A multiple injury treatment dispatching system and method

Abstract

The application relates to the technical field of first-aid dispatching, and particularly discloses a multiple-injury treatment dispatching system and method, which comprises the following modules: a voice processing module, which is used for converting voice call information between a call terminal and a dispatching center into text information after the call terminal dials an emergency call to the dispatching center, and extracting injury information; a scene recognition module, which is used for recognizing whether the current scene is a multiple-injury scene and whether there is a demand to move the injured person according to the injury information; when the recognition result is yes, operation guidance information containing an image uploading link is generated; an image acquisition module, which acquires multiple-angle on-site images of the injured person collected by the call terminal; and a carrying guidance module, which is used for labeling a note label of a moving risk area on the multiple-angle on-site images of the injured person by using a large model after receiving the multiple-angle on-site images of the injured person. The technical scheme of the application can give concrete disposal instructions to on-site witnesses based on on-site conditions before first-aid personnel arrive at the scene.

Description

Technical Field

[0001] This invention relates to the field of emergency medical dispatching technology, and in particular to a dispatching system and method for the treatment of multiple injuries. Background Technology

[0002] Multiple injuries refer to severe damage to two or more anatomical sites or organs caused by the same traumatic factor, with at least one injury being life-threatening. Treatment of multiple injuries (especially traffic accident injuries) is highly time-sensitive; the golden hour is clinically recognized as crucial for reducing disability and mortality rates. Existing emergency medical dispatch systems primarily focus on monitoring vital signs en route to the ambulance and synchronizing information alerts between the ambulance and the target hospital, striving to achieve a closed-loop treatment process of immediate admission upon boarding.

[0003] In these systems, the primary function of the dispatch center is resource matching and route planning to ensure that professional emergency responders can arrive at the scene and take care of the injured as quickly as possible. However, in the actual treatment process, there is a gap in treatment guidance between the end of the 120 emergency call and the arrival of emergency personnel. During this stage, the dispatch center can often only provide verbal guidance to the caller. Because non-professionals at the scene lack medical background, they not only find it difficult to accurately describe the complex details of the injuries, but are also more likely to move the injured blindly or position them incorrectly in a state of anxiety. Especially for car accident victims, unless there is an immediate danger at the scene, such as a risk of vehicle fire or being on a busy highway, they should not be moved easily; blindly moving them can easily lead to catastrophic consequences.

[0004] Existing technical solutions generally neglect to effectively guide the first witnesses at the scene before emergency personnel arrive, and lack a multi-injury treatment dispatch system and method that can provide concrete treatment instructions based on the scene situation. Summary of the Invention

[0005] One of the objectives of this invention is to provide a multi-injury treatment dispatch system that can provide concrete handling instructions to on-site witnesses based on the situation before emergency personnel arrive.

[0006] To solve the above-mentioned technical problems, this application provides the following technical solution: A multiple injury treatment and dispatch system, comprising: The voice processing module is used to convert the voice call information between the call terminal and the dispatch center into text information after the emergency call is connected to the call terminal. The module extracts the injury information from the text information through a pre-set large model and sends the injury information to the emergency terminal of the assigned emergency personnel. The scene recognition module is used to identify whether the current scene is a multiple injury scene and whether there is a need to move the injured person based on the injury information; when the recognition result is yes, it generates operation guidance information including an image upload link and sends it to the call terminal; The image acquisition module is used to output preset photo-taking prompts in the display interface generated by the call terminal in response to the triggering of the image upload link, and to acquire multi-angle on-site images of the injured person collected by the call terminal in response to the upload operation command in the display interface. The transport guidance module is used to mark the risk areas of movement on the multi-angle on-site images of the injured person after receiving them, using a large model, and then send the marked images to the emergency terminal for manual review. It is also used to send the marked images to the display interface of the call terminal after receiving the approval instruction from the emergency terminal.

[0007] Furthermore, the scene recognition module is also used to encapsulate a preset moving prohibition field and a link guidance field into the operation guidance information when generating the operation guidance information; wherein, the moving prohibition field is used to display a preset text warning on the interface of the call terminal that restricts the movement of the wounded in non-emergency evacuation environments, and the link guidance field is used to guide the user to collect on-site images through an image upload link and obtain wounded movement guidance.

