Bedside skin flap blood flow monitoring and early warning device and computing equipment

Abstract

The invention discloses a bedside skin flap blood flow monitoring and early warning device and computing equipment, and the device comprises a skin flap tissue perfusion monitoring module which comprises a probe housing, a microcirculation blood flow velocity sensor, a tissue oxygenation degree sensor and a flexible connecting arm; the data acquisition and transmission module is used for receiving the blood flow velocity data and the oxygenation degree data through a data line and carrying out analog-to-digital conversion and data packaging; the central processing unit comprises a data storage module, a data analysis module and an early warning module; the data analysis module comprises a baseline establishment sub-module, an anomaly detection sub-module and a trend prediction sub-module; and the early warning module is used for displaying a red alarm through a bedside display screen and sending a short message alarm containing the patient name, the bed number, the early warning type and the severity information to a medical staff mobile terminal through the wireless notification module. According to the invention, the abnormal condition of skin flap blood perfusion can be found and predicted in time, and the workload of medical staff is reduced.

Description

Technical Field

[0001] The present invention relates to the field of medical device auxiliary technology, and in particular to a bedside flap blood flow monitoring and early warning device and device, and a computing device. Background Art

[0002] Currently, flap blood flow monitoring primarily involves clinical observation and handheld device methods. Clinical observation assesses blood flow by observing indicators such as flap color, temperature, and capillary refill time. However, this method is highly subjective and relies on the experience of medical staff. Early subtle changes in blood flow can be difficult to detect, potentially delaying treatment. Among handheld devices, handheld Doppler flowmeters can measure blood flow velocity on the flap surface. While more objective than clinical observation, they only provide instantaneous blood flow information, are unable to perform continuous monitoring and trend analysis, and are easily affected by the operator's skill level. Laser Doppler flowmetry (LDF) can continuously monitor microcirculatory blood flow velocity, but is typically expensive and complex to operate, making it difficult to popularize bedside use in general wards. Furthermore, existing LDF systems lack intelligent data analysis and early warning capabilities, requiring medical staff to stare at the screen for extended periods, which can lead to fatigue and the potential for missing critical blood flow changes. In addition, since flap blood flow monitoring is mainly based on subjective judgment methods such as color, temperature, tension, and capillary refill tests, continuous observation is impossible and is easily affected by the experience, subjective judgment, and environmental factors of medical staff. Continuous testing with objective indicators is required.

[0003] To solve the above problems, the present invention provides a bedside flap blood flow monitoring and early warning device, which can timely detect and predict abnormal flap blood perfusion conditions and reduce the workload of medical staff. Summary of the Invention

[0004] In view of the above problems, the present invention provides a bedside flap blood flow monitoring and early warning device and device, and computing equipment.

[0005] According to one aspect of the present invention, a bedside flap blood flow monitoring and early warning device is provided, comprising:

[0006] A flap tissue perfusion monitoring module (100) comprises a probe housing (103), a microcirculation blood flow velocity sensor (101), a tissue oxygenation sensor (102) and a flexible connecting arm (104); wherein the probe housing (103) is made of a biocompatible material and has an arc-shaped contact surface for fitting the flap surface; the microcirculation blood flow velocity sensor (101) is built into the probe housing (103) for measuring the microcirculation blood flow velocity of the flap tissue in real time and generating corresponding blood flow velocity data; the tissue oxygenation sensor (102) is built into the probe housing (103) for measuring the tissue oxygenation of the flap tissue in real time and generating corresponding oxygenation data; one end of the flexible connecting arm (104) is connected to the probe housing (103), and the other end is connected to a bedside support rod (500) via a universal joint (105) for adjusting and fixing the position of the probe housing (103);

[0007] A data acquisition and transmission module (200) is connected to the flap tissue perfusion monitoring module (100), receives the blood flow velocity data and oxygenation data via a data line, and performs analog-to-digital conversion and data packaging;

[0008] The central processing unit (300) includes a data storage module (301), a data analysis module (302) and an early warning module (303); the data storage module (301) is used to store the received monitoring data; the data analysis module (302) includes a baseline establishment submodule (302a), an abnormality detection submodule (302b) and a trend prediction submodule (302c); wherein the baseline establishment submodule (302a) is used to calculate the patient's individualized baseline blood flow parameter range based on normal skin blood flow data near the flap; the abnormality detection submodule (302b) is used to compare the real-time monitoring data with the baseline blood flow parameter range, and when the real-time blood flow velocity is lower than 15% of the lower limit of the baseline blood flow velocity range or the real-time oxygenation is lower than 10% of the lower limit of the baseline oxygenation range, it is determined that an abnormal blood perfusion index exists; the trend prediction submodule (302c) predicts the blood perfusion change trend in the next 30 minutes based on the blood flow velocity and oxygenation data of the past hour;

[0009] The early warning module (303) is connected to the data analysis module (302), and generates an early warning signal when the abnormal detection submodule (302b) detects an abnormal blood perfusion index, or when the trend prediction submodule (302c) predicts that the future blood flow velocity or oxygenation will be lower than a preset threshold, and displays a red alarm through the bedside display screen (400), and sends a text message alarm containing the patient's name, bed number, warning type and severity information to the medical staff's mobile terminal through the wireless notification module (401).

[0010] In an optional manner, the bedside display screen (400) is connected to the central processing unit (300) for displaying blood flow velocity, oxygenation, trend curve, blood perfusion change trend and warning information in real time;

[0011] The wireless notification module (401) is connected to the central processing unit (300) and is used to send warning information to the mobile terminal of medical staff through the mobile communication network.

