Physical examination guiding method based on intelligent wearable device, electronic device and storage medium

Abstract

The invention discloses a physical examination guiding method based on intelligent wearable equipment, electronic equipment and a storage medium. The physical examination guiding method comprises the following steps: acquiring physical examination item information; establishing and keeping communication connection with the intelligent wearable device, and sending the physical examination item information to the intelligent wearable device; obtaining an electronic three-dimensional map, and department position information, average time consumption information and current people number information of each physical examination item; according to the current people number information of all the physical examination items, the average time consumption information of the uncompleted items and the current people number information, obtaining predicted waiting time through a time calculation model; and receiving the current position information from the intelligent wearable device, generating a physical examination guide route through a route planning model based on the electronic three-dimensional map according to the current position information and the department position information corresponding to the unfinished item with the shortest predicted waiting time, and sending the physical examination guide route to the intelligent wearable device. Real-time and accurate physical examination guidance can be provided for physical examinees, the physical examination process is optimized, and the physical examination efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of intelligent interaction technologies, and particularly to a physical examination guidance method, an electronic device, and a storage medium based on intelligent wearable devices. Background Art

[0002] In the field of medical physical examinations, the traditional physical examination process has many inconveniences. With the improvement of people's health awareness, the demand for physical examinations is increasing day by day, and the number of people undergoing physical examinations in major hospitals and physical examination institutions is constantly increasing.

[0003] Currently, when undergoing a physical examination, examinees usually need to hold a paper physical examination form and search for locations and queue up by themselves among various departments. The layout of hospitals is often relatively complex, and it is quite challenging for those who come for a physical examination for the first time to find the locations of each physical examination department. This not only wastes a lot of time but also easily makes examinees feel anxious and exhausted. At the same time, due to the lack of real-time understanding of the queuing situation for each physical examination item, examinees may spend too much waiting time on certain items, resulting in low efficiency of the entire physical examination process. For example, it may happen that an examinee first goes to an item with a large number of people queuing, while ignoring an item with a smaller number of people queuing and a shorter estimated time-consuming next to it, thus unnecessarily prolonging the physical examination time.

[0004] This traditional physical examination mode lacks effective guidance and management, and cannot provide the optimal physical examination route and time arrangement for examinees based on their real-time positions and the queuing situations of each item, seriously affecting the experience of examinees and the efficiency of physical examinations. Summary of the Invention

[0005] This application aims to at least solve one of the technical problems existing in the prior art. For this purpose, this application proposes a physical examination guidance method, an electronic device, and a storage medium based on intelligent wearable devices, which can provide real-time and accurate physical examination guidance for examinees, optimize the physical examination process, and improve the efficiency of physical examinations.

[0006] In a first aspect, this application provides a physical examination guidance method based on intelligent wearable devices, which is applied to a physical examination management platform. The physical examination guidance method includes: Obtain the physical examination item information of the examinee, and establish a corresponding personal physical examination monitoring library according to the physical examination item information; wherein, the personal physical examination monitoring library is used to record the completed items and uncompleted items; Establish and maintain a communication connection with the intelligent wearable device, and send the physical examination item information to the corresponding intelligent wearable device; Obtain an electronic three-dimensional map, as well as the department location information, average time-consuming information, and current number of people information of each physical examination item; Based on the current number information of all the physical examination items, the average time consumption information corresponding to the unfinished items, and the current number information, through a preset time prediction model, obtain the predicted waiting time for each unfinished item; Receive the current location information from the intelligent wearable device, and based on the current location information and the department location information corresponding to the unfinished item with the shortest predicted waiting time, generate a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model; Send the physical examination guidance route to the intelligent wearable device; Receive the completion feedback signal from the intelligent wearable device and update the personal physical examination monitoring library.

[0007] The physical examination guidance method based on a smart wearable device according to the embodiments of the first aspect of the present application has at least the following beneficial effects: The physical examination management platform obtains the physical examination item information of the examinee, and constructs a personal physical examination monitoring library based on this. The personal physical examination monitoring library records the completed items and uncompleted items. The platform establishes and maintains a communication connection with the smart wearable device, and sends the physical examination item information to the corresponding device, so that the examinee can know the content of their physical examination items at any time through the smart wearable device. The platform obtains an electronic three-dimensional map, as well as the department location information, average time-consuming information, and current number of people information of each physical examination item. Based on the average time-consuming information and current number of people information corresponding to the uncompleted items, and comprehensively considering the current number of people information of all physical examination items, it can better reflect the overall operation load of the hospital at the current time point. Through a preset time calculation model, the predicted waiting time for each uncompleted item is calculated. The platform receives the current location information of the examinee fed back by the smart wearable device, combines it with the department location information corresponding to the uncompleted item with the shortest predicted waiting time, and generates a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model. The generated physical examination guidance route is sent to the smart wearable device, and the examinee can intuitively see the best route to the next physical examination department. When the examinee completes a certain item, the smart wearable device sends a completion feedback signal to the platform, and the platform updates the personal physical examination monitoring library accordingly, so as to always accurately track the physical examination progress. With the help of the time calculation model, the waiting time for each uncompleted item is predicted based on the average time-consuming and current number of people information, and then the route to the department with the shortest waiting time is planned, enabling the examinee to preferentially select items with fewer people in line and shorter time-consuming for physical examination, effectively avoiding wasting too much time in queuing, greatly improving the overall efficiency of the physical examination, shortening the total physical examination time, and enhancing the experience of the examinee. At the same time, by obtaining the electronic three-dimensional map and the department location information, using the path planning model to generate the guidance route and sending it to the smart wearable device, the examinee can clearly know the route to each physical examination department, greatly reducing the difficulty of finding departments in the complex hospital environment and saving the time spent on finding departments.

