Data processing system and method based on hospital monitoring data

Abstract

The invention discloses a data processing system and method based on hospital monitoring data. The system comprises a personnel information acquisition module, an image information acquisition module, a ward information acquisition module, a data processing module and an information sending module. The personnel information acquisition module is used for acquiring patient information in a ward; the image acquisition module is used for acquiring image information in a hospital; the ward information acquisition module is used for acquiring ward information; the data processing module is used for processing the patient information, obtaining patient warning information, processing image information in a hospital, obtaining abnormal person warning information, abnormal doctor seeing warning information and abnormal occupancy warning information, and processing ward information to obtain ward warning information. According to the invention, more comprehensive hospital monitoring data processing can be carried out, so that the hospital is helped to carry out more intelligent hospital management.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a data processing system and method based on hospital monitoring data. Background Art

[0002] Hospital monitoring data is an important part of hospital operation and management, and is of great significance for improving medical quality and ensuring patient safety. The data processing of hospital monitoring data is a complex and systematic process that requires the joint efforts and collaboration of relevant departments and personnel in the hospital. By strengthening data quality management, data security protection, and breaking the data island phenomenon, the quality and utilization efficiency of hospital monitoring data can be improved, providing strong support for medical quality improvement and patient safety management; The data processing system and method will be applied in the process of hospital monitoring data processing. The data processing system and method will be used to process the hospital detection data, so as to better discover the abnormalities of hospital data and perform corresponding processing.

[0003] Existing data processing systems are mostly single data processing and are not suitable for the complex data environment of hospitals, which makes it impossible to better realize the intelligent management of hospitals and has a certain impact on the use of data processing systems. Therefore, a data processing system and method based on hospital monitoring data are proposed. Summary of the invention

[0004] The technical problem to be solved by the present invention is: how to solve the problem that the existing data processing systems are mostly single data processing and are not suitable for the complex data environment of the hospital, resulting in the inability to better realize the intelligent management of the hospital, which has a certain impact on the use of the data processing system. A data processing system based on hospital monitoring data is provided.

[0005] The present invention solves the above technical problems through the following technical solutions. The present invention includes a personnel information acquisition module, an image information acquisition module, a ward information acquisition module, a data processing module and an information sending module; The personnel information collection module is used to collect patient information in the ward; The image acquisition module is used to collect image information in the hospital, and the image information in the hospital includes image information of people in the hospital, image information of people outside the doctor's office, and image information of the ward corridor; The ward information collection module is used to collect ward information; The data processing module is used to process patient information to obtain patient warning information, process imaging information in the hospital to obtain abnormal personnel warning information, abnormal medical treatment warning information and abnormal occupancy warning information, and process ward information to obtain ward warning information; The information sending module is used to send the patient warning information, abnormal personnel warning information, abnormal medical treatment warning information, abnormal occupancy warning information and ward warning information to a preset receiving terminal after the above information is generated.

[0006] Furthermore, the process of obtaining the patient warning information is as follows: Extract the collected patient information, which includes the patient's real-time location information, the patient's restricted area, and the patient's status information; The patient's real-time location information and patient status information are collected by the collection device worn by the patient; Continuously collect the patient's real-time location information within a single day, process the patient's real-time location information continuously collected within a single day to obtain location evaluation parameters, and generate patient warning information when the location evaluation parameters are abnormal; Process the patient status information to obtain the patient's real-time parameters. When the patient's real-time parameters are abnormal, generate patient warning information; The patient's real-time location information and the patient restricted area are processed. When the patient's real-time location information is outside the patient restricted area, patient warning information is generated. The patient's real-time location information and the patient restricted area are processed to obtain location abnormality parameters. When the location abnormality parameters are abnormal, patient warning information is generated.

[0007] Furthermore, the process of obtaining the position evaluation parameters and the process of abnormality determination are as follows: Extract the real-time location information of patients collected continuously within a single day, and mark the real-time location information of patients as A1, A2, A3...An in the order of collection time, where n is the number of collection times; Connect points A1 and A2 to obtain line segment L1, connect points A2 and A3 to obtain line segment L2... Connect points An-1 and An to obtain line segment Ln-1; Then, the length from line segment L1 to line segment Ln-1 is measured, and the sum of the lengths of line segment L1, line segment L2, ..., line segment Ln-1 is calculated, so as to obtain the position evaluation parameter; Then, the patient's allowed movement distance information is collected. When the position evaluation parameter is greater than the patient's allowed movement distance information, it indicates that there is an abnormality in the position evaluation parameter.