[0012] In an optional manner, the flexible connecting arm (104) includes a proximal fixing module, a middle adjustable module and a distal probe connecting module;

[0013] wherein the proximal fixing module is fixed to the universal joint (105) via a C-shaped clamp having a ratchet locking mechanism;

[0014] The intermediate adjustable module is composed of three joint units of the same structure connected in series, each joint unit comprising two fork-shaped arms made of polyamide material, the fork-shaped arms being connected by a ball stud, each ball stud being equipped with a locking nut for fixing the angle of the joint; the joint units are connected by a locking mechanism comprising a buckle and a release button, and the joint units are disassembled or assembled by pressing the release button to adjust the length and curvature of the flexible connecting arm (104);

[0015] The distal probe connection module is composed of a groove matching the shape of the probe housing (103) and a locking mechanism.

[0016] In an optional manner, the universal joint (105) includes a base, a rotation axis, a pitch axis and a roll axis;

[0017] The base is fixed to the top of the bedside support rod (500) by four bolts, and the rotating shaft is connected to the base by a ball bearing; the pitch axis is a U-shaped bracket, which is connected to the rotating shaft by two hinges; a locking screw is installed in the middle of the pitch axis to fix the pitch angle; the roll axis is connected to the pitch axis by two hinges, and the top of the roll axis is connected to the proximal fixing module of the flexible connecting arm (104).

[0018] In an optional manner, the probe housing (103) includes an upper shell and a lower shell;

[0019] The upper shell is provided with heat dissipation holes; the lower shell contacts the skin flap, the surface of the lower shell is coated with biocompatible hydrogel, and the interior of the lower shell is provided with a sensor fixing structure for fixing the microcirculation blood flow velocity sensor (101) and the tissue oxygenation sensor (102) to ensure contact between the sensor and the skin flap tissue; the microcirculation blood flow velocity sensor (101) and the tissue oxygenation sensor (102) are connected to the data acquisition and transmission module (200) through a connector; the edge of the probe housing (103) is chamfered, and the bottom of the probe housing (103) is provided with multiple micro suction cups to enhance the adsorption force with the skin flap surface.

[0020] In an optional manner, the bedside support rod (500) includes a base, an inner rod, an outer rod, a locking mechanism, and a top connector;

[0021] The base is provided with four universal wheels; the inner rod slides inside the outer rod and the height is adjusted by a locking mechanism; the top connecting piece of the locking mechanism is connected to the universal joint (105) by a threaded connection.

[0022] In an optional manner, the abnormality detection submodule (302b) determines whether there is an abnormal blood perfusion indicator based on the cumulative sum control diagram;

[0023] Specifically, the upper limit and lower limit of the cumulative sum are calculated based on the blood flow velocity at time t, the baseline blood flow velocity, and the drift amount;

[0024] If the upper limit of the cumulative sum is greater than the preset control limit or the lower limit of the cumulative sum is less than the negative preset control limit, it is determined that an abnormal blood perfusion index exists;

[0025] The calculation formula for the upper limit of the cumulative sum is:

[0026] S H (t)=max(0,S H (t-1)+(y t -μ0)-k)

[0027] The calculation formula for the lower limit of the cumulative sum is:

[0028] S L (t)=min(0,S L (t-1)+(y t -μ0)+k)

[0029] Among them, y t is the blood flow velocity at time t; μ0 is the baseline blood flow velocity; k is the allowed drift, σ is the standard deviation of baseline blood velocity.

[0030] In an optional manner, the trend prediction submodule (302c) adopts a chaos prediction formula based on phase space and Lyapunov exponent, and the chaos prediction formula is:

[0031]

[0032] Among them, k is the number of recent data points involved in the prediction; T is the prediction step size; y t is the blood flow velocity at past time t; λ is the Lyapunov exponent, t0 is the starting point for eliminating transient effects; X t is point t in the phase space, X t =[y t ,y t+τ ,y t+2 τ,…,y t+(m-1)τ ], τ is the time delay, τ=argmin τ MI(y t ,y t+τ ); MI is the mutual information function; m is the dimension, which is calculated by the false nearest neighbor method; N is the quantization parameter.

[0033] In an optional manner, the warning module (303) further comprises an intelligent graded warning unit (303d), and the intelligent graded warning unit (303d) performs a dynamic evolution graded warning according to hemodynamic parameters;

[0034] When the blood flow velocity drops by more than 15% of the baseline or the oxygenation level drops by more than 10% of the baseline, a yellow warning signal is triggered, the bedside display screen (400) flashes a yellow light accompanied by a warning sound, and sends a warning message to the medical staff's mobile terminal through the wireless notification module (401);

[0035] When the abnormal state lasts for more than 5 minutes or the trend prediction submodule (302c) predicts that the blood flow velocity will be 30% lower than the baseline in the next 10 minutes, it will automatically upgrade to an orange warning, the bedside device will start the sound and light linkage alarm, and push a report containing the patient's historical monitoring data trend chart to the nursing station console;

[0036] When the real-time blood flow velocity is lower than 50% of the baseline or an imminent blood perfusion collapse is predicted, a red critical warning is immediately triggered, the sound and light alarm system of the entire ward is activated, and the monitoring data chain before and after the event is recorded as medical evidence.

[0037] According to another aspect of the present invention, there is provided a computing device comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0038] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned bedside flap blood flow monitoring and early warning device.