[0008] According to some embodiments of the first aspect of the present application, obtaining the predicted waiting time for each of the uncompleted items through a preset time calculation model according to the current number of people information of all the physical examination items, the average time-consuming information and the current number of people information corresponding to the uncompleted items includes: Obtain the current time; According to the current time and a preset first look-up table, obtain a queuing correction coefficient; wherein, the first look-up table is used to represent the corresponding relationship between different time periods and different queuing correction coefficients, and the first look-up table corresponding to each physical examination item is different; Based on the queuing correction coefficient of all the physical examination items, the current number information, the queuing correction coefficient corresponding to the unfinished items, the average time-consuming information, and the current number information, the predicted waiting time for each unfinished item is obtained through a preset time calculation model.

[0009] According to some embodiments of the first aspect of the present application, the time calculation model is: ; where P i represents the predicted waiting time, T i represents the average time-consuming information of the i-th unfinished item, N i represents the current number information of the i-th unfinished item, C i represents the queuing correction coefficient of the i-th unfinished item, N j represents the current number information of the j-th physical examination item, C j represents the queuing correction coefficient of the j-th physical examination item, ∑(N j * C j ) represents the sum of N j * C j for all physical examination items.

[0010] According to some embodiments of the first aspect of the present application, before the step of obtaining the queuing correction coefficient according to the current time and a preset first look-up table, the following steps are further included: Obtain the historical data information of each physical examination item; wherein, the historical data information includes historical time periods, multiple sets of corresponding historical number information and historical time-consuming information in each historical time period; Establish a correction model; Input the average time-consuming information corresponding to the physical examination item, the historical number information corresponding to the same historical time period, and the historical time-consuming information into the correction model to obtain multiple candidate correction coefficients; Perform weighted average processing on the multiple candidate correction coefficients to obtain a target correction coefficient; wherein, in the weighted average processing, the weight of each candidate correction coefficient is obtained according to the time generated by the corresponding historical number information and historical time-consuming information; Establish the first look-up table according to the historical time period and the corresponding target correction coefficient.

[0011] According to some embodiments of the first aspect of the present application, the smart wearable device includes an ultra-wideband positioning module, and the smart wearable device is used to connect to ultra-wideband positioning base stations at different positions in the physical examination center through the ultra-wideband positioning module; Receiving the current location information from the intelligent wearable device, including: Receiving a plurality of distance information sets from the intelligent wearable device; wherein, each distance information set includes a base station identifier and distance information between the ultra-wideband positioning base station corresponding to the base station identifier; Calculating the current location information in a three-dimensional space according to the distance information sets.

[0012] According to some embodiments of the first aspect of the present application, generating a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model according to the current location information and the department location information corresponding to the unfinished item with the shortest predicted waiting time, including: Sending the unfinished item with the shortest predicted waiting time to the intelligent wearable device to wait for the physical examinee to confirm the next recommended physical examination item; Responding to a confirmation instruction from the intelligent wearable device, and taking the unfinished item with the shortest predicted waiting time as the target physical examination item; Responding to a cancellation instruction from the intelligent wearable device, obtaining a selection instruction generated by the physical examinee from the unfinished items, and taking the physical examination item corresponding to the selection instruction as the target physical examination item; Generating a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model according to the current location information and the department location information corresponding to the target physical examination item.

[0013] According to some embodiments of the first aspect of the present application, after the step of sending the physical examination guidance route to the intelligent wearable device, further including: Continuously obtaining the current location information, and determining the current walking direction according to the change of the current location information; Generating a target walking direction according to the current walking direction, the current location information and the physical examination guidance route; Sending the target walking direction to the intelligent wearable device to display the target walking direction on the screen of the intelligent wearable device.

[0014] According to some embodiments of the first aspect of the present application, after the step of receiving the completion feedback signal from the intelligent wearable device and updating the personal physical examination monitoring library, further including: When the unfinished items in the personal physical examination monitoring library are empty, obtaining preset end point location information; Generating a return guidance route based on the electronic three-dimensional map through a preset path planning model according to the current location information and the end point location information; Send the returned guiding route to the smart wearable device.

[0015] In a second aspect, the present application further provides an electronic device, which is characterized by including: At least one memory; At least one processor; At least one program; The program is stored in the memory, and the processor executes at least one of the programs to implement the physical examination guiding method based on a smart wearable device as described in any embodiment of the first aspect.

[0016] In a third aspect, the present application further provides a computer-readable storage medium, which stores computer-executable signals for executing the physical examination guiding method based on a smart wearable device as described in any embodiment of the first aspect.

[0017] The additional aspects and advantages of the present application will be partly given in the following description, partly become obvious from the following description, or be understood through the practice of the present application. Description of the Drawings

[0018] The additional aspects and advantages of the present application will become obvious and easy to understand in combination with the following description of the embodiments with reference to the accompanying drawings, where: Figure 1 is a flowchart of the physical examination guiding method based on a smart wearable device provided by an embodiment of the present application; Figure 2 is for the present application Figure 1 a flowchart of step S140; Figure 3 is for the present application Figure 2 a flowchart before step S220; Figure 4 is for the present application Figure 1 a flowchart of the first part in step S150; Figure 5 is for the present application Figure 1 a flowchart of the second part in step S150; Figure 6 is for the present application Figure 1 a flowchart after step S160; Figure 7 is for the present application Figure 1 a flowchart after step S170. Detailed Embodiments

[0019] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary only for explaining the present application and should not be construed as limiting the present application.

