Small emergency first-aid machine with remote video consultation function

Abstract

The present application relates to the field of communication technology, in particular to a small emergency first-aid machine with remote video consultation function. It includes a road detection unit based on a road detection sensor module to monitor road conditions in real time, to ensure that patients receive emergency care in the shortest possible time; an information collection unit based on an information management module to input and manage patient personal information and symptom description; a vital sign monitoring unit based on the data collected by the information collection unit, which applies an abnormality detection algorithm to monitor and analyze the patient's vital signs through a portable vital sign monitoring module; a video consultation unit based on the results of the vital sign monitoring unit analysis, which establishes a video connection with a remote doctor through a remote video module to consult with the patient; a response dispatch unit based on the consultation results of the video consultation unit to provide first aid to the patient and plan subsequent medical treatment. Through video consultation, the patient receives professional guidance from a remote doctor, improving the quality of first aid.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, specifically, a small emergency first-aid machine with remote video consultation function. BACKGROUND

[0002] A small emergency first-aid machine with remote video consultation function is an innovative medical device that integrates advanced robotic technology, communication technology, multimedia processing, artificial intelligence (AI), Internet of Things (IoT), cloud computing, and medical expertise. This machine is designed to be compact and portable, allowing it to be quickly deployed to the scene in emergency situations, providing immediate medical assistance to the injured or ill. It is equipped with a high-definition camera and microphone, enabling real-time video connection with remote experts through high-speed stable 5G networks or other advanced wireless communication technologies, allowing doctors to remotely view patient conditions and guide on-site rescue personnel in preliminary treatment. Built-in sensors can monitor patients' vital signs such as heart rate, blood pressure, and oxygen saturation, and transmit data to the medical team in real time, helping them make more accurate diagnoses. Using AI algorithms, the machine can also analyze collected data to identify potential health risks and assist in decision-making. In addition, it may integrate virtual reality (VR) or augmented reality (AR) technology to provide more intuitive visual assistance, or access the latest medical research and clinical guidelines through a cloud computing platform, ensuring that the medical services provided are up-to-date and most appropriate. The power management system ensures long-term operation without external power supply, suitable for various complex emergency scenarios. In summary, this small emergency first-aid machine is a multifunctional mobile medical station designed to improve the efficiency and quality of emergency medical services, shorten response time, and save more lives.

[0003] In the existing small emergency first-aid machine with remote video consultation function, in remote areas or during natural disasters, or due to poor traffic conditions causing delays, signal instability or complete interruption may occur, affecting remote video consultation emergency care. Although the performance of hardware devices such as high-definition cameras and sensors continues to improve, they may still reduce image and sound quality in complex environments, affecting doctors' accurate judgment of patient conditions. Therefore, a small emergency first-aid machine with remote video consultation function is designed. SUMMARY

[0004] The present application aims to provide a small emergency first-aid machine with remote video consultation function to solve the problem of unstable or completely interrupted signal and affected emergency rescue of remote video consultation due to delay caused by poor traffic conditions in remote areas or natural disasters in the prior art.

[0005] To achieve the above-mentioned purpose, the present application aims to provide a small emergency first-aid machine with remote video consultation function, comprising a road surface detection unit, which monitors road conditions in real time based on a road surface detection sensor module, to ensure that patients receive emergency treatment in the shortest time;

[0006] An information collection unit, which enters and manages personal information and symptom description of patients based on an information management module;

[0007] A vital sign monitoring unit, which monitors and analyzes the vital signs of patients through an abnormality detection algorithm applied by a portable vital sign monitoring module based on the data collected by the information collection unit;

[0008] A video consultation unit, which establishes video connection with remote doctors through a remote video module based on the results of analysis by the vital sign monitoring unit, to consult patients;

[0009] A response dispatching unit, which performs first-aid treatment on patients and plans subsequent medical treatment based on the consultation results of the video consultation unit.

[0010] As a further improvement of the present technical solution, the road surface detection unit comprises a road surface detection sensor module, which is used to perceive road conditions in real time, to help the emergency first-aid machine avoid obstacles and optimize the driving path, and to ensure that patients receive emergency treatment in the shortest time.