[0008] Furthermore, the process of obtaining the patient's real-time parameters and the process of determining whether the patient's real-time parameters are abnormal are as follows: Extract the collected patient status information, including patient temperature information, patient heart rate information and patient blood pressure information; Collect the duration of the patient's body temperature exceeding the standard temperature range and obtain the duration of abnormal body temperature; Collect the duration of the patient's heart rate information exceeding the standard heart rate range, and obtain the duration of abnormal heart rate; Collect the duration of the patient's blood pressure information exceeding the preset standard range, and obtain the duration of abnormal blood pressure; The duration of abnormal body temperature, abnormal heart rate and abnormal blood pressure constitute the patient's real-time parameters; When any of the patient's real-time parameters is greater than the preset value, it means that the patient's real-time parameters are abnormal; The acquisition process of the position abnormality parameter and the abnormality determination process are as follows: extracting the patient's real-time position information and the patient's restricted area; The real-time location information of the patient is continuously collected m times within a preset time length, and the number of times the real-time location information of the patient is less than the preset value with respect to the patient restricted area is extracted, that is, the location abnormality parameter is obtained. When the location abnormality parameter is greater than the preset value, it indicates that there is an abnormality.

[0009] Furthermore, the collection device worn by the patient is also used to collect wearing status information. When the wearing status information is abnormal, an abnormal warning message of the collection device is generated; The collection device consists of two straps for connection and a collection body; A device for collecting connection force is provided at the connection of the two connected watch straps to collect connection force information after wearing; The wearing status information includes the connection force information, the pressure between the acquisition body and the wearing surface, and the contact surface temperature information; When any two of the connection force information is less than a preset value, the pressure between the collection body and the wearing surface is less than a preset value, and the contact surface temperature information is less than a preset value appear at the same time, an abnormal warning message of the collection device is generated.

[0010] Furthermore, the process of obtaining the abnormal personnel warning information is as follows: Extract the collected image information of people in the hospital, where the image information of people in the hospital is the face images of people who appeared in the hospital in the previous x days; Perform facial recognition processing on the image information of people in the hospital to obtain facial information; Extracting facial images of people whose image information appears more than a preset number of times in the hospital and setting them as marked people; Then, the number of times the marked person appears at the preset location in the hospital in a single day is collected. When the number of times the marked person appears at the preset location in the hospital in a single day exceeds a preset value, the day is marked as an abnormal day; After collecting data for x consecutive days, the number of abnormal days is extracted. When the number of abnormal days is greater than x / 2, an abnormal personnel warning message is generated, x ≥ 7.

[0011] Furthermore, the process of obtaining the abnormal warning information of the medical consultation is as follows: Extract the collected and imported image information of people outside the doctor's office, perform human body recognition on the image information of people outside the doctor's office, and after recognizing the human body, select each human body frame to obtain the human body frame; The human body frame is processed to obtain personnel assessment parameters. When the personnel assessment parameters are abnormal, abnormal medical treatment warning information is generated; The process of obtaining personnel evaluation parameters and determining abnormalities is as follows: Extract the collected human frames, process the human frames, obtain the distance information between the human frames, extract the number of distance information between the human frames that is less than the preset value, that is, obtain the personnel evaluation parameter. When the personnel evaluation parameter is greater than the preset value, it means that the personnel evaluation parameter is abnormal; After the consultation begins, the location of the consulting room entrance is extracted, the number of human body frames within the preset range of the consulting room entrance is extracted, and an evaluation parameter is obtained. When the evaluation parameter is greater than a preset value, an abnormal consultation warning message is generated.

[0012] Furthermore, the abnormal occupancy warning information acquisition process is as follows: Extracting the image information of the ward corridor, the image information of the ward corridor is the image information of the ward corridor road; Preset signs are set up on the ward corridors, and the image information of the ward corridors is used to identify the preset signs. After the preset signs are identified, the real-time preset sign area is collected; Then, the standard area when the preset sign is set is collected, and the ratio of the real-time preset sign area to the standard area is calculated to obtain the evaluation ratio. When the evaluation ratio is less than the preset value, an abnormal occupancy warning message is generated.

[0013] Furthermore, the process of obtaining the ward warning information is as follows: Extract the collected ward information, which includes ward environment temperature information, ward environment humidity information and ward environment dust concentration information; When the ward environment temperature information exceeds the preset range for a preset time, the ward environment humidity information is greater than the preset value for a preset time, or the ward environment dust concentration information is greater than the preset value for a preset time, a ward warning message is generated.

