Intelligent wounded carrying stretcher system

Abstract

The application discloses an intelligent wounded person carrying stretcher system and belongs to the field of medical instruments. The intelligent wounded person carrying stretcher system comprises a first support, a second support, a third support, a bearing cloth and a connecting assembly, and further comprises a vital sign monitoring system and a cloud analysis platform. The application solves the problems of inconvenience in carrying and single function of the existing stretcher. The folding effect of the first support, the second support and the third support is realized through the connecting assembly. After folding, the stretcher is fixed through the upper belt and can be carried on the body through the shoulder strap. The vital sign monitoring system is matched with the stretcher to realize real-time monitoring of the vital sign data and the temperature data of the wounded person. The single function of the traditional stretcher is changed. The data compression, fragmentation and transmission monitoring are carried out on the monitored data, the efficiency of data transmission is improved, the corresponding first-aid measures are taken in time through the analysis of the monitored data, and the treatment opportunity of the wounded person is avoided.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, specifically to an intelligent patient transport stretcher system. Background Technology

[0002] A stretcher is a piece of medical equipment used to transport the wounded. Its main structure consists of stretcher poles and a soft canvas. However, existing stretchers still have the following problems in practical use:

[0003] 1. Although existing stretchers can be folded to reduce their size, they still need to be carried by hand. Holding them for a long time will put a lot of stress on the arms, which is not conducive to the subsequent transportation of the wounded.

[0004] 2. Existing stretchers have limited functionality, only capable of basic transport. They cannot monitor the vital signs of the injured in real time, thus failing to provide timely information about the injured's physical condition and making it difficult to detect potential dangers in advance, thereby delaying emergency treatment.

[0005] Therefore, since the existing needs are not met, we have proposed an intelligent patient transport stretcher system. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent stretcher system for transporting wounded soldiers. The system uses connecting components to achieve a folding effect for the first, second, and third supports. After folding, the stretcher is secured by an upper strap and then carried on a shoulder strap, allowing the transporter to carry the stretcher on their back for easy transport. The stretcher is also equipped with a vital signs monitoring system, enabling real-time monitoring of the wounded soldier's physical condition, which is beneficial for timely understanding of the wounded soldier's physical condition and solves the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an intelligent patient transport stretcher system, comprising a first support, a second support, a third support, a load-bearing cloth, and a connecting component. The patient transport stretcher is composed of the first support, the second support, the third support, and the load-bearing cloth, and the first support, the second support, and the third support are interconnected by the connecting component.

[0008] The supporting fabric is laid on the frame formed by the first support, the second support and the third support. An upper strap and a lower strap are respectively provided above and below the supporting fabric, and heating elements are provided inside the supporting fabric, the upper strap and the lower strap.

[0009] It also includes vital sign monitoring systems and cloud-based analytics platforms;

[0010] The vital signs monitoring system is configured to monitor the vital signs data and body temperature data of the injured person in real time through various sensors installed on the upper strap. The vital signs data include heart rate data, respiratory data and blood oxygen saturation data.

[0011] The real-time monitored vital signs data and body temperature data are compressed and segmented before being transmitted to the cloud analysis platform. The segmentation process determines the possible segmentation range based on network quality assessment indicators, rule base matching results, and policy priority analysis. It also analyzes the current data transmission success status and the possible segmentation range to determine the actual segmentation size of the data, thereby achieving dynamic segmentation optimization.

[0012] The cloud-based analysis platform is configured to analyze the real-time monitored vital sign data and body temperature data, and to feed back the real-time monitored vital sign data, body temperature data, and analysis results to the remote monitoring personnel. The analysis results include:

[0013] If abnormalities are detected in vital sign data, an alert will be issued via the audio-visual device on the first support.

[0014] If abnormal body temperature data is detected, heating pads are installed inside the support fabric, upper and lower straps to maintain the injured person's body temperature.

[0015] Furthermore, the vital signs monitoring system includes:

[0016] The data acquisition module is configured to deploy various sensors on the upper strap. By attaching the sensors to the injured person's body, the module can monitor the injured person's vital signs and body temperature data in real time. The vital signs data include heart rate data, respiratory data, and blood oxygen saturation data.

[0017] The data preprocessing module is configured to preprocess vital sign data and body temperature data, including:

[0018] Remove invalid, duplicate, and abnormal data from vital sign and body temperature data;

[0019] A filtering algorithm is used to remove noise from vital sign data and body temperature data;

[0020] The data transmission module is configured to compress the pre-processed vital sign data and body temperature data and transmit them to the cloud analysis platform.

[0021] Furthermore, the data transmission module includes:

[0022] The data compression module is configured to compress vital sign data and body temperature data. After compression, the vital sign data and body temperature data are packaged and data information is added, including type identifier, data timestamp, data source device ID and data packet sequence number.

[0023] The data fragmentation module is configured to fragment the packaged data packet, split the data packet into multiple fragments, transmit each fragment independently, and add fragment sequence number and total fragment number information to each fragment.

[0024] The transmission monitoring module is configured to monitor various quality indicators during the data transmission process in real time, including transmission success rate, transmission delay, packet loss rate, and bit error rate. By statistically analyzing these indicators, it can determine whether any problems have occurred during the transmission process. If problems occur, it can promptly feed back the monitored quality indicators and problem information to maintenance personnel.

[0025] Furthermore, the data sharding module also includes:

[0026] The transmission network status is evaluated in real time according to the set evaluation interval to obtain quality evaluation indicators;

[0027] The acquired quality assessment indicators are used as screening criteria to match the initial sharding adjustment strategy from the preset rule base.

[0028] If there is only a single initial sharding adjustment strategy, then the currently obtained initial sharding adjustment strategy will be used as the actual sharding adjustment strategy.

[0029] If there are multiple initial sharding adjustment strategies and all have the same adjustment direction, then extract the maximum adjustment magnitude and combine it with the adjustment direction to generate the actual sharding adjustment strategy.

[0030] If there are multiple initial sharding adjustment strategies and the adjustment directions are not all the same, then obtain the corresponding rule-related indicators for each initial sharding adjustment strategy.

[0031] By combining the preset priority score of the rule association index with the effective value of the strategy, the priority association score of each initial shard adjustment strategy is determined;

[0032] The initial sharding adjustment strategies are sorted from largest to smallest according to the priority association score to obtain a strategy priority list;

[0033] By comparing and analyzing the adjustment direction and priority correlation score difference of the top two strategies in the strategy priority list, the actual sharding adjustment strategy is determined.

[0034] Using the actual sharding adjustment strategy, the initial sharding size of the current data is adjusted to obtain the possible range of sharding.