[0011] As a further improvement of the present technical solution, the information collection unit comprises an information management module, which comprises a data collection module and a data storage module;

[0012] The data collection module is used to collect and preliminarily process personal information of patients, patient information and vital sign data in real time.

[0013] The data storage module is used to store the collected data and ensure efficient retrieval and long-term preservation of the data.

[0014] As a further improvement of the technical solution, the specific steps involved in monitoring and analyzing the patient's vital signs by the portable vital sign monitoring module applying the anomaly detection algorithm are:

[0015] S4.1, collecting and displaying the patient's vital sign data in real time by the portable vital sign monitoring module;

[0016] S4.2, uploading the vital sign data and analyzing the data by the anomaly detection algorithm;

[0017] S4.3, the system sends an alarm according to the preset threshold.

[0018] As a further improvement of the technical solution, the specific steps involved in S4.2, uploading the vital sign data and analyzing the data by the anomaly detection algorithm are:

[0019] S4.21, transmitting the vital sign data collected by the portable vital sign monitoring module to the database;

[0020] S4.22, preprocessing the received vital sign data;

[0021] S4.23, according to the historical data and medical standards, a baseline model is established for each kind of vital sign data by the Isolation Forest algorithm;

[0022] S4.24, applying the anomaly detection algorithm to identify data points beyond the baseline model range.

[0023] As a further improvement of the technical solution, the specific steps involved in S4.23, according to the historical data and medical standards, a baseline model is established for each kind of vital sign data by the Isolation Forest algorithm are:

[0024] Calculate the average path length:

[0025] For each data point x i , the path length in the tth isolated tree is h t (x i );

[0026] Calculate the average path length E(h(x i )) of the data point x i ;

[0027]

[0028] Where T represents the number of isolated trees, t represents the tth isolated tree, and i represents the index variable.

[0029] Standardized score:

[0030] c(n) = 2H(n - 1) - (2(n - 1) / n);

[0031] wherein n represents the number of samples; H(*) represents the harmonic number; c(n) represents the normalized score;

[0032] Anomaly score:

[0033]

[0034] wherein S(x i ,n) represents the anomaly score;

[0035] The anomaly score is combined with the medical standard to define a comprehensive score:

[0036]

[0037] wherein C(x i ,j) represents the comprehensive score; j represents the index of the vital sign; x i,j represents the jth vital sign value of the data point x i ; L j represents the lower limit of the medical definition of the jth vital sign; U j represents the upper limit of the medical definition of the jth vital sign.

[0038] As a further improvement of the technical solution, in S4.24, the expression involved in applying the anomaly detection algorithm to identify data points that exceed the range of the baseline model is:

[0039]

[0040] wherein Anomalies represents the set of anomaly points; X new represents the new data set; represents the maximum comprehensive score; θ represents the threshold value of anomaly detection.

[0041] As a further improvement of the technical solution, the specific steps involved in establishing a video connection with a remote doctor through the remote video module for a patient consultation are:

[0042] S7.1, based on the results of the sign monitoring unit analysis, determine whether remote video consultation needs to be started;

[0043] S7.2, establish a video connection with a remote doctor through a remote video module to ensure network stability and image clarity;

[0044] S7.3, the doctor observes the patient's condition through the video, and shares the patient's medical records and real-time vital sign data during the video conference;

[0045] S7.4, the doctor makes a diagnosis and treatment suggestion according to the video consultation.

[0046] As a further improvement of the technical solution, the remote video module is used to establish a high-definition video connection with the remote doctor at the scene of emergency, realize remote consultation and real-time medical guidance, transmit high-quality audio and video data through high-speed network, enable the remote doctor to observe the patient's condition, listen to the patient's voice, and view real-time vital sign monitoring data.

[0047] As a further improvement of the technical solution, the specific steps involved in the first aid treatment of the patient and the planning of subsequent medical treatment are:

[0048] S10.1, immediately call emergency medical services and provide accurate location and patient condition;

[0049] S10.2, adjust the first aid measures in time according to the patient's condition;

[0050] S10.3, continuously monitor the patient's vital signs and record changes during the transfer process;

[0051] S10.4, develop a rehabilitation plan after the patient's condition stabilizes.