[0020] In the description of the present application, it should be understood that for the orientation description, such as up, down, front, back, left, right, etc., the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application.

[0021] In the description of the present application, if the first and second are described only for the purpose of distinguishing technical features, it should not be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0022] In the description of the present application, unless otherwise clearly defined, words such as setting, installation, connection, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present application in combination with the specific content of the technical solution.

[0023] In the field of medical examinations, there are many inconveniences in the traditional examination process. With the improvement of people's health awareness, the demand for physical examinations is increasing day by day, and the number of people undergoing physical examinations in major hospitals and physical examination institutions is constantly increasing.

[0024] Currently, when undergoing a physical examination, examinees usually need to hold a paper physical examination form and find their own positions and queue up between different departments. The layout of the hospital is often relatively complex. For those who come for a physical examination for the first time, it is quite challenging to find the locations of each physical examination department, which not only wastes a lot of time but also easily makes the examinees feel anxious and exhausted. At the same time, due to the lack of real-time understanding of the queuing situation of each physical examination item, the examinee may spend too much waiting time on certain items, resulting in low efficiency of the entire physical examination process. For example, it may happen that the examinee first goes to an item with a large number of people queuing, while ignoring an item with a smaller number of people queuing and a shorter estimated time-consuming next to it, thus unnecessarily prolonging the physical examination time.

[0025] This traditional physical examination mode lacks effective guidance and management, and cannot provide the examinee with the optimal physical examination route and time arrangement according to the real-time position of the examinee and the queuing situation of each item, seriously affecting the experience of the examinee and the physical examination efficiency.

[0026] Based on this, the present application provides a physical examination guidance method, an electronic device, and a storage medium based on a smart wearable device to solve the above technical problems. The technical solutions provided by the present application will be described in detail one by one below.

[0027] In the first aspect, referring to Figure 1 , the present application provides a physical examination guidance method based on a smart wearable device, which is applied to a physical examination management platform. The physical examination guidance method includes: Step S110: Obtain the physical examination item information of the examinee, and establish a corresponding personal physical examination monitoring library according to the physical examination item information; wherein, the personal physical examination monitoring library is used to record the completed items and uncompleted items.

[0028] Step S120: Establish and maintain a communication connection with the smart wearable device, and send the physical examination item information to the corresponding smart wearable device.

[0029] Step S130: Obtain an electronic three-dimensional map, as well as the department location information, average time-consuming information, and current number information of each physical examination item.

[0030] Step S140: According to the current number information of all physical examination items, the average time-consuming information and current number information corresponding to the uncompleted items, through a preset time calculation model, obtain the predicted waiting time for each uncompleted item.

[0031] Step S150: Receive the current location information from the smart wearable device, and based on the current location information and the department location information corresponding to the uncompleted item with the shortest predicted waiting time, generate a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model.

[0032] Step S160: Send the physical examination guidance route to the smart wearable device.

[0033] Step S170: Receive the completion feedback signal from the smart wearable device, and update the personal physical examination monitoring library.

[0034] In steps S110 to S170, the physical examination management platform obtains the physical examination item information of the examinee, and constructs a personal physical examination monitoring library based on this. The personal physical examination monitoring library records the completed items and uncompleted items. The platform establishes and maintains a communication connection with the smart wearable device, and sends the physical examination item information to the corresponding device, so that the examinee can know the content of their physical examination items at any time through the smart wearable device. The platform obtains the electronic three-dimensional map, as well as the department location information, average time-consuming information, and current number of people information of each physical examination item. Based on the average time-consuming information and current number of people information corresponding to the uncompleted items, and comprehensively considering the current number of people information of all physical examination items, it can better reflect the overall operation load of the hospital at the current time point. Through a preset time calculation model, the predicted waiting time for each uncompleted item is calculated. The platform receives the current location information of the examinee fed back by the smart wearable device, combines it with the department location information corresponding to the uncompleted item with the shortest predicted waiting time, and generates a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model. The generated physical examination guidance route is sent to the smart wearable device, and the examinee can intuitively see the best route to the next physical examination department. When the examinee completes a certain item, the smart wearable device sends a completion feedback signal to the platform, and the platform updates the personal physical examination monitoring library accordingly, so as to always accurately track the physical examination progress. With the help of the time calculation model, the waiting time for each uncompleted item is predicted according to the average time-consuming and current number of people information, and then the route to the department with the shortest waiting time is planned, enabling the examinee to preferentially select the items with fewer queuing people and shorter time-consuming for physical examination, effectively avoiding wasting too much time in queuing, greatly improving the overall efficiency of the physical examination, shortening the total physical examination time, and enhancing the experience of the examinee. At the same time, by obtaining the electronic three-dimensional map and the location information of each department, using the path planning model to generate the guidance route and sending it to the smart wearable device, the examinee can clearly know the route to each physical examination department, greatly reducing the difficulty of finding departments in the complex hospital environment and saving the time spent on finding departments.

