Infusion speed alarm and infusion speed monitoring alarm system

Abstract

The invention relates to the technical field of medical devices, and discloses an infusion speed alarm, comprising a body, wherein a card slot is provided on the outer side of the body, a switch and an indicator light are provided on the front surface of the body, and a monitor and an alarm are provided in the body, wherein the monitor comprises a sensor, a data collector, an image processing module, a data analysis module, and a controller, wherein dripping speed data is collected through the sensor, and the infusion speed of the patient is set through a nurse station host and a mobile phone of a nurse on duty, or the recommended speed and speed threshold are calculated after the patient's physical information is input through the device, so as to monitor the infusion speed according to the threshold, and when the infusion speed changes and blood return occurs due to changes in body position, accidental toggling of a regulating valve, or the end of dripping, the infusion device operation can be adjusted and removed in time, and an alarm will be issued in a variety of ways to prevent personnel from missing the alarm information, thereby improving safety.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, in particular to an infusion speed alarm and an infusion speed monitoring alarm system thereof. Background Art

[0002] Intravenous infusion is a commonly used treatment method in clinical medical work. Studies have shown that the use rate of intravenous infusion in hospitalized patients is 93.13%, and the average number of infusion bottles (bags) used per bed per day is 3.76 bottles (bags). The infusion speed is determined according to the age, disease, and nature of the drug of the hospitalized patient. Too fast infusion may cause heart failure or other serious consequences in the patient, which not only harms the patient's health, but also may cause medical accidents. The awareness of following medical advice is weak, and patients and their families adjust the intravenous speed at will in private.

[0003] Nurses are too busy to regularly check on patients’ infusion status; patients’ body positions change and the intravenous infusion speed increases, but they fail to detect it in time. Existing infusion alarms can only give an alarm after the drip stops, but cannot measure the speed. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an infusion speed alarm and an infusion speed monitoring alarm system thereof, which solve the problems raised in the above-mentioned background technology.

[0005] To solve the above technical problems, according to one aspect of the present invention, more specifically, an infusion speed monitoring alarm system includes an infusion speed alarm. The infusion speed alarm includes a body, a card slot is provided on the outside of the body, a switch and an indicator light are provided on the front surface of the body, a monitor and an alarm are included in the body, the monitor includes a sensor, a data collector, an image processing module, a data analysis module, and a controller, and the alarm includes an alarm light and a buzzer; the sensor is arranged on the inner side wall of the card slot, and the alarm light and the buzzer are both arranged on the surface of the body;

[0006] It also includes a host computer, a monitoring terminal, and a cloud database. The host computer is a nurse station host, which is connected to the monitor via a USB or wireless module, and can view the infusion status of each patient in real time, and can also set parameters for the system;

[0007] The monitoring terminal can check notifications, modify settings, and input parameters through a mobile phone APP, so that medical staff can dynamically monitor the infusion status;

[0008] The sensor is a high-speed camera that captures and collects dripping data in the drip pot of the infusion tube;

[0009] The data collector is responsible for collecting sensor data and preprocessing the collected data to improve the quality of the data and facilitate subsequent processing;

[0010] The controller is responsible for controlling the operation of the entire monitoring system; the controller processes and analyzes the droplet image information captured by the sensor to extract the droplet velocity information;

[0011] The cloud database records and stores the data captured and collected by the sensor in real time for subsequent query and statistical analysis. The integrity and traceability of the data need to be ensured during the recording and storage process for subsequent investigation and analysis;

[0012] The image processing module comprises:

[0013] Image segmentation: Segment the droplet part from the background in the image;

[0014] Feature extraction: Analyze the droplet motion by extracting the geometric features and motion features of the droplet;

[0015] Trajectory tracking: By tracking the trajectory of the droplet, the motion law of the droplet and the interaction between the droplet and the wall are analyzed;

[0016] Image reconstruction: By tracking and recording the motion trajectory of the droplets, the motion of the droplets is reconstructed in three dimensions to more intuitively display the motion trajectory of the droplets;