[0035] Extract the probability of successful transmission of current data within a preset time period and compare it with a preset success threshold determined based on data priority;

[0036] If the comparison result is positive, then the middle value is selected from the possible range of the fragments as the actual fragment size of the current data;

[0037] If the comparison result is negative, the data-priority adjustment direction is adjusted according to the upper or lower limit of the range extracted from the possible range of the fragments to obtain the actual fragment size of the current data.

[0038] Furthermore, the cloud-based analytics platform includes:

[0039] The data analysis module is configured to compare real-time monitored vital sign data and body temperature data with preset thresholds, analyze whether there are any abnormalities in the vital sign data and body temperature data based on the comparison results, determine the abnormality score of the vital sign data, and then determine the abnormality level based on the abnormality score.

[0040] The early warning and adjustment module is configured to issue early warnings or adjust the temperature based on the analysis results from the data analysis module. Specifically:

[0041] If the analysis results indicate abnormalities in vital sign data, an early warning command will be immediately generated based on the level of abnormality and sent to the audio-visual device. The audio-visual device will then play sounds and flash lights to alert the handling personnel.

[0042] If the analysis results show abnormalities in body temperature data, a control command is immediately generated. The control command signal controls the heating pads on the support cloth, upper strap, and lower strap to provide warmth to the injured person until the injured person's body temperature is maintained within the set threshold range.

[0043] The feedback interaction module is configured to provide an interactive interface for remote monitoring personnel. On the interactive interface, the vital signs data and body temperature data of the injured person are displayed in real time through visual icons and graphics, as well as the analysis results of the data analysis module. At the same time, the warning and adjustment module sends warning commands to the sound and light device in real time, as well as adjusts the working parameters of the heating element.

[0044] Furthermore, the preset threshold is specifically:

[0045] The threshold for heart rate data is 40-300 beats per minute;

[0046] Threshold for respiratory data: i.e. respiratory rate, is 12-20 breaths / minute;

[0047] The threshold for blood oxygen saturation data is 90%~100%.

[0048] The threshold for body temperature data is 35.5℃ to 37.5℃.

[0049] Furthermore, the connecting assembly includes a connecting rod, a slot, and a connecting shaft. The slot is located at the connection between the first bracket, the second bracket, and the third bracket. The connecting rod is inserted into the slot and fixed by the connecting shaft, thereby realizing the connection and folding of the first bracket, the second bracket, and the third bracket.

[0050] Furthermore, the upper and lower straps are provided with tear-off tabs for fixing and adjusting, and the back of the support fabric located at the first bracket is provided with a carrying strap for carrying the wounded on a stretcher.

[0051] Furthermore, the first bracket is equipped with folding feet on both sides, the third bracket is equipped with folding wheels on both sides, and the third bracket has a movable groove with a foot baffle on the movable groove. The foot baffle is connected to the movable groove through a pivot.

[0052] Compared with the prior art, the beneficial effects of the present invention are:

[0053] 1. This invention, through the design of the connecting components, allows the first, second, and third supports to be easily connected and folded. After folding, they are secured by the upper strap, and the folded stretcher can be carried on the body via the provided shoulder straps, greatly reducing the strain on the arms and effectively alleviating the fatigue of the transport personnel. This facilitates the continued transport of the injured and improves the efficiency and sustainability of the transport. Furthermore, the third support is equipped with folding wheels on both sides and a footrest for placing the injured person's feet. This design allows for convenient single-person transport of the injured when there are insufficient transport personnel.

[0054] 2. This invention utilizes a vital sign monitoring system to monitor the vital sign data and body temperature data of the injured in real time. By compressing, segmenting, and monitoring the transmission of vital sign and body temperature data, the efficiency and integrity of data transmission can be improved. The cloud analysis platform analyzes the received vital sign and body temperature data, which can promptly detect abnormalities in the injured, thereby issuing timely warnings or maintaining stable body temperature. By combining the vital sign monitoring system with the system, real-time monitoring of the injured's physical condition is achieved, changing the traditional stretcher's single function of only transporting patients. This allows for timely understanding of the injured's health status, enabling timely implementation of appropriate emergency measures and avoiding delays in treatment. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the overall structure of the patient transport stretcher of the present invention;

[0056] Figure 2This is a folding diagram of the first bracket, second bracket, and third bracket of the present invention;

[0057] Figure 3 For the present invention Figure 2 Enlarged view of point A in the middle;

[0058] Figure 4 This is a side view of the patient transport stretcher of the present invention after folding.

[0059] Figure 5 This is a schematic diagram of the back of the patient transport stretcher of the present invention after folding;

[0060] Figure 6 This is a schematic diagram of the patient transport stretcher of the present invention.

[0061] In the diagram: 1. First support; 2. Second support; 3. Third support; 31. Foot guard; 32. Movable groove; 4. Supporting fabric; 5. Connecting assembly; 51. Connecting rod; 52. Slot; 53. Connecting shaft; 6. Upper strap; 7. Lower strap; 8. Tear-off tape; 9. Folding feet; 10. Folding wheels; 11. Shoulder strap; 12. Sound and light device. Detailed Implementation

[0062] 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 some embodiments of the present invention, and not all embodiments. 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.

[0063] To address the technical issue that while existing stretchers can be folded to reduce size, they still require hand handling during transport, which puts significant strain on the arms and hinders subsequent patient transfer, please refer to [the relevant documentation / reference]. Figures 1-5 This embodiment provides the following technical solution:

[0064] The intelligent patient transport stretcher system includes a first support 1, a second support 2, a third support 3, a load-bearing cloth 4, and a connecting component 5. The patient transport stretcher is composed of the first support 1, the second support 2, the third support 3, and the load-bearing cloth 4. The first support 1, the second support 2, and the third support 3 are interconnected by the connecting component 5.

[0065] The supporting fabric 4 is laid on the frame formed by the first support 1, the second support 2 and the third support 3. The upper strap 6 and the lower strap 7 are respectively provided above and below the supporting fabric 4, and heating elements are provided inside the supporting fabric 4, the upper strap 6 and the lower strap 7.

