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

Abstract

The application discloses a physical examination guiding method based on a smart wearable device, an electronic device and a storage medium, and comprises the following steps: acquiring physical examination item information; establishing and maintaining a communication connection with the smart wearable device, and sending the physical examination item information to the smart wearable device; acquiring an electronic three-dimensional map, department location information of each physical examination item, average time consumption information and current number information; obtaining a predicted waiting time through a time calculation model according to the current number information of all physical examination items, the average time consumption information and the current number information of unfinished items; receiving current position information from the smart wearable device, and generating a physical examination guiding route based on the electronic three-dimensional map through a path planning model according to the current position information and department location information corresponding to an unfinished item with the shortest predicted waiting time, and sending the physical examination guiding route to the smart wearable device. The application can provide real-time and accurate physical examination guidance for examinees, optimize a physical examination process and improve physical examination efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent interaction, in particular to a physical examination guiding method based on a smart wearable device, an electronic device and a storage medium. BACKGROUND

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

[0003] Currently, when a physical examination person performs physical examination, he / she usually needs to hold a paper physical examination sheet and find the location and queue by himself / herself. The layout of a hospital is often complex, and it is quite a challenge for a person who comes to the hospital for the first time to find the location of each physical examination department. This not only wastes a lot of time, but also easily causes the physical examination person to feel anxious and tired. At the same time, due to the lack of real-time understanding of the queuing situation of each physical examination item, the physical examination person may spend too much waiting time on some items, resulting in low efficiency of the whole physical examination process. For example, the physical examination person may go to an item with a large number of people first, ignoring the item next to him / her with a small number of people and a short estimated time, thereby unnecessarily prolonging the physical examination time.

[0004] This traditional physical examination mode lacks effective guidance and management, and cannot provide the physical examination person with the optimal physical examination route and time arrangement according to his / her real-time location and the queuing situation of each item, which seriously affects the experience and efficiency of the physical examination person. SUMMARY

[0005] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides a physical examination guiding method based on a smart wearable device, an electronic device and a storage medium, which can provide real-time and accurate physical examination guidance for the physical examination person, optimize the physical examination process and improve the physical examination efficiency.

[0006] In a first aspect, the present application provides a physical examination guiding method based on a smart wearable device, applied to a physical examination management platform, the physical examination guiding method comprising:

[0007] obtaining physical examination item information of a physical examination person, 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 completed items and uncompleted items;

[0008] establishing and maintaining a communication connection with a smart wearable device, and sending the physical examination item information to the corresponding smart wearable device;

[0009] obtaining an electronic three-dimensional map, and department location information, average time consumption information and current number information of each physical examination item;

[0010] According to the current number of people information of all the physical examination projects, the average time consumption information corresponding to the unfinished projects and the current number of people information, a predicted waiting time of each unfinished project is obtained through a preset time estimation model;

[0011] Receiving current position information from the smart wearable device, and according to the current position information and the department location information corresponding to the unfinished project with the shortest predicted waiting time, a physical examination guide route is generated based on the electronic three-dimensional map through a preset path planning model;

[0012] The physical examination guide route is sent to the smart wearable device;

[0013] Receiving a completion feedback signal from the smart wearable device, the personal physical examination monitoring library is updated.

[0014] According to the method for guiding physical examination based on the smart wearable device, the physical examination management platform obtains the physical examination item information of the examinee, and constructs a personal physical examination monitoring library based on the information. The personal physical examination monitoring library records the completed items and the unfinished 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 physical examination item content at any time through the smart wearable device. The platform obtains an electronic three-dimensional map, department location information, average time consumption information and current number information of each physical examination item. According to the average time consumption information and the current number information of the unfinished items, and by comprehensively considering the current number information of all the physical examination items, the overall operation load of the hospital at the current time point can be better reflected. Through a preset time calculation model, the predicted waiting time of each unfinished item is calculated. The platform receives the current position information of the examinee fed back by the smart wearable device, combines the department location information corresponding to the unfinished item with the shortest predicted waiting time, generates a physical examination guiding route based on the electronic three-dimensional map and a preset path planning model, and sends the generated physical examination guiding route to the smart wearable device. The examinee can intuitively see the best route to the next examination department. When the examinee completes an item, the smart wearable device sends a completion feedback signal to the platform, and the platform updates the personal physical examination monitoring library according to the feedback signal, so as to always keep track of the physical examination progress. By means of the time calculation model, the average time consumption and the current number information are used to predict the waiting time of each unfinished item, and then the route to the department of the item with the shortest waiting time is planned, so that the examinee can preferentially select the item with less queue number and shorter time consumption 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 improving the experience of the examinee. At the same time, by obtaining the electronic three-dimensional map and the department location information, the guiding route is generated by using the path planning model and sent to the smart wearable device, so that the examinee can clearly know the route to each examination department, greatly reducing the difficulty of finding the department in the complex environment of the hospital and saving the time spent in finding the department.