[0017] Image processing uses edge detection algorithm and frame difference algorithm for image processing;

[0018] Edge detection algorithm: used to detect the edge of the droplet, thereby extracting the shape and size information of the droplet;

[0019] Inter-frame difference algorithm: used to calculate the pixel difference between adjacent frames to detect the movement speed of the droplet; the inter-frame difference algorithm effectively removes background interference and improves the accuracy of droplet speed detection;

[0020] Patients were divided into three groups according to their age groups: the first group was 19-59 years old, the second group was 1-18 years old, and the third group was 60 years old and above;

[0021] The recommended infusion speed and speed threshold calculation formula for the first-level population are as follows:

[0022] Na=(W / H²)*K

[0023] Nb=(0.61×H+0.0128×W-0.1529)*K

[0024] X = [Na × (Nb / 2) + Na × (Nb / 2 + 1)] / 2

[0025] Wherein, W is the patient's weight in kg; H is the height in m; K is the ratio of therapeutic drugs; X, Na, and Nb are all infusion rates in drops / minute; the infusion alarm threshold is the Na-Nb interval; X is the recommended infusion rate;

[0026] The formula for calculating the recommended infusion rate for the secondary population is as follows:

[0027] / 18

[0028]

[0029]

[0030] The formula for calculating the recommended infusion speed for level 3 population is as follows:

[0031]

[0032]

[0033]

[0034] Among them, S is the average infusion rate for adults, , The recommended infusion rates for 1, 2, ..., 18, ..., 60, 61, ..., and 77 years old are shown respectively. The infusion alarm threshold is .

[0035] Furthermore, the data analysis module performs statistical distribution analysis on the data processed by the image processing module to understand the distribution of the dripping speed, and after setting the alarm threshold, it can detect abnormal conditions of the infusion speed; finally, by monitoring and analyzing the infusion speed, the infusion effect is evaluated, and the data is transmitted to the controller.

[0036] Furthermore, the data analysis module uses a mean and median algorithm to calculate the mean and median of the droplet velocity, thereby determining the overall level of the droplet velocity.

[0037] The beneficial effects of the infusion speed alarm device and the infusion speed monitoring alarm system of the present invention are as follows:

[0038] During the use of the present invention, the dripping speed data is collected by the sensor, and the patient's infusion speed is set through the nurse station host and the on-duty nurse's mobile phone, or the patient's physical information is input through the device to calculate the recommended speed and speed threshold, so as to monitor the infusion speed according to the threshold. When the body position changes, the regulating valve is accidentally turned, the dripping ends, resulting in changes in the infusion speed and blood return, the infusion device operation can be adjusted and removed in time, and alarms will be issued in various ways to prevent people from missing the alarm information, thereby improving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0040] Figure 1 It is a structural diagram of the infusion speed alarm;

[0041] Figure 2 This is a structural diagram of the infusion speed monitoring and alarm system.

[0042] In the figure: 1. body; 2. switch; 3. card slot; 4. sensor; 5. warning light; 6. buzzer; 7. indicator light. DETAILED DESCRIPTION

[0043] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0044] like Figure 1 As shown, according to one aspect of the present invention, an infusion speed monitoring alarm system is provided, including an infusion speed alarm, the infusion speed alarm including a body 1, a card slot 3 is provided on the outside of the body 1, a switch 2 and an indicator light are provided on the front surface of the body 1, a monitor and an alarm are included in the body 1, the monitor includes a sensor 4, a data collector, an image processing module, a data analysis module, and a controller, and the alarm includes an alarm light 5 and a buzzer 6; the sensor 4 is arranged on the inner side wall of the card slot 3, and the alarm light and the buzzer are both arranged on the surface of the body 1;

[0045] It also includes a host computer, a monitoring terminal, and a cloud database. The host computer is the host of the nurse station, which is connected to the monitor via a USB or wireless module. It can view the infusion status of each patient in real time and set parameters for the system.

