Internet of things hemostatic clip positioning system and positioning method

Abstract

The application provides an Internet of Things hemostatic clamp positioning system and a positioning method, wherein the positioning system comprises: an Internet of Things intestinal hemostatic clamp comprising a hemostatic clamp body and a passive UHF RFID tag arranged on the hemostatic clamp body; an extracorporeal reader-writer for being communicatively connected with the Internet of Things intestinal hemostatic clamp, receiving and analyzing radio frequency signals emitted by the passive UHF RFID tag to obtain RFID data information; a client connected with each extracorporeal reader-writer, for receiving and forwarding the RFID data to a server; and the server connected with the client, for analyzing and calculating three-dimensional position information of the Internet of Things intestinal hemostatic clamp in real time based on the RFID data and a preset positioning algorithm, and feeding back the three-dimensional position information to the client. The application can realize real-time high-precision positioning of the hemostatic clamp.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, and in particular to an Internet of Things (IoT) hemostatic clip positioning system and positioning method. Background Technology

[0002] Currently, in clinical medical applications, hemostatic clips are suitable for use with endoscopes. Under endoscopic visualization, clips are placed in the upper and lower digestive tracts to treat bleeding from various causes, such as arterial bleeding, persistent oozing, and bleeding from vascular stumps requiring mechanical hemostasis. However, existing hemostatic clips have the following problems:

[0003] 1. High risk of hemostatic clip dislodgement: Traditional titanium alloy hemostatic clips may dislodge after surgery due to intestinal peristalsis, tissue necrosis or improper operation. They need to be passively discovered through endoscopic re-examination or patient symptoms (such as bleeding, abdominal pain), which poses a risk of delay.

[0004] 2. Lack of monitoring methods: Existing technology lacks real-time, non-invasive methods for monitoring the position of hemostatic clips, making it impossible to predict early detachment;

[0005] 3. Poor patient compliance: Frequent endoscopic re-examinations increase patient suffering and medical costs.

[0006] Therefore, there is an urgent need for an IoT-based hemostatic clip positioning system and method to facilitate real-time and accurate monitoring of the position of the hemostatic clip in the intestine, preventing secondary bleeding or intestinal damage caused by dislodgement. Summary of the Invention

[0007] The purpose of this invention is to provide an Internet of Things (IoT) hemostatic clip positioning system and method, aiming to solve the technical problem that traditional hemostatic clips, due to a lack of monitoring and accurate positioning, cause them to fall off and cause injury to patients.

[0008] To achieve the above objectives, in a first aspect, the present invention provides an Internet of Things (IoT) intestinal hemostasis clip, comprising:

[0009] The hemostatic clip body is biocompatible, with two opposing clamping arms at one end and a micro cavity at the other end.

[0010] A passive UHF RFID tag is adapted and encapsulated within the miniature cavity. Its tag antenna adopts a flexible, deformable, and foldable structure, which is used to identify the position information of the hemostatic clip body through an external reader.

[0011] The outer surface of the other end of the hemostatic clip body is provided with a wave-transmitting window array to enhance the penetration of radio frequency signals, so as to realize the wireless signal interaction between the passive UHF RFID tag and the Internet of Things positioning system.

[0012] As a further improvement to the above solution, the flexible deformable folding structure is a serpentine or zigzag folding layout to adapt to the spatial constraints of the micro cavity and maintain the stability of radio frequency performance.

[0013] As a further improvement to the above solution, the passive UHF RFID tag operates at a frequency of 860-960MHz and is covered with a biocompatible epoxy resin layer.

[0014] As a further improvement to the above scheme, the wave-transparent window array includes at least three wave-transparent units, and the plurality of wave-transparent units are arranged periodically, each wave-transparent unit being made of a low dielectric constant polymer material.

[0015] Secondly, the present invention also provides an Internet of Things (IoT) hemostatic clip positioning system, comprising:

[0016] Such as the Internet of Things intestinal hemostasis clip provided in the first aspect;

[0017] At least three external readers are used to wirelessly communicate with the IoT intestinal hemostasis clip, receive and analyze the radio frequency signals emitted by its passive UHF RFID tag, and obtain RFID data information.

[0018] The client is wirelessly connected to each external reader / writer and is used to receive and forward the RFID data to the server.

[0019] The server connects wirelessly to the client, analyzes and calculates the three-dimensional position information of the IoT intestinal hemostasis clip in real time based on the RFID data and a preset positioning algorithm, and feeds the three-dimensional position information back to the client.

[0020] As a further improvement to the above solution, the at least three external readers are deployed within a preset space, with their antenna directions covering the potential activity area of ​​the IoT intestinal hemostasis clip, and the spatial coordinates of each external reader are known and pre-stored on the server.

[0021] As a further improvement to the above solution, the client includes:

[0022] The data receiving module is used to receive RFID data sent by the external reader / writer;

[0023] The data transmission module transmits RFID data to the server in real time via wired or wireless networks (such as Wi-Fi or 5G).

[0024] The interactive interface module is used to display the 3D location information fed back by the server and supports user operations (such as querying historical tracks and setting warning thresholds).

[0025] As a further improvement to the above solution, the server includes:

[0026] The data storage module is used to store the spatial coordinates, RFID data, and historical positioning results of the external reader / writer;

[0027] The positioning algorithm module, based on the RFID signal arrival time difference (TDOA) and received signal strength (RSSI) of multiple readers and writers, combined with a preset mathematical model, calculates the three-dimensional coordinates (x, y, z) and direction of movement of the IoT intestinal hemostasis clip;

[0028] The early warning module sends an early warning command to the client when the three-dimensional location information exceeds a preset safety range or when the RSSI value of the RFID data drops sharply.

[0029] As a further improvement to the above scheme, the client and the server interact with each other via HTTP / HTTPS protocol or MQTT message queue, and the update frequency of the three-dimensional position information is ≥1Hz.

[0030] Thirdly, the present invention also provides a positioning method for an Internet of Things hemostatic clip positioning system as provided in the second aspect, the steps of which include:

[0031] The RFID data information is obtained by receiving and parsing the radio frequency signals emitted by the passive UHF RFID tag of the Internet of Things intestinal hemostasis clip through at least three external readers that are asymmetrically distributed along the intestinal anatomical path.

[0032] Based on the RFID data, the real-time three-dimensional position and direction of movement of the IoT intestinal hemostasis clip are calculated using the RSSI-TDOA fusion algorithm.

[0033] Based on the three-dimensional position and direction of movement of the hemostatic clip, and / or the RFID data, it is determined whether the IoT intestinal hemostatic clip is abnormal, and if abnormal, an early warning message is issued.

[0034] As a further improvement to the above scheme, the method for calculating the real-time position and movement direction of the hemostatic clip using the RSSI-TDOA fusion algorithm is as follows:

[0035] S1. The received signal strength indicator (RSSI) in the RFID data is calibrated based on the signal strength-distance model;

[0036] The time difference of arrival (TDOA) in the RFID data is obtained using the double-sided two-way ranging (DS-TWR) method.

[0037] S2. Based on the calibrated RSSI, obtain the distance estimate between the hemostatic clip and each reader / writer to determine the preliminary location area of ​​the hemostatic clip;

[0038] S3. Within the initial location area, the time difference of the measurement signal reaching each external reader is calculated using TDOA, and then the time difference is converted into a distance difference. Based on the distance difference, a hyperbolic equation system is established, and the initial three-dimensional coordinates of the hemostatic clip are obtained by solving the hyperbolic equation system.