[0066] The technical effects of the above-mentioned solution are as follows: The stretcher structure, composed of the first support 1, the second support 2, the third support 3, and the supporting fabric 4, provides good support and load-bearing capacity for the injured. The first support 1, the second support 2, and the third support 3 are interconnected by connecting components 5, allowing for folding when not in use, greatly reducing the stretcher's volume and floor space, facilitating storage and transportation. The upper strap 6 and the lower strap 7 are respectively located above and below the supporting fabric 4, securely fixing the injured to the stretcher and preventing slippage or body displacement due to bumps or shaking during transport, ensuring the safety of the injured during transport. Furthermore, the upper strap 6 can also secure the folded stretcher, allowing it to be folded like a backpack (e.g.,...). Figures 4-5 As shown in the figure, heating pads are installed inside the carrying cloth 4, upper strap 6 and lower strap 7 to facilitate carrying. In cold environments or when the wounded person's body temperature is low, they can keep the wounded person warm, help maintain the wounded person's body temperature, and prevent the wounded person's physical condition from deteriorating due to low temperature.

[0067] The connecting component 5 includes a connecting rod 51, a slot 52, and a connecting shaft 53. The slot 52 is located at the connection between the first bracket 1, the second bracket 2, and the third bracket 3. The connecting rod 51 is inserted into the slot 52 and fixed by the connecting shaft 53, thereby realizing the connection and folding of the first bracket 1, the second bracket 2, and the third bracket 3.

[0068] The technical effect of the above technical solution is as follows: the connecting rod 51 is inserted into the slot 52 and is fixed firmly through the connecting shaft 53. This not only enables the support to maintain a stable connection, but also enables the support to fold. The design of the connecting component 5 makes the stretcher flexible in the process of connection and folding, so that the stretcher can be folded when not in use, which greatly reduces the volume and floor space, thus making it convenient to store, carry and transport.

[0069] The upper strap 6 and the lower strap 7 are provided with tear-off tape 8 for fixing and adjustment, and the back of the support cloth 4 located at the first bracket 1 is provided with a carrying strap 11 for carrying the wounded on a stretcher.

[0070] The technical effects of the above-mentioned technical solution are as follows: The tear-off tape 8 is easy to use and firmly adheres, allowing the transport personnel to quickly fix the upper strap 6 and lower strap 7 to different parts of the injured person's body, achieving rapid fixation and preventing the injured person's body from shifting or slipping during transport, thus ensuring the injured person's safety and stability. The carrying strap 11 allows the transport personnel to carry the stretcher on their back, freeing their hands and facilitating flexible movement in complex terrain or confined spaces, such as going up and down stairs or traversing obstacles. This improves the flexibility and efficiency of stretcher carrying, greatly reduces the strain on the transport personnel's arms, effectively alleviates their fatigue, and is conducive to the continuous transport of the injured person, thus improving the efficiency and sustainability of the transport.

[0071] The first bracket 1 is equipped with folding feet 9 on both sides, the third bracket 3 is equipped with folding wheels 10 on both sides, and the third bracket 3 is provided with a movable groove 32. The movable groove 32 is provided with a foot baffle 31, which is connected to the movable groove 32 by a pivot.

[0072] The technical effects of the above-mentioned technical solution are as follows: Both the folding support legs 9 and the folding wheels 10 have folding functions, which can be folded and stored when not in use, without increasing the volume of the stretcher, making it easy to carry and store. When needed, they can be quickly unfolded, making operation simple and improving the practicality and emergency response speed of the stretcher. When the stretcher is placed on the ground, unfolding the folding support legs 9 and the folding wheels 10 can support the stretcher and ensure its stable placement. The folding wheels 10 provide convenience when the stretcher needs to be moved, especially when there are not enough transport personnel, allowing one person to push the stretcher to move, making the stretcher more versatile and flexible. The design of the movable groove 32 and the foot guard 31 provides flexible placement and protection for the injured person's feet, meeting the comfort and safety of the injured person during the transport process. Furthermore, the foot guard 31 can be rotated and adjusted through the pivot, and can also be folded and stored when not in use, without increasing the volume of the stretcher.

[0073] To address the technical problem that existing functions are too limited, only capable of basic transport, and unable to monitor vital signs in real time, thus hindering timely understanding of the injured's condition and early detection of potential dangers, ultimately delaying emergency treatment, please refer to [link to relevant documentation]. Figure 6 This embodiment provides the following technical solution:

[0074] The intelligent patient transport stretcher system also includes a vital signs monitoring system and a cloud-based analysis platform;

[0075] The vital signs monitoring system is configured to monitor the vital signs data and body temperature data of the injured person in real time through various sensors installed on the upper strap 6. The vital signs data include heart rate data, respiratory data and blood oxygen saturation data.

[0076] The real-time monitored vital signs data and body temperature data are compressed and segmented before being transmitted to the cloud analysis platform. The segmentation process determines the possible segmentation range based on network quality assessment indicators, rule base matching results, and policy priority analysis. It also analyzes the current data transmission success status and the possible segmentation range to determine the actual segmentation size of the data, thereby achieving dynamic segmentation optimization.

[0077] The cloud-based analysis platform is configured to analyze the real-time monitored vital sign data and body temperature data, and to feed back the real-time monitored vital sign data, body temperature data, and analysis results to the remote monitoring personnel. The analysis results include:

[0078] If the vital signs data show abnormalities, an alert will be issued through the sound and light device 12 on the first support 1, so that rescuers can detect the dangerous situation of the injured person at the first time, take timely first aid measures, and prevent the injury from worsening.

[0079] If abnormal body temperature data is detected, heating pads installed in the support cloth 4, upper strap 6, and lower strap 7 will maintain the injured person's body temperature, enabling rescuers to detect the injured person's dangerous condition immediately and take timely first aid measures to prevent the injury from worsening.

[0080] The technical effects of the above-mentioned solution are as follows: The vital signs monitoring system, by setting various sensors on the upper strap 6, can monitor the vital signs and body temperature data of the injured in real time, providing rescuers with real-time and accurate information on the injured's physical condition. This allows rescuers to promptly detect changes in the injured's condition and take appropriate treatment measures in advance, improving the targeting and effectiveness of the rescue. The cloud analysis platform analyzes the monitored data, helping on-site personnel to better cope with various emergencies, optimize on-site treatment, and improve the quality of rescue. At the same time, the cloud analysis platform feeds back the monitored data and analysis results to remote monitoring personnel, realizing real-time information sharing between the rescue site and remote medical experts. Remote medical experts can use this data to promptly grasp the vital signs information of the injured, providing professional medical guidance and suggestions for subsequent treatment and diagnosis. Through the vital signs monitoring system and the cloud analysis platform, the traditional stretcher's single function of only carrying is changed, enabling timely monitoring of the injured's health status.

[0081] Vital signs monitoring system, including:

[0082] The data acquisition module is configured to deploy various sensors on the upper strap 6. By attaching the sensors to the injured person's body, the module can monitor the injured person's vital signs and body temperature data in real time. The vital signs data include heart rate data, respiratory data, and blood oxygen saturation data.