[0035] It should be noted that the smart wearable device used to implement the physical examination guidance function needs to have positioning, communication, and information display capabilities. It can be a smart bracelet, a smart watch, a customized medical smart chest card, etc., and this application does not make any limitations in this regard.

[0036] Refer to Figure 2 , it can be understood that in step S140, it can be understood but not limited to the following steps: Step S210: Obtain the current time.

[0037] Step S220: Obtain a queuing correction coefficient according to the current time and a preset first comparison table; wherein, the first comparison table is used to represent the correspondence between different time periods and different queuing correction coefficients, and the first comparison table corresponding to each physical examination item is different.

[0038] Step S230: According to the queuing correction coefficients of all the physical examination items, the current number information, the queuing correction coefficients corresponding to the unfinished items, the average time-consuming information and the current number information, use a preset time calculation model to obtain the predicted waiting time for each unfinished item.

[0039] In steps S210 to S230, the physical examination management platform first accurately obtains the current time information. Based on the obtained current time, the platform consults the first comparison table corresponding to each physical examination item. Since the busy degrees of different physical examination items vary in different time periods, each item has a dedicated first comparison table. This comparison table details the correspondence between different time periods and different queuing correction coefficients. For example, for the blood routine examination item, in the time period from 8:00 to 9:00 in the morning, the corresponding queuing correction coefficient may be 1.2, while in the time period from 2:00 to 3:00 in the afternoon, the corresponding queuing correction coefficient may be 0.8. The platform substitutes the obtained queuing correction coefficient, combined with the average time-consuming information and the current number information corresponding to the unfinished items, into the preset time calculation model to calculate the predicted waiting time for each unfinished item, providing accurate time data support for the subsequent physical examination route planning. Considering the influence of different time periods on the queuing situation of each physical examination item, by introducing the queuing correction coefficient, the waiting time can be predicted more in line with the actual scenario. Compared with simply estimating based only on the average time-consuming and the current number, this method fully considers the change in the queuing situation caused by the time factor, making the prediction result more accurate. For example, the number of people queuing for some popular physical examination items will increase significantly during the morning peak period. Through the queuing correction coefficient, the predicted waiting time can be reasonably adjusted to avoid the waste of time caused by inaccurate estimated time for the physical examination person. In addition, a more accurate predicted waiting time enables the physical examination management platform to make more scientific and reasonable decisions when planning the physical examination route. The platform can preferentially arrange the physical examination person to go to the project department with the shortest waiting time according to the accurate predicted waiting time of each item, further improving the physical examination efficiency, reducing the staying time of the physical examination person in the hospital, and enhancing the overall physical examination experience.

[0040] It can be understood that, wherein, the time calculation model is: ; wherein, P i represents the predicted waiting time, T i represents the average time-consuming information of the i-th unfinished item, N i represents the current number information of the i-th unfinished item, C iRepresents the queuing correction coefficient of the i-th unfinished item, N j Represents the current number of people information of the j-th physical examination item, C j Represents the queuing correction coefficient of the j-th physical examination item, ∑(N j * C j ) represents the N of all physical examination items j * C j The sum.

[0041] In step S310, this time prediction model not only considers the average time consumption, current number of people and queuing correction coefficient of the unfinished item itself, but also combines the relevant data of all physical examination items. By incorporating the comprehensive busyness factor of the overall project, the prediction of the waiting time for each unfinished item becomes more comprehensive and accurate.

[0042] In this formula, the calculation of associating with other items (i.e., ∑(N j *C j )) is for the consideration of relative weights. The individual N i *C i reflects the impact of the current queuing number and queuing correction coefficient of the i-th item on its time. However, in the actual physical examination scenario, the waiting times of each item are not isolated. When calculating the predicted time of a certain item, considering the sum of N j *C j of all items can balance the mutual influence among items as a whole. The model operates based on the data of all physical examination items and can better reflect the overall operation load of the hospital at the current time point. For example, if the hospital is overall in a busy state, the queuing numbers of multiple items are large (N j is large) and the queuing correction coefficient (C i ) also shows an increase in time consumption, then this sum will be large. In the formula, when this sum is large, the relative proportion of N i *C i in it will be adjusted, so that the calculated P i is more in line with the actual situation, comprehensively reflecting the impact of the busyness of the entire hospital physical examination process on the time of a single item, avoiding calculating the time of a single item in isolation, helping the physical examination management platform to plan the physical examination process from a macro perspective, reasonably guide the physical examination personnel to different departments, balance the flow of people in each department, avoid the situation that some departments are overcrowded while some departments' resources are idle, and improve the accuracy and rationality of the prediction.

[0043] Referring to Figure 3 , it can be understood that before step S220, it may also include but not limited to the following steps: Step S410: Obtain the historical data information of each physical examination item; wherein, the historical data information includes the historical time period, multiple sets of corresponding historical number information and historical time-consuming information in each historical time period.

[0044] Step S420: Establish a correction model.

[0045] Step S430: Input the average time-consuming information corresponding to the physical examination item, the historical number information and the historical time-consuming information corresponding to the same historical time period into the correction model to obtain multiple candidate correction coefficients.

[0046] Step S440: Perform weighted average processing on the multiple candidate correction coefficients to obtain the target correction coefficient; wherein, in the weighted average processing, the weight of each candidate correction coefficient is obtained according to the time generated by the corresponding historical number information and historical time-consuming information.

[0047] Step S450: Establish a first look-up table according to the historical time period and the corresponding target correction coefficient.