[0039] S4. Based on the weighted fusion of RSSI and TDOA results using Kalman filtering, obtain the corrected coordinates (x, y, z) and direction of movement of the hemostatic clip in three-dimensional space.

[0040] As a further improvement to the above scheme, the signal strength-distance model is specifically shown in the following equation:

[0041]

[0042] Wherein, α is the fat attenuation coefficient (preferably, α=0.35), β is the muscle attenuation coefficient (preferably, β=0.02), d is the straight-line distance from the reader to the hemostatic clip (cm), and C is the body position compensation constant.

[0043] As a further improvement to the above scheme, the method for establishing the hyperbola equation system based on the distance difference in step S3 is as follows:

[0044] S31. Calculate the time difference between any two external readers, as shown in the following formula:

[0045] ;

[0046] Where c is the equivalent propagation speed of electromagnetic waves in human tissue (approximately 1.5 × 10⁻⁶). 8 m / s), (x,y,z) are the coordinates of the hemostasis clip, (x i ,y i ,z i Let (x) be the coordinates of one of the external readers / writers. j ,y j ,z j () represents the coordinates of another external reader / writer;

[0047] S32. Obtain the distance difference between any two external readers, as shown in the following formula:

[0048] ;

[0049] S33. Obtain the system of hyperbolic equations. Taking external reader i as the reference point, form hyperbolas with external readers j and k respectively, as shown below:

[0050] .

[0051] As a further improvement to the above scheme, the method for obtaining the corrected coordinates (x, y, z) of the hemostatic clip in three-dimensional space in step S4 is as follows:

[0052] The initial location region obtained by RSSI positioning and the initial three-dimensional coordinates obtained by TDOA positioning are fused by Kalman Filter (KF). Taking advantage of the complementary error characteristics of the two (RSSI is sensitive to dynamic changes in the environment but has strong global stability, while TDOA has high ranging accuracy but depends on time synchronization), the high-precision three-dimensional corrected coordinate movement direction is output through state estimation and observation update.

[0053] As a further improvement to the above solution, determining whether the IoT intestinal hemostasis clip is abnormal specifically includes at least one of the following situations:

[0054] Abnormal displacement: The cumulative displacement exceeds the safety threshold (e.g., 5cm) and continues for more than the preset time (e.g., 10 minutes);

[0055] Abnormal displacement direction: The displacement direction angle θ deviates from the normal movement direction of the intestinal anatomical path (such as the ascending direction of descending colon to rectum) by more than a preset angle (such as ±30°);

[0056] Abnormal signal strength: A sudden drop in the RSSI value of RFID data (e.g., RSSI drops from -60dBm to below -90dBm within 1 minute) indicates that the hemostatic clip has entered the shielded area (e.g., it has been expelled from the body or detached from the intestines).

[0057] As a further improvement to the above solution, the issuance of early warning information specifically includes:

[0058] Push warning instructions to the client that include the anomaly type (displacement / direction / signal strength), anomaly timestamp, and suggested handling measures;

[0059] The suggested handling measures are dynamically generated based on the type of abnormality. For example, when the displacement is abnormal, the prompt is "Check the fixation status of the hemostatic clip"; when the signal strength is abnormal, the prompt is "Confirm whether the hemostatic clip has been removed".

[0060] Because the present invention adopts the above technical solutions, the beneficial effects of this application are as follows:

[0061] 1. This invention provides an IoT-based intestinal hemostatic clip. By integrating a passive UHF RFID tag within a miniature cavity of the clip body and combining it with an external IoT positioning system, a wireless interactive link of "tag-reader-system" is constructed. This allows for real-time acquisition of the clip's spatial location information and status parameters (such as the trend of tag signal strength changes). Medical personnel continuously track the clip's position through the backend system. When abnormal displacement (such as exceeding a preset safety range) or a sudden drop in signal strength (indicating potential detachment) is detected, timely intervention measures (such as endoscopic repositioning or secondary hemostasis) can be taken, fundamentally eliminating the risk of secondary bleeding and significantly improving postoperative patient safety.

[0062] In addition, the present invention uses an antenna with a flexible, deformable, and foldable structure. Its material has a similar elastic modulus to the biocompatible polymer material of the hemostatic clip body. During intestinal peristalsis, it can deform synchronously with the clamping arm, avoiding antenna breakage due to stress concentration.

[0063] The intestinal environment contains a large amount of water (approximately 75% water content), mucus, and soft tissue, which strongly attenuates UHF radio frequency signals. Traditional single antenna structures are difficult to effectively identify hemostatic clips deep within the body (such as the colon) (the conventional identification distance is <10cm). This invention sets a wave-transmitting window array (composed of multiple regularly arranged microwave transmission windows, made of biocompatible ceramic or high-transparency polymer composite material) on the outer surface of the hemostatic clip body, and improves signal penetration through the following mechanism.

[0064] Multipath transmission: The array-distributed transparent windows break the directional limitation of a single window, allowing radio frequency signals to enter from multiple angles and reducing signal loss caused by intestinal wall blockage;

[0065] Impedance matching: The dielectric constant of the transparent window material forms a gradient match with the intestinal tissue, reducing interface reflection and improving signal transmittance;

[0066] Enhanced Focusing: By optimizing the size and spacing of the transparent window, an electromagnetic wave focusing effect can be formed in the direction of the tag antenna, concentrating the signal energy on the target area and extending the effective identification distance to 20-30cm (covering most of the colorectal area);

[0067] This setup enables the external reader to quickly and accurately acquire the position information of the hemostatic clip during colonoscopy or postoperative follow-up, meeting the needs of real-time clinical monitoring.

[0068] This invention employs a passive UHF RFID tag (powered by the radio frequency field of an external reader), eliminating the need for a built-in battery and avoiding the failure risks associated with traditional active tags due to battery leakage or depletion. It also reduces the size and weight of the hemostatic clip, minimizing mechanical pressure on intestinal tissue. Through its integration with IoT technology, this invention offers significant advantages in real-time monitoring, signal reliability, biosafety, and clinical applicability. It effectively addresses the technical challenges of traditional intestinal hemostatic clips, such as the inability to monitor position and their tendency to detach, leading to secondary bleeding. This provides a safer and smarter solution for the treatment of intestinal hemorrhage.

[0069] 2. This invention also provides an IoT-based hemostatic clip positioning system. This invention utilizes an external passive UHF RFID reader / writer for wireless interaction with the hemostatic clip tag, enabling real-time acquisition of the hemostatic clip's location information without contact with the human body or the use of radioactive equipment. Medical personnel only need to place three or more readers / writers on the patient's body surface (covering the surgical area) to complete positioning via wireless signals (such as the 900MHz band), completely avoiding invasive procedures and radiation risks. This is particularly suitable for long-term postoperative monitoring scenarios (such as when patients require multiple follow-up examinations or home observation). This invention employs at least three external readers / writers (preferably distributed in a triangle or ring on the patient's body surface), combined with a pre-set positioning algorithm on the server side (such as a weighted centroid method based on signal strength, a time difference of arrival algorithm, or a hybrid positioning algorithm), to accurately calculate the three-dimensional coordinates of the hemostatic clip, thereby achieving high-precision positioning of the hemostatic clip.