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

[0053] 1. In the small emergency first aid machine with remote video consultation function, the road conditions are monitored in real time, the driving path is optimized, obstacles and uneven road surfaces are avoided, the transportation time is reduced, and the patient can obtain emergency medical care in the shortest time. The doctor can access these information through the remote video consultation unit, make preparations in advance, and improve the consultation efficiency. Continuous monitoring of the patient's temperature, heart rate, blood pressure, blood oxygen saturation and other key vital signs can timely detect abnormal conditions and guide first aid measures. The portable design makes the monitoring module can be used in any scene, and the first aid personnel can master the patient's state at any time on the scene or during the transfer process.

[0054] 2. In the small emergency first aid machine with remote video consultation function, the professional guidance of the remote doctor is obtained through video consultation, and the quality of first aid is improved. During the video consultation process, the patient's medical records, vital sign data and image materials can be shared in real time, helping the doctor to fully understand the disease and make accurate judgments. According to the real-time condition of the patient, the first aid measures and subsequent treatment plan are flexibly adjusted to ensure the continuity and efficiency of the treatment process. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 The overall flowchart of the present application;

[0056] The meanings of the various numbers in the figure are:

[0057] 1, road detection unit; 11, road detection sensor module; 2, information acquisition unit; 21, information management module; 211, data acquisition module; 212, data storage module; 3, vital sign monitoring unit; 31, portable vital sign monitoring module; 4, video consultation unit; 41, remote video module; 5, response dispatching unit. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0059] EMBODIMENT

[0060] Please refer to Figure 1 As shown in the figure, a small emergency first-aid machine with remote video consultation function is provided, which includes a road detection unit 1. The road detection unit 1 monitors road conditions in real time based on a road detection sensor module 11, to ensure that the patient obtains emergency care in the shortest time.

[0061] In this example, the road detection unit 1 includes a road detection sensor module 11, which is used to sense road conditions in real time, to help the emergency first-aid machine avoid obstacles and optimize the driving path, and to ensure that the patient obtains emergency care in the shortest time.

[0062] Specifically, the road detection sensor module 11 is used to sense road conditions in real time, to help the small emergency first-aid machine avoid obstacles and optimize the driving path, and to ensure that the machine can smoothly and quickly reach the patient's location, so as to provide emergency care for the patient in the shortest time. Through accurate road condition monitoring and intelligent path planning, this unit significantly improves the speed and safety of emergency response, especially on complex or uneven road surfaces, to ensure that the patient can obtain timely medical assistance within the golden rescue time.

[0063] The small emergency first-aid machine with remote video consultation function also includes an information acquisition unit 2, which enters and manages the personal information and symptom description of the patient based on an information management module 21.

[0064] In the embodiment, the information acquisition unit 2 includes an information management module 21, which includes a data acquisition module 211 and a data storage module 212.

[0065] The data collection module 211 is configured to collect and preliminarily process patient information and vital sign data in real time.

[0066] The data storage module 212 is configured to store the collected data and ensure efficient retrieval and long-term storage of the data.

[0067] Specifically, the data collection module 211 is responsible for collecting and preliminarily processing patient information and vital sign data in real time, ensuring that emergency personnel can quickly and accurately record key information of the patient; and the data storage module 212 is configured to securely store these data and support efficient retrieval and long-term storage, so as to quickly call when needed. Through this unit, the small emergency first-aid machine can quickly acquire and manage patient information at the scene of emergency, provide accurate and comprehensive data support for remote video consultation, help doctors make timely and accurate diagnosis and treatment decisions, and thus improve the efficiency of emergency and the success rate of treatment of patients.

[0068] The small emergency first-aid machine with remote video consultation function further comprises a vital sign monitoring unit 3, which monitors and analyzes the vital signs of the patient based on the data collected by the information collection unit 2 through the portable vital sign monitoring module 31 and an abnormality detection algorithm.