[0083] The data preprocessing module is configured to preprocess vital sign data and body temperature data, including:

[0084] By removing invalid, duplicate, and abnormal data from vital sign and body temperature data, the original collected data is purified, improving the purity and validity of the data and avoiding misjudgments or analytical biases caused by data quality issues.

[0085] By employing filtering algorithms to remove noise from vital sign data and body temperature data, the influence of interference factors can be effectively reduced, making the data more accurately reflect the actual vital signs of the injured.

[0086] The data transmission module is configured to compress the pre-processed vital sign data and body temperature data and transmit them to the cloud analysis platform, which is the vital sign monitoring system and the cloud analysis platform.

[0087] The technical effects of the above solution are as follows: The data acquisition module deploys various sensors on the upper strap 6, closely fitting the injured person's body. It can monitor vital signs such as heart rate, respiration, and blood oxygen saturation, as well as body temperature data in real time and accurately, providing a reliable basis for subsequent analysis and decision-making. Covering the monitoring of multiple key vital signs, it can not only reflect the basic physiological state of the injured person, but also promptly capture any abnormal changes that may occur, providing rescuers with more comprehensive information about the injured person and helping to more accurately assess the severity of the injured person's condition and their urgent needs. The data preprocessing module purifies the original acquired data by removing invalid, duplicate, and abnormal data, as well as noise, improving the purity and effectiveness of the data and ensuring the credibility and usability of the data transmitted and analyzed subsequently. The data transmission module compresses the preprocessed data before transmitting it to the cloud analysis platform, reducing the amount of data transmitted, improving transmission efficiency, and saving communication resources and time costs. In emergency rescue scenarios, fast and stable data transmission is crucial, ensuring that monitoring data is delivered to the cloud for analysis and processing in a timely manner, avoiding information delays caused by data transmission delays.

[0088] The data transmission module includes:

[0089] The data compression module is configured to compress vital sign data and body temperature data. After compression, the vital sign data and body temperature data are packaged and data information is added, including type identifier, data timestamp, data source device ID and data packet sequence number.

[0090] The data fragmentation module is configured to fragment the packaged data packet, split the data packet into multiple fragments, transmit each fragment independently, and add fragment sequence number and total fragment number information to each fragment.

[0091] The transmission monitoring module is configured to monitor various quality indicators during the data transmission process in real time, including transmission success rate, transmission delay, packet loss rate, and bit error rate. By statistically analyzing these indicators, it can determine whether any problems have occurred during the transmission process. If problems occur, it can promptly feed back the monitored quality indicators and problem information to maintenance personnel.

[0092] The technical effects of the above solution are as follows: The data compression module can effectively reduce the volume of vital sign data and body temperature data, enabling more data to be transmitted in the same amount of time, reducing transmission delay, and ensuring that remote monitoring personnel can obtain the latest information on the injured in a timely manner, providing real-time basis for rescue decisions. After compression, the data is packaged and information such as type identifier, data timestamp, data source device ID, and data packet sequence number is added, making the data more standardized, easy to identify and manage. Remote monitoring personnel can quickly distinguish different types of monitoring data, understand the data collection time and source device, and facilitate data organization, analysis, and traceability. The data fragmentation module splits the data packet into multiple fragments for independent transmission, reducing the impact of the loss of a single data packet on the overall data. Even if some fragments are lost or erroneous, as long as enough fragments are received, the complete data can still be restored, improving the reliability of data transmission. The transmission monitoring module monitors the quality indicators during the data transmission process in real time, such as transmission success rate, transmission delay, packet loss rate, and bit error rate. Once a transmission problem is detected, the relevant indicators and problem information can be quickly fed back to maintenance personnel, thereby enabling targeted optimization and improvement, improving the overall quality and efficiency of data transmission, and providing reliable communication support for remote monitoring and rescue of the injured.

[0093] The data sharding module further includes:

[0094] The transmission network status is evaluated in real time according to the set evaluation interval to obtain quality evaluation indicators;

[0095] The acquired quality assessment indicators are used as screening criteria to match the initial sharding adjustment strategy from the preset rule base.

[0096] If there is only a single initial sharding adjustment strategy, then the currently obtained initial sharding adjustment strategy will be used as the actual sharding adjustment strategy.

[0097] If there are multiple initial sharding adjustment strategies and all have the same adjustment direction, then extract the maximum adjustment magnitude and combine it with the adjustment direction to generate the actual sharding adjustment strategy.

[0098] If there are multiple initial sharding adjustment strategies and the adjustment directions are not all the same, then obtain the corresponding rule-related indicators for each initial sharding adjustment strategy.

[0099] By combining the preset priority score of the rule association index with the effective value of the strategy, the priority association score of each initial shard adjustment strategy is determined;

[0100] The initial sharding adjustment strategies are sorted from largest to smallest according to the priority association score to obtain a strategy priority list;

[0101] By comparing and analyzing the adjustment direction and priority correlation score difference of the top two strategies in the strategy priority list, the actual sharding adjustment strategy is determined.

[0102] Using the actual sharding adjustment strategy, the initial sharding size of the current data is adjusted to obtain the possible range of sharding.

[0103] Extract the probability of successful transmission of current data within a preset time period and compare it with a preset success threshold determined based on data priority;

[0104] If the comparison result is positive, then the middle value is selected from the possible range of the fragments as the actual fragment size of the current data;

[0105] If the comparison result is negative, the data-priority adjustment direction is adjusted according to the upper or lower limit of the range extracted from the possible range of the fragments to obtain the actual fragment size of the current data.

[0106] In this embodiment, the evaluation interval refers to a pre-set time interval used to periodically evaluate the transmission network status, such as 10 seconds; the transmission network status refers to the real-time status of the data transmission network; the quality evaluation index refers to the index used to measure network quality, specifically including bandwidth, packet loss rate, latency, and jitter.

[0107] In this embodiment, each rule in the preset rule base defines specific network quality conditions (such as thresholds for bandwidth, packet loss rate, latency, and jitter) and corresponding fragmentation adjustment strategies (such as increasing or decreasing fragment size). These rules are pre-defined by combining expert experience, historical data analysis, and other methods. For example, there are rules such as: if bandwidth > 10Mbps and packet loss rate < 1%, then the fragment size increases by 1KB; if latency < 50ms and jitter < 10ms, then the fragment size increases by 200B. The initial fragmentation adjustment strategy refers to the preliminary fragmentation adjustment scheme obtained by matching the rules base according to the quality assessment indicators. The adjustment direction includes both increasing and decreasing directions. The maximum adjustment magnitude refers to the adjustment value of the strategy with the largest adjustment magnitude (adjustment amount) among multiple initial strategies with the same adjustment direction.