[0014] The present invention also provides a data processing method based on hospital monitoring data, which is implemented based on the above data processing system and includes the following steps: Step 1: Collect patient information in the ward; Step 2: Collect image information of people in the hospital, people outside the doctor's office, and images of ward corridors; Step 3: Collect ward information in the ward; Step 4: Process the patient information and obtain the patient warning information; Step 5: Process the image information of people in the hospital to obtain warning information of abnormal people; Process the image information of people outside the doctor's office to obtain abnormal warning information about the visit; Process the image information of the ward corridor to obtain abnormal occupancy warning information; Step 6: Process the ward information to obtain ward warning information; Step 7: Send each generated warning message to a preset receiving terminal.

[0015] Compared with the prior art, the present invention has the following advantages: the data processing system and method based on hospital monitoring data realizes refined patient management by processing patient data. Through the collection device worn by the patient, the system can obtain the patient's location information in real time, and judge whether the patient exceeds the allowed range of action based on the location evaluation parameters, and timely generate patient warning information, which helps to prevent the patient from getting lost or entering a dangerous area. The system can monitor the patient's body temperature, heart rate, blood pressure and other key physiological parameters in real time, and perform comprehensive processing. Once an abnormality is found, a warning message is immediately generated, which helps medical staff to take rescue measures in time to ensure the safety of the patient. By monitoring the wearing status information of the collection device, the system can timely detect equipment abnormalities, ensure the accuracy and reliability of the data, and avoid false alarms or missed alarms caused by equipment failures. By processing relevant imaging information, the hospital safety management can be intelligentized. The system can identify people who frequently appear in the hospital and determine whether there are abnormalities based on their behavior patterns, which helps the hospital to promptly discover and deal with potential safety hazards.

[0016] By monitoring the flow of people outside the doctor's office, the system can evaluate the congestion level of the treatment area in real time. Once an abnormality is found, it will immediately generate abnormal treatment warning information, which will help the hospital optimize the treatment process and improve treatment efficiency.

[0017] The system can monitor the occupancy of ward corridors in real time and immediately generate warning messages if abnormal occupancy is detected, which helps hospitals keep corridors clear and ensure that people can be evacuated quickly in an emergency.

[0018] By processing ward information, the system can monitor environmental parameters such as temperature, humidity and dust concentration in the ward in real time. Once an abnormality is detected, it will immediately generate ward warning information, which will help the hospital to improve the ward environment in a timely manner and enhance the patient's hospitalization experience.

[0019] This enables integrated processing of hospital monitoring data and more comprehensive and intelligent hospital management, making the system and method more worthy of promotion and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a structural block diagram of the data processing system of the present invention. DETAILED DESCRIPTION

[0021] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0022] like Figure 1 As shown, this embodiment provides a technical solution: a data processing system based on hospital monitoring data, including a personnel information collection module, an image information collection module, a ward information collection module, a data processing module and an information sending module; The personnel information collection module is used to collect patient information in the ward; The image acquisition module is used to collect image information in the hospital, including image information of people in the hospital, image information of people outside the doctor's office, and image information of the ward corridor; The ward information collection module is used to collect ward information; The data processing module is used to process patient information, obtain patient warning information, process imaging information in the hospital, obtain abnormal personnel warning information, abnormal medical treatment warning information and abnormal occupancy warning information, and process ward information to obtain ward warning information; The information sending module is used to send the patient warning information, abnormal personnel warning information, abnormal medical treatment warning information, abnormal occupancy warning information and ward warning information to a preset receiving terminal after the above information is generated.

[0023] The process of obtaining patient warning information is as follows: Extract the collected patient information, which includes the patient's real-time location information, the patient's restricted area, and the patient's status information; The patient's real-time location information and patient status information are collected by the collection device worn by the patient; Continuously collect the patient's real-time location information within a single day, process the patient's real-time location information continuously collected within a single day to obtain location evaluation parameters, and generate patient warning information when the location evaluation parameters are abnormal; Process the patient status information to obtain the patient's real-time parameters. When the patient's real-time parameters are abnormal, generate patient warning information; Processing the patient's real-time location information and the patient restricted area, when the patient's real-time location information is outside the patient restricted area, generating patient warning information, processing the patient's real-time location information and the patient restricted area to obtain location abnormality parameters, when the location abnormality parameters are abnormal, generating patient warning information; Through the above process, real-time monitoring and response are achieved: through the collection device worn by the patient, the system can obtain the patient's real-time location information and status information in real time. This real-time monitoring ensures that medical staff can quickly understand the patient's current condition and respond in time.