[0069] In an embodiment, the specific steps involved in monitoring and analyzing the vital signs of the patient through the portable vital sign monitoring module 31 and an abnormality detection algorithm are as follows:

[0070] S4.1, collecting and displaying the vital sign data of the patient in real time through the portable vital sign monitoring module 31;

[0071] S4.2, uploading the vital sign data and performing data analysis through an abnormality detection algorithm;

[0072] Specifically, the vital sign data includes heart rate, blood pressure, respiratory rate, body temperature, and blood oxygen saturation (SpO2).

[0073] In this example, the specific steps involved in uploading the vital sign data and performing data analysis through an abnormality detection algorithm are as follows:

[0074] S4.21, transmitting the vital sign data collected by the portable vital sign monitoring module to a database;

[0075] S4.22, preprocessing the received vital sign data;

[0076] S4.23, establishing a baseline model for each kind of vital sign data through an isolation forest algorithm according to historical data and medical standards;

[0077] In this example, the steps involved in establishing a baseline model for each vital sign data according to historical data and medical standards by the Isolation Forest algorithm are as follows:

[0078] Calculate the average path length:

[0079] For each data point x i , the path length in the tth isolation tree is h t (x i );

[0080] Calculate the average path length E(h(x i )) of the data point x i ;

[0081]

[0082] where T represents the number of isolation trees; t represents the tth isolation tree; i represents the index variable;

[0083] Standardized score:

[0084] c(n) = 2H(n-1) - (2(n-1) / n);

[0085] where n represents the number of samples; H(*) represents the harmonic number; c(n) represents the standardized score;

[0086] Abnormal score:

[0087]

[0088] where S(x i ,n) represents the abnormal score;

[0089] The abnormal score is combined with the medical standard to define the comprehensive score:

[0090]

[0091] where C(x i ,j) represents the comprehensive score; j represents the index of the vital sign; x i,j represents the jth vital sign value of the data point x i ; L j represents the lower limit of the medical definition of the jth vital sign; U j represents the upper limit of the medical definition of the jth vital sign.

[0092] Specifically, through this process, the vital sign monitoring unit can not only monitor the patient's vital signs in real time, but also accurately identify abnormal situations based on historical data and medical standards, issue timely alerts and provide detailed analysis results. This provides scientific and reliable data support for remote video consultation, helping doctors make more accurate diagnoses and treatment decisions, significantly improving emergency efficiency and patient treatment success rate.

[0093] S4.24, apply anomaly detection algorithm to identify data points beyond the baseline model range.

[0094] In this example, the expression involved in applying the anomaly detection algorithm to identify data points beyond the baseline model range is:

[0095]

[0096] Where Anomalies represents the set of anomaly points; X new represents the new data set; represents the maximum comprehensive score; and θ represents the threshold value of anomaly detection.

[0097] Specifically, the example is:

[0098]

[0099]

[0100] First, the collected vital sign data is transmitted to the database to ensure safe storage and subsequent processing of the data; then, the received data is preprocessed to remove noise and outliers, ensuring the accuracy and consistency of the data; next, according to historical data and medical standards, a baseline model is established for each vital sign using the Isolation Forest algorithm to define the normal range; finally, the anomaly detection algorithm is applied to identify data points beyond the baseline model range, to timely discover potential critical situations and issue alerts. This process not only ensures real-time monitoring and accurate analysis of patient vital signs, but also provides reliable data support for remote video consultation, helping doctors make timely and accurate diagnoses and treatment decisions, significantly improving emergency efficiency and patient treatment success rate.

[0101] S4.3, the system issues an alert according to the preset threshold value.

[0102] Specifically, the portable vital sign monitoring module 31 collects and displays the patient's vital sign data such as heart rate, blood pressure, blood oxygen saturation, etc. in real time, and uploads these data to the system for abnormal detection algorithm analysis. Once the monitored vital signs exceed the preset normal threshold, the system will immediately issue an alarm to alert emergency personnel and remote doctors to potential critical situations. This process ensures that the patient's vital signs are continuously and accurately monitored, helping the emergency team to promptly detect and handle abnormal conditions, providing reliable data support for remote video consultation, and thus improving emergency efficiency and patient treatment success rate.

