a set value, thereby monitoring the drainage data.
  • the monitoring module 30 may be further configured to determine a change in the properties of the drainage fluid based on the changes in the color and turbidity.
  • the change in the properties may be that the drainage fluid is doped with an abnormal substance, for example, a blood clot or gas appears in the drainage fluid. All of them will cause the color or turbidity of the drainage fluid to change.
  • the color change can be based on the three-channel RGB value to calculate the color change value of the drainage fluid over time.
  • the change value can be either the amount of change in the overall color of the drainage fluid or the amount of change in the color value of a channel .
  • the change of the turbidity can be monitored based on the brightness value of the image. When the change of the properties of the drainage fluid exceeds the preset threshold, the monitoring module 30 can start an alarm to promptly remind the patient's family or medical staff to view or process it.
  • the monitoring module 30 includes a first data receiving unit 31, a data processing unit 32 and a first display unit 33, the first data receiving unit 31 and the image processing module 20 are connected by a data line , Used to receive the color, turbidity, and drainage data of the drainage fluid, and transmit the received data to the data processing unit 32.
  • the data processing unit 32 can perform calculations on the relevant data, such as calculating the flow through the drainage tube based on the drainage flow data The flow rate of the drainage fluid and the change in the properties of the drainage fluid based on the change in color and turbidity.
  • the data processing unit 32 can also calculate the estimated full time based on the flow velocity and the volume of the current drainage bottle.
  • At least one of the drainage data is displayed in real time by the first display unit 33. Because the drainage bottle or drainage bag is mostly placed at the bottom of the bed or is covered, the real-time display of the drainage data can make it easier to observe the drainage flow, drainage color, or turbidity.
  • the content displayed by the first display unit 33 can be selected according to specific needs. The number can also be adjusted according to the needs, one display unit can be set, or multiple display units can be set, for example, they are set beside the bed and the nurse station respectively.
  • the first display unit 33 may be a display unit of various forms, such as a liquid crystal display, a light column, a digital display adjustable instrument, etc., and may be an integrated type or a split type. Among them, the color display method of the drainage liquid can be visually displayed through the color information, and can also be displayed numerically through the RGB component.
  • the first display unit 33 may also be an operation device such as a handheld PDA, and the drainage data is wirelessly transmitted to the device for medical personnel to view at any time.
  • the first display unit 33 and the data processing unit 32 are connected in a wired or wireless manner, for example, the drainage data can be transmitted to the first display unit 33 via Bluetooth to achieve the purpose of remote real-time monitoring.
  • the data processing unit 32 may use a single chip microcomputer, a processor, and the like with data calculation and processing capabilities to perform calculation processing on the drainage data, and it may further include an input system, an output system, and a wireless communication module connected to the processor.
  • the data processing unit 32 is connected to the negative pressure treatment device through a wired or wireless method. For example, when it is judged that the drainage fluid property changes and it is judged that there is gas in the drainage fluid, a control signal is sent to the negative pressure treatment device, for example Increase the negative pressure to draw gas.
  • the monitoring module 30 further includes a first alarm unit 34 for issuing an alarm when at least one of the determined drainage volume, flow rate, color, turbidity, and property changes exceeds a predetermined threshold
  • the data processing unit 32 may compare the turbidity with a predetermined threshold to determine whether abnormalities such as blood clots appear in the drainage fluid, and accordingly trigger the first alarm unit 34 to generate an alarm signal.
  • the predetermined threshold may be fixedly set in the data processing unit 32, or may be input and set through an input system of a control panel such as the threshold setting unit 36, so that different thresholds may be set according to different drainage types and patient signs.
  • the alarm signal may be an alarm signal such as sound and light, thereby attracting the attention of the patient and his family or medical staff, and reminding the attention of the drainage situation, thereby reducing the workload of the medical staff. For example, in the clinical situation, a sudden change of the drainage fluid properties may occur in a short time due to rupture of blood vessels. If the optimal treatment period is not easily found in time, such abnormal conditions can be found in time by the monitoring device of the present invention. The medical risks caused by the lack or negligence of medical staff during the monitoring process are avoided.
  • the monitoring system further includes a central monitoring module 50, which can be used as a part of the monitoring function of the monitoring center of the nurse station or the monitoring management center of the hospital to monitor the monitoring data of multiple monitoring modules 30 in real time
  • the data processing unit 32 of each monitoring module can associate the drainage data with the identification information (name, bed number, age, etc.) of the corresponding patient, and send the corresponding data to the central monitoring module 50 in a wired or wireless manner through the communication unit 35 , which includes: a second data receiving unit 51 for receiving monitoring data sent by a plurality of monitoring modules, a storage unit 52 for recording and storing the monitoring data, and a second display unit 53 for displaying multiple monitoring simultaneously
  • the monitoring data of the module for example, can display patient identification information, drainage data, the estimated full time of the drainage container, etc., and display the data such as the curve of drainage volume, flow rate, color and/or turbidity with time through the image.
  • the central monitoring module 50 can centrally monitor the relevant data of the
  • the central monitoring module 50 may further include: an information processing unit 56 configured to process the received identification information and drainage data, and through the information processing unit 56 and the storage unit 52, the patient's identification information and The drainage data is edited and processed, so that the hospital staff can centrally store and query the historical drainage data of each patient.
  • the central monitoring module 50 may further include a threshold setting unit 52 and a second alarm unit 54 which are respectively used to set a predetermined threshold value of the monitoring data of each monitoring module and that the monitoring data of any one of the multiple monitoring modules exceeds When the threshold is predetermined, an alarm signal is issued. It can be understood that the first alarm unit 34 and the second alarm unit 54 can respectively alert the patient/family and nurse/doctor of the abnormal drainage situation, and remind the medical staff to take necessary measures, so that the medical risk can be minimized.
  • FIG. 6 is a flowchart of a drainage monitoring method according to an embodiment of the present application, including the following steps:
  • step S110 the video stream data of the drainage fluid is acquired.
  • the drainage monitoring method of the present invention can be applied to various medical procedures, and the drainage fluid includes various drainage fluids such as intraoperative lumen drainage and postoperative urine drainage.
  • a video collection device such as a 2 million pixel camera can be used to align the drainage device to capture the drainage process and obtain video stream data.
  • video stream data can be stored as AVI, MPG and other general formats.
  • the present invention uses video stream data to dynamically monitor the drainage process, thus achieving more accurate drainage monitoring.
  • step S120 the video stream data is processed to obtain drainage data of the drainage fluid.
  • the processing of video stream data can be implemented on a data processor with image processing capabilities such as a microcontroller chip or a DSP processor.
  • the obtained drainage data includes the drainage flow, color, and turbidity of the drainage liquid.
  • the processing of the video streaming data includes image sampling, color extraction, turbidity detection, and drainage flow reading. The specific processing can be described above The image processing module is implemented and will not be repeated here.
  • data such as the drainage volume, color, and turbidity of the drainage liquid can be obtained in a centralized manner, thereby obtaining all-round information on the drainage of the patient.
  • step S130 the drainage data is received and monitored.