[0039] According to the solution provided by the present invention, it comprises: a flap tissue perfusion monitoring module (100), comprising a probe housing (103), a microcirculation blood flow velocity sensor (101), a tissue oxygenation sensor (102) and a flexible connecting arm (104); wherein the probe housing (103) is made of a biocompatible material and has an arc-shaped contact surface for fitting the flap surface; the microcirculation blood flow velocity sensor (101) is built into the probe housing (103) for real-time measurement of the microcirculation blood flow velocity of the flap tissue and generation of corresponding blood flow velocity data; the tissue oxygenation sensor (102) is built into the probe housing (103) for real-time measurement of the microcirculation blood flow velocity of the flap tissue and generation of corresponding blood flow velocity data. The flexible connecting arm (104) is connected to the probe housing (103) at one end and connected to the bedside support rod (500) via a universal joint (105) at the other end for adjusting and fixing the position of the probe housing (103); a data acquisition and transmission module (200) is connected to the flap tissue perfusion monitoring module (100), receives the blood flow velocity data and oxygenation data via a data line, and performs analog-to-digital conversion and data packaging; a central processing unit (300) includes a data storage module (301), a data analysis module (302) and an early warning module (303); the data storage module The block (301) is used to store the received monitoring data; the data analysis module (302) includes a baseline establishment submodule (302a), an abnormality detection submodule (302b) and a trend prediction submodule (302c); wherein the baseline establishment submodule (302a) is used to calculate the patient's individualized baseline blood flow parameter range based on the normal skin blood flow data near the flap; the abnormality detection submodule (302b) is used to compare the real-time monitoring data with the baseline blood flow parameter range, and when the real-time blood flow velocity is lower than 15% of the lower limit of the baseline blood flow velocity range or the real-time oxygenation is lower than 10% of the lower limit of the baseline oxygenation range, it is determined that there is an abnormal blood perfusion indicator. The trend prediction submodule (302c) predicts the blood perfusion change trend in the next 30 minutes based on the blood flow velocity and oxygenation data of the past hour; the early warning module (303) is connected to the data analysis module (302), and generates an early warning signal when the abnormality detection submodule (302b) detects an abnormal blood perfusion index, or when the trend prediction submodule (302c) predicts that the future blood flow velocity or oxygenation will be lower than a preset threshold, and displays a red alarm on the bedside display screen (400), and sends a text message alarm containing the patient's name, bed number, warning type and severity information to the medical staff's mobile terminal through the wireless notification module (401). The present invention can timely detect and predict abnormal flap blood perfusion, reducing the workload of medical staff.

[0040] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0042] Figure 1 A schematic diagram showing the flow of a bedside flap blood flow monitoring and early warning device according to an embodiment of the present invention is shown;

[0043] Figure 2 A schematic diagram showing the framework of a bedside flap blood flow monitoring and early warning device according to an embodiment of the present invention is shown;

[0044] Figure 3 A schematic structural diagram of a computing device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0045] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0046] Figure 1 The following is a flow chart showing the process of the bedside flap blood flow monitoring and early warning device according to an embodiment of the present invention. Figure 2 FIG. 1 shows a schematic diagram of a bedside flap blood flow monitoring and early warning device according to an embodiment of the present invention. Figure 1 、 Figure 2 As shown, including:

[0047] A flap tissue perfusion monitoring module (100) comprises a probe housing (103), a microcirculation blood flow velocity sensor (101), a tissue oxygenation sensor (102) and a flexible connecting arm (104); wherein the probe housing (103) is made of a biocompatible material and has an arc-shaped contact surface for fitting the flap surface; the microcirculation blood flow velocity sensor (101) is built into the probe housing (103) for measuring the microcirculation blood flow velocity of the flap tissue in real time and generating corresponding blood flow velocity data; the tissue oxygenation sensor (102) is built into the probe housing (103) for measuring the tissue oxygenation of the flap tissue in real time and generating corresponding oxygenation data; one end of the flexible connecting arm (104) is connected to the probe housing (103), and the other end is connected to a bedside support rod (500) via a universal joint (105) for adjusting and fixing the position of the probe housing (103);

[0048] A data acquisition and transmission module (200) is connected to the flap tissue perfusion monitoring module (100), receives the blood flow velocity data and oxygenation data via a data line, and performs analog-to-digital conversion and data packaging;

[0049] The central processing unit (300) includes a data storage module (301), a data analysis module (302) and an early warning module (303); the data storage module (301) is used to store the received monitoring data; the data analysis module (302) includes a baseline establishment submodule (302a), an abnormality detection submodule (302b) and a trend prediction submodule (302c); wherein the baseline establishment submodule (302a) is used to calculate the patient's individualized baseline blood flow parameter range based on normal skin blood flow data near the flap; the abnormality detection submodule (302b) is used to compare the real-time monitoring data with the baseline blood flow parameter range, and when the real-time blood flow velocity is lower than 15% of the lower limit of the baseline blood flow velocity range or the real-time oxygenation is lower than 10% of the lower limit of the baseline oxygenation range, it is determined that an abnormal blood perfusion index exists; the trend prediction submodule (302c) predicts the blood perfusion change trend in the next 30 minutes based on the blood flow velocity and oxygenation data of the past hour;

[0050] The early warning module (303) is connected to the data analysis module (302), and generates an early warning signal when the abnormal detection submodule (302b) detects an abnormal blood perfusion index, or when the trend prediction submodule (302c) predicts that the future blood flow velocity or oxygenation will be lower than a preset threshold, and displays a red alarm through the bedside display screen (400), and sends a text message alarm containing the patient's name, bed number, warning type and severity information to the medical staff's mobile terminal through the wireless notification module (401).