[0108] In this embodiment, the rule-related indicators refer to the quality assessment indicators used to filter out the current strategy. For example, based on the current quality assessment indicator 1 (bandwidth > 10Mbps) and quality assessment indicator 2 (packet loss rate < 1%), the initial fragmentation adjustment strategy 1 is obtained from the preset rule base: the fragment size is increased by 1KB. At this time, the rule-related indicators refer to bandwidth and packet loss rate.

[0109] In this embodiment, the preset priority score refers to the weighted score pre-set for the quality assessment index, and the value range is [missing value]. The first metric is used to evaluate the importance of indicators in characterizing network status; the second metric is used to represent the actual effect of the current strategy in historical applications, generally referring to the increase in success rate over a period of time (e.g., 1 hour); the third metric is obtained by first calculating the sum of the preset priority scores of all quality evaluation indicators selected for the current strategy, and then normalizing the weighted average of the sum of priority scores and the strategy effective value. The weights assigned to the sum of priority scores and the strategy effective value are obtained by solving a matrix constructed using the analytic hierarchy process (AHP) for pairwise comparisons and scoring, and their values ​​range from [value missing]. The strategy priority list refers to the list after the initial sharding adjustment strategies are sorted from largest to smallest according to their priority association scores.

[0110] In this embodiment, if the adjustment directions of the first and second strategies in the pre-listed strategy are the same or different, and the priority association score difference exceeds the baseline score threshold, then the first strategy is used as the actual sharding adjustment strategy.

[0111] If the adjustment directions of the first and second strategies in the pre-listed strategies are inconsistent, and the difference in priority association scores does not exceed the baseline score threshold, then the two strategies are compromised based on the priority association scores to generate the actual sharding adjustment strategy.

[0112] The benchmark score threshold generally refers to 5% of the current maximum priority association score; the compromise process specifically refers to the method of generating the final strategy by compromising between the two strategies when the adjustment directions of the first and second strategies in the strategy priority list are inconsistent and the difference in priority association scores does not exceed the benchmark score threshold.

[0113] In this embodiment, for example, there is a first-place strategy. Increase fragment size by 100 bytes (preferred association score = 0.9), second strategy. Fragment size reduced by 50 bytes (preferred association score = 0.88); baseline score threshold = ;

[0114] At this point, the first-mover strategy Second-hand strategy If the priority correlation score difference of 0.02 does not exceed the baseline score threshold of 0.045, then the compromise adjustment value = (100B × 0.9 + (-50B) × 0.88) / (0.9 + 0.88) ≈ 25.8B (rounded).

[0115] The final actual fragmentation adjustment strategy is generated: the fragment size is increased by 25.8B.

[0116] In this embodiment, the initial fragment size refers to the fragment size before the current data is fragmented; the actual fragment adjustment strategy refers to the fragment size adjustment scheme finally determined after analyzing the network quality assessment indicators, rule base matching results and strategy priority; the possible fragment range refers to the upper and lower limits calculated by rounding based on the initial fragment size, combined with the adjustment range, adjustment direction and set allowable fluctuation (e.g. ±5%) in the actual fragment adjustment strategy.

[0117] For example, if the initial fragment size is defined as 1KB, and the actual fragment adjustment strategy is "increase by 1KB", with an allowable fluctuation of ±5%, then the possible fragment size range is: [1.05KB, 1.95KB].

[0118] In this embodiment, the preset time period refers to the time window used to calculate the probability of successful data transmission; the probability of successful transmission refers to the proportion of the number of successful data transmissions within the preset time period to the total number of transmissions; the data priority refers to the level pre-classified according to the importance of the data, for example, vital sign data is of high priority and body temperature data is of low priority; the preset success threshold refers to the pre-determined target value for transmission success rate, with different data priorities corresponding to different thresholds; the comparison result refers to the result of subtracting the corresponding preset success threshold from the probability of successful transmission of the current data.

[0119] In this embodiment, the data priority adjustment direction refers to the configuration of the fragment size adjustment direction based on the data priority. That is, if the data priority is high, the data priority adjustment direction is to reduce the fragment size, in order to reduce the impact of a single data transmission failure. If the data priority is low, the data priority adjustment direction is to increase the fragment size, in order to improve transmission efficiency.

[0120] In this embodiment, when the data priority adjustment direction is to increase the fragment size, the upper limit of the range is extracted from the possible range of fragments; when the data priority adjustment direction is to decrease the fragment size, the lower limit of the range is extracted from the possible range of fragments.

[0121] In this embodiment, for example, there is data The data priority is high priority, the success rate of transmission within the preset time period is 96%, the corresponding preset success threshold for high priority is 95%, and the possible range of fragments is [1.05KB, 1.95KB].

[0122] At this point, the comparison result = 96% - 95% = 1% > 0, which is positive. Therefore, the median value, 1.5KB, is selected from the possible fragment range [1.05KB, 1.95KB] as the current data. The actual fragment size;

[0123] For example, there is data The data priority is low priority, the success rate of transmission within the preset time period is 90%, the corresponding preset success threshold for low priority is 92%, and the possible range of fragments is [1.25KB, 1.75KB].

[0124] At this point, the comparison result = 90% - 92% = -2% < 0, which is negative. Based on the low priority of the data, the data priority adjustment direction is determined to increase the fragment size. Therefore, the upper limit of the range of 1.75KB is extracted from the possible fragment range [1.25KB, 1.75KB]. The upper limit of the range of 1.75KB is adjusted to obtain the current data. Actual fragment size ;

[0125] For example, there is data The data priority is high priority, the success rate of transmission within the preset time period is 90%, the corresponding preset success threshold for high priority is 95%, and the corresponding possible fragment range is [1.35KB, 1.65KB].

[0126] At this point, the comparison result = 90% - 95% = -5% < 0, which is negative. Based on the high priority of the data, the data priority adjustment direction is determined to be to reduce the fragment size. Therefore, the lower limit of the range of 1.35KB is extracted from the possible fragment range [1.35KB, 1.65KB]. The lower limit of the range of 1.35KB is adjusted to obtain the current data. Actual fragment size .

[0127] The beneficial effects of the above technical solution are as follows: by utilizing the actual fragmentation adjustment strategy determined after analysis based on network quality assessment indicators, rule base matching results, and policy priority, the possible fragmentation range can be obtained. Then, by combining the current successful data transmission status with the possible fragmentation range, the actual fragmentation size of the data can be determined. This can effectively achieve dynamic fragmentation optimization, thereby helping to improve data transmission efficiency and reliability.