[0048] In steps S410 to S430, the physical examination management platform starts the data collection program, extracts the historical data information of each physical examination item from the past physical examination record database of the hospital. These data cover different historical time periods, and in each historical time period, there are multiple sets of corresponding historical number information and historical time-consuming information. A correction model dedicated to calculating the correction coefficient is constructed. This model can be a regression model based on machine learning, such as linear regression, multiple linear regression, etc., or a more complex neural network model, which is not specifically limited in this application. Input the average time-consuming information corresponding to each physical examination item, as well as the historical number information and historical time-consuming information corresponding to the same historical time period, into the established correction model in sequence.

[0049] In steps S440 to S450, perform weighted average processing on the obtained multiple candidate correction coefficients. In the weighted average process, the weight of each candidate correction coefficient is determined according to the time generated by the corresponding historical number information and historical time-consuming information. The closer the time is to the present, the higher its corresponding weight, because the recent data can better reflect the current actual situation. For example, the weight of the data within the past month is higher than the weight of the data half a year ago. Through this weighted average calculation, the target correction coefficient of each physical examination item in each historical time period is obtained. The platform organizes and correlates the historical time period and the corresponding target correction coefficient to establish a first look-up table.

[0050] Through the analysis of a large amount of historical data, combined with the operation of the correction model and weighted average processing, the influence of different time periods, different queuing numbers and time-consuming situations on the correction coefficient is fully considered. Compared with simple empirical settings or single data references, this method can more accurately determine the queuing correction coefficient corresponding to each time period, thereby improving the accuracy of subsequent predicted waiting times.

[0051] Referring to Figure 4 , it can be understood that the smart wearable device includes an ultra-wideband positioning module, and the smart wearable device is used to connect to ultra-wideband positioning base stations at different positions in the physical examination center through the ultra-wideband positioning module. In the step of "receiving the current location information from the smart wearable device" in step S150, it may include but is not limited to the following steps: Step S510: Receive multiple sets of distance information from the smart wearable device; wherein, each set of distance information includes a base station identifier and the distance information between the ultra-wideband positioning base station corresponding to the base station identifier; Step S520: Calculate the current location information in the three-dimensional space according to the set of distance information.

[0052] In steps S510 to S520, when the physical examinee wears the smart wearable device and enters the physical examination center, the ultra-wideband positioning module in the smart wearable device automatically activates the search function. This module continuously sends ultra-wideband signals of a specific frequency to scan the ultra-wideband positioning base stations pre-deployed at different positions in the physical examination center. The smart wearable device periodically receives signals from the ultra-wideband positioning base stations through the established ultra-wideband positioning module. Based on the time-of-flight (TOF) principle of ultra-wideband positioning technology, the smart wearable device calculates the time elapsed from the signal being emitted by the base station to its own reception, and then converts it into the distance to each base station. After each reception, the smart wearable device integrates the obtained distance information with the corresponding base station identifier to form a set of distance information. For example, the set of distance information may be presented in the form of [Base Station A, 5 meters; Base Station B, 8 meters; Base Station C, 6 meters]. Multiple such sets of distance information are continuously sent to the physical examination management platform. After receiving multiple sets of distance information from the smart wearable device, the physical examination management platform uses a specific algorithm for position calculation. In the three-dimensional space, trilateration or multilateration methods are usually adopted. Taking trilateration as an example, assuming that the coordinates of three ultra-wideband positioning base stations are (x1, y1, z1), (x2, y2, z2), (x3, y3, z3) respectively, and the distances between the smart wearable device and these three base stations are d1, d2, d3. Subsequently, by constructing a system of equations, the coordinates (x, y, z) of the smart wearable device in the three-dimensional space, that is, the current location information of the physical examinee, can be obtained. If there are more sets of distance information, the multilateration method will use the distance information of more base stations for more accurate position calculation, further improving the accuracy of positioning.

[0053] Ultra-wideband positioning technology can provide centimeter-level positioning accuracy, which is significantly improved compared to traditional Bluetooth positioning, Wi-Fi positioning and other technologies. This enables the physical examination management platform to accurately know the specific location of the examinee in the physical examination center, including the floor, room number and even the specific direction. Even in crowded areas or places with more signal obstruction, such as elevators and corridor corners, the ultra-wideband positioning module can still accurately calculate the examinee's location through signal interaction of multiple base stations to ensure the stability of the physical examination guidance. For example, in the complex floor structure and numerous department layouts of large physical examination centers, it can accurately guide the examinee to the next physical examination department to avoid getting lost or going the wrong way due to inaccurate positioning, greatly saving the examinee's time in finding the department.

[0054] Reference Figure 5 It can be understood that the step of "generating a physical examination guidance route based on the current location information and the department location information corresponding to the unfinished project with the shortest predicted waiting time, based on the electronic three-dimensional map, and through a preset path planning model" in step S150 may include but is not limited to the following steps: Step S610: sending the unfinished item with the shortest predicted waiting time to the smart wearable device, so as to wait for the examinee to confirm the next recommended physical examination item; Step S620: In response to the confirmation instruction from the smart wearable device, the unfinished item with the shortest predicted waiting time is used as the target physical examination item; Step S630: responding to the cancel instruction from the smart wearable device, obtaining a selection instruction generated by the examinee's selection from the unfinished items, and taking the physical examination item corresponding to the selection instruction as the target physical examination item; Step S640: Generate a physical examination guidance route based on the current location information and the department location information corresponding to the target physical examination item, based on the electronic three-dimensional map and through a preset path planning model.