[0103] The small emergency first aid machine with remote video consultation function also includes a video consultation unit 4, which establishes a video connection with a remote doctor through a remote video module 41 based on the results of the analysis by the vital sign monitoring unit 3, and conducts a consultation for the patient;

[0104] In an embodiment, the specific steps involved in establishing a video connection with a remote doctor through a remote video module 41 for a consultation for the patient are:

[0105] S7.1, based on the results of the analysis by the vital sign monitoring unit 3, determine whether remote video consultation needs to be initiated;

[0106] S7.2, establish a video connection with a remote doctor through a remote video module 41 to ensure network stability and image clarity;

[0107] In this example, the remote video module 41 is used to establish a high-definition video connection with a remote doctor at the scene of the emergency, enabling remote consultation and real-time medical guidance, and transmitting high-quality audio and video data through high-speed networks, allowing the remote doctor to observe the patient's condition, listen to the patient's voice, and view real-time vital sign monitoring data.

[0108] Specifically, this module transmits high-quality audio and video data, allowing the remote doctor to clearly observe the patient's condition, listen to the patient's voice, and view real-time vital sign monitoring data. This not only provides professional medical support for the scene of the emergency, ensuring that the patient receives accurate diagnosis and treatment recommendations in the first instance, but also significantly improves emergency efficiency and treatment success rate, especially in resource-limited or remote areas, greatly expanding the coverage of quality medical services.

[0109] S7.3, the doctor observes the patient's condition through the video and shares the patient's medical records and real-time vital sign data during the video conference;

[0110] S7.4, the doctor provides diagnosis and treatment recommendations based on the video consultation.

[0111] Specifically, through this process, the video consultation unit not only provides timely professional medical support for the patient, but also ensures the scientificity and effectiveness of the first aid measures, significantly improving the efficiency of first aid and the success rate of patient treatment. This remote collaboration method is particularly suitable for remote or resource-limited areas, greatly expanding the coverage of high-quality medical services.

[0112] The small emergency first aid machine with remote video consultation function further comprises a response dispatching unit 5 that performs first aid treatment on the patient and plans subsequent medical treatment based on the consultation result of the video consultation unit 4.

[0113] In an embodiment, the specific steps involved in performing first aid treatment on the patient and planning subsequent medical treatment are as follows:

[0114] S10.1, immediately call emergency medical services and provide accurate location and patient condition;

[0115] S10.2, adjust the first aid measures according to the patient's condition;

[0116] S10.3, continuously monitor the patient's vital signs and record changes during the transfer process;

[0117] S10.4, develop a rehabilitation plan after the patient's condition stabilizes.

[0118] Specifically, through these steps, the response dispatching unit not only ensures the safety and effective treatment of the patient at the scene of the emergency and during the transfer process, but also provides a scientific basis for subsequent rehabilitation treatment, significantly improving the efficiency and quality of the entire first aid process. This integrated first aid system is particularly suitable for resource-limited or remote areas, greatly expanding the coverage of high-quality medical services and improving the survival rate and rehabilitation effect of patients.

[0119] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only preferred examples of the present application and are not intended to limit the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application.