[0051] In this embodiment, continuous and objective monitoring of flap blood perfusion is achieved through built-in microcirculation blood flow velocity sensors and tissue oxygenation sensors, overcoming the subjectivity and instantaneousness of traditional methods. An individualized baseline blood flow parameter range is established based on normal skin blood flow data near the flap to avoid misjudgments due to individual differences. The data analysis module performs abnormality detection and trend prediction based on the set threshold, generates early warning signals in a timely manner, and notifies medical staff. The flexible connecting arm and bedside support rod make it easy to adjust and fix the position of the probe so that it can fit the surface of the flap. Different levels of early warning correspond to different response measures to ensure a rapid response to critical situations. The wireless notification module sends the early warning information to the medical staff's mobile terminal. At the same time, its blood flow data can be summarized and displayed as a waveform on the computer screen at the nurse station, making it convenient for medical staff to remotely monitor the patient's blood perfusion. The above-mentioned integrated design reduces the difficulty of operation and is easy to promote and use in clinical practice.

[0052] Specifically, the flap tissue perfusion monitoring module (100) manufactures a probe housing (103) based on a biocompatible material (such as medical silicone) to ensure good contact with the skin and reduce allergic reactions. The microcirculation blood flow velocity sensor (101) (laser Doppler sensor) and the tissue oxygenation sensor (102) (near infrared spectroscopy sensor) are built into the probe housing (103). The flexible connecting arm (104) adjusts the length and curvature as needed, and the universal joint (105) achieves multi-angle adjustment, making it convenient to fix the probe in a suitable position. The data acquisition and transmission module (200) uses an analog-to-digital converter (ADC) to convert the blood flow velocity data and oxygenation data into digital signals, and transmits the data to the central processing unit (300) via a data line (such as USB or Bluetooth). The baseline establishment submodule (302a) calculates the individualized baseline blood flow parameter range, the abnormality detection submodule (302b) determines whether there is an abnormal blood perfusion index based on the cumulative sum control chart, and the trend prediction submodule (302c) uses a chaotic prediction formula based on phase space and Lyapunov exponent to predict the future blood perfusion change trend. The early warning module (303) generates different levels of early warning signals based on the results of the abnormality detection submodule (302b) and the trend prediction submodule (302c), displays the early warning information on the bedside display screen (400), and sends a text message alert to the medical staff's mobile terminal through the wireless notification module (401). The bedside display screen (400) uses an LCD or LED display screen to display blood flow velocity, oxygenation, trend curve, blood perfusion change trend and early warning information in real time, making it convenient for medical staff to view and operate. For example, a patient undergoes lower limb flap repair surgery and uses the device for blood flow monitoring after the surgery. The baseline establishment submodule (302a) calculates the patient's baseline blood flow velocity range of 50-70 ml / min and the baseline oxygenation range of 60-80% based on the normal skin blood flow data near the flap. On the third day after the surgery, the abnormality detection submodule (302b) detects that the patient's real-time blood flow velocity has dropped to 40 ml / min, which is 15% lower than the lower limit of the baseline blood flow velocity range (i.e., 50×0.85=42.5 ml / min). The early warning module (303) generates a yellow early warning signal, and the bedside display (400) flashes a yellow light accompanied by a prompt sound and sends a prompt message to the medical staff's mobile terminal through the wireless notification module (401). After receiving the early warning message, the medical staff immediately examined the patient and found that the flap blood vessels were slightly twisted. After treatment, the patient's blood flow velocity returned to normal, avoiding flap necrosis. Although the current blood flow rate has only slightly decreased, the trend prediction submodule (302c) predicts that the blood flow rate will drop to 30% of the baseline (ie, below 21 ml / min) within the next 30 minutes.Predicting a significant decrease in blood flow velocity, the intelligent graded warning unit (303d) automatically upgraded the warning to orange. The bedside device activated an audible and visual alarm and simultaneously sent a report containing a trend chart of the patient's historical monitoring data to the nursing station console. Upon receiving the upgraded warning and report, medical staff immediately took more proactive intervention measures (such as adjusting body position and administering vasodilators), ultimately preventing blood perfusion collapse.

[0053] In an optional manner, the bedside display screen (400) is connected to the central processing unit (300) for displaying blood flow velocity, oxygenation, trend curve, blood perfusion change trend and warning information in real time;

[0054] The wireless notification module (401) is connected to the central processing unit (300) and is used to send warning information to the mobile terminal of medical staff through the mobile communication network.

[0055] In this embodiment, the changing trends of blood perfusion are displayed in the form of trend curves. In addition to blood flow parameters, warning information is also displayed. This allows bedside medical staff to directly observe and make decisions, eliminating the need to query data elsewhere, thus improving response speed. Furthermore, warning information can be sent to medical staff immediately, allowing them to understand the situation in a timely manner even if they are not at the bedside.

[0056] In an optional manner, the flexible connecting arm (104) includes a proximal fixing module, a middle adjustable module and a distal probe connecting module;

[0057] wherein the proximal fixing module is fixed to the universal joint (105) via a C-shaped clamp having a ratchet locking mechanism;

[0058] The intermediate adjustable module is composed of three joint units of the same structure connected in series, each joint unit comprising two fork-shaped arms made of polyamide material, the fork-shaped arms being connected by a ball stud, each ball stud being equipped with a locking nut for fixing the angle of the joint; the joint units are connected by a locking mechanism comprising a buckle and a release button, and the joint units are disassembled or assembled by pressing the release button to adjust the length and curvature of the flexible connecting arm (104);

[0059] The distal probe connection module is composed of a groove matching the shape of the probe housing (103) and a locking mechanism.

[0060] In this embodiment, three joint units are connected in series, each with adjustable angles, providing a high degree of bending freedom and facilitating adjustments to the flexible arm's posture. Attaching and detaching the joint units via snaps and release buttons allows for easy adjustment of the flexible arm's length to accommodate varying operating spaces.

[0061] In an optional manner, the universal joint (105) includes a base, a rotation axis, a pitch axis and a roll axis;

[0062] The base is fixed to the top of the bedside support rod (500) by four bolts, and the rotating shaft is connected to the base by a ball bearing; the pitch axis is a U-shaped bracket, which is connected to the rotating shaft by two hinges; a locking screw is installed in the middle of the pitch axis to fix the pitch angle; the roll axis is connected to the pitch axis by two hinges, and the top of the roll axis is connected to the proximal fixing module of the flexible connecting arm (104).