[0024] The system processes the real-time location information of patients collected continuously within a single day and generates location assessment parameters. This assessment helps to identify whether the patient is moving as expected, such as whether he frequently leaves the ward or enters a dangerous area. When the location assessment parameters are abnormal, the system immediately generates a warning message, which improves the safety management level of the patient.

[0025] Status monitoring and health warning: The processing of patient status information can obtain the patient's real-time parameters, such as heart rate, blood pressure, etc. When these parameters exceed the normal range, the system will also generate warning information to remind medical staff to pay attention to the patient's health status and take timely intervention measures.

[0026] Restricted area management: The system can monitor the real-time location of patients based on their restricted area information. When a patient enters a restricted area, the system will immediately generate a warning message to prevent the patient from entering dangerous or inappropriate areas. At the same time, by processing the patient's real-time location information and the patient's restricted area, the system can also obtain abnormal location parameters, further improving the accuracy and safety of patient management.

[0027] Improve medical efficiency and quality. Through automated and intelligent data processing, the system can reduce the manual monitoring work of medical staff, allowing them to focus more on the treatment and care of patients. At the same time, the system's real-time monitoring and early warning functions help medical staff to promptly detect and deal with abnormal conditions of patients, thereby improving medical efficiency and quality; It realizes the automatic processing of multiple information such as the patient's position, movement status and patient status, eliminating the trouble of manual monitoring. On the basis of better ensuring the safety of patients, it greatly reduces the workload of medical staff.

[0028] The process of obtaining the location evaluation parameters and the abnormality determination process are as follows: Extract the real-time location information of patients collected continuously within a single day, and mark the real-time location information of patients as A1, A2, A3...An in the order of collection time, where n is the number of collection times; Connect points A1 and A2 to obtain line segment L1, connect points A2 and A3 to obtain line segment L2... Connect points An-1 and An to obtain line segment Ln-1; Then, the length from line segment L1 to line segment Ln-1 is measured, and the sum of the lengths of line segment L1, line segment L2, ..., line segment Ln-1 is calculated, so as to obtain the position evaluation parameter; Then, the patient's allowed movement distance information is collected. When the position evaluation parameter is greater than the patient's allowed movement distance information, it means that the position evaluation parameter is abnormal. The above process realizes refined location monitoring. By continuously collecting the real-time location information of patients and marking it in chronological order as A1, A2, A3...An, the system can accurately track the patient's movement trajectory within a day. This refined monitoring helps to detect abnormal movement patterns of patients, such as frequently leaving the ward and wandering in a specific area for a long time.

[0029] By calculating the sum of the lengths of line segments L1 to Ln-1, the system generates an intuitive location assessment parameter, which is the total distance the patient moves in a day. This parameter can directly reflect the patient's activity level and provide a quantitative assessment standard for medical staff.

[0030] By comparing the location assessment parameters with the patient's allowed range of motion information, the system can accurately determine whether the patient has exceeded the allowed range of motion. This comparison not only takes into account the patient's overall activity level, but also combines the patient's personal situation and medical needs, thereby improving the accuracy of abnormal judgment.

[0031] Since the permissible movement distance information is set based on the patient's personal situation and medical needs, this process supports personalized patient management. Different patients can be assigned different permissible movement distances based on their health status, treatment plan and other factors, ensuring targeted and effective management.

[0032] The process of obtaining the patient's real-time parameters and determining abnormalities of the patient's real-time parameters are as follows: Extract the collected patient status information, including patient temperature information, patient heart rate information and patient blood pressure information; Collect the duration of the patient's body temperature exceeding the standard temperature range and obtain the duration of abnormal body temperature; Collect the duration of the patient's heart rate information exceeding the standard heart rate range, and obtain the duration of abnormal heart rate; Collect the duration of the patient's blood pressure information exceeding the preset standard range, and obtain the duration of abnormal blood pressure; The duration of abnormal body temperature, abnormal heart rate and abnormal blood pressure constitute the patient's real-time parameters; When any of the patient's real-time parameters is greater than the preset value, it means that the patient's real-time parameters are abnormal; The process of obtaining position abnormality parameters and abnormality determination is as follows: extracting the patient's real-time position information and the patient's restricted area; Continuously collect m times of patient real-time location information within a preset time period, extract the number of times that the distance between the m times of patient real-time location information and the patient restricted area is less than a preset value, that is, obtain the position abnormality parameter. When the position abnormality parameter is greater than the preset value, it indicates that there is an abnormality; The system can continuously collect the patient's real-time location information within a preset period of time, which ensures that medical staff can understand the patient's current location in a timely manner. When the patient's position is abnormal in relation to the restricted area, the system can quickly generate an alert message, allowing medical staff to respond in a timely manner.