Claims

1. A small emergency rescue machine with remote video consultation function, characterized in that: Comprising a road surface detection unit (1) for real-time monitoring of road conditions based on a road surface detection sensor module (11) to ensure that the patient receives emergency care in the shortest possible time; an information collection unit (2) for entering and managing the personal information and symptom description of the patient based on an information management module (21); a vital sign monitoring unit (3) for monitoring and analyzing the vital signs of the patient by applying an anomaly detection algorithm through a portable vital sign monitoring module (31) based on the data collected by the information collection unit (2); The specific steps involved in monitoring and analyzing the vital signs of the patient by applying an anomaly detection algorithm through a portable vital sign monitoring module (31) are as follows: S4.1, real-time collection and display of patient vital sign data through a portable vital sign monitoring module (31); S4.2, data analysis through an anomaly detection algorithm after uploading vital sign data; S4.3, the system sends an alarm according to the preset threshold; In S4.2, the specific steps involved in data analysis through an anomaly detection algorithm after uploading vital sign data are as follows: S4.21, transmitting the vital sign data collected by the portable vital sign monitoring module to the database; S4.22, preprocessing the received vital sign data; S4.23, establishing a baseline model for each vital sign data through an isolation forest algorithm based on historical data and medical standards; S4.24, applying an anomaly detection algorithm to identify data points outside the baseline model range; a video consultation unit (4) for establishing a video connection with a remote doctor through a remote video module (41) based on the results of the vital sign monitoring unit (3) analysis to conduct a consultation for the patient; a response dispatching unit (5) for emergency treatment of the patient based on the consultation results of the video consultation unit (4) and planning of subsequent medical treatment; The road surface detection unit (1) includes a road surface detection sensor module (11) for real-time sensing of road conditions to help the emergency ambulance avoid obstacles and optimize the driving path to ensure that the patient receives emergency care in the shortest possible time; The information collection unit (2) includes an information management module (21) comprising a data collection module (211) and a data storage module (212); The data collection module (211) is used to collect and preliminarily process patient information and vital sign data in real time; The data storage module (212) is used to store the collected data and ensure efficient retrieval and long-term preservation of the data.

2. A small-sized emergency first-aid machine with remote video consultation function according to claim 1, characterized in that: In S4.23, the steps involved in establishing a baseline model for each vital sign data through an isolation forest algorithm based on historical data and medical standards are as follows: Calculate the average path length: For each data point , the path length in the isolated tree is ; and the path length in the isolated tree is Computing data points of average path length ; ； wherein, represents the number of isolated trees; represents the number of the isolated tree; represents an index variable; Standardized score: ； wherein, represents the number of samples; represents the harmonic number; represents the normalized score; Abnormal score: ； wherein, represents an abnormal score; Abnormal score combined with medical standards to define comprehensive score: ； in, This indicates the overall score; An index representing vital signs; Representing data points The Individual vital signs values; Indicates the first The lower limit of the medical definition of a vital sign; Indicates the first The upper limit of the medical definition of a vital sign.

3. The small-sized emergency first-aid machine with remote video consultation function according to claim 1, characterized in that: In S4.24, the expression involved in applying an anomaly detection algorithm to identify data points that exceed the range of the baseline model is: ； wherein, represents a set of outliers; represents a new data set; represents a maximum composite score; represents a threshold for anomaly detection.

4. The compact emergency medical service machine having a remote video consultation function according to claim 1, characterized by: The specific steps involved in establishing a video connection with a remote doctor through the remote video module (41) for patient consultation are: S7.1, based on the results of the analysis by the vital sign monitoring unit (3), determine whether remote video consultation needs to be started; S7.2, establish a video connection with a remote doctor through the remote video module (41) to ensure network stability and image clarity; S7.3, the doctor observes the patient's condition through the video and shares the patient's medical records and real-time vital sign data during the video conference; S7.4, the doctor proposes diagnosis and treatment suggestions based on the video consultation.

5. A compact emergency medical service machine having a remote video consultation function according to claim 4, characterized in that: In S7.2, the remote video module (41) is used to establish a high-definition video connection with a remote doctor at the scene of the emergency, enabling remote consultation and real-time medical guidance. High-quality audio and video data are transmitted through high-speed networks, allowing the remote doctor to observe the patient's condition, listen to the patient's voice, and view real-time vital sign monitoring data.

6. The compact emergency medical service machine having a remote video consultation function according to claim 1, characterized by: The specific steps involved in providing first aid to the patient and planning subsequent medical treatment are: S10.1, immediately call emergency medical services and provide accurate location and patient condition; S10.2, adjust emergency measures as needed based on the patient's condition; S10.3, continuously monitor the patient's vital signs and record changes during transportation; S10.4, develop a rehabilitation plan after the patient's condition stabilizes.

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