[0008] Furthermore, the transport guidance module is also used to identify key human body points in multi-angle on-site images of the injured using a large model, map virtual models of transport personnel occupying positions on the multi-angle on-site images of the injured, and use preset dotted line identifiers to mark the hand support points, force vector directions, and operation instruction information corresponding to each virtual model of transport personnel occupying positions.

[0009] Furthermore, the transport guidance module is also used to match the target placement posture from a preset transport position library based on injury information and multi-angle on-site images of the injured person, and generate a placement reference image showing the expected placement position of the injured person after the transport is completed, and send the placement reference image to the call terminal.

[0010] Furthermore, the voice processing module is also used to acquire the voice assistance instructions fed back by the emergency terminal in response to receiving injury information, and to convert the voice assistance instructions into semantic prompts; The transport guidance module is also used to input semantic prompts as constraint parameters into the large model and to correct the annotation logic of the precaution labels in real time.

[0011] Furthermore, the transport guidance module is also used to invoke a preset multi-person collaborative transport plan to determine the recommended number of people required for this transport.

[0012] Furthermore, the transport guidance module is also used to generate a number confirmation request instruction after determining the recommended number of people required for this transport, and send it to the calling terminal; receive the number of people input from the calling terminal; if the current available number of people is lower than the recommended number, it is also used to send a location extraction request to the voice processing module, and the voice processing module retrieves the location information of the injured person identified and marked from the text information during the voice call; The transport guidance module is also used to send a query request carrying the location information of the injured person to the connected traffic information system through a preset data interface, and to obtain the current real-time traffic flow information and historical traffic frequency data of the road segment corresponding to the location of the injured person. The handling guidance module is also used to determine whether other vehicles will pass through the road segment within a preset time window based on real-time traffic flow information and historical traffic frequency data. If the judgment result is that there is a high probability that no vehicles will pass through or the user actively chooses to handle the current number of people, it is also used to input the actual number of available people as a constraint parameter into the multi-person collaborative handling plan, and recalculate the hand support point allocation strategy, force vector direction adjustment plan and operation instruction information correction content of each handling person under the condition of reduced number of people.

[0013] Furthermore, it also includes a vital signs acquisition module, which communicates with the vital signs monitoring equipment on the ambulance to acquire the vital signs data of the injured person in real time, including heart rate, blood pressure, blood oxygen saturation, respiratory rate, and body temperature data. The information flow module is used to encapsulate the dynamic changes in vital signs data during transport into structured electronic medical record documents and push them to the emergency information system of the target hospital.

[0014] The second objective of this solution is to provide a method for scheduling the treatment of multiple injuries using the aforementioned system.

[0015] This solution utilizes a pre-built large model to semantically analyze voice communication information, automatically extracting injury information from on-site descriptions and synchronizing it to the emergency terminal. This overcomes the limitations of traditional dispatch modes, such as low efficiency and susceptibility to misunderstandings from verbal communication, thus improving the accuracy and timeliness of emergency information flow. The scene recognition module automatically assesses multiple injury scenarios and emergency evacuation and relocation needs, ensuring the necessity of initiating treatment guidance and avoiding unnecessary mishandling of the injured. The relocation guidance module dynamically marks risk areas and precautions for movement on the real-world image of the injured using the large model, transforming medical treatment principles into visually clear instructions with illustrations. This allows on-site witnesses to clearly identify areas where traction is prohibited and axial stability requirements, reducing the risk of catastrophic secondary injuries such as spinal cord injury and massive bleeding due to unprofessional relocation. By setting up manual review by emergency personnel, the guidance content generated by the large model is professionally reviewed before being distributed to the scene. In summary, this solution can provide on-site witnesses with concrete treatment instructions based on the on-site situation before emergency personnel arrive. Attached Figure Description

[0016] Figure 1 This is a logic block diagram of a first embodiment of a multi-injury treatment and dispatch system. Detailed Implementation

[0017] The following detailed description illustrates the specific implementation method: Example 1 like Figure 1 As shown, this embodiment of a multi-injury treatment and dispatch system includes a call terminal and an emergency terminal, as well as a cloud server. The cloud server includes a voice processing module, a scene recognition module, an image acquisition module, and a handling guidance module.