[0070] This invention achieves fully automated flow of positioning data through a wireless communication link of "hemostatic clip-reader-client-server," significantly reducing the operational burden on medical staff. It employs passive UHF RFID tags (powered by the reader's radio frequency field), eliminating the need for built-in batteries and avoiding the failure risk of traditional active positioning devices due to battery depletion. Furthermore, the distributed deployment of multiple readers further enhances the system's robustness. Additionally, the positioning system transforms the hemostatic clip from a "passive hemostasis tool" into an "active monitoring and positioning node," and its deep integration with electronic medical record (EMR) systems and surgical navigation systems can further expand clinical application scenarios. The IoT hemostatic clip positioning system provided by this invention effectively solves the technical pain points of traditional hemostatic clip positioning—relying on invasive examinations, high radiation risks, and poor real-time performance—through multi-reader collaborative positioning, wireless data interaction, and cloud-based intelligent computation. It has significant advantages in improving diagnostic and treatment safety, efficiency, and accuracy, providing an intelligent, full-cycle solution for the treatment of intestinal bleeding disorders.

[0071] 3. This invention also provides a method for locating IoT-enabled intestinal hemostatic clips. Through a combination of asymmetric reader layout, RSSI-TDOA fusion algorithm, and intelligent anomaly detection, it overcomes the technical bottlenecks of traditional hemostatic clip positioning, which relies on invasive examinations, lacks accuracy, and has poor real-time performance. This method offers significant advantages in positioning reliability, dynamic monitoring capabilities, and timely risk warning. Specifically, at least three external readers are asymmetrically distributed along the intestinal anatomical path (e.g., with the surgical wound as the center, reader 1 is located 5cm above the umbilicus on the abdominal midline, reader 2 is located at the corresponding surface position of the 12th thoracic vertebra, and reader 3 is located 10cm medial to the right anterior superior iliac spine), forming an "anterior-posterior-lateral" three-dimensional coverage network. This layout avoids signal attenuation caused by intestinal peristalsis or intestinal gas obstruction from a single reader. This invention ensures that the hemostatic clip is captured by at least two readers in each segment of the intestine (especially in curved and folded areas), providing multi-dimensional data support for the RSSI and TDOA algorithms. A fusion algorithm is employed, combining the distance estimate from RSSI with the spatial geometric constraints of TDOA through Kalman filtering, leveraging their complementarity to reduce the systematic error of a single algorithm. The IoT-based intestinal hemostatic clip positioning method provided by this invention, through asymmetric reader layout, RSSI-TDOA fusion algorithm, and intelligent anomaly detection, effectively solves the technical pain points of traditional positioning methods, such as insufficient accuracy, poor real-time performance, and high radiation risk. It demonstrates significant advantages in improving positioning reliability, dynamic monitoring capabilities, and the timeliness of risk warnings, providing an intelligent, full-cycle solution for the treatment of intestinal hemorrhagic diseases. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0073] Figure 1 This is a schematic diagram of the structure of an IoT intestinal hemostasis clip disclosed in this invention;

[0074] Figure 2 This is a schematic diagram of the structure of an Internet of Things hemostatic clip positioning system disclosed in this invention;

[0075] Figure 3 This is a schematic diagram of the positioning method of an Internet of Things intestinal hemostasis clip disclosed in this invention;

[0076] Figure 4 This is a flowchart illustrating the RSSI-TDOA fusion algorithm disclosed in this invention.

[0077] Figure label:

[0078] 1. Hemostatic clip body; 11. Clamping arm; 12. Miniature cavity; 2. Passive UHF RFID tag.

[0079] The realization of the objective, functional characteristics and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0080] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] It should be noted that the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0082] Example 1

[0083] This invention provides an IoT-based intestinal hemostatic clip, which, through the collaborative design of the clip body 1, a passive UHF RFID tag 2, and a transparent window array, achieves real-time monitoring of the clip's position within the intestine and reliable signal interaction. The following is in conjunction with the appendix... Figure 1 The technical solution of the present invention will be described in detail below with reference to specific embodiments:

[0084] The hemostatic clip body 1 is made of biocompatible materials, preferably medical-grade titanium alloy (such as TC4 titanium alloy) or biodegradable polymer materials (such as polyglycolic acid PGA, molecular weight ≥300,000 Da, degradation period 60-90 days); one end has two opposing clamping arms 11, and the other end has a micro cavity 12, with a wave-transparent window array on the outer surface; specifically, the structure of each component is as follows:

[0085] The clamping arms 11 extend from the proximal end of the main body (near the end of the micro cavity 12) to the distal end. In the initial state, the distance between the inner sides of the two arms is 1-3 mm (closed state). The clamping force is provided by the elastic metal wire inside the main body. The distal end of the clamping arm 11 is processed into an arc-shaped chamfer to avoid damage to the intestinal mucosa. The inner surface is provided with a micro-tooth structure to enhance the friction with the bleeding wound and prevent slippage and dislodgement.

[0086] The miniature cavity 12 is located at the far end of the body (away from the end of the clamping arm 11). The inner wall of the cavity is treated with plasma to increase the surface energy and ensure the bonding strength between the encapsulation material and the body.

[0087] A wave-transmitting window array, distributed circumferentially along the outer surface of the body, contains at least three wave-transmitting units arranged periodically; each wave-transmitting unit is circular or square, and is made of a low-dielectric-constant polymer material (such as polytetrafluoroethylene PTFE, dielectric constant ε). r ≈2.1; with intestinal tissue (ε r (≈70) to form gradient impedance matching and reduce signal reflection.

[0088] The passive UHF RFID tag 2 is adapted and encapsulated within the miniature cavity 12. Its tag antenna adopts a flexible, deformable, and foldable structure, and its operating frequency covers 860-960MHz (compliant with global UHF RFID frequency band standards). The external coating is a biocompatible epoxy resin layer. The specific structure of each component is shown below:

[0089] The tag antenna adopts a serpentine or zigzag folding layout (preferably serpentine structure) to adapt to the spatial constraints of the miniature cavity 12; the serpentine folding line width is 0.1-0.2mm, the line spacing is 0.05-0.1mm, and the folding period is 1-2mm (i.e., turning once every 1-2mm); this setting allows it to deform synchronously with the hemostatic clip body 1 during intestinal peristalsis, avoiding breakage caused by stress concentration;

[0090] The RFID chip is a low-power passive chip (such as NXPUCODE7, operating frequency 860-960MHz, reading distance ≥2m), which is attached to the end of the antenna with conductive adhesive. The entire tag (antenna + chip) is covered with a biocompatible epoxy resin layer, which is injected into the micro cavity 12 after vacuum degassing to fill the gap between the antenna and the cavity, ensuring that the tag is fixedly connected and sealed to the body.

[0091] Wave-transmitting window arrays, through multi-path transmission, impedance matching, and focusing enhancement mechanisms, overcome the signal attenuation bottleneck in the complex intestinal environment. Specifically,

[0092] The periodically arranged transparent units allow radio frequency signals to be incident from multiple angles (such as 0°, 60°, 120° directions), avoiding signal loss caused by the intestinal wall blocking a single window;

[0093] Materials of wave-transmitting elements (such as PTFE, ε) r ≈2.1) and intestinal tissue (ε r Dielectric constant gradient matching of ≈70) reduces the interface reflection coefficient;

[0094] The size and spacing of the wave-transparent cells are optimized to focus electromagnetic waves in the direction of the tag antenna.