[0033] By counting the number of times the patient's real-time location information is less than the preset value in the patient's restricted area, the system can accurately quantify the frequency of patients entering or approaching the restricted area. This accuracy helps avoid false alarms and missed alarms, and improves the reliability and accuracy of the system.

[0034] By promptly detecting and handling abnormal relationships between the patient's position and restricted areas, the system helps prevent patients from entering dangerous areas or performing inappropriate activities. This preventive management strategy can significantly reduce the risk of accidents for patients in hospitals and improve medical safety.

[0035] The collection device worn by the patient is also used to collect wearing status information. When the wearing status information is abnormal, an abnormal warning message of the collection device is generated; The collection device consists of two straps for connection and a collection body; A device for collecting connection force is provided at the connection of the two connected watch straps to collect connection force information after wearing; The wearing status information includes the connection force information, the pressure between the acquisition body and the wearing surface, and the contact surface temperature information; When any two of the connection force information is less than a preset value, the pressure between the collection body and the wearing surface is less than a preset value, and the contact surface temperature information is less than a preset value occur at the same time, an abnormal warning message of the collection device is generated; By monitoring the connection force information after wearing, the pressure between the collection body and the wearing surface, and the contact surface temperature information, the system can promptly detect abnormal conditions of the collection device. This helps ensure that the device is always in good working condition, thereby improving its reliability and stability.

[0036] Abnormalities in data collection equipment may lead to inaccurate data or equipment failure, which in turn affects patient monitoring and management. By generating abnormal data collection equipment warning information, the system can remind medical staff to check and repair equipment in a timely manner, thereby avoiding potential patient safety risks.

[0037] Optimize wearing comfort: The pressure between the main body and the wearing surface and the contact surface temperature information reflect the impact of the device on the patient's comfort. When these parameters are abnormal, the system can remind medical staff to adjust the wearing method of the device or replace it with a more suitable device, thereby optimizing the patient's wearing experience.

[0038] Early warning to reduce the impact of failures: The system can generate abnormal warning information of the acquisition equipment when any two of the connection force information, pressure size and contact surface temperature information are abnormal at the same time. This early warning mechanism helps medical staff to detect and deal with equipment failures in a timely manner, thereby reducing the impact of failures on patient monitoring and management.

[0039] The process of obtaining abnormal personnel warning information is as follows: Extract the collected image information of people in the hospital, where the image information of people in the hospital is the face images of people who appeared in the hospital in the previous x days; Perform facial recognition processing on the image information of people in the hospital to obtain facial information; Extracting facial images of people whose image information appears more than a preset number of times in the hospital and setting them as marked people; Then, the number of times the marked person appears at the preset location in the hospital in a single day is collected. When the number of times the marked person appears at the preset location in the hospital in a single day exceeds a preset value, the day is marked as an abnormal day; After collecting data for x consecutive days, the number of abnormal days is extracted. When the number of abnormal days is greater than x / 2, an abnormal personnel warning message is generated, x≥7; The above process improves the hospital's safety management level. By extracting the image information of people in the hospital and performing face recognition processing, the system can accurately identify and record the flow of people in the hospital. This helps the hospital management to understand the safety status of the hospital in a timely manner, discover potential safety hazards, and take corresponding measures to improve the hospital's safety management level.

[0040] The system can automatically screen out marked persons based on the number of times they appear in the hospital. These marked persons may be frequent visitors, hospital staff, or potential unsafe factors. By focusing on these persons, the system can more effectively prevent and handle possible safety incidents.

[0041] The system can monitor the number of times a marked person appears at a preset location in real time and issue an early warning when the number exceeds the preset value. This real-time monitoring and early warning mechanism helps hospitals respond to and handle abnormal situations in a timely manner to prevent the situation from escalating.

[0042] The hospital's ability to respond to security incidents has been enhanced. Through this data processing system, the hospital can more quickly identify and respond to potential security incidents. For example, when a marked person appears frequently on an abnormal day, the system can immediately issue an alarm to remind hospital security personnel to strengthen monitoring and prevention.

[0043] Improve hospital management efficiency. The system's automation and intelligence can reduce the workload of hospital security personnel and improve their work efficiency. At the same time, through data analysis, the system can also provide hospital management with more accurate and comprehensive security information to help them better manage the hospital.