[0018] The voice processing module converts the voice call information between the calling terminal and the dispatch center into text information after the emergency call is connected. It then extracts injury information from the text information using a pre-set large model and sends this information to the emergency terminal of the assigned emergency personnel. In this embodiment, the calling terminal is a smartphone used by the person making the emergency call at the scene. The injury information includes the type of injury, the injured body part, key physical signs, and semantic tags of the scene environment. For example, the voice call information between the calling terminal and the dispatch center includes a scene description such as, "A motorcyclist fell off a roadside hillside. This place is on the edge of a cliff. It's raining, and rocks are falling from above. The person can't move, and their leg seems deformed." The injury information extracted by the voice processing module using the large model is specifically: Type of injury: traffic accident injury (motorcycle fall injury); Injured body part: lower limb; Key physical signs: suspected fracture / deformity, unable to move independently; Scene environment semantic tags: cliff edge, rainy weather, landslide risk, need for emergency evacuation and relocation.

[0019] The scene recognition module is used to identify whether the current situation is a multiple injury scenario and whether there is a need to move the injured person based on the injury information. When the recognition result is yes, it generates operation guidance information including an image upload link and sends it to the calling terminal. In this embodiment, the scene recognition module has a pre-set set of rules for determining multiple injury scenarios and a set of rules for determining moving needs. After obtaining the injury information, the scene recognition module first matches the injury mechanism in the multiple injury scenario determination rule set with the injury type field "traffic accident injury (motorcycle fall injury)" and the injured part field "lower limb" to determine that the current accident may have multiple injuries, and the recognition result is yes. The scene recognition module also retrieves the semantic label fields "cliff edge", "rainy weather", "landslide risk" and "emergency evacuation required" from the scene environment and compares them with the emergency evacuation scenario labels in the moving need determination rule set to confirm that the current environment poses a continuous safety threat to the injured person and on-site personnel, and determines that there is an emergency evacuation need, and the recognition result is yes. In other embodiments, an optional manual backup solution is also provided, in which dispatch center operators determine whether it is a multiple injury scenario and whether there is a need to move the injured.

[0020] The scene recognition module also encapsulates preset handling prohibition fields and link guidance fields into the operation guidance information when generating it. The handling prohibition field displays a preset text warning on the call terminal interface restricting the movement of the injured person in non-emergency evacuation environments. The link guidance field instructs users to upload images of the scene via an image upload link to obtain handling guidance. For example, an important reminder might appear: "The injured person is suspected of having a fracture. Unprofessional handling may cause secondary injury. This is currently only an emergency evacuation handling guide; please operate with caution under the system's guidance. Click here to upload images of the injured person at the scene and obtain handling guidance."

[0021] The image acquisition module is used to output preset photo-taking prompts in the display interface generated by the call terminal in response to the triggering of the image upload link, and to acquire multi-angle on-site images of the injured person collected by the call terminal in response to the upload operation command in the display interface. The transport guidance module is used to mark the risk areas of movement on the multi-angle on-site images of the injured after receiving them. It is also used to identify key human body points in the multi-angle on-site images of the injured using the large model, map the virtual models of transport personnel on the multi-angle on-site images of the injured, and use preset dotted line identifiers to mark the hand support points, force vector direction and operation instruction information corresponding to each virtual model of transport personnel. It is also used to match the target placement posture from a preset transport position library based on injury information and multi-angle on-site images of the injured, and generate a placement reference image showing the expected placement position of the injured after the transport is completed. Specifically, The transport guidance module uses a pre-built large model to identify key human points in each image of the injured person. These key human points include at least: the top of the head, cervical vertebrae, left and right shoulder joints, left and right elbow joints, left and right wrist joints, left and right hip joints, left and right knee joints, and left and right ankle joints. Through key point matching and 3D reconstruction of multi-angle images, a 3D posture topology map of the injured person is generated. The transport guidance module combines the injury information extracted from the speech processing module, including "injured area: lower limb" and "key physical signs: suspected fracture / deformity," to identify the "lower limb" area as a high-risk management area on the 3D posture topology map. Precaution labels are then overlaid at the corresponding locations in the 2D on-site image. For example, a floating label "Suspected fracture area - Do not pull alone" is placed on the injured person's leg, and a label "Maintain axial stability during transport" is placed on the waist. The transport guidance module is also used to invoke preset multi-person collaborative transport plans to determine the recommended number of people required for the transport, for example, suggesting 3 people to work together; it overlays virtual models of the corresponding number of transport personnel onto multi-angle images of the injured person, for example, displaying them as semi-transparent humanoid outlines; it uses preset dotted line identifiers to mark the images, for example: hand support points are marked with dotted circles, respectively marked on the injured person's shoulder and back, both sides of the pelvis, and the uninjured area of ​​the distal lower leg. The force vector direction is marked with dotted lines with arrows, starting from the hand support point of each virtual transporter and pointing to the preset lifting direction (for example, a vertically upward arrow indicates "lift vertically", and a diagonal arrow indicates "maintain traction direction"); the operation instruction information is attached next to the corresponding virtual model in the form of text bubbles, for example, "Position 1: Support the head and shoulders with both hands, keep the neck neutral", "Position 2: Support the waist and hips with both hands, as the main load-bearing", "Position 3: Support the lower legs with both hands, be careful to avoid deformed areas". The transport guidance module also accesses a pre-set transport position library, which stores various standard placement posture templates and their corresponding applicable injury condition mapping tables. Using "Injury Type: Traffic Accident Fall Injury" and "Injury Location: Suspected Lower Limb Fracture" as query keys, it matches the data in the mapping table to determine the target placement posture as "Supine Neutral Position after Lower Limb Immobilization". A large model is then called to generate a placement reference image of the target supine neutral position, showing the expected state of the injured person lying flat in a safe area with their legs temporarily immobilized by a hard object. The image is labeled with the text "Recommended Post-Transport Placement Posture Reference" in the corner.