[0095] The IoT-based intestinal hemostasis clip of this invention needs to be used in conjunction with an external reader / writer and an IoT positioning system. The specific workflow is as follows:

[0096] The doctor delivers the hemostatic clamp body 1 to the bleeding wound through an endoscope, closes the clamping arm 11 to stop the bleeding, and at this time the RFID tag in the miniature cavity 12 is sealed and fixed.

[0097] The external reader transmits radio frequency signals (frequency 860-960MHz) to the hemostatic clip. The tag antenna receives the energy and reflects the modulated signal. After demodulation, the reader obtains the tag ID, signal strength (RSSI), and timestamp information.

[0098] The external reader uploads data to the IoT positioning system. The system calculates the spatial position of the hemostatic clip based on the signal strength attenuation model and performs real-time monitoring in conjunction with the preset safety range. When a sudden drop in signal strength or the position exceeds the safety range is detected, the system automatically triggers an alert, prompting the doctor to perform an endoscopic re-examination or intervention.

[0099] Traditional intestinal hemostatic clips rely solely on physical clamping for hemostasis, lacking the ability to actively monitor postoperative detachment. If the clip shifts or falls off due to intestinal peristalsis, tissue contraction, or external force, the previously hemostatic wound may be exposed and bleed again, potentially leading to hemorrhagic shock or requiring a second surgery. This invention integrates a passive UHF RFID tag 2 within the miniature cavity 12 of the hemostatic clip body 1, and combines this with an external IoT positioning system to construct a wireless interactive link between the tag and reader / writer and the system. This allows for real-time acquisition of the clip's spatial location and status parameters (such as the trend of tag signal strength changes). Medical staff continuously track the clip's position through the backend system. When abnormal displacement (such as exceeding a preset safety range) or a sudden drop in signal strength (indicating potential detachment) is detected, timely intervention measures (such as endoscopic repositioning or secondary hemostasis) can be taken, fundamentally eliminating the risk of secondary bleeding and significantly improving postoperative patient safety.

[0100] In addition, the antenna of the present invention adopts a flexible and deformable foldable structure. Its material has a similar elastic modulus to the biocompatible polymer material of the hemostatic clip body 1. During intestinal peristalsis, it can deform synchronously with the clamping arm 11 to avoid antenna breakage caused by stress concentration.

[0101] The intestinal environment contains a large amount of water (approximately 75% water content), mucus, and soft tissue, which strongly attenuates UHF radio frequency signals. Traditional single-antenna structures are difficult to effectively identify deep hemostatic clips in the body (the conventional identification distance is <10cm). This invention sets a wave-transmitting window array (composed of multiple regularly arranged microwave transmission windows, made of biocompatible ceramic or high-transparency polymer composite material) on the outer surface of the hemostatic clip body 1. Through multi-path transmission, impedance matching, and focusing enhancement mechanisms, it overcomes the signal attenuation bottleneck of the complex intestinal environment. This design enables the external reader (handheld or fixed) to quickly and accurately obtain the position information of the hemostatic clip during colonoscopy or postoperative follow-up, meeting the needs of real-time clinical monitoring.

[0102] This invention employs a passive UHF RFID tag 2 (powered by the radio frequency field of an external reader), eliminating the need for a built-in battery and avoiding the failure risks of traditional active tags due to battery leakage or depletion. It also reduces the size and weight of the hemostatic clip body 1, minimizing mechanical pressure on intestinal tissue. Furthermore, the hemostatic clip body 1 is made of medical-grade titanium alloy or biodegradable polymer materials, meeting ISO10993 standards for biocompatibility. The sealed encapsulation of the microcavity 12 further prevents the infiltration of bodily fluids, ensuring no toxic substances are released during long-term placement in the body, avoiding inflammatory reactions or tissue adhesions, and meeting the safety requirements for clinical implantable devices.

[0103] This invention, through its organic integration with Internet of Things (IoT) technology, has significant advantages in real-time monitoring, signal reliability, biosafety, and clinical applicability. It effectively solves the technical pain points of traditional intestinal hemostatic clips, such as the inability to monitor position and the tendency to fall off, leading to secondary bleeding. It provides a safer and smarter solution for the treatment of intestinal hemorrhagic diseases.

[0104] Example 2

[0105] This invention provides an IoT-based hemostatic clip positioning system. Through a technical architecture combining IoT hemostatic clips, multi-reader collaboration, and cloud-based intelligent computation, it achieves real-time three-dimensional positioning and risk warning for intestinal hemostatic clips. The following is in conjunction with the appendix... Figure 2 The document provides a detailed description of the structure, connection method, and workflow of each component of the system, along with specific implementation examples.

[0106] This system includes an IoT intestinal hemostatic clip as shown in Example 1, at least three external readers, a client, and a server. A closed-loop data flow of "hemostatic clip-reader-client-server" is formed through a wireless communication link. The external readers receive the radio frequency signal of the hemostatic clip tag and parse the data. The client forwards the data to the server. The server calculates the three-dimensional position of the hemostatic clip based on multi-source data and positioning algorithms. Finally, the client feeds back the real-time position and warning information.

[0107] The external reader / writer is the core of the system's signal reception and analysis; its deployment and performance directly affect the positioning accuracy and reliability. The specific implementation is as follows:

[0108] The external reader / writer needs to be deployed within a predetermined spatial area on the patient's body surface (e.g., a circular area with a radius of 50cm centered on the surgical wound), and the antenna direction of each reader / writer needs to cover the potential movement area of ​​the hemostatic clip. To avoid signal obstruction, the reader / writer antenna is preferably a directional antenna, which is fixed to the patient's body surface by a bracket to ensure that the main lobe of the antenna points towards the intestinal region. In this embodiment, three external readers / writers are provided, respectively located 5cm above the umbilicus on the midline of the abdomen, at the corresponding body surface position of the 12th thoracic vertebra (back), and 10cm medial to the right anterior superior iliac spine (lateral waist). This arrangement can cover the anatomical projection area of ​​the intestine (jejunum, ileum, colon), forming an asymmetric triangular network and reducing the signal attenuation blind zone in the body. The spatial coordinates (x, y) of each external reader / writer are specified. i ,y i ,z i (i=1,2,3…) needs to be pre-measured and stored on the server. The external reader uses an industrial-grade UHF RFID reader module (such as the ThingMagic M6e series), with an operating frequency of 860-960MHz (compliant with ETSI EN302208 standard), a transmit power of ≤30dBm, and a receive sensitivity of -105dBm.

[0109] The client, acting as a hub for data relay and user interaction, employs a modular design to implement data reception, transmission, and visualization functions, specifically including:

[0110] The data receiving module is used to receive RFID data sent by the external reader. Specifically, the client connects to the external reader via a wireless LAN or Bluetooth 5.2 to receive the raw RFID data sent by the reader. The RFID data includes tag ID, signal strength (RSSI), time difference of arrival (TDOA, which requires the reader to support time synchronization), and timestamp information. The data format adopts the JSON protocol.

[0111] The data transmission module transmits RFID data to the server in real time via wired or wireless networks (such as Wi-Fi or 5G). Specifically, the client forwards RFID data to the server in real time via HTTP / HTTPS protocols or MQTT message queues (low latency). To meet real-time requirements, the client performs preliminary filtering on the raw data (such as moving average filtering with a window size of 5) to remove noise interference before uploading, reducing the computational load on the server.