[0044] Ensure the normal operation of the hospital: By effectively identifying and warning abnormal personnel, the system can ensure the normal operation of the hospital and prevent hospital chaos and casualties caused by security incidents.

[0045] The process of obtaining abnormal medical treatment warning information is as follows: Extract the collected and imported image information of people outside the doctor's office, perform human body recognition on the image information of people outside the doctor's office, and after recognizing the human body, select each human body frame to obtain the human body frame; The human body frame is processed to obtain personnel assessment parameters. When the personnel assessment parameters are abnormal, abnormal medical treatment warning information is generated; The process of obtaining personnel evaluation parameters and determining abnormalities is as follows: Extract the collected human frames, process the human frames, obtain the distance information between the human frames, extract the number of distance information between the human frames that is less than the preset value, that is, obtain the personnel evaluation parameter. When the personnel evaluation parameter is greater than the preset value, it means that the personnel evaluation parameter is abnormal; After the consultation begins, the location of the consulting room entrance is extracted, the number of human frames within the preset range of the consulting room entrance is extracted, and an evaluation parameter is obtained. When the evaluation parameter is greater than a preset value, an abnormal consultation warning message is generated; The system can monitor the flow of people outside the doctor's office in real time, quickly select each human body through human body recognition technology, and calculate the personnel evaluation parameters in real time. Once the parameters are abnormal, the system immediately generates abnormal medical treatment warning information, allowing the hospital to respond and handle abnormal situations quickly, thereby maintaining a good medical treatment order. The system accurately evaluates the degree of crowding and personnel distribution in the treatment area by calculating the distance information between each human body frame and the number of human body frames within the preset range of the clinic entrance. This precise identification and evaluation capability helps hospitals understand the actual situation of the treatment area more accurately.

[0046] By real-time monitoring and evaluation of the flow of people in the treatment area, the system can promptly detect potential safety hazards, such as overcrowding, sudden collapse of patients, and other emergencies. This helps hospitals take measures in advance to prevent safety incidents and ensure the safety of patients and medical staff.

[0047] The process of obtaining abnormal occupancy warning information is as follows: Extracting the image information of the ward corridor, the image information of the ward corridor is the image information of the ward corridor road; Preset signs are set up on the ward corridors, and the image information of the ward corridors is used to identify the preset signs. After the preset signs are identified, the real-time preset sign area is collected; Then, the standard area when the preset sign is set is collected, and the ratio of the real-time preset sign area to the standard area is calculated to obtain the evaluation ratio. When the evaluation ratio is less than the preset value, abnormal occupancy warning information is generated; The above process extracts the image information of the ward corridor and identifies the preset logo, so that the system can monitor the occupancy of the corridor in real time. Once the evaluation ratio is less than the preset value, an abnormal occupancy warning message is generated, allowing the hospital to respond quickly and handle the abnormal occupancy of the corridor, ensuring that the corridor is unobstructed and providing convenience for patients and medical staff.

[0048] The system calculates the ratio of the real-time preset identification area to the standard area to obtain an accurate assessment ratio, thereby accurately determining whether the corridor is abnormally occupied. This precise identification and assessment capability helps avoid false alarms and missed alarms, and improves the reliability and accuracy of the system.

[0049] By monitoring corridor occupancy in real time, the system can promptly detect and handle corridor occupancy issues, thereby optimizing the use of hospital resources. This helps reduce problems such as longer waiting times for patients and reduced work efficiency of medical staff caused by corridor occupancy, and improves the overall operational efficiency of the hospital.

[0050] Improve hospital management level: The intelligent abnormal occupancy warning system not only improves the hospital's management efficiency of corridor occupancy, but also enables the hospital to have a more comprehensive understanding of the actual situation of the corridor. This helps the hospital to formulate a more scientific and reasonable corridor management strategy and improve the overall management level.

[0051] The process of obtaining ward warning information is as follows: Extract the collected ward information, which includes ward environment temperature information, ward environment humidity information and ward environment dust concentration information; When the ward environment temperature information exceeds the preset range for a preset time, the ward environment humidity information is greater than the preset value for a preset time, or the ward environment dust concentration information is greater than the preset value for a preset time, a ward warning message is generated; The above process comprehensively monitors the ward environment: the system can simultaneously monitor multiple parameters such as the ward's ambient temperature, humidity, and dust concentration, and comprehensively reflect the actual situation of the ward. This helps the hospital to promptly discover and deal with ward environmental problems, and provide patients with a more comfortable and safe hospitalization environment.