[0055] In step S610 to step S630, after the physical examination management platform completes the calculation of the predicted waiting time for each unfinished physical examination item, it screens out the unfinished items with the shortest predicted waiting time. The platform sends the project information to the smart wearable device, and the smart wearable device will inform the examinee of the next recommended physical examination item by means of a pop-up window, vibration or voice prompt, waiting for the examinee to confirm the operation. For example, a prompt pops up on the screen of the smart wearable device: "It is recommended that you undergo a routine blood test next. The project is expected to have the shortest waiting time. Are you sure to go?" When the examinee views the prompt of the smart wearable device, if he agrees to undergo a physical examination according to the recommendation, he will issue a confirmation instruction on the device. After receiving the confirmation instruction, the smart wearable device immediately transmits it to the physical examination management platform. In response to this confirmation instruction, the platform formally determines the unfinished project with the shortest predicted waiting time as the target physical examination project, and clarifies the target direction for subsequent route planning. If the examinee issues a cancellation instruction on the smart wearable device for personal reasons (such as wanting to undergo a specific examination first, having questions about the recommended project, etc.). The smart wearable device sends the cancellation command to the physical examination management platform, and the platform immediately starts the autonomous selection process. The examinee can select the physical examination item he wants to do first from the list of unfinished items displayed in the personal physical examination monitoring library on the smart wearable device and generate a selection instruction. The smart wearable device transmits the selection instruction to the platform, and the platform responds to this instruction and uses the physical examination item corresponding to the selection instruction as the target physical examination item.

[0056] In step S640, the physical examination management platform obtains the current location information of the examinee and the location information of the department corresponding to the determined target physical examination items. Based on the pre-loaded electronic three-dimensional map, the preset path planning model is called. The path planning model takes the current location as the starting point and the location of the department of the target physical examination item as the end point. It comprehensively considers various elements in the map, such as corridors, stairs, elevators, department distribution, etc., and calculates an optimal route from the starting point to the end point through an algorithm, that is, the physical examination guidance route.

[0057] In the above steps, the personal wishes of the examinees are fully respected by giving them the right to independently choose the examination items. The examinees can flexibly decide the order of the examinations according to their own circumstances and needs, rather than completely passively accepting the system recommendations. This interactive method enhances the examinees' sense of participation and control during the examination, making the examination process more humane and greatly improving the user experience. The clear method of determining the target examination items ensures that the path planning model can calculate the route for the accurate starting point and end point. Whether it is based on system recommendations or the target items selected by the examinees themselves, the generated examination guidance route can more accurately meet the actual needs of the examinees, avoid route deviations caused by unclear targets, further improve the efficiency of the examination, and reduce the time the examinees spend walking around the hospital and unnecessary waiting.

[0058] ReferenceFigure 6 , it can be understood that after step S160, it further includes but is not limited to the following steps: Step S710: Continuously obtain the current location information and determine the current walking direction according to the change of the current location information; Step S720: Generate a target walking direction according to the current walking direction, the current location information, and the physical examination guidance route; Step S730: Send the target walking direction to the smart wearable device to display the target walking direction on the screen of the smart wearable device.

[0059] In steps S710 to S730, the physical examination management platform maintains a real-time communication connection with the smart wearable device and continuously receives the current location information fed back by the ultra-wideband positioning module of the smart wearable device. The platform can update the latest position coordinates of the physical examinee at a set time interval (such as once per second), and determine the current walking direction of the physical examinee by using the vector calculation method based on at least two continuously obtained current location information. The platform compares and analyzes the determined current walking direction with the physical examination guidance route. First, find the path point on the physical examination guidance route that is closest to the current location, and then calculate the target direction that should be taken along the physical examination guidance route from the current location according to the position information of this path point and the next path point. For example, if the physical examination guidance route is a straight line to the right front here and the current walking direction is to the left, the platform will comprehensively consider the current location, the current walking direction, and the trend of the physical examination guidance route, and calculate a corrected target walking direction to guide the physical examinee back to the correct route. The physical examination management platform sends the generated target walking direction to the smart wearable device through wireless communication. After receiving the target walking direction information, the smart wearable device displays it in an intuitive way on its screen. For example, it may display an arrow icon, and the arrow direction is the target walking direction, and at the same time, it can be accompanied by text prompts such as "Please turn right and go forward in this direction" to enable the physical examinee to clearly understand the next walking direction.

[0060] By obtaining the location information in real time and dynamically adjusting the target walking direction, it is possible to timely correct the situation where the physical examinee may deviate from the route during walking. Compared with the traditional static navigation guidance, this real-time dynamic navigation method can better adapt to the actual walking situation of the physical examinee in the complex hospital environment, avoid getting lost or delaying the physical examination time caused by temporarily changing the route, going in the wrong direction, etc., and greatly improve the accuracy of navigation.

[0061] Refer to Figure 7 , it can be understood that after step S170, it may further include but is not limited to the following steps: Step S810: When the unfinished items in the personal physical examination monitoring library are empty, obtain the preset end position information.

[0062] Step S820: Generate a return guidance route based on the current location information and the end - point location information, using a preset path - planning model based on an electronic 3D map.

[0063] Step S830: Send the return guidance route to the smart wearable device.