[0063] In this embodiment, the rotation axis, pitch axis and roll axis provide three rotational degrees of freedom, supporting the flexible connecting arm (104) to adjust its posture in three-dimensional space, and can flexibly point the probe to different directions and angles. The locking screw of the pitch axis fixes the pitch angle to prevent accidental changes in the angle during operation. For example, the monitor bracket next to the bed is fixed to the support rod beside the bed with four bolts. The rotation axis supports the monitor to rotate 360 ​​degrees horizontally, which is convenient for doctors to observe from different angles. The pitch axis adjusts the tilt angle of the monitor screen to adapt to medical staff of different heights and sitting postures. The roll axis adjusts the horizontal direction of the monitor screen. Medical staff can easily adjust the various axes of the universal joint to adjust the monitor screen to the best viewing position.

[0064] In an optional manner, the probe housing (103) includes an upper shell and a lower shell;

[0065] The upper shell is provided with heat dissipation holes; the lower shell contacts the skin flap, the surface of the lower shell is coated with biocompatible hydrogel, and the interior of the lower shell is provided with a sensor fixing structure for fixing the microcirculation blood flow velocity sensor (101) and the tissue oxygenation sensor (102) to ensure contact between the sensor and the skin flap tissue; the microcirculation blood flow velocity sensor (101) and the tissue oxygenation sensor (102) are connected to the data acquisition and transmission module (200) through a connector; the edge of the probe housing (103) is chamfered, and the bottom of the probe housing (103) is provided with multiple micro suction cups to enhance the adsorption force with the skin flap surface.

[0066] In this embodiment, the heat dissipation holes of the upper shell dissipate the heat generated inside the probe, reducing the temperature of the sensor and electronic components. The lower shell is coated with biocompatible hydrogel to reduce irritation and allergic reactions when the probe contacts the skin. The internal sensor fixing structure ensures that the microcirculation blood flow velocity sensor and the tissue oxygenation sensor maintain stable contact with the flap tissue. The chamfered edges and the bottom micro suction cup enhance the adsorption force between the probe and the flap surface. Among them, the upper and lower shells are made of lightweight, durable plastic (ABS, PC) or metal (aluminum alloy), and the upper and lower shells are connected by means of snaps, screws or adhesives. The hydrogel includes polyvinyl alcohol (PVA), polyacrylamide (PAM) and hyaluronic acid.

[0067] In an optional manner, the bedside support rod (500) includes a base, an inner rod, an outer rod, a locking mechanism, and a top connector;

[0068] The base is provided with four universal wheels; the inner rod slides inside the outer rod and the height is adjusted by a locking mechanism; the top connecting piece of the locking mechanism is connected to the universal joint (105) by a threaded connection.

[0069] In this embodiment, the inner rod slides within the outer rod and adjusts its height via a locking mechanism to accommodate patients of varying heights. The locking mechanism and threaded connection ensure stable and reliable height locking of the support rod. The top connector is threaded to the universal joint, allowing for easy adjustment of the connection angle to accommodate the installation of various devices or accessories.

[0070] In an optional manner, the abnormality detection submodule (302b) determines whether there is an abnormal blood perfusion indicator based on the cumulative sum control diagram;

[0071] Specifically, the upper limit and lower limit of the cumulative sum are calculated based on the blood flow velocity at time t, the baseline blood flow velocity, and the drift amount;

[0072] If the upper limit of the cumulative sum is greater than the preset control limit or the lower limit of the cumulative sum is less than the negative preset control limit, it is determined that an abnormal blood perfusion index exists;

[0073] The calculation formula for the upper limit of the cumulative sum is:

[0074] S H (t)=max(0,S H (t-1)+(y t -μ0)-k)

[0075] The calculation formula for the lower limit of the cumulative sum is:

[0076] S L (t)=min(0,S L (t-1)+(yt -μ0)+k)

[0077] Among them, y t is the blood flow velocity at time t; μ0 is the baseline blood flow velocity; k is the allowed drift, σ is the standard deviation of baseline blood velocity.

[0078] In this embodiment, the CUSUM control chart method is highly sensitive to small, sustained deviations. By amplifying the signal through accumulated deviations, even small drifts can be detected. Because the CUSUM control chart method can detect changes earlier, it can provide earlier warnings, creating opportunities for timely intervention. More importantly, the CUSUM control chart method does not require extensive historical data; only baseline blood flow velocity and standard deviation are required for anomaly detection, making it easy to deploy in real-world applications.

[0079] In an optional manner, the trend prediction submodule (302c) adopts a chaos prediction formula based on phase space and Lyapunov exponent, and the chaos prediction formula is:

[0080]

[0081] Among them, k is the number of recent data points involved in the prediction; T is the prediction step size; y t is the blood flow velocity at past time t; λ is the Lyapunov exponent, t0 is the starting point for eliminating transient effects; X t is point t in the phase space, X t =[y t ,y t+τ ,y t+2 τ,…,y t+(m-1)τ ], τ is the time delay, τ=argmin τ MI(y t ,y t+τ ); MI is the mutual information function; m is the dimension, which is calculated by the false nearest neighbor method; N is the quantization parameter.

[0082] In this embodiment, blood flow velocity is affected by multiple factors and exhibits nonlinear variations. The chaos prediction method, based on phase space reconstruction and the Lyapunov exponent, is capable of predicting short-term trends in blood flow velocity. The Lyapunov exponent reflects the degree of chaos in the system, reducing the impact of noise on the prediction results. Furthermore, only a small amount of historical data is required for prediction, reducing the cost and difficulty of data acquisition.