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Hematology (AREA)
  • Animal Behavior & Ethology (AREA)
  • Multimedia (AREA)
  • General Physics & Mathematics (AREA)
  • Vascular Medicine (AREA)
  • Anesthesiology (AREA)
  • Biomedical Technology (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • External Artificial Organs (AREA)
  • Image Analysis (AREA)
  • Alarm Systems (AREA)
  • Invalid Beds And Related Equipment (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
PCT/CN2019/126662 2018-12-29 2019-12-19 一种基于图像识别的引流监控系统及方法 WO2020135226A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2021538480A JP7211668B2 (ja) 2018-12-29 2019-12-19 画像認識に基づく排出監視システム及び方法
US17/304,841 US20210316060A1 (en) 2018-12-29 2021-06-26 Medical drainage monitoring method, apparatus, and system based on image recognition

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811652811.4A CN109498857B (zh) 2018-12-29 2018-12-29 一种基于图像识别的引流监控系统及方法
CN201811652811.4 2018-12-29

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US17/304,841 Continuation-In-Part US20210316060A1 (en) 2018-12-29 2021-06-26 Medical drainage monitoring method, apparatus, and system based on image recognition

Publications (1)

Publication Number Publication Date
WO2020135226A1 true WO2020135226A1 (zh) 2020-07-02

Family

ID=65757188

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/126662 WO2020135226A1 (zh) 2018-12-29 2019-12-19 一种基于图像识别的引流监控系统及方法

Country Status (3)