[0112] The interactive interface module (based on a web frontend or mobile app) displays the 3D location information fed back by the server and supports user operations (such as querying historical tracks and setting warning thresholds); it supports the following functions:

[0113] 3D position display: Using Three.js or Unity3D engine, dynamically annotate the 3D coordinates (x, y, z) of the hemostatic clip on the human anatomical model (CT / MRI image overlay), with an error ≤3cm;

[0114] Historical trajectory query: Retrieve historical location data stored on the server to generate a location-time curve to assist in analyzing the movement pattern of the hemostatic clip;

[0115] Warning settings: Users can set a safety range through the interface. When the hemostatic clip exceeds the range, a red warning box will pop up on the interface and an audio reminder will be given.

[0116] Parameter configuration: Supports adjusting parameters such as reader sampling frequency and positioning algorithm type (TDOA / RSSI / hybrid algorithm).

[0117] The server is the core computing unit of the system, enabling intelligent management of the entire process through data storage, algorithm calculation, and risk warning. Specifically, it includes:

[0118] The data storage module stores the spatial coordinates, RFID data, and historical positioning results of the external reader / writer. Specifically, the server uses a combination of relational databases (such as MySQL) and non-relational databases (such as Redis) to store the data.

[0119] Basic data: Spatial coordinates of the external reader (x i ,y i ,z i The mapping relationship between hemostatic clip label ID and patient information (such as patient name, hospital number, and surgery time);

[0120] Real-time data: Raw RFID data (RSSI, TDOA, timestamp) and filtered data uploaded by the client;

[0121] Historical data: Location results (3D coordinates (x, y, z)), direction of movement, warning records (time, type, processing status);

[0122] The positioning algorithm module, based on the RFID signal time difference of arrival (TDOA) and received signal strength (RSSI) of the multi-reader RFID signals, combined with a preset mathematical model, calculates the three-dimensional coordinates (x, y, z) and direction of movement of the IoT intestinal hemostasis clip; the server, based on the RFID signals of the multi-reader RFID, uses a hybrid positioning algorithm to calculate the three-dimensional coordinates of the hemostasis clip, the specific steps of which are as follows:

[0123] TDOA positioning: Utilizing the time difference (Δt) of the signals arriving from three readers. 12 ,Δt 13 Based on the propagation speed of electromagnetic waves, a system of equations is established. Taking external reader i as the reference point, the equations form hyperbolas with external readers j and k, as shown below:

[0124] ;

[0125] RSSI correction: Introducing a logarithmic attenuation model of received signal strength and distance to correct errors in TDOA calculation results and improve positioning accuracy;

[0126] Dynamic filtering: Extended Kalman filter (EKF) is used to fuse multi-time localization results, eliminate positional jumps caused by intestinal peristalsis, and output a smooth three-dimensional coordinate sequence;

[0127] The early warning module sends an early warning command to the client when the three-dimensional position information exceeds the preset safety range. The early warning module judges whether the position of the hemostatic clip is abnormal in real time based on the safety range parameters stored on the server: position out-of-bounds detection: calculate the spatial distance between the current coordinates of the hemostatic clip and the center of the wound. If D>Dmax (preset maximum safety distance, such as 2cm), or the RSSI value of the RFID data drops sharply, an early warning is triggered.

[0128] Movement trend analysis: The movement speed and direction (azimuth angle θ) of the hemostatic clip are calculated using historical coordinates. If the speed exceeds the threshold or the direction deviates from the normal intestinal peristalsis direction (such as moving towards non-wound areas), a secondary warning is triggered.

[0129] Warning push: Warning information is pushed to the client via HTTP interface and recorded in the database at the same time (including warning time, type, hemostatic clip ID, current location, etc.).

[0130] The present invention provides an IoT hemostatic clip positioning system, the workflow of which is as follows:

[0131] The doctor obtains the coordinates of the patient's body surface reference points using a 3D laser scanner. Combined with the location of the surgical wound (located endoscopically), the doctor calculates and records the spatial coordinates (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3) of the external reader to the server. The doctor then inserts an IoT intestinal hemostatic clip into the bleeding wound using an endoscope, closes the clamping arm 11 to achieve hemostasis, and the hemostatic clip tag enters the working state. The external reader transmits radio frequency signals at a frequency of 1Hz. The hemostatic clip tag receives the energy and reflects the modulated signal. After receiving and parsing the signal, the reader transmits the data to the client via Wi-Fi 6. The client forwards the data to the server. The server's positioning algorithm module calculates the 3D coordinates of the hemostatic clip based on a TDOA+RSSI hybrid algorithm and corrects the error using an extended Kalman filter. Finally, the results (x, y, z) and the direction of movement are fed back to the client's visualization interface. If the hemostatic clip's position exceeds the safe range or its movement speed is abnormal, a red warning pops up on the client interface. The doctor can view the historical trajectory and current position through the interface and decide whether to perform endoscopic repositioning or a secondary hemostasis operation.

[0132] Traditional methods for confirming the location of intestinal hemostatic clips primarily rely on postoperative endoscopic follow-up (requiring insertion of an endoscope to the bleeding site) or X-ray / CT imaging. The former is an invasive procedure that may cause intestinal mucosal damage or perforation; the latter carries the risk of radiation exposure and cannot achieve continuous monitoring. This invention utilizes an external passive UHF RFID reader for wireless interaction with the hemostatic clip tag, enabling real-time acquisition of the hemostatic clip's location information without contact with the human body or the use of radioactive equipment. Medical staff only need to place three or more readers on the patient's body surface (covering the surgical area) to complete the positioning via wireless signals (such as the 900MHz band), completely avoiding invasive procedures and radiation risks. This is particularly suitable for long-term postoperative monitoring scenarios (such as when patients require multiple follow-up examinations or home observation). This invention employs at least three external readers (preferably distributed in a triangle or ring on the patient's body surface), combined with a pre-set positioning algorithm on the server side (such as a weighted centroid method based on signal strength (RSSI), a time difference of arrival (TDOA) algorithm, or a hybrid positioning algorithm), to accurately calculate the three-dimensional coordinates of the hemostatic clip.

[0133] This invention achieves fully automated flow of positioning data through a wireless communication link of "hemostatic clip-reader-client-server," significantly reducing the operational burden on medical staff. It employs a passive UHF RFID tag 2 (power provided by the reader's radio frequency field), eliminating the need for a built-in battery and avoiding the failure risk of traditional active positioning devices due to battery depletion. Simultaneously, the distributed deployment of multiple readers further enhances the system's robustness. Furthermore, the positioning system of this invention transforms the hemostatic clip from a "passive hemostasis tool" into an "active monitoring node," and its deep integration with electronic medical record (EMR) systems and surgical navigation systems can further expand clinical application scenarios. The IoT hemostatic clip positioning system provided by this invention, through multi-reader collaborative positioning, wireless data interaction, and cloud-based intelligent computation, effectively solves the technical pain points of traditional hemostatic clip positioning, such as reliance on invasive examinations, high radiation risks, and poor real-time performance. It has significant advantages in improving diagnostic and treatment safety, efficiency, and accuracy, providing an intelligent, full-cycle solution for the treatment of intestinal bleeding disorders.