[0022] The transport guidance module is also used to send the generated images to the emergency terminal for manual review; it is also used to send the generated images to the display interface of the call terminal after receiving the approval instruction from the emergency terminal.

[0023] In this embodiment, if emergency personnel need to adjust the generated image, the voice processing module is also used to obtain the voice assistance instructions fed back by the emergency terminal in response to receiving injury information, and convert the voice assistance instructions into semantic prompts; the handling guidance module is also used to input the semantic prompts as constraint parameters into the large model and correct the labeling logic of the precaution labels in real time.

[0024] This embodiment also provides a method for scheduling the treatment of multiple injuries, using the above-mentioned system.

[0025] This embodiment, through the collaboration of a voice processing module and a scene recognition module, fills the gap in treatment between making an emergency call and the arrival of emergency personnel at the scene. By using a large model to semantically analyze voice information, it can accurately identify multiple injury scenarios and emergency evacuation and relocation needs, breaking the limitations of traditional dispatching methods that rely solely on verbal instructions, resulting in low communication efficiency and a high risk of misjudgment. This solution utilizes an image acquisition and relocation guidance module to transform abstract medical treatment principles into concrete, visual instructions. By dynamically marking risk areas, key points on the human body, and virtual positioning models on real-world images of the injured person, non-professional on-site witnesses can intuitively grasp key details such as hand support points and force direction. This significantly reduces the risk of secondary injury caused by blind relocation or improper positioning. Simultaneously, a manual review mechanism by emergency personnel is introduced to ensure that the AI-generated guidance plan is reviewed by professional medical personnel before distribution, ensuring both the timeliness of treatment and the authority and safety of the guidance content.

[0026] Example 2 The difference between this embodiment and Embodiment 1 is that in this embodiment, the moving guidance module, after determining the recommended number of people needed for the move (e.g., recommending 3 people to work together), generates a number confirmation request instruction and sends it to the calling terminal. Upon receiving the request instruction, the calling terminal displays an interactive window containing text prompts such as "The system recommends that 3 people are needed to complete this move. Are there enough people available on site?", and provides two clickable controls: "Sufficient" and "Not enough, enter manually". If the calling terminal responds to the user's click on the "Sufficient" control, the moving guidance module maintains the original recommended number of people plan unchanged.

[0027] If the calling terminal responds to the user's click on the "Not enough, manually enter" control, the interactive window further presents a numeric input field for the user to enter the current actual number of available people (e.g., the user enters "2" people). After receiving this actual number of available people parameter, the transport guidance module determines that the current number of available people is lower than the recommended number and also sends a location retrieval request to the voice processing module. The voice processing module retrieves the location information of the injured persons identified and marked from the text information during the voice call. The location information of the injured persons includes at least latitude and longitude coordinates or a textual geographical location description (e.g., "Near G318 National Highway chainage K1234, about 20 meters below the xxx viewing platform").