[0064] In steps S810 to S830, the physical examination management platform continuously monitors the status of the personal physical examination monitoring library. When the platform receives a completion feedback signal from the smart wearable device, it updates the status of the corresponding physical examination items in the personal physical examination monitoring library one by one. After each update, the platform automatically checks the list of uncompleted items in the personal physical examination monitoring library. If it is found that the list of uncompleted items is empty, it means that the examinee has completed all the scheduled physical examination items, and at this time, the subsequent return guidance process is triggered. Once it is determined that the examinee has completed all physical examination items, the physical examination management platform obtains the preset end - point location information from the pre - set database. The physical examination management platform combines the current location information of the examinee currently obtained from the smart wearable device and the end - point location information just obtained, and based on the electronic 3D map, calls the preset path - planning model to calculate an optimal route from the current location of the examinee to the end - point location, that is, the return guidance route. After receiving the return guidance route information, the smart wearable device will present it to the examinee on its screen in a display manner similar to the physical examination guidance route, such as through map markings, arrow indications, and text descriptions, etc., to guide the examinee to reach the end - point location smoothly. The smart wearable device directly provides a clear return guidance route, which greatly saves the time of the examinee, especially in the case of being unfamiliar with the hospital environment, avoiding the trouble caused by getting lost and improving the overall convenience of the physical examination service.

[0065] In a second aspect, the present application also provides an electronic device, including: at least one memory; at least one processor; at least one program; the program is stored in the memory, and the processor executes at least one program to implement the personalized display method of the nurse terminal operation interface according to any one of the embodiments of the first aspect.

[0066] In this electronic device, the physical examination management platform obtains the physical examination item information of the examinee, and constructs a personal physical examination monitoring database based on this. The personal physical examination monitoring database records the completed items and uncompleted items. The platform establishes and maintains a communication connection with the smart wearable device, and sends the physical examination item information to the corresponding device, so that the examinee can know the content of their physical examination items at any time through the smart wearable device. The platform obtains the electronic three-dimensional map, as well as the department location information, average time-consuming information, and current number information of each physical examination item. According to the average time-consuming information and current number information corresponding to the uncompleted items, through a preset time calculation model, the predicted waiting time for each uncompleted item is calculated. The platform receives the current location information of the examinee fed back by the smart wearable device, combines it with the department location information corresponding to the uncompleted item with the shortest predicted waiting time, and based on the electronic three-dimensional map, generates a physical examination guidance route through a preset path planning model. The generated physical examination guidance route is sent to the smart wearable device, and the examinee can intuitively see the best route to the next physical examination department. When the examinee completes a certain item, the smart wearable device sends a completion feedback signal to the platform, and the platform updates the personal physical examination monitoring database accordingly, so as to always accurately track the physical examination progress. With the help of the time calculation model, the waiting time for each uncompleted item is predicted according to the average time-consuming and current number information, and then the route to the department with the shortest waiting time is planned, so that the examinee can preferentially choose the items with fewer queuing people and shorter time-consuming for physical examination, effectively avoiding wasting too much time in queuing, greatly improving the overall efficiency of the physical examination, shortening the total physical examination time, and enhancing the experience of the examinee. At the same time, by obtaining the electronic three-dimensional map and the department location information of each department, using the path planning model to generate the guidance route and sending it to the smart wearable device, the examinee can clearly know the route to each physical examination department, greatly reducing the difficulty of finding departments in the complex hospital environment and saving the time spent on finding departments.

[0067] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs, non-transitory computer-executable programs, and signals, such as the program instructions / signals corresponding to the processing module in the embodiments of the present application. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions, and signals stored in the memory, that is, implements the personalized display method of the nurse terminal operation interface in the above method embodiments.

[0068] The memory may include a program storage area and a data storage area. The program storage area may store an operating system and application programs required for at least one function. The data storage area may store relevant data of the personalized display method for the nurse terminal operation interface described above, etc. In addition, the memory may include a high-speed random access memory and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely provided with respect to the processor, and these remote memories may be connected to the processing module through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0069] One or more signals are stored in the memory and, when executed by one or more processors, implement the personalized display method for the nurse terminal operation interface in any of the above method embodiments.

[0070] In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, and when the computer program is executed by one or more processors, the one or more processors may be caused to execute the personalized display method for the nurse terminal operation interface in the above method embodiments.

[0071] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0072] Through the description of the above embodiments, those of ordinary skill in the art can understand that all or some of the steps and systems disclosed above can be implemented as software, firmware, hardware, and their appropriate combinations. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable signals, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, a communication medium typically includes computer-readable signals, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0073] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or a similar expression means any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0074] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the above division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0075] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0076] In addition, in each embodiment of the present application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0077] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. And the aforementioned storage medium includes: various media that can store programs such as USB flash drives, mobile hard disks, read-only memory (ROM for short), random access memory (RAM for short), magnetic disks or optical discs.

[0078] The above has described the embodiments of the present application in detail with reference to the accompanying drawings. However, the present application is not limited to the above embodiments. Within the scope of knowledge possessed by those of ordinary skill in the art to which the present application pertains, various changes can be made without departing from the purpose of the present application.