[0134] Example 3

[0135] This invention also provides a positioning method for an IoT hemostatic clip positioning system as provided in Embodiment 2. Through a technical approach of "asymmetric reader / writer layout + RSSI-TDOA fusion algorithm + intelligent anomaly detection," it achieves three-dimensional real-time positioning and risk warning of the intestinal hemostatic clip; the following is in conjunction with the appendix... Figure 3 The implementation steps of the method are described in detail, along with specific embodiments.

[0136] Step S1: Signal Acquisition and Data Acquisition

[0137] The radio frequency (RF) signal from the hemostatic clip tag is received and analyzed by an asymmetrically distributed external reader to obtain the raw RFID data. Specifically, the reader actively transmits the RF signal at a frequency of 1 Hz. After the passive UHF RFID chip of the hemostatic clip tag receives the energy, it reflects and modulates the signal through a serpentine folded antenna. The signal contains the tag ID, RSSI, TDOA, and timestamp information. The reader converts the received RF signal into digital data and transmits it to the client via Wi-Fi 6.

[0138] Step S2, Data Preprocessing: RSSI Calibration and TDOA Measurement

[0139] To eliminate environmental interference (such as signal attenuation caused by intestinal fluid and gas), RSSI and TDOA data need to be calibrated and measured accurately.

[0140] RSSI calibration:

[0141] ;

[0142] Where α = 0.35 (fat attenuation coefficient), β = 0.02 (muscle attenuation coefficient), d = straight-line distance from the reader to the hemostatic clip (cm), and C is the body position compensation constant.

[0143] TDOA measurement:

[0144] TDOA is obtained through the two-way ranging method (DS-TWR), and the specific process is as follows:

[0145] The hemostatic clip tag sends a signal to the reader R1, and R1 records the transmission time t. 1a It also sends a response signal, and the tag records the response reception time t. 1b ;

[0146] The tag transmits a signal to R2, and R2 records the transmission time t. 2a It also sends a response signal, and the tag records the response reception time t. 2b ;

[0147] TDOA is calculated as: Δt 12 =((t 2b- t 2a )-(t 1b- t 1a )) / 2 (Eliminate tag clock error);

[0148] DS-TWR compensates for clock deviations between the tag and the reader through two bidirectional communications, ensuring the accuracy of TDOA measurements.

[0149] Step S3: Hemostatic clip position calculation - RSSI - TDOA fusion algorithm

[0150] The initial location region is obtained through RSSI, and then the hyperbolic equations of TDOA are solved. Finally, the corrected coordinates are obtained by Kalman filtering. The specific implementation steps are as follows:

[0151] S31. Preliminary location area determination based on RSSI

[0152] Using the calibrated RSSI model, the estimated distances between the hemostatic clips and each reader / writer were calculated:

[0153] ;

[0154] Where, d i The distance from the hemostatic clamp to the reader i (i=1,2,3);

[0155] Draw circles with radii d1, d2, and d3, centered on the three readers. The intersection of the three circles is the initial location area of ​​the hemostatic clip.

[0156] S32. Solving 3D Coordinates Based on TDOA

[0157] Within the initial location region, a system of hyperbolic equations is established using the time difference of TDOA. For readers A, B, and C, the coordinates are (x...). A ,y A ,z A ), (x B ,y B ,z B ), (x C ,y C ,z C If the coordinates of the hemostatic clip are (x, y, z), then the distance difference satisfies the following formula:

[0158] ;

[0159] The above nonlinear equations were solved numerically to obtain the preliminary three-dimensional coordinates (x, y) of the hemostatic clip. p ,y p ,z p );

[0160] S33, Kalman filter fusion correction

[0161] To eliminate systematic errors (such as gut gas scattering) in the RSSI model and clock skew in TDOA, an extended Kalman filter (EKF) is used to fuse the results of the two algorithms.

[0162] State vector: defined as (position and velocity components), where, , , These are the estimated three-dimensional coordinates of the hemostatic clip at time k; , , These are the three-dimensional velocity components of the hemostatic clip at time k, used to characterize the direction of movement (the direction of the velocity vector is the direction of movement);

[0163] Predictive model: Based on the position and velocity at the previous moment, predict the state at the current moment;

[0164] Update the model: Use the distance estimate of RSSI and the coordinate solution of TDOA as observations to correct the prediction state;

[0165] Output: The final result is the corrected three-dimensional coordinates (x, y, z) and the direction of movement (the azimuth angle θ is calculated by the difference between the coordinates of adjacent time points).

[0166] Step S4: Anomaly detection and early warning information issuance

[0167] Based on the three-dimensional position and direction of movement of the hemostatic clip, and / or RFID data, determine whether the hemostatic clip is abnormal and trigger a differentiated warning.

[0168] S41. Determining whether the IoT intestinal hemostasis clip is abnormal specifically includes at least one of the following situations:

[0169] Abnormal displacement: The cumulative displacement exceeds the safety threshold (e.g., 5cm) and continues for more than the preset time (e.g., 10 minutes);

[0170] Abnormal displacement direction: The displacement direction angle θ deviates from the normal movement direction of the intestinal anatomical path (such as the ascending direction of descending colon to rectum) by more than a preset angle (such as ±30°);

[0171] Abnormal signal strength: A sudden drop in the RSSI value of RFID data (e.g., RSSI drops from -60dBm to below -90dBm within 1 minute) indicates that the hemostatic clip has entered the shielded area (e.g., it has been expelled from the body or detached from the intestines).

[0172] S42. The issuance of the warning information specifically includes:

[0173] Push warning instructions to the client that include the anomaly type (displacement / direction / signal strength), anomaly timestamp, and suggested handling measures;

[0174] The suggested handling measures are dynamically generated based on the type of abnormality. For example, when the displacement is abnormal, the prompt is "Check the fixation status of the hemostatic clip"; when the signal strength is abnormal, the prompt is "Confirm whether the hemostatic clip has been removed".

[0175] This invention overcomes the technical bottlenecks of traditional hemostatic clips, which rely on invasive examinations, lack accuracy, and have poor real-time performance, through a combination of asymmetric reader layout, RSSI-TDOA fusion algorithm, and intelligent anomaly detection. It achieves significant advantages in positioning reliability, dynamic monitoring capabilities, and timely risk warning. Specifically, at least three external readers are asymmetrically distributed along the intestinal anatomical path (e.g., with the surgical wound as the center, reader 1 is located 5cm above the umbilicus on the abdominal midline, reader 2 is located at the corresponding surface position of the 12th thoracic vertebra, and reader 3 is located 10cm medial to the right anterior superior iliac spine), forming an "anterior-posterior-lateral" three-dimensional coverage network. This layout avoids signal attenuation caused by intestinal peristalsis or intestinal gas obstruction of a single reader, ensuring that the hemostatic clip is positioned in each segment of the intestine. In particular, signals from curved and folded areas can be captured by at least two readers, providing multi-dimensional data support for RSSI and TDOA algorithms. A fusion algorithm is adopted, which combines the distance estimate of RSSI with the spatial geometric constraints of TDOA through Kalman filtering, and reduces the systematic error of a single algorithm by utilizing the complementarity of the two. The IoT intestinal hemostatic clip positioning method provided by this invention effectively solves the technical pain points of insufficient accuracy, poor real-time performance and high radiation risk of traditional positioning methods through asymmetric reader layout, RSSI-TDOA fusion algorithm and intelligent anomaly judgment. It has formed significant advantages in improving positioning reliability, dynamic monitoring capabilities and risk warning timeliness, and provides an intelligent and full-cycle solution for the treatment of intestinal hemorrhagic diseases.