[0128] The working principle of the above technical solution is as follows: First, the transmission network status is evaluated in real time according to a set evaluation interval to generate quality evaluation indicators. Then, using the obtained quality evaluation indicators as screening conditions, an initial fragmentation adjustment strategy is obtained by matching from a preset rule base. If only a single strategy exists, it is directly used as the actual fragmentation adjustment strategy. If multiple strategies exist and their adjustment directions are consistent, the maximum adjustment magnitude is extracted and combined with the adjustment direction to generate the final strategy. If the adjustment directions are inconsistent, the priority association score of each strategy is calculated and sorted to obtain a strategy priority list. Subsequently, the top two strategies in the list are compared and analyzed to determine the actual fragmentation adjustment strategy. Then, the initial fragmentation size of the current data is adjusted using the actual fragmentation adjustment strategy to obtain the possible fragmentation range. Next, the success transmission probability of the current data within a preset time period is extracted and compared with a preset success threshold determined based on data priority. If the comparison result is positive, the median value is selected from the possible fragmentation range as the actual fragmentation size. If the comparison result is negative, the upper or lower limit of the range is extracted from the possible fragmentation range according to the data priority adjustment direction and adjusted to obtain the actual fragmentation size of the current data.

[0129] Cloud-based analytics platforms, including:

[0130] The data analysis module is configured to compare real-time monitored vital sign data and body temperature data with preset thresholds, analyze whether there are any abnormalities in the vital sign data and body temperature data based on the comparison results, determine the abnormality score of the vital sign data, and then determine the abnormality level based on the abnormality score.

[0131] The preset threshold is specifically as follows:

[0132] The threshold for heart rate data is 40-300 beats per minute. It should be noted that some injured persons may have a slow heart rate (i.e., more than 40 beats per minute), or some injured persons may have a heart rate of 160-170 beats per minute due to heart disease.

[0133] Threshold for respiratory data: i.e. respiratory rate, is 12-20 breaths / minute;

[0134] The threshold for blood oxygen saturation data is 90%~100%.

[0135] The threshold for body temperature data is 35.5℃ ~ 37.5℃;

[0136] The early warning and adjustment module is configured to issue early warnings or adjust the temperature based on the analysis results from the data analysis module. Specifically:

[0137] If the analysis results indicate abnormalities in vital sign data, an early warning command will be immediately generated based on the level of abnormality and sent to the audio-visual device 12. The audio-visual device 12 will then play a sound and flash a light to alert the handling personnel.

[0138] If the analysis results show abnormalities in body temperature data, a control command is immediately generated. The control command signal controls the heating pads on the support cloth 4, upper strap 6, and lower strap 7 to provide warmth to the injured person until the injured person's body temperature is maintained within the set threshold range.

[0139] The feedback interaction module is configured to provide an interactive interface for remote monitoring personnel. On the interactive interface, the vital signs data and body temperature data of the injured person are displayed in real time through visual icons and graphics, as well as the analysis results of the data analysis module. At the same time, the warning commands sent by the warning and adjustment module to the sound and light device 12 are displayed in real time, as well as the working parameters of the heating element are adjusted.

[0140] In this embodiment, if the real-time monitored vital signs data or body temperature data does not fall within the corresponding preset threshold range, it is determined that the vital signs data or body temperature data is abnormal.

[0141] In this embodiment, the formula for calculating the data anomaly score is as follows:

[0142]

[0143] In the formula, Y represents the score of abnormal performance of vital signs data; This refers to the amount of vital sign data that exceeds a preset threshold. This represents the total amount of vital sign data, with a value of 3, specifically referring to heart rate data, respiratory data, and blood oxygen saturation data. This represents the frequency of abnormal situations for the i-th vital sign data that exceeds the preset threshold within a preset time period. This represents the weight of the impact of data anomaly frequency on the degree of abnormality in analyzed vital signs, with a value range of [value missing]. ; This represents the upper limit of the preset threshold corresponding to the i-th vital sign data that exceeds the preset threshold. This represents the lower limit of the preset threshold corresponding to the i-th vital characteristic data that exceeds the preset threshold. This is represented by the value of the i-th vital sign data that exceeds the preset threshold. This represents the weight of the impact of data anomaly degree on the analysis of vital sign anomaly degree, with a value range of [value missing]. ;

[0144] The weights assigned to the frequency and severity of data anomalies are obtained by solving a matrix constructed using the analytic hierarchy process (AHP) for pairwise comparisons and scoring. The preset time period refers to a pre-defined time range, such as one day, for acquiring anomaly analysis data of vital signs. The frequency of anomalies refers to the number of times historical values ​​of vital signs data that currently exceed the preset threshold exceed the preset threshold range within the preset time period.

[0145] In this embodiment, the anomaly performance level is determined by the anomaly representation value (within a range of 100%) after normalization of the data anomaly performance score. The anomaly level is used as the matching condition from a preset anomaly level mapping table. This table consists of a series of anomaly characteristic numerical ranges and corresponding anomaly levels, including mild, moderate, and severe levels to reflect the severity of data anomalies. For example, the anomaly characteristic numerical range is... The anomaly level is mild, and the numerical range of the anomaly is [range missing]. The anomaly level is moderate, and the numerical range of the anomaly characteristics is [range missing]. The abnormality level is severe.

[0146] In this embodiment, different warning methods and generated warning commands correspond to different levels of abnormality. The significance of this is to take more targeted and appropriate warning measures based on the severity of the abnormality in the injured person's vital signs data, so that transport personnel or rescue personnel can quickly and accurately understand the urgency of the injured person's current condition, thereby facilitating the rational allocation of rescue resources. For example, when the level of abnormality in the injured person's vital signs data is mild, a warning command is generated to control the sound and light device 12 to emit a soft, long-interval sound, reminding transport personnel to observe the injured person's condition. When the level of abnormality is moderate, a warning command is generated to control the sound and light device 12 to emit a rapid sound and flashing lights, reminding transport personnel to check the injured person's condition as soon as possible and prepare for further treatment. When the level of abnormality is severe, a warning command is generated to control the sound and light device 12 to emit a continuous, loud alarm sound and a strong light signal, reminding transport personnel to immediately provide emergency rescue to the injured person.