Country Link
JP (1) JP7211668B2 (ja)
CN (1) CN109498857B (ja)
WO (1) WO2020135226A1 (ja)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115308101A (zh) * 2022-09-27 2022-11-08 恒天益科技（深圳）有限公司 水质监测管理方法及系统
CN117045884A (zh) * 2023-10-11 2023-11-14 吉林医药学院 一种胸外科用引流监测装置

Families Citing this family (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109498857B (zh) * 2018-12-29 2020-10-16 刘铁楠 一种基于图像识别的引流监控系统及方法
US11318241B2 (en) 2019-03-27 2022-05-03 Medsix Inc. System and method for wound monitoring
CN110013574A (zh) * 2019-05-10 2019-07-16 上海市东方医院（同济大学附属东方医院） 引流液液量实时监测方法
CN110599879A (zh) * 2019-09-26 2019-12-20 赣南医学院第一附属医院 静脉导管冲管封管教学装置及方法
CN111603622B (zh) * 2020-07-06 2024-08-16 中国科学院大学宁波华美医院 便携式引流管监测装置
CN114053489A (zh) * 2020-07-31 2022-02-18 西伯股份有限公司 引流袋管理系统及其引流袋
CN112089409A (zh) * 2020-10-14 2020-12-18 皖南医学院第一附属医院（皖南医学院弋矶山医院） 内瘘流量监测报警装置
CN112642022B (zh) * 2020-12-31 2022-07-05 遵义师范学院 一种输液监控系统及监控方法
CN112861734A (zh) * 2021-02-10 2021-05-28 北京农业信息技术研究中心 一种料槽余食监测方法及系统
CN114397929B (zh) * 2022-01-18 2023-03-31 中山东菱威力电器有限公司 一种可以改善冲洗水初始温度的智能马桶盖控制系统
CN116440340B (zh) * 2023-04-27 2024-01-23 苏州鸿博医疗器械有限公司 一种冲洗引流装置及控制系统
CN117373627A (zh) * 2023-10-17 2024-01-09 深圳市萨米医疗中心 一种用于监护的移动管理装置
CN118356538B (zh) * 2024-05-06 2024-10-25 中国人民解放军总医院第一医学中心 应用于胸腔闭式引流的监测装置

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101201605A (zh) * 2007-12-07 2008-06-18 华中科技大学 一种基于机器视觉的医疗输液速度监测与控制系统
CN101505813A (zh) * 2006-08-23 2009-08-12 B布劳恩阿维图姆公司 用于体外血液处理的医疗设备
CN101720024A (zh) * 2009-11-23 2010-06-02 深圳市宾利达智能科技有限公司 智能识别监控系统及其监控方法
US20130010094A1 (en) * 2011-07-09 2013-01-10 Siddarth Satish System and method for estimating extracorporeal blood volume in a physical sample
CN103830791A (zh) * 2012-11-27 2014-06-04 深圳先进技术研究院 自动化腹膜透析机
CN104316527A (zh) * 2014-11-07 2015-01-28 昆山韦睿医疗科技有限公司 一种对排出的透析液的自动检测方法、装置
CN108053872A (zh) * 2017-12-27 2018-05-18 苏州麦迪斯顿医疗科技股份有限公司 一种透析数据的采集装置及其采集方法
CN109498857A (zh) * 2018-12-29 2019-03-22 刘铁楠 一种基于图像识别的引流监控系统及方法

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009037612A2 (en) 2007-09-19 2009-03-26 Koninklijke Philips Electronics N.V. Method and apparatus for detecting an abnormal situation
US20090149776A1 (en) 2007-12-05 2009-06-11 Adams Scott C Optical sensor for detecting infection and other anomalous conditions associated with catheter systems
CN102612338B (zh) * 2009-11-20 2016-05-04 基文影像公司 用于控制体内装置的功率消耗的系统和方法
CN109738621B (zh) * 2012-05-14 2021-05-11 高斯外科公司 用于估计液体罐中的血液成分的量的系统和方法
CN202751632U (zh) * 2012-08-21 2013-02-27 张晓东 颅内压不间断监护下脑室外引流自动控制装置
US10321870B2 (en) 2014-05-01 2019-06-18 Ramot At Tel-Aviv University Ltd. Method and system for behavioral monitoring
TWI525578B (zh) 2015-08-05 2016-03-11 國立清華大學 用於腹膜透析中腹膜併發症評估的影像分析方法及裝置
DE102016008332A1 (de) 2016-07-07 2018-01-11 Fresenius Medical Care Deutschland Gmbh Verfahren zur Erfassung von Symptomen einer Peritonitis
US11282602B2 (en) 2016-10-26 2022-03-22 Carefusion 2200, Inc. Device and method for mobile monitoring of drainage catheter
CN107497004A (zh) * 2017-10-10 2017-12-22 西安汇智医疗集团有限公司 一种智能脑脊液引流控制与识别警示系统