[0028] The transport guidance module also sends a query request, carrying the location information of the injured person or the road segment identifier of that location, to the connected traffic information system via a preset data interface. The traffic information system returns the current real-time traffic flow information and historical traffic frequency data for that road segment based on the query request. The transport guidance module also determines whether other vehicles will pass through the road segment within a preset time window (e.g., 3 minutes) based on the real-time traffic flow information and historical traffic frequency data. When the determination result is "high probability of a vehicle passing through," the transport guidance module generates a waiting suggestion message and sends it to the calling terminal. The waiting suggestion message may include, for example: "A vehicle is expected to pass through this road segment within 3 minutes. We suggest you wait briefly, ensuring your safety, to obtain more personnel to assist in the transport and reduce the risk of single-person operation." Simultaneously, the interface provides "Continue to wait" and "Continue transporting according to the current number of people" selection buttons. If the user selects "Continue to wait," the system remains in standby mode; if the user selects "Continue transporting according to the current number of people," the transport guidance module triggers a replanning process for the transport plan.

[0029] When the judgment result is "high probability no vehicle passing by" or the user actively chooses to move according to the current number of people, it is also used to input the actual available number of people (e.g., "2") as a constraint parameter into the multi-person collaborative moving plan, and recalculate the hand support point allocation strategy, force vector direction adjustment scheme, and operation instruction information correction content for each mover under the condition of reduced number of people. For example, when the number of people is reduced from 3 to 2, the replanned output is as follows: In the virtual model of the first transporter's position, which was originally planned for 3 people, the hand support point was changed from "both hands supporting the head and shoulders" to "one arm passing under the armpit to hug the chest, and the other hand supporting the back of the neck". The corresponding force vector direction arrow and operation instruction information were updated to: "Position 1: Hug the wounded person's chest and back, keep the head and neck aligned with the trunk axis, and use it as one of the main lifting force points". In the virtual model of the third transporter, originally planned for 3 people, the hand support point was adjusted to "both hands support the popliteal fossa of both knees respectively", and the operation instruction information was updated to: "Position 2: support the popliteal fossa of the injured person's legs, keep in sync with position 1 when lifting, and be careful to avoid the deformed area of ​​the lower leg suspected of being fractured". At the same time, the system removes the virtual models of porters occupying the positions of the third person in the original plan from the image.

[0030] Unlike existing technologies that merely use real-time traffic flow information to plan ambulance routes and avoid congestion, this solution innovatively combines traffic flow data with an assessment of manpower shortages in on-site treatment. By analyzing real-time traffic flow and historical frequency at the location of the injured person, it predicts whether subsequent vehicles will pass through during the critical treatment time window, thus scientifically guiding on-site personnel to either wait for reinforcements or proceed with the transport under existing conditions. When the available manpower is insufficient, the system can automatically trigger a logical restructuring of the transport plan based on actual manpower constraints, reallocating force points and correcting operational instructions. This maximizes the use of limited manpower, providing a more scientific opportunity for life-threatening injuries to avoid danger.

[0031] Example 3 The difference between this embodiment and Embodiment 1 is that the system in this embodiment also includes a vital sign acquisition module and an information transfer module.

[0032] The vital signs acquisition module is connected to the vital signs monitoring equipment on the ambulance to acquire the vital signs data of the injured person in real time after the ambulance receives the injured person, including heart rate, blood pressure, blood oxygen saturation, respiratory rate and body temperature data. The information flow module is used to encapsulate the dynamic changes in the vital signs data of the injured during the transfer into a structured electronic medical record document and push it to the emergency information system of the target hospital.

[0033] After the ambulance picks up the injured, the system digitally records the dynamic evolution of key vital signs such as heart rate, blood oxygen, and blood pressure, eliminating the risk of information omissions or verbal errors that may occur during manual handover. The information flow module encapsulates this real-time data into structured electronic medical record documents and pushes them to the hospital system in advance. This allows the hospital's medical team to formulate surgical plans based on the complete trend of vital signs before the injured arrive, eliminating internal hospital response delays and having significant clinical value in improving the survival rate and prognosis of patients with multiple injuries.