[0083] Specifically, the one-dimensional time series data (blood flow velocity) is reconstructed into a multi-dimensional phase space, and the mutual information function MI(y t ,y t+τ)Calculate the time series y t and y t+τ The mutual information between the two points is calculated, and the time delay τ is selected as the time delay that causes the mutual information to reach a local minimum for the first time. The false nearest neighbors (FNN) method is used to determine the embedding dimension. When the number of false nearest neighbors is lower than a certain threshold, the corresponding embedding dimension is considered the optimal embedding dimension. Each point in the phase space represents the state at a certain moment. For example, the time series data is blood flow velocity data for the past hour, collected once a minute. The time delay is calculated using the mutual information function (5 minutes). The embedding dimension (m) is calculated using the false nearest neighbor method to obtain m = 3. The Lyapunov exponent is calculated to obtain λ = 0.1. The number of nearest data points k = 20. The blood flow velocity prediction value for the next 10 minutes is calculated according to the above chaotic prediction formula.

[0084] In an optional manner, the warning module (303) further comprises an intelligent graded warning unit (303d), and the intelligent graded warning unit (303d) performs a dynamic evolution graded warning according to hemodynamic parameters;

[0085] When the blood flow velocity drops by more than 15% of the baseline or the oxygenation level drops by more than 10% of the baseline, a yellow warning signal is triggered, the bedside display screen (400) flashes a yellow light accompanied by a warning sound, and sends a warning message to the medical staff's mobile terminal through the wireless notification module (401);

[0086] When the abnormal state lasts for more than 5 minutes or the trend prediction submodule (302c) predicts that the blood flow velocity will be 30% lower than the baseline in the next 10 minutes, it will automatically upgrade to an orange warning, the bedside device will start the sound and light linkage alarm, and push a report containing the patient's historical monitoring data trend chart to the nursing station console;

[0087] When the real-time blood flow velocity is lower than 50% of the baseline or an imminent blood perfusion collapse is predicted, a red critical warning is immediately triggered, the sound and light alarm system of the entire ward is activated, and the monitoring data chain before and after the event is recorded as medical evidence.

[0088] In this embodiment, the dynamic evolution graded warning system not only considers whether current hemodynamic parameters exceed thresholds but also considers the duration of the abnormal state and future trends, thereby enhancing the sensitivity of the warning. Besides audible and visual alarms, the system also provides timely information to medical staff through wireless notifications and push notifications, and provides trend charts of historical patient data, helping them quickly understand the patient's condition progression. The trend prediction submodule enables early detection of potential risks, allowing for more time for intervention.

[0089] According to the solution provided by the present invention, it comprises: a flap tissue perfusion monitoring module (100), comprising a probe housing (103), a microcirculation blood flow velocity sensor (101), a tissue oxygenation sensor (102) and a flexible connecting arm (104); wherein the probe housing (103) is made of a biocompatible material and has an arc-shaped contact surface for fitting the flap surface; the microcirculation blood flow velocity sensor (101) is built into the probe housing (103) for real-time measurement of the microcirculation blood flow velocity of the flap tissue and generation of corresponding blood flow velocity data; the tissue oxygenation sensor (102) is built into the probe housing (103) for real-time measurement of the microcirculation blood flow velocity of the flap tissue and generation of corresponding blood flow velocity data. The flexible connecting arm (104) is connected to the probe housing (103) at one end and connected to the bedside support rod (500) via a universal joint (105) at the other end for adjusting and fixing the position of the probe housing (103); a data acquisition and transmission module (200) is connected to the flap tissue perfusion monitoring module (100), receives the blood flow velocity data and oxygenation data via a data line, and performs analog-to-digital conversion and data packaging; a central processing unit (300) includes a data storage module (301), a data analysis module (302) and an early warning module (303); the data storage module The block (301) is used to store the received monitoring data; the data analysis module (302) includes a baseline establishment submodule (302a), an abnormality detection submodule (302b) and a trend prediction submodule (302c); wherein the baseline establishment submodule (302a) is used to calculate the patient's individualized baseline blood flow parameter range based on the normal skin blood flow data near the flap; the abnormality detection submodule (302b) is used to compare the real-time monitoring data with the baseline blood flow parameter range, and when the real-time blood flow velocity is lower than 15% of the lower limit of the baseline blood flow velocity range or the real-time oxygenation is lower than 10% of the lower limit of the baseline oxygenation range, it is determined that there is an abnormal blood perfusion indicator. The trend prediction submodule (302c) predicts the blood perfusion change trend in the next 30 minutes based on the blood flow velocity and oxygenation data of the past hour; the early warning module (303) is connected to the data analysis module (302), and generates an early warning signal when the abnormality detection submodule (302b) detects an abnormal blood perfusion index, or when the trend prediction submodule (302c) predicts that the future blood flow velocity or oxygenation will be lower than a preset threshold, and displays a red alarm on the bedside display screen (400), and sends a text message alarm containing the patient's name, bed number, warning type and severity information to the medical staff's mobile terminal through the wireless notification module (401). The present invention can timely detect and predict abnormal flap blood perfusion, reducing the workload of medical staff.

[0090] Figure 3The schematic diagram of the structure of the computing device embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0091] like Figure 3 As shown, the computing device may include: a processor 302 , a communications interface 304 , a memory 306 , and a communication bus 308 .

[0092] Processor 302, communication interface 304, and memory 306 communicate with each other via communication bus 308. Communication interface 304 is used to communicate with other devices, such as client devices or other server network elements. Processor 302 is used to execute program 310, which specifically performs the steps described in the aforementioned embodiment of the bedside flap blood flow monitoring and early warning device.