[0147] The beneficial effects of the above technical solution are as follows: by calculating the abnormal performance score of the data, the degree of abnormality of the vital signs data of the injured can be quantified, providing the transport personnel with an accurate basis for assessing the condition of the injured; determining the level of abnormal performance based on the abnormal performance score can provide an effective basis for generating targeted early warning instructions, making the subsequent rescue measures more scientific, and thus helping to ensure that the transport personnel can respond quickly according to the urgency of the injured's condition.

[0148] The technical effects of the above solution are as follows: The data analysis module compares the real-time monitored vital sign data and body temperature data with preset thresholds (thresholds are set based on the normal physiological index range), which can accurately determine whether any data is abnormal, ensuring the accuracy and reliability of the assessment of the injured person's physical condition. Once the data exceeds or falls below the normal threshold, it can react quickly and promptly detect abnormal changes in the injured person's vital signs, providing timely basis for subsequent early warning and treatment, and avoiding delays in rescue due to data lag. Based on the data analysis results, when the vital sign data is abnormal, the early warning and adjustment module immediately generates an early warning command and sends it to the sound and light device 12. Through the dual reminder of sound and light, it quickly attracts the attention of the transport personnel, enabling them to take appropriate first aid measures at the first time, improving the timeliness and effectiveness of the rescue. When the body temperature data is abnormal, it automatically generates an early warning command. The system generates control commands to precisely adjust the temperature of the heating elements on the support fabric 4, upper strap 6, and lower strap 7, providing warmth to the injured until their body temperature returns to the normal threshold range. This intelligent adjustment function effectively addresses low-temperature environments or hypothermia, reducing physiological risks caused by abnormal body temperature and ensuring the safety of the injured. The feedback and interaction module provides remote monitoring personnel with an intuitive interface, displaying real-time vital signs, body temperature data, and analysis results through visual icons and graphics. This allows remote monitoring personnel to clearly and quickly understand the latest condition of the injured, facilitating accurate judgment and decision-making. The cloud-based analysis platform, through data analysis, early warning reminders, and feedback interaction, provides intelligent decision-making support for the rescue process, enabling rescue personnel to respond more scientifically and rationally to various injured situations, improving the professionalism and success rate of the rescue.

[0149] Working Principle: The design of the connecting components allows for easy connection and folding of the first support 1, the second support 2, and the third support 3. With the cooperation of the upper strap 6 and the carrying strap 11, the folded stretcher can be carried on the body, greatly reducing the strain on the arms and effectively alleviating the fatigue of the transport personnel. This facilitates continuous transport of the injured, improving efficiency and sustainability. The third support 3 is equipped with folding wheels 10 on both sides, allowing for single-person transport when there are insufficient personnel. The vital signs monitoring system monitors the injured person's vital signs and body temperature in real time, compressing, segmenting, and monitoring the data transmission to improve efficiency and ensure data integrity. Analysis of the monitored data through a cloud-based analysis platform allows for timely detection of abnormalities, enabling timely warnings or maintenance of stable body temperature. Combined with the vital signs monitoring system, real-time monitoring of the injured person's physical condition is achieved, moving beyond the traditional single function of a stretcher to include transport and enabling timely assessment of the injured person's health status.