[0046] The monitoring terminal can check notifications, modify settings, and input parameters through a mobile phone APP, allowing medical staff to dynamically monitor the infusion status;

[0047] Sensor 4 is a high-speed camera that captures and collects the dripping data in the drip pot of the infusion tube;

[0048] The data collector is responsible for collecting data from the sensor 4 and performing preprocessing on the collected data, such as denoising and filtering, to improve the quality of the data and facilitate subsequent processing;

[0049] The controller is responsible for controlling the operation of the entire monitoring system; the controller processes and analyzes the droplet image information captured by the sensor 4 to extract the droplet velocity information;

[0050] The cloud database records and stores the data captured by sensor 4 in real time for subsequent query and statistical analysis. The integrity and traceability of the data need to be ensured during the recording and storage process for subsequent investigation and analysis.

[0051] In this embodiment, the image processing module includes:

[0052] Image segmentation: Segment the droplet part from the background in the image;

[0053] Feature extraction: Analyze the droplet motion by extracting the droplet's geometric features (such as radius, diameter, area, etc.) and motion features (such as speed, acceleration, etc.);

[0054] Trajectory tracking: By tracking the trajectory of the droplet, the movement law of the droplet and the interaction between the droplet and the wall are analyzed; (the analysis method is any one of the optical flow method, inter-frame difference method, and Kalman filter)

[0055] Image reconstruction: By tracking and recording the motion trajectory of the droplets, the motion of the droplets is reconstructed in three dimensions to more intuitively display the motion trajectory of the droplets.

[0056] In this embodiment, the image processing uses an edge detection algorithm and an inter-frame difference algorithm to perform image processing;

[0057] Edge detection algorithm: used to detect the edge of the droplet, so as to extract the shape and size information of the droplet (either Sobel algorithm or Canny algorithm);

[0058] Inter-frame difference algorithm: used to calculate the pixel differences between adjacent frames to detect the movement speed of droplets; the inter-frame difference algorithm effectively removes background interference and improves the accuracy of droplet speed detection.

[0059] In this embodiment, the data analysis module performs statistical distribution analysis on the data processed by the image processing module to understand the distribution of the dripping speed, and after setting the alarm threshold, it can detect abnormal conditions of the infusion speed (such as sudden acceleration or slowing down, etc.); finally, by monitoring and analyzing the infusion speed, the infusion effect is evaluated, and the data is transmitted to the controller.

[0060] In this embodiment, the data analysis module uses a mean and median algorithm to calculate the mean and median of the droplet velocity, thereby determining the overall level of the droplet velocity.

[0061] In this embodiment, the patients are divided into three groups according to their age groups, namely, the first group is 19-59 years old, the second group is 1-18 years old, and the third group is 60 years old and above.

[0062] In this embodiment, the recommended infusion speed and speed threshold calculation formula for the first-level population are as follows:

[0063] Na=(W / H²)*K

[0064] Nb=(0.61×H+0.0128×W-0.1529)*K

[0065] X = [Na × (Nb / 2) + Na × (Nb / 2 + 1)] / 2

[0066] Wherein, W is the patient's weight in kg; H is the height in m; K is the ratio of therapeutic drugs; X, Na, and Nb are all infusion rates in drops / minute; the infusion alarm threshold is the Na-Nb interval; X is the recommended infusion rate;

[0067] The formula for calculating the recommended infusion rate for the secondary population is as follows:

[0068] / 18

[0069]

[0070]

[0071] The formula for calculating the recommended infusion speed for level 3 population is as follows:

[0072]

[0073]

[0074]

[0075] Among them, S is the average infusion rate for adults, , The recommended infusion rates for 1, 2, ..., 18, ..., 60, 61, ..., and 77 years old are shown respectively. The infusion alarm threshold is .

[0076] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by ordinary technicians in this technical field within the essential scope of the present invention also fall within the protection scope of the present invention.