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101505813A (zh) * 2006-08-23 2009-08-12 B布劳恩阿维图姆公司 用于体外血液处理的医疗设备
CN101201605A (zh) * 2007-12-07 2008-06-18 华中科技大学 一种基于机器视觉的医疗输液速度监测与控制系统
CN101720024A (zh) * 2009-11-23 2010-06-02 深圳市宾利达智能科技有限公司 智能识别监控系统及其监控方法
US20130010094A1 (en) * 2011-07-09 2013-01-10 Siddarth Satish System and method for estimating extracorporeal blood volume in a physical sample
CN103830791A (zh) * 2012-11-27 2014-06-04 深圳先进技术研究院 自动化腹膜透析机
CN104316527A (zh) * 2014-11-07 2015-01-28 昆山韦睿医疗科技有限公司 一种对排出的透析液的自动检测方法、装置
CN108053872A (zh) * 2017-12-27 2018-05-18 苏州麦迪斯顿医疗科技股份有限公司 一种透析数据的采集装置及其采集方法
CN109498857A (zh) * 2018-12-29 2019-03-22 刘铁楠 一种基于图像识别的引流监控系统及方法

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115308101A (zh) * 2022-09-27 2022-11-08 恒天益科技（深圳）有限公司 水质监测管理方法及系统
CN117045884A (zh) * 2023-10-11 2023-11-14 吉林医药学院 一种胸外科用引流监测装置
CN117045884B (zh) * 2023-10-11 2023-12-26 吉林医药学院 一种胸外科用引流监测装置

Also Published As

Publication number Publication date
JP7211668B2 (ja) 2023-01-24
CN109498857A (zh) 2019-03-22
CN109498857B (zh) 2020-10-16
JP2022516157A (ja) 2022-02-24

Similar Documents

Publication Publication Date Title
WO2020135226A1 (zh) 一种基于图像识别的引流监控系统及方法
US20210316060A1 (en) Medical drainage monitoring method, apparatus, and system based on image recognition
CN103623480A (zh) 一种病房床头智能终端服务系统
US20220101977A1 (en) Intelligent Intracranial Hematoma Removal and Drainage System
CN206930346U (zh) 实时尿液/体液监测系统
CN103566436A (zh) 输液监控方法和输液监控系统
CN206410732U (zh) 病房环境与病人生理参数监控系统
CN105498042B (zh) 一种基于视频的非避光式输液自动报警方法及其装置
CN115252962A (zh) 一种基于机器视觉的智能输液报警方法及系统
CN203263374U (zh) 一种无线综合监测装置
CN106651713A (zh) 一种基于医养结合的便携式健康管理互动装置及控制方法
CN113261926A (zh) 一种基于信息化技术的血透患者家居管理方法及系统
CN203852362U (zh) 一种医用尿流量动态检测仪
CN203634563U (zh) 一种病房床头智能终端服务系统
CN206193790U (zh) 基于互联网的慢病信息化系统
CN206301393U (zh) 一种适合居家环境的生理指标动态监测系统
CN115154685A (zh) 一种高精度引流液监测系统
CN215194492U (zh) 一种智能点滴系统
CN213155938U (zh) 一种急性心衰早期预警监护仪系统
CN204496497U (zh) 用于病房数据采集的机器人系统
WO2017063149A1 (zh) 多级输液报警系统及其探测端装置
CN103720478A (zh) 一种医用尿流量检测仪
CN214970342U (zh) 可控滴速输液报警器
US20240019287A1 (en) Methods, apparatuses, and computer program products for measuring fluid volumes
CN203329130U (zh) 智能输液压力测速装置

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: 19902963

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2021538480

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19902963

Country of ref document: EP

Kind code of ref document: A1