[0034] The above are merely embodiments of the present invention. The invention is not limited to the fields covered by these embodiments. Commonly known structures and characteristics in the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are able to access all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A multiple trauma treatment and dispatch system, characterized in that, include: The voice processing module is used to convert the voice call information between the call terminal and the dispatch center into text information after the emergency call is connected to the call terminal. The module extracts the injury information from the text information through a pre-set large model and sends the injury information to the emergency terminal of the assigned emergency personnel. The scene recognition module is used to identify whether the current scene is a multiple injury scene and whether there is a need to move the injured person based on the injury information; when the recognition result is yes, it generates operation guidance information including an image upload link and sends it to the call terminal; The image acquisition module is used to output preset photo-taking prompts in the display interface generated by the call terminal in response to the triggering of the image upload link, and to acquire multi-angle on-site images of the injured person collected by the call terminal in response to the upload operation command in the display interface. The transport guidance module is used to mark the risk areas of movement on the multi-angle on-site images of the injured person after receiving them, using a large model, and then send the marked images to the emergency terminal for manual review. It is also used to send the marked images to the display interface of the call terminal after receiving the approval instruction from the emergency terminal.

2. The multiple injury treatment and dispatch system according to claim 1, characterized in that: The scene recognition module is also used to encapsulate a preset moving prohibition field and a link guidance field into the operation guidance information when generating the operation guidance information; wherein, the moving prohibition field is used to display a preset text warning on the interface of the call terminal that restricts the movement of the wounded in non-emergency evacuation environments, and the link guidance field is used to guide the user to collect on-site images through the image upload link and obtain wounded movement guidance.

3. The multiple injury treatment and dispatch system according to claim 2, characterized in that: The transport guidance module is also used to identify key human body points in multi-angle on-site images of the injured using a large model, map virtual models of transport personnel to the multi-angle on-site images of the injured, and use preset dotted line identifiers to mark the hand support points, force vector directions, and operation instruction information corresponding to each virtual model of transport personnel.

4. The multiple injury treatment and dispatch system according to claim 3, characterized in that: The transport guidance module is also used to match the target placement posture from a preset transport position library based on injury information and multi-angle on-site images of the injured, and generate a placement reference image showing the expected placement position of the injured after the transport is completed, and send the placement reference image to the call terminal.

5. The multiple injury treatment and dispatch system according to claim 4, characterized in that: The voice processing module is also used to acquire the voice assistance instructions fed back by the emergency terminal in response to receiving injury information, and to convert the voice assistance instructions into semantic prompts; The transport guidance module is also used to input semantic prompts as constraint parameters into the large model and to correct the annotation logic of the precaution labels in real time.

6. The multiple injury treatment and dispatch system according to claim 5, characterized in that: The transport guidance module is also used to call a preset multi-person collaborative transport plan to determine the recommended number of people required for this transport.

7. The multiple injury treatment and dispatch system according to claim 6, characterized in that: The transport guidance module is also used to generate a number confirmation request instruction after determining the recommended number of people required for this transport, and send it to the calling terminal; receive the number of people input from the calling terminal; if the current available number of people is lower than the recommended number, it is also used to send a location extraction request to the voice processing module, and the voice processing module retrieves the location information of the injured person identified and marked from the text information during the voice call; The transport guidance module is also used to send a query request carrying the location information of the injured person to the connected traffic information system through a preset data interface, and to obtain the current real-time traffic flow information and historical traffic frequency data of the road segment corresponding to the location of the injured person. The handling guidance module is also used to determine whether other vehicles will pass through the road segment within a preset time window based on real-time traffic flow information and historical traffic frequency data. If the judgment result is that there is a high probability that no vehicles will pass through or the user actively chooses to handle the current number of people, it is also used to input the actual number of available people as a constraint parameter into the multi-person collaborative handling plan, and recalculate the hand support point allocation strategy, force vector direction adjustment plan and operation instruction information correction content of each handling person under the condition of reduced number of people.

8. The multiple injury treatment and dispatch system according to claim 7, characterized in that: It also includes a vital signs acquisition module, which communicates with the vital signs monitoring equipment on the ambulance to acquire vital signs data of the injured in real time, including heart rate, blood pressure, blood oxygen saturation, respiratory rate, and body temperature data; The information flow module is used to encapsulate the dynamic changes in vital signs data during transport into structured electronic medical record documents and push them to the emergency information system of the target hospital.

9. A method for scheduling the treatment of multiple injuries, characterized in that, Use the system according to any one of claims 1-8.

Images