Claims

1. A physical examination guidance method based on a smart wearable device, characterized in that, Applied to a physical examination management platform, the physical examination guidance method includes: Obtaining the physical examination item information of the examinee, and establishing a corresponding personal physical examination monitoring library according to the physical examination item information; wherein, the personal physical examination monitoring library is used to record the completed items and the uncompleted items; Establishing and maintaining a communication connection with the intelligent wearable device, and sending the physical examination item information to the corresponding intelligent wearable device; Obtaining an electronic three-dimensional map, as well as the department location information, average time-consuming information and current number information of each physical examination item; According to the current number information of all the physical examination items, the average time-consuming information corresponding to the uncompleted items and the current number information, through a preset time calculation model, obtaining the predicted waiting time of each uncompleted item; Receiving the current location information from the intelligent wearable device, and based on the current location information and the department location information corresponding to the uncompleted item with the shortest predicted waiting time, generating a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model; Sending the physical examination guidance route to the intelligent wearable device; Receiving the completion feedback signal from the intelligent wearable device, and updating the personal physical examination monitoring library.

2. The physical examination guidance method based on the intelligent wearable device according to claim 1, wherein The step of obtaining the predicted waiting time of each uncompleted item through a preset time calculation model according to the current number information of all the physical examination items, the average time-consuming information corresponding to the uncompleted items and the current number information includes: Obtaining the current time; According to the current time and a preset first look-up table, obtaining a queuing correction coefficient; wherein, the first look-up table is used to represent the corresponding relationship between different time periods and different queuing correction coefficients, and the first look-up table corresponding to each physical examination item is different; According to the queuing correction coefficients of all the physical examination items, the current number information, the queuing correction coefficients corresponding to the uncompleted items, the average time-consuming information and the current number information, through a preset time calculation model, obtaining the predicted waiting time of each uncompleted item.

3. The physical examination guidance method based on the smart wearable device according to claim 2, wherein The time calculation model is: ； Among them, P i represents the predicted waiting time, T i represents the average time-consuming information of the i-th unfinished item, N i represents the current number of people of the i-th unfinished item, C i represents the queuing correction coefficient of the i-th unfinished item, N j represents the current number of people of the j-th physical examination item, C j represents the queuing correction coefficient of the j-th physical examination item, ∑(N j * C j ) represents the sum of N j * C j for all physical examination items.

4. The physical examination guidance method based on the intelligent wearable device according to claim 2, wherein Before the step of obtaining the queuing correction coefficient according to the current time and the preset first look-up table, it further includes: Obtaining the historical data information of each physical examination item; wherein, the historical data information includes historical time periods, multiple groups of corresponding historical number information and historical time-consuming information in each historical time period; Establishing a correction model; Inputting the average time-consuming information corresponding to the physical examination item, the historical number information and the historical time-consuming information corresponding to the same historical time period into the correction model to obtain multiple candidate correction coefficients; Performing a weighted average process on the multiple candidate correction coefficients to obtain a target correction coefficient; wherein, in the weighted average process, the weight of each candidate correction coefficient is obtained according to the time generated by the corresponding historical number information and historical time-consuming information; Establishing the first look-up table according to the historical time period and the corresponding target correction coefficient.

5. The physical examination guidance method based on a smart wearable device according to claim 1, wherein The intelligent wearable device includes an ultra-wideband positioning module, and the intelligent wearable device is used to connect to ultra-wideband positioning base stations at different positions in the physical examination center through the ultra-wideband positioning module; The receiving of the current position information from the intelligent wearable device includes: Receiving a plurality of distance information sets from the intelligent wearable device; wherein, the distance information set includes a base station identifier and distance information from the ultra-wideband positioning base station corresponding to the base station identifier; Calculating the current position information in a three-dimensional space according to the distance information set.

6. The physical examination guidance method based on the smart wearable device according to claim 1, wherein The generating of a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model according to the current position information and the department position information corresponding to the unfinished item with the shortest predicted waiting time includes: Sending the unfinished item with the shortest predicted waiting time to the intelligent wearable device to wait for the physical examination person to confirm the next recommended physical examination item; Responding to a confirmation instruction from the intelligent wearable device, taking the unfinished item with the shortest predicted waiting time as the target physical examination item; Responding to a cancellation instruction from the intelligent wearable device, obtaining a selection instruction generated by the physical examination person from the unfinished items, and taking the physical examination item corresponding to the selection instruction as the target physical examination item; Generating a physical examination guidance route based on the electronic three-dimensional map through a preset path planning model according to the current position information and the department position information corresponding to the target physical examination item.

7. The physical examination guidance method based on the smart wearable device according to claim 1, wherein After the step of sending the physical examination guidance route to the intelligent wearable device, it further includes: Continuously obtaining the current position information and determining the current walking direction according to the change of the current position information; Generating a target walking direction according to the current walking direction, the current position information and the physical examination guidance route; Sending the target walking direction to the intelligent wearable device to display the target walking direction on the screen of the intelligent wearable device.

8. The physical examination guidance method based on the intelligent wearable device according to claim 1, characterized in that After the step of receiving a completion feedback signal from the intelligent wearable device and updating the personal physical examination monitoring library, it further includes: When the unfinished items in the personal physical examination monitoring library are empty, obtaining preset end position information; Generating a return guidance route based on the electronic three-dimensional map through a preset path planning model according to the current position information and the end position information; Sending the return guidance route to the intelligent wearable device.

9. An electronic device, characterized in that, Includes: At least one memory; At least one processor; At least one program; The program is stored in the memory, and the processor executes at least one of the programs to implement the physical examination guidance method based on an intelligent wearable device according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable signals for executing the physical examination guidance method based on an intelligent wearable device according to any one of claims 1 to 8.

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