[0176] In a preferred embodiment, the method for establishing the hyperbola equation system based on the distance difference in step S32 is as follows:

[0177] S321. Calculate the time difference between any two external readers, as shown in the following formula:

[0178] ;

[0179] Where c is the equivalent propagation speed of electromagnetic waves in human tissue (approximately 1.5 × 10⁻⁶). 8 m / s), (x,y,z) are the coordinates of the hemostasis clip, (x i ,y i ,z i Let (x) be the coordinates of one of the external readers / writers. j ,y j ,z j () represents the coordinates of another external reader / writer;

[0180] S322. Obtain the distance difference between any two external readers, as shown in the following formula:

[0181] ;

[0182] S323. Obtain the system of hyperbolic equations. Taking external reader i as the reference point, form hyperbolas with external readers j and k respectively, as shown below:

[0183] ;

[0184] Specifically, in this embodiment, the example of setting up three external readers / writers will be used for illustration.

[0185] Taking reader A as the reference point, a system of hyperbolic equations is formed with B and C respectively, as shown below:

[0186] ;

[0187] To solve the above hyperbolic equation, and to simplify the nonlinear equation, we assume the position of the hemostatic clip is ( The deviation is ( ). The formula for the position of the hemostatic clip after it has been moved is: ;

[0188] A first-order Taylor expansion of the distance difference equation yields the thread equation system, as shown below:

[0189] ;

[0190] in,

[0191] ;

[0192] Specifically, the thread equations are solved using the least squares method, and the thread equations can be represented in matrix form as shown below:

[0193] ;

[0194] Where H is the matrix coefficient. b is the observation vector, obtained by solving using the least squares method. , ;

[0195] Based on the obtained Iterate and update the position until convergence.

[0196] To further illustrate the process of determining the position of the hemostatic clip, we will use three readers as an example. The coordinates of the three readers are A(0,0,0); B(30,0,0); and C(15,26,0). The actual position coordinates of the hemostatic clip are P(10,15,5).

[0197] The measurement time difference is shown below:

[0198] ;

[0199] Predict the initial position coordinates of the stop clamp. Given (8, 13, 4), solve iteratively. ;

[0200] After the first iteration ;

[0201] After the second iteration

[0202] After the third iteration, it converged to P(10.1,14.9,4.9) with an error of 0.3 cm.

[0203] In a preferred embodiment, in step S33, see... Figure 4 The steps for obtaining the corrected coordinates (x, y, z) of the hemostatic clip in three-dimensional space are as follows:

[0204] The preliminary location region from RSSI positioning (RSS positioning result, a coarse location estimate based on a signal strength attenuation model, with large errors but high real-time performance and low computational cost) is fused with the preliminary 3D coordinates from TDOA positioning (based on hyperbolic positioning using time difference, with high accuracy but susceptible to multipath effects) using a Kalman filter (KF). This fusion leverages the complementary error characteristics of both methods (RSSI is sensitive to dynamic environmental changes but has strong global stability, while TDOA has high ranging accuracy but relies on time synchronization; the stability of RSSI compensates for occasional jumps in TDOA, while the high accuracy of TDOA corrects for systematic errors in RSSI). Through state estimation and observation updates, a high-precision 3D corrected coordinate movement direction is output. The specific implementation steps are as follows:

[0205] S331. Determine the system state and observation model of the Kalman filter.

[0206] S3311, Definition of State Vector

[0207] To simultaneously track the three-dimensional position and direction of movement of the hemostatic clip, the state vector is defined as:

[0208] ;

[0209] S3312, Construction of Observation Model

[0210] The Kalman-filtered observations are obtained by fusing the initial location region of RSSI with the three-dimensional coordinates of TDOA. The observation model is shown in the following equation:

[0211] ;

[0212] in, for k The fused observation vector at time step is in the form of [x RSSI(k) ,y RSSI(k) ,z RSSI(k) ,x TDOA(k) , y TDOA(k) ,z TDOA(k) ] T (The first 3 dimensions are RSSI position estimates, and the last 3 dimensions are TDOA coordinate solutions);

[0213] H is the observation matrix (a 6×6 identity matrix, since the observed values ​​directly correspond to the 6 components of the state vector);

[0214] For the observed noise vector;

[0215] Preferred, ;

[0216] S332. Initialize Kalman filter parameters

[0217] S3321, Initial State Estimation

[0218] The initial state is determined by the initial RSSI position region of S2 and the TDOA three-dimensional coordinates of S3:

[0219] Position components (x(0), y(0), z(0)): Take the three-dimensional coordinates calculated by TDOA in step S3;

[0220] velocity components ( , , ): Calculated using historical data of the preliminary RSSI location area in step S2 (e.g., the position difference between the two most recent times is divided by the sampling period; if historical data is insufficient, it is set to 0).

[0221] S3322, Initial covariance matrix P(0)

[0222] The initial covariance reflects the uncertainty of the state estimation and needs to be considered in conjunction with the location area error of RSSI and the three-dimensional coordinate error of TDOA.

[0223] RSSI location area error: Its standard deviation (e.g., ±10 mm, corresponding to a variance of 10) is determined through calibration experiments. 2 mm 2 );

[0224] TDOA 3D coordinate error: determined by the clock calibration parameters of the hyperbolic positioning system (e.g., ±5mm, corresponding to a variance of 5). 2 mm2 );

[0225] Initial variance of velocity component: Since the initial velocity is unknown, it is set to 1 / 4 of the position variance (an empirical value that reflects the velocity uncertainty in low-speed movement scenarios).

[0226] The initial covariance matrix is ​​a diagonal block matrix as shown below:

[0227] ;

[0228] in, , , Take the weighted sum of the location variances of RSSI and TDOA (the weights are adjusted according to the confidence level, such as TDOA having a higher weight). , , The variance of the velocity component;

[0229] S333. Calculate the observation noise covariance matrix R(k).

[0230] The observation noise covariance R(k) needs to be quantified to determine the joint uncertainty of RSSI and TDOA observations. The specific steps are as follows:

[0231] S3331, Single Sensor Noise Characteristics Analysis

[0232] RSSI observation noise: follows a Gaussian distribution with a mean of 0 and a variance of... Determined by factors such as signal attenuation model error and multipath effects (e.g., obtained through statistical analysis of historical data). =25mm 2 );

[0233] TDOA observation noise: follows a Gaussian distribution with mean 0 and variance Determined by factors such as time synchronization error and clock drift (e.g., obtained through clock calibration parameters of a hyperbolic positioning system). =10mm 2 ).

[0234] S3332, Calculation of Fusion Noise Covariance

[0235] Since the observations of RSSI and TDOA are independent, the fused noise covariance is a weighted sum of the variances of the two (the weights reflect the confidence level of the sensors):

[0236] ;

[0237] S334, Execute the Kalman filter recursive process.