[0093] Specifically, the program 310 may include program codes, which include computer operation instructions.

[0094] Processor 302 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in a computing device may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0095] The memory 306 is used to store the program 310. The memory 306 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0096] According to the solution provided by the present invention, it comprises: a flap tissue perfusion monitoring module (100), comprising a probe housing (103), a microcirculation blood flow velocity sensor (101), a tissue oxygenation sensor (102) and a flexible connecting arm (104); wherein the probe housing (103) is made of a biocompatible material and has an arc-shaped contact surface for fitting the flap surface; the microcirculation blood flow velocity sensor (101) is built into the probe housing (103) for real-time measurement of the microcirculation blood flow velocity of the flap tissue and generation of corresponding blood flow velocity data; the tissue oxygenation sensor (102) is built into the probe housing (103) for real-time measurement of the microcirculation blood flow velocity of the flap tissue and generation of corresponding blood flow velocity data. The flexible connecting arm (104) is connected to the probe housing (103) at one end and connected to the bedside support rod (500) via a universal joint (105) at the other end for adjusting and fixing the position of the probe housing (103); a data acquisition and transmission module (200) is connected to the flap tissue perfusion monitoring module (100), receives the blood flow velocity data and oxygenation data via a data line, and performs analog-to-digital conversion and data packaging; a central processing unit (300) includes a data storage module (301), a data analysis module (302) and an early warning module (303); the data storage module The block (301) is used to store the received monitoring data; the data analysis module (302) includes a baseline establishment submodule (302a), an abnormality detection submodule (302b) and a trend prediction submodule (302c); wherein the baseline establishment submodule (302a) is used to calculate the patient's individualized baseline blood flow parameter range based on the normal skin blood flow data near the flap; the abnormality detection submodule (302b) is used to compare the real-time monitoring data with the baseline blood flow parameter range, and when the real-time blood flow velocity is lower than 15% of the lower limit of the baseline blood flow velocity range or the real-time oxygenation is lower than 10% of the lower limit of the baseline oxygenation range, it is determined that there is an abnormal blood perfusion indicator. The trend prediction submodule (302c) predicts the blood perfusion change trend in the next 30 minutes based on the blood flow velocity and oxygenation data of the past hour; the early warning module (303) is connected to the data analysis module (302), and generates an early warning signal when the abnormality detection submodule (302b) detects an abnormal blood perfusion index, or when the trend prediction submodule (302c) predicts that the future blood flow velocity or oxygenation will be lower than a preset threshold, and displays a red alarm on the bedside display screen (400), and sends a text message alarm containing the patient's name, bed number, warning type and severity information to the medical staff's mobile terminal through the wireless notification module (401). The present invention can timely detect and predict abnormal flap blood perfusion, reducing the workload of medical staff.

[0097] Those skilled in the art will appreciate that modules in the devices of the embodiments may be adaptively modified and deployed in one or more devices different from the embodiments. Modules, units, or components in the embodiments may be combined into a single module, unit, or component, and furthermore, they may be divided into multiple submodules, subunits, or subcomponents. All features disclosed in this specification (including the accompanying claims, abstract, and drawings), as well as all processes or units of any method or device disclosed therein, may be combined in any combination, except where at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that provides the same, equivalent, or similar purpose. Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in the claims below, any of the claimed embodiments may be used in any combination. The present invention may be implemented using hardware comprising a number of different elements and using a suitably programmed computer. In a unit claim that lists several means, several of these means may be embodied by the same hardware item. Unless otherwise specified, the steps in the above embodiments should not be understood as limiting the order of execution.

Claims

1. A bedside flap blood flow monitoring and early warning device, characterized in that: include: A flap tissue perfusion monitoring module (100) comprises a probe housing (103), a microcirculation blood flow velocity sensor (101), a tissue oxygenation sensor (102) and a flexible connecting arm (104); wherein the probe housing (103) is made of a biocompatible material and has an arc-shaped contact surface for fitting the flap surface; the microcirculation blood flow velocity sensor (101) is built into the probe housing (103) for measuring the microcirculation blood flow velocity of the flap tissue in real time and generating corresponding blood flow velocity data; the tissue oxygenation sensor (102) is built into the probe housing (103) for measuring the tissue oxygenation of the flap tissue in real time and generating corresponding oxygenation data; one end of the flexible connecting arm (104) is connected to the probe housing (103), and the other end is connected to a bedside support rod (500) via a universal joint (105) for adjusting and fixing the position of the probe housing (103); A data acquisition and transmission module (200) is connected to the flap tissue perfusion monitoring module (100), receives the blood flow velocity data and oxygenation data via a data line, and performs analog-to-digital conversion and data packaging; The central processing unit (300) includes a data storage module (301), a data analysis module (302) and an early warning module (303); the data storage module (301) is used to store the received monitoring data; the data analysis module (302) includes a baseline establishment submodule (302a), an abnormality detection submodule (302b) and a trend prediction submodule (302c); wherein the baseline establishment submodule (302a) is used to calculate the patient's individualized baseline blood flow parameter range based on normal skin blood flow data near the flap; the abnormality detection submodule (302b) is used to compare the real-time monitoring data with the baseline blood flow parameter range, and when the real-time blood flow velocity is lower than 15% of the lower limit of the baseline blood flow velocity range or the real-time oxygenation is lower than 10% of the lower limit of the baseline oxygenation range, it is determined that an abnormal blood perfusion index exists; the trend prediction submodule (302c) predicts the blood perfusion change trend in the next 30 minutes based on the blood flow velocity and oxygenation data of the past hour; The early warning module (303) is connected to the data analysis module (302), and generates an early warning signal when the abnormal detection submodule (302b) detects an abnormal blood perfusion index, or when the trend prediction submodule (302c) predicts that the future blood flow velocity or oxygenation will be lower than a preset threshold, and displays a red alarm through the bedside display screen (400), and sends a text message alarm containing the patient's name, bed number, warning type and severity information to the medical staff's mobile terminal through the wireless notification module (401).

2. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The bedside display screen (400) is connected to the central processing unit (300) and is used to display blood flow velocity, oxygenation, trend curve, blood perfusion change trend and warning information in real time; The wireless notification module (401) is connected to the central processing unit (300) and is used to send warning information to the mobile terminal of medical staff through the mobile communication network.

3. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The flexible connecting arm (104) comprises a proximal fixing module, a middle adjustable module and a distal probe connecting module; wherein the proximal fixing module is fixed to the universal joint (105) via a C-shaped clamp having a ratchet locking mechanism; The intermediate adjustable module is composed of three joint units of the same structure connected in series, each joint unit comprising two fork-shaped arms made of polyamide material, the fork-shaped arms being connected by a ball stud, each ball stud being equipped with a locking nut for fixing the angle of the joint; the joint units are connected by a locking mechanism comprising a buckle and a release button, and the joint units are disassembled or assembled by pressing the release button to adjust the length and curvature of the flexible connecting arm (104); The distal probe connection module is composed of a groove matching the shape of the probe housing (103) and a locking mechanism.

4. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The universal joint (105) includes a base, a rotation axis, a pitch axis and a roll axis; The base is fixed to the top of the bedside support rod (500) by four bolts, and the rotating shaft is connected to the base by a ball bearing; the pitch axis is a U-shaped bracket, which is connected to the rotating shaft by two hinges; a locking screw is installed in the middle of the pitch axis to fix the pitch angle; the roll axis is connected to the pitch axis by two hinges, and the top of the roll axis is connected to the proximal fixing module of the flexible connecting arm (104).

5. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The probe housing (103) comprises an upper housing and a lower housing; The upper shell is provided with heat dissipation holes; the lower shell contacts the skin flap, the surface of the lower shell is coated with biocompatible hydrogel, and the interior of the lower shell is provided with a sensor fixing structure for fixing the microcirculation blood flow velocity sensor (101) and the tissue oxygenation sensor (102) to ensure contact between the sensor and the skin flap tissue; the microcirculation blood flow velocity sensor (101) and the tissue oxygenation sensor (102) are connected to the data acquisition and transmission module (200) through a connector; the edge of the probe housing (103) is chamfered, and the bottom of the probe housing (103) is provided with multiple micro suction cups to enhance the adsorption force with the skin flap surface.

6. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The bedside support rod (500) comprises a base, an inner rod, an outer rod, a locking mechanism and a top connector; The base is provided with four universal wheels; the inner rod slides inside the outer rod and the height is adjusted by a locking mechanism; the top connecting piece of the locking mechanism is connected to the universal joint (105) by a threaded connection.

7. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The abnormality detection submodule (302b) determines whether there is an abnormal blood perfusion indicator based on the cumulative sum control diagram; Specifically, the upper limit and lower limit of the cumulative sum are calculated based on the blood flow velocity at time t, the baseline blood flow velocity, and the drift amount; If the upper limit of the cumulative sum is greater than the preset control limit or the lower limit of the cumulative sum is less than the negative preset control limit, it is determined that an abnormal blood perfusion index exists; The calculation formula for the upper limit of the cumulative sum is: S H (t)=max(0,S H (t-1)+(y t -μ0)-k) The calculation formula for the lower limit of the cumulative sum is: S L (t)=min(0,S L (t-1)+(y t -μ0)+k) Among them, y t is the blood flow velocity at time t; μ0 is the baseline blood flow velocity; k is the allowed drift, σ is the standard deviation of baseline blood velocity.

8. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The trend prediction submodule (302c) adopts a chaos prediction formula based on phase space and Lyapunov exponent, and the chaos prediction formula is: Among them, k is the number of recent data points involved in the prediction; T is the prediction step size; y t is the blood flow velocity at past time t; λ is the Lyapunov exponent, t0 is the starting point for eliminating transient effects; X t is point t in the phase space, X t =[y t ,y t+τ ,y t+2 τ,…,y t+(m-1)τ ], τ is the time delay, τ=argmin τ MI(y t ,y t+τ ); MI is the mutual information function; m is the dimension, which is calculated by the false nearest neighbor method; N is the quantization parameter.

9. The bedside flap blood flow monitoring and early warning device according to claim 1, characterized in that: The warning module (303) further comprises an intelligent graded warning unit (303d), and the intelligent graded warning unit (303d) performs a dynamic evolution graded warning according to the hemodynamic parameters; When the blood flow velocity drops by more than 15% of the baseline or the oxygenation level drops by more than 10% of the baseline, a yellow warning signal is triggered, the bedside display screen (400) flashes a yellow light accompanied by a warning sound, and sends a warning message to the medical staff's mobile terminal through the wireless notification module (401); When the abnormal state lasts for more than 5 minutes or the trend prediction submodule (302c) predicts that the blood flow velocity will be 30% lower than the baseline in the next 10 minutes, it will automatically upgrade to an orange warning, the bedside device will start the sound and light linkage alarm, and push a report containing the patient's historical monitoring data trend chart to the nursing station console; When the real-time blood flow velocity is lower than 50% of the baseline or an imminent blood perfusion collapse is predicted, a red critical warning is immediately triggered, the sound and light alarm system of the entire ward is activated, and the monitoring data chain before and after the event is recorded as medical evidence.

10. A computing device comprising: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned bedside flap blood flow monitoring and early warning device.

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