[0052] Accurate early warning and timely processing: When the parameters of the ward environment temperature, humidity or dust concentration exceed the preset range or last for more than the preset time, the system can automatically generate ward warning information. This accurate early warning and timely processing mechanism helps hospitals take timely measures to avoid adverse effects of environmental problems on patients.

[0053] A data processing method based on hospital monitoring data, the method comprising: Step 1: Collect patient information in the ward; Step 2: Collect image information of people in the hospital, people outside the doctor's office, and images of ward corridors; Step 3: Collect ward information in the ward; Step 4: Process the patient information and obtain the patient warning information; Step 5: Process the image information of people in the hospital to obtain warning information of abnormal people; Process the image information of people outside the doctor's office to obtain abnormal warning information about the visit; Process the image information of the ward corridor to obtain abnormal occupancy warning information; Step 6: Process the ward information to obtain ward warning information; Step 7: Send each generated warning message to a preset receiving terminal.

[0054] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0055] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0056] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A data processing system based on hospital monitoring data, characterized in that: It includes personnel information collection module, image information collection module, ward information collection module, data processing module and information sending module; The personnel information collection module is used to collect patient information in the ward; The image acquisition module is used to collect image information in the hospital, and the image information in the hospital includes image information of people in the hospital, image information of people outside the doctor's office, and image information of the ward corridor; The ward information collection module is used to collect ward information; The data processing module is used to process patient information to obtain patient warning information, process imaging information in the hospital to obtain abnormal personnel warning information, abnormal medical treatment warning information and abnormal occupancy warning information, and process ward information to obtain ward warning information; The information sending module is used to send the patient warning information, abnormal personnel warning information, abnormal medical treatment warning information, abnormal occupancy warning information and ward warning information to a preset receiving terminal after the above information is generated.

2. A data processing system based on hospital monitoring data according to claim 1, characterized in that: The process of obtaining the patient warning information is as follows: Extract the collected patient information, which includes the patient's real-time location information, the patient's restricted area, and the patient's status information; The patient's real-time location information and patient status information are collected by the collection device worn by the patient; Continuously collect the patient's real-time location information within a single day, process the patient's real-time location information continuously collected within a single day to obtain location evaluation parameters, and generate patient warning information when the location evaluation parameters are abnormal; Process the patient status information to obtain the patient's real-time parameters. When the patient's real-time parameters are abnormal, generate patient warning information; The patient's real-time location information and the patient restricted area are processed. When the patient's real-time location information is outside the patient restricted area, patient warning information is generated. The patient's real-time location information and the patient restricted area are processed to obtain location abnormality parameters. When the location abnormality parameters are abnormal, patient warning information is generated.

3. A data processing system based on hospital monitoring data according to claim 2, characterized in that: The acquisition process of the position evaluation parameters and the abnormality determination process are as follows: Extract the real-time location information of patients collected continuously within a single day, and mark the real-time location information of patients as A1, A2, A3...An in the order of collection time, where n is the number of collection times; Connect points A1 and A2 to obtain line segment L1, connect points A2 and A3 to obtain line segment L2... Connect points An-1 and An to obtain line segment Ln-1; Then, the length from line segment L1 to line segment Ln-1 is measured, and the sum of the lengths of line segment L1, line segment L2, ..., line segment Ln-1 is calculated, so as to obtain the position evaluation parameter; Then, the patient's allowed movement distance information is collected. When the position evaluation parameter is greater than the patient's allowed movement distance information, it indicates that there is an abnormality in the position evaluation parameter.

4. A data processing system based on hospital monitoring data according to claim 2, characterized in that: The process of obtaining the patient's real-time parameters and determining whether the patient's real-time parameters are abnormal are as follows: Extract the collected patient status information, including patient temperature information, patient heart rate information and patient blood pressure information; Collect the duration of the patient's body temperature exceeding the standard temperature range and obtain the duration of abnormal body temperature; Collect the duration of the patient's heart rate information exceeding the standard heart rate range, and obtain the duration of abnormal heart rate; Collect the duration of the patient's blood pressure information exceeding the preset standard range, and obtain the duration of abnormal blood pressure; The duration of abnormal body temperature, abnormal heart rate and abnormal blood pressure constitute the patient's real-time parameters; When any of the patient's real-time parameters is greater than the preset value, it means that the patient's real-time parameters are abnormal; The acquisition process of the position abnormality parameters and the abnormality determination process are as follows: extracting the patient's real-time position information and the patient's restricted area; The real-time location information of the patient is continuously collected m times within a preset time length, and the number of times the real-time location information of the patient is less than the preset value with respect to the patient restricted area is extracted, that is, the location abnormality parameter is obtained. When the location abnormality parameter is greater than the preset value, it indicates that there is an abnormality.