[0238] Kalman filtering achieves state estimation through a "prediction-update" loop, simultaneously outputting the three-dimensional position and direction of movement (velocity vector); the following example uses the transition from time k to time k+1:

[0239] S3341. Prediction Steps (Predicting the Current State Based on Historical States)

[0240] Utilizing the optimal state estimation at time k Covariance Predict the state at time k+1. Covariance :

[0241] ;

[0242] ;

[0243] Where F is the state transition matrix (6×6), which describes the kinematic characteristics in low-speed movement scenarios, as shown below:

[0244] ;

[0245] (Δt is the sampling period, such as 10ms; assuming acceleration is 0 and velocity remains constant);

[0246] Q is the process noise covariance matrix (reflecting model uncertainty), taken as a diagonal matrix (e.g., Q=diag(10)). -4 10 -4 10 -4 10 -6 10 -6 10 -6 (This indicates that random disturbances due to positional changes are negligible).

[0247] S3342, Update Steps (Using Fuded Observations to Correct Predictions)

[0248] By correcting the predicted state using the fused observation Z(k+1) at time k+1, a more accurate estimate is obtained. Covariance The specific process is as follows:

[0249] Calculate the residuals (the deviation between observations and predictions):

[0250] ;

[0251] Calculate the residual covariance:

[0252] ;

[0253] Calculate the Kalman gain:

[0254] ;

[0255] Corrected state estimation:

[0256] ;

[0257] Update the covariance matrix:

[0258] ;

[0259] S3343, Calculation of Movement Direction (Based on Velocity Vector)

[0260] Corrected state vector Includes three-dimensional velocity components ( , , It can be directly used to characterize the direction of movement of the hemostatic clip;

[0261] The specific direction is represented by the direction angle of the velocity vector:

[0262] Azimuth angle: The angle between the projection of the velocity vector onto the horizontal plane and the x-axis, calculated using the following formula: .

[0263] S335, Output corrected coordinates and movement direction

[0264] After multiple "prediction-update" loops, the Kalman filter converges, finally outputting the corrected 3D coordinates at time k. , , ) and direction of movement (azimuth angle θ).

[0265] In some preferred embodiments, the fusion weight ratio of the Kalman filter can also be dynamically adjusted. Specifically, if the RSSI signal-to-noise ratio is less than a preset value (preferably 20 dB), it is determined to be of low quality, and the weight ratio is reduced; if the TDOA multipath suppression ratio is less than a preset value (preferably 10 dB), it is determined to be of low quality, and the weight ratio is increased; the weight ratio of RSSI and TDOA can also be adjusted through a weight adaptive formula, specifically, the weight adaptive formula is as follows:

[0266] ;

[0267] in, This is a smoothing factor, defaulting to 0.1, to prevent sudden weight changes. This is the weight value of RSSI;

[0268] ;

[0269] in This is the weight value of TDOA, which needs to be ensured. and They add up to 10.

[0270] To verify the accuracy of the RSSI-TDOA fusion algorithm used in this invention, the errors obtained by comparing the hemostatic clip position obtained using only RSSI, only TDOA, and RSSI-TDOA fusion with the actual position are shown in the table below:

[0271]

[0272] As can be seen from the table above, the RSSI-TDOA fusion algorithm provided by this invention has the smallest error, which means that the hemostatic clip positioning method provided by this invention has high accuracy.

[0273] The above are merely preferred embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention's specification and drawings under the inventive concept of the present invention, or direct or indirect applications in other related technical fields, are within the patent protection scope of the present invention.

Claims

1. An Internet of Things (IoT) hemostatic clip positioning system, characterized in that, include: An Internet of Things (IoT) intestinal hemostasis clip, comprising a hemostasis clip body and a passive UHF RFID tag disposed on the hemostasis clip body; At least three external readers are used to wirelessly communicate with the IoT intestinal hemostasis clip, receive and analyze the radio frequency signals emitted by its passive UHF RFID tag, and obtain RFID data information. The client is wirelessly connected to each external reader / writer and is used to receive and forward the RFID data to the server. The server connects wirelessly to the client and, based on the RFID data and a preset positioning algorithm, uses the RSSI-TDOA fusion algorithm to calculate the real-time three-dimensional position and movement direction of the IoT intestinal hemostasis clip, and feeds back the three-dimensional position and movement direction to the client. The steps of calculating the real-time three-dimensional position and direction of movement of the IoT intestinal hemostasis clip using the RSSI-TDOA fusion algorithm are as follows: S1. Obtain the time difference of arrival in the RFID data using a two-way ranging method; S2. Based on the calibrated RSSI, obtain the distance estimate between the hemostatic clip and each reader / writer to determine the preliminary location area of ​​the hemostatic clip; specifically, calibrate the received signal strength in the RFID data based on the signal strength-distance model; and the signal strength-distance model is specifically shown in the following formula: ； Where α is the fat attenuation coefficient, β is the muscle attenuation coefficient, and d is the straight-line distance from the reader to the hemostatic clip. C 组织衰减 This is the postural compensation constant; S3. Within the initial location area, the time difference of the measurement signal reaching each external reader is calculated using TDOA, and then the time difference is converted into a distance difference. Based on the distance difference, a hyperbolic equation system is established, and the initial three-dimensional coordinates of the hemostatic clip are obtained by solving the hyperbolic equation system. S4. Based on the weighted fusion of RSSI and TDOA results using Kalman filtering, obtain the corrected coordinates (x, y, z) and direction of movement of the hemostatic clip in three-dimensional space.

2. The IoT hemostatic clip positioning system according to claim 1, characterized in that, The at least three external readers are deployed within a preset space, with their antenna directions covering the potential activity area of ​​the IoT intestinal hemostasis clip, and the spatial coordinates of each external reader are known and pre-stored on the server.

3. The IoT hemostatic clip positioning system according to claim 1 or 2, characterized in that, The client includes: The data receiving module is used to receive RFID data sent by the external reader / writer; The data transmission module transmits RFID data to the server in real time via wired or wireless network; The interactive interface module is used to display the 3D position information fed back by the server and supports user operations.

4. The IoT hemostatic clip positioning system according to claim 1 or 2, characterized in that, The server includes: The data storage module is used to store the spatial coordinates, RFID data, and historical positioning results of the external reader / writer; The positioning algorithm module calculates the three-dimensional coordinates (x, y, z) and direction of movement of the IoT intestinal hemostasis clip based on the time difference of arrival of RFID signals from multiple readers and the strength of received signals, combined with a preset mathematical model. The early warning module sends an early warning command to the client when the three-dimensional location information exceeds the preset safety range or when the RSSI value of the RFID data drops sharply.

5. The IoT hemostatic clip positioning system according to claim 1 or 2, characterized in that, The steps for establishing a system of hyperbola equations based on distance differences are as follows: S31. Calculate the time difference between any two external readers, as shown in the following formula: ； Where c is the equivalent propagation speed of electromagnetic waves in human tissue, and (x,y,z) are the coordinates of the hemostasis clip. i ,y i ,z i Let (x) be the coordinates of one of the external readers / writers. j ,y j ,z j () represents the coordinates of another external reader / writer; S32. Obtain the distance difference between any two external readers, as shown in the following formula: ； S33. Obtain the system of hyperbolic equations. Taking external reader i as the reference point, form hyperbolas with external readers j and k respectively, as shown below: 。 6. The IoT hemostatic clip positioning system according to claim 1 or 2, characterized in that, In step S4, the preliminary location area of ​​RSSI positioning and the preliminary three-dimensional coordinates of TDOA positioning are fused by Kalman filtering. Taking advantage of the complementary error characteristics of the two, high-precision three-dimensional corrected coordinates and movement direction are output through state estimation and observation update.

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