Claims

1. An infusion speed monitoring and alarm system, comprising an infusion speed alarm, characterized in that: The infusion speed alarm comprises a body (1), a card slot (3) is provided on the outside of the body (1), a switch (2) and an indicator light are provided on the front surface of the body (1), a monitor and an alarm are included in the body (1), the monitor comprises a sensor (4), a data collector, an image processing module, a data analysis module, and a controller, and the alarm comprises an alarm light (5) and a buzzer (6); the sensor (4) is arranged on the inner side wall of the card slot (3), and the alarm light and the buzzer are both arranged on the surface of the body (1); It also includes a host computer, a monitoring terminal, and a cloud database. The host computer is a nurse station host, which is connected to the monitor via a USB or wireless module, and can view the infusion status of each patient in real time, and can also set parameters for the system; The monitoring terminal can check notifications, modify settings, and input parameters through a mobile phone APP, so that medical staff can dynamically monitor the infusion status; The sensor (4) is a high-speed camera that captures and collects data on the dripping liquid in the drip pot of the infusion tube; The data collector is responsible for collecting data from the sensor (4) and preprocessing the collected data to improve the quality of the data and facilitate subsequent processing; The controller is responsible for controlling the operation of the entire monitoring system; the controller processes and analyzes the droplet image information captured by the sensor (4) to extract the droplet velocity information; The cloud database records and stores the data captured and collected by the sensor (4) in real time for subsequent query and statistical analysis. The integrity and traceability of the data need to be ensured during the recording and storage process for subsequent investigation and analysis; The image processing module comprises: Image segmentation: Segment the droplet part from the background in the image; Feature extraction: Analyze the droplet motion by extracting the geometric features and motion features of the droplet; Trajectory tracking: By tracking the trajectory of the droplet, the motion law of the droplet and the interaction between the droplet and the wall are analyzed; Image reconstruction: By tracking and recording the motion trajectory of the droplets, the motion of the droplets is reconstructed in three dimensions to more intuitively display the motion trajectory of the droplets; Image processing uses edge detection algorithm and frame difference algorithm for image processing; Edge detection algorithm: used to detect the edge of the droplet, thereby extracting the shape and size information of the droplet; Inter-frame difference algorithm: used to calculate the pixel difference between adjacent frames to detect the movement speed of the droplet; the inter-frame difference algorithm effectively removes background interference and improves the accuracy of droplet speed detection; Patients were divided into three groups according to their age groups: the first group was 19-59 years old, the second group was 1-18 years old, and the third group was 60 years old and above; The recommended infusion speed and speed threshold calculation formula for the first-level population are as follows: Na=(W / H²)*K Nb=(0.61×H+0.0128×W-0.1529)*K X = [Na × (Nb / 2) + Na × (Nb / 2 + 1)] / 2 Wherein, W is the patient's weight in kg; H is the height in m; K is the ratio of therapeutic drugs; X, Na, and Nb are all infusion rates in drops / minute; the infusion alarm threshold is the Na-Nb interval; X is the recommended infusion rate; The formula for calculating the recommended infusion rate for the secondary population is as follows: The formula for calculating the recommended infusion speed for level 3 population is as follows: Among them, S is the average infusion rate for adults, , The recommended infusion rates for 1, 2, ..., 18, ..., 60, 61, ..., and 77 years old are shown respectively. The infusion alarm threshold is .

2. The infusion speed monitoring and alarm system according to claim 1, characterized in that: The data analysis module performs statistical distribution analysis on the data processed by the image processing module to understand the distribution of the dripping speed, and after setting the alarm threshold, it can detect abnormal conditions of the infusion speed; finally, by monitoring and analyzing the infusion speed, the infusion effect is evaluated, and the data is transmitted to the controller.

3. The infusion speed monitoring and alarm system according to claim 1, characterized in that: The data analysis module uses a mean and median algorithm to calculate the mean and median of the droplet velocity, thereby determining the overall level of the droplet velocity.

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