5. A data processing system based on hospital monitoring data according to claim 2, characterized in that: The collection device worn by the patient is also used to collect wearing status information. When the wearing status information is abnormal, an abnormal warning message of the collection device is generated; The collection device consists of two straps for connection and a collection body; A device for collecting connection force is provided at the connection of the two connected watch straps to collect connection force information after wearing; The wearing status information includes the connection force information, the pressure between the acquisition body and the wearing surface, and the contact surface temperature information; When any two of the connection force information is less than a preset value, the pressure between the collection body and the wearing surface is less than a preset value, and the contact surface temperature information is less than a preset value appear at the same time, an abnormal warning message of the collection device is generated.

6. A data processing system based on hospital monitoring data according to claim 1, characterized in that: The process of obtaining the abnormal personnel warning information is as follows: Extract the collected image information of people in the hospital, where the image information of people in the hospital is the face images of people who appeared in the hospital in the previous x days; Perform facial recognition processing on the image information of people in the hospital to obtain facial information; Extracting facial images of people whose image information appears more than a preset number of times in the hospital and setting them as marked people; Then, the number of times the marked person appears at the preset location in the hospital in a single day is collected. When the number of times the marked person appears at the preset location in the hospital in a single day exceeds a preset value, the day is marked as an abnormal day; After collecting data for x consecutive days, the number of abnormal days is extracted. When the number of abnormal days is greater than x / 2, an abnormal personnel warning message is generated, x ≥ 7.

7. A data processing system based on hospital monitoring data according to claim 1, characterized in that: The process of obtaining the abnormal medical treatment warning information is as follows: Extract the collected and imported image information of people outside the doctor's office, perform human body recognition on the image information of people outside the doctor's office, and after recognizing the human body, select each human body frame to obtain the human body frame; The human body frame is processed to obtain personnel assessment parameters. When the personnel assessment parameters are abnormal, abnormal medical treatment warning information is generated; The process of obtaining personnel evaluation parameters and determining abnormalities is as follows: Extract the collected human frames, process the human frames, obtain the distance information between the human frames, extract the number of distance information between the human frames that is less than the preset value, that is, obtain the personnel evaluation parameter. When the personnel evaluation parameter is greater than the preset value, it means that the personnel evaluation parameter is abnormal; After the consultation begins, the location of the consulting room entrance is extracted, the number of human body frames within the preset range of the consulting room entrance is extracted, and an evaluation parameter is obtained. When the evaluation parameter is greater than a preset value, an abnormal consultation warning message is generated.

8. A data processing system based on hospital monitoring data according to claim 1, characterized in that: The abnormal occupancy warning information acquisition process is as follows: Extracting the image information of the ward corridor, the image information of the ward corridor is the image information of the ward corridor road; Preset signs are set up on the ward corridors, and the image information of the ward corridors is used to identify the preset signs. After the preset signs are identified, the real-time preset sign area is collected; Then, the standard area when the preset sign is set is collected, and the ratio of the real-time preset sign area to the standard area is calculated to obtain the evaluation ratio. When the evaluation ratio is less than the preset value, an abnormal occupancy warning message is generated.

9. A data processing system based on hospital monitoring data according to claim 1, characterized in that: The process of obtaining the ward warning information is as follows: Extract the collected ward information, which includes ward environment temperature information, ward environment humidity information and ward environment dust concentration information; When the ward environment temperature information exceeds the preset range for a preset time, the ward environment humidity information is greater than the preset value for a preset time, or the ward environment dust concentration information is greater than the preset value for a preset time, a ward warning message is generated.

10. A data processing method based on hospital monitoring data, characterized in that: The data processing system according to any one of claims 1 to 9 is implemented, comprising the following steps: Step 1: Collect patient information in the ward; Step 2: Collect image information of people in the hospital, people outside the doctor's office, and images of ward corridors; Step 3: Collect ward information in the ward; Step 4: Process the patient information and obtain the patient warning information; Step 5: Process the image information of people in the hospital to obtain warning information of abnormal people; Process the image information of people outside the doctor's office to obtain abnormal warning information about the visit; Process the image information of the ward corridor to obtain abnormal occupancy warning information; Step 6: Process the ward information to obtain ward warning information; Step 7: Send each generated warning message to a preset receiving terminal.

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