[0150] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0151] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. An intelligent patient transport stretcher system, comprising a first support (1), a second support (2), a third support (3), a support fabric (4), and a connecting assembly (5), characterized in that, The patient transport stretcher consists of a first support (1), a second support (2), a third support (3), and a support cloth (4). The first support (1), the second support (2), and the third support (3) are connected to each other by a connecting component (5). The support cloth (4) is laid on the frame formed by the first support (1), the second support (2), and the third support (3). An upper strap (6) and a lower strap (7) are respectively provided above and below the support cloth (4). Heating pads are provided inside the support cloth (4), the upper strap (6), and the lower strap (7). It also includes vital sign monitoring systems and cloud-based analytics platforms; The vital signs monitoring system is configured to monitor the vital signs data and body temperature data of the injured person in real time through various sensors set on the upper strap (6). The vital signs data include heart rate data, respiratory data and blood oxygen saturation data. The real-time monitored vital signs data and body temperature data are compressed and segmented before being transmitted to the cloud analysis platform. The segmentation process determines the possible segmentation range based on network quality assessment indicators, rule base matching results and strategy priority analysis. It also analyzes the current data transmission success status and the possible segmentation range to determine the actual segmentation size of the data and achieve dynamic segmentation optimization. The fragmentation process includes: The transmission network status is evaluated in real time according to the set evaluation interval to obtain quality evaluation indicators; The acquired quality assessment indicators are used as screening criteria to match the initial sharding adjustment strategy from the preset rule base. If there is only a single initial sharding adjustment strategy, then the currently obtained initial sharding adjustment strategy will be used as the actual sharding adjustment strategy. If there are multiple initial sharding adjustment strategies and all have the same adjustment direction, then extract the maximum adjustment magnitude and combine it with the adjustment direction to generate the actual sharding adjustment strategy. If there are multiple initial sharding adjustment strategies and the adjustment directions are not all the same, then obtain the corresponding rule-related indicators for each initial sharding adjustment strategy. By combining the preset priority score of the rule association index with the effective value of the strategy, the priority association score of each initial shard adjustment strategy is determined; The initial sharding adjustment strategies are sorted from largest to smallest according to the priority association score to obtain a strategy priority list; By comparing and analyzing the adjustment direction and priority correlation score difference of the top two strategies in the strategy priority list, the actual sharding adjustment strategy is determined. Using the actual sharding adjustment strategy, the initial sharding size of the current data is adjusted to obtain the possible range of sharding. Extract the probability of successful transmission of current data within a preset time period and compare it with a preset success threshold determined based on data priority; If the comparison result is positive, then the middle value is selected from the possible range of the fragments as the actual fragment size of the current data; If the comparison result is negative, the data-priority adjustment direction is adjusted according to the upper or lower limit of the range extracted from the possible range of the fragments to obtain the actual fragment size of the current data. The preset priority score is a pre-defined weighted score for the quality assessment indicators, with a value range of (0,1), used to evaluate the importance of the indicators in representing the network status; the strategy effectiveness value represents the actual effect of the current strategy in historical applications; the priority correlation score is obtained by calculating the sum of the preset priority scores of all quality assessment indicators of the current strategy, and then normalizing the weighted average of the sum of priority scores and the strategy effectiveness value. The weights assigned to the sum of priority scores and the strategy effectiveness value are obtained by solving the matrix constructed by pairwise comparison and scoring using the analytic hierarchy process, with a value range of (0,1); the strategy priority list is formed by sorting the initial partitioning adjustment strategies in descending order of priority correlation scores. The strategy is as follows: If the adjustment directions of the first and second strategies in the pre-listed strategy are the same, or if they are different, and the difference in priority association scores exceeds the baseline score threshold, then the first strategy is used as the actual sharding adjustment strategy. If the adjustment directions of the first and second strategies in the pre-listed strategy are different, and the difference in priority association scores does not exceed the baseline score threshold, then a compromise is performed on the two strategies based on the priority association scores to generate the actual sharding adjustment strategy. The baseline score threshold is set to 5% of the current maximum priority association score. The compromise is a method for generating the final strategy by compromising the current two strategies when the adjustment directions of the first and second strategies in the priority list are different and the difference in priority association scores does not exceed the baseline score threshold. The cloud-based analysis platform is configured to compare and analyze the real-time monitored vital signs data and body temperature data with preset thresholds, and to feed back the real-time monitored vital signs data and body temperature data and analysis results to remote monitoring personnel. The analysis results include: if the vital signs data are abnormal, an alert is issued through the sound and light device (12) on the first support (1); if the body temperature data is abnormal, the body temperature of the injured person is maintained by heating pads installed in the support cloth (4), upper strap (6) and lower strap (7). The cloud-based analytics platform includes: The data analysis module is configured to compare real-time monitored vital sign data and body temperature data with preset thresholds, analyze whether there are any abnormalities in the vital sign data and body temperature data based on the comparison results, determine the abnormality score of the vital sign data, and then determine the abnormality level based on the abnormality score. The early warning and adjustment module is configured to issue early warning reminders or temperature adjustments based on the analysis results of the data analysis module. Specifically, if the analysis result shows that the vital signs data is abnormal, an early warning instruction will be generated immediately in combination with the level of abnormality and sent to the sound and light device (12). The sound and light device (12) will play a sound and flash a light to remind the transport personnel. If the analysis result shows that the body temperature data is abnormal, a control instruction will be generated immediately. The control instruction signal will control the heating pads on the carrying cloth (4), upper strap (6) and lower strap (7) to keep the injured warm until the injured person's body temperature is kept within the set threshold range. The feedback interaction module is configured to provide an interactive interface for remote monitoring personnel. On the interactive interface, the vital signs data and body temperature data of the injured person and the analysis results of the data analysis module are displayed in real time through visual icons and graphics. At the same time, the warning instructions sent by the warning and adjustment module to the sound and light device (12) and the working parameters of the heating element are displayed in real time. The formula for calculating the data anomaly score is as follows: In the formula, Y represents the score of abnormal performance of vital signs data; This refers to the amount of vital sign data that exceeds a preset threshold. This represents the total amount of vital sign data, with a value of 3, specifically referring to heart rate data, respiratory data, and blood oxygen saturation data. This represents the frequency of abnormal situations for the i-th vital sign data that exceeds the preset threshold within a preset time period. This represents the weight of the impact of data anomaly frequency on the degree of abnormality in analyzed vital signs, with a value range of [value missing]. ; This represents the upper limit of the preset threshold corresponding to the i-th vital sign data that exceeds the preset threshold. This represents the lower limit of the preset threshold corresponding to the i-th vital characteristic data that exceeds the preset threshold. This is represented by the value of the i-th vital sign data that exceeds the preset threshold. This represents the weight of the impact of data anomaly degree on the analysis of vital sign anomaly degree, with a value range of [value missing]. ; The weights assigned to the frequency and severity of data anomalies are obtained by solving the matrix constructed by pairwise comparison and scoring using the analytic hierarchy process. The preset time period refers to a pre-defined time range for acquiring anomaly analysis data of vital signs. The frequency of anomalies refers to the number of times the historical values ​​of vital signs data that currently exceed the preset threshold exceed the preset threshold range within the preset time period.

2. The intelligent patient transport stretcher system according to claim 1, characterized in that, The vital signs monitoring system includes: The data acquisition module is configured to deploy various sensors on the upper strap (6). By attaching the sensors to the injured person's body, the vital signs data and body temperature data of the injured person are monitored in real time. Among them, the vital signs data include heart rate data, respiratory data and blood oxygen saturation data. The data preprocessing module is configured to preprocess vital sign data and body temperature data, including: Remove invalid, duplicate, and abnormal data from vital sign and body temperature data; A filtering algorithm is used to remove noise from vital sign data and body temperature data; The data transmission module is configured to compress the pre-processed vital sign data and body temperature data and transmit them to the cloud analysis platform.

3. The intelligent patient transport stretcher system according to claim 2, characterized in that, The data transmission module includes: The data compression module is configured to compress vital sign data and body temperature data. After compression, the vital sign data and body temperature data are packaged and data information is added, including type identifier, data timestamp, data source device ID and data packet sequence number. The data fragmentation module is configured to fragment the packaged data packet, split the data packet into multiple fragments, transmit each fragment independently, and add fragment sequence number and total fragment number information to each fragment. The transmission monitoring module is configured to monitor various quality indicators during the data transmission process in real time, including transmission success rate, transmission delay, packet loss rate, and bit error rate. By statistically analyzing these indicators, it can determine whether any problems have occurred during the transmission process. If problems occur, it can promptly feed back the monitored quality indicators and problem information to maintenance personnel.

4. The intelligent patient transport stretcher system according to claim 1, characterized in that, The preset threshold is specifically: The threshold for heart rate data is 40-300 beats per minute; Threshold for respiratory data: i.e. respiratory rate, is 12-20 breaths / minute; The threshold for blood oxygen saturation data is 90%~100%. The threshold for body temperature data is 35.5℃ to 37.5℃.

5. The intelligent patient transport stretcher system according to claim 1, characterized in that, The connecting component (5) includes a connecting rod (51), a slot (52) and a connecting shaft (53). The slot (52) is located at the connection between the first bracket (1), the second bracket (2) and the third bracket (3). The connecting rod (51) is inserted into the slot (52) and fixed by the connecting shaft (53) to realize the connection and folding of the first bracket (1), the second bracket (2) and the third bracket (3).

6. The intelligent patient transport stretcher system according to claim 1, characterized in that, The upper strap (6) and lower strap (7) are provided with tear-off tape (8) for fixing and adjusting, and the back of the bearing cloth (4) located at the first bracket (1) is provided with a carrying strap (11) for carrying the wounded on a stretcher.

7. The intelligent patient transport stretcher system according to claim 1, characterized in that, Folding feet (9) are installed on both sides of the first bracket (1), folding wheels (10) are installed on both sides of the third bracket (3), and a movable groove (32) is opened on the third bracket (3). A foot baffle (31) is provided on the movable groove (32), and the foot baffle (31) is connected to the movable groove (32) through a rotating shaft.

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