[0015] According to some embodiments of the first aspect of the application, the predicted waiting time of each unfinished item is obtained according to the current number information of all the physical examination items, the average time consumption information and the current number information of the unfinished items, and a preset time calculation model, comprising:

[0016] obtaining the current time;

[0017] obtaining 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 corresponding relationship between different time periods and different queuing correction coefficients, and the first comparison table corresponding to each physical examination item is different.

[0018] According to the queuing correction coefficient of all the physical examination projects and the current number information, the queuing correction coefficient corresponding to the unfinished project, the average time consumption information and the current number information, a predicted waiting time of each unfinished project is obtained through a preset time estimation model.

[0019] According to some embodiments of the first aspect of the present application, the time estimation model is:

[0020] ;

[0021] wherein P i represents the predicted waiting time, T i represents the average time consumption information of the i-th unfinished project, N i represents the current number information of the i-th unfinished project, C i represents the queuing correction coefficient of the i-th unfinished project, N j represents the current number information of the j-th physical examination project, C j represents the queuing correction coefficient of the j-th physical examination project, ∑(N j * C j ) represents the sum of N j * C j of all physical examination projects.

[0022] 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 comparison table, the method further comprises:

[0023] obtaining historical data information of each physical examination project; wherein the historical data information comprises historical time periods, a plurality of sets of corresponding historical number information and historical time consumption information in each historical time period;

[0024] establishing a correction model;

[0025] inputting the average time consumption information of the physical examination project, the historical number information and the historical time consumption information corresponding to the same historical time period into the correction model to obtain a plurality of candidate correction coefficients;

[0026] performing weighted average processing on the plurality of candidate correction coefficients to obtain a target correction coefficient; wherein the weight of each candidate correction coefficient in the weighted average processing is generated according to the time generated from the corresponding historical number information and the historical time consumption information;

[0027] establishing the first comparison table according to the historical time period and the corresponding target correction coefficient.

[0028] According to some embodiments of the first aspect of the application, the smart wearable device comprises an ultra-wideband positioning module, and the smart wearable device is configured to connect with ultra-wideband positioning base stations at different positions of the physical examination center through the ultra-wideband positioning module;

[0029] The current position information received from the smart wearable device comprises:

[0030] A plurality of distance information sets are received from the smart wearable device, wherein each distance information set comprises a base station identifier and distance information between the base station identified by the base station identifier and an ultra-wideband positioning base station.

[0031] The current position information in a three-dimensional space is calculated according to the distance information sets.

[0032] According to some embodiments of the first aspect of the application, the physical examination guide route is generated based on the electronic three-dimensional map and a preset path planning model according to the current position information and the department location information corresponding to the unfinished examination item with the shortest predicted waiting time.

[0033] The unfinished examination item with the shortest predicted waiting time is sent to the smart wearable device to wait for confirmation of the next recommended examination item by the examinee.

[0034] In response to a confirmation instruction from the smart wearable device, the unfinished examination item with the shortest predicted waiting time is taken as a target examination item.

[0035] In response to a cancellation instruction from the smart wearable device, a selection instruction generated by the examinee from the unfinished examination items is obtained, and an examination item corresponding to the selection instruction is taken as a target examination item.

[0036] The physical examination guide route is generated based on the electronic three-dimensional map and a preset path planning model according to the current position information and the department location information corresponding to the target examination item.

[0037] According to some embodiments of the first aspect of the application, after the step of sending the physical examination guide route to the smart wearable device, the method further comprises:

[0038] The current position information is continuously obtained, and a current walking direction is determined according to a change in the current position information.

[0039] A target walking direction is generated according to the current walking direction, the current position information, and the physical examination guide route.

[0040] send the target walking direction to the smart wearable device to display the target walking direction on a screen of the smart wearable device.

[0041] According to some embodiments of the first aspect of the present application, after the step of updating the personal physical examination monitoring library based on the feedback signal from the smart wearable device, the method further comprises:

[0042] when the unfinished items in the personal physical examination monitoring library are empty, obtaining preset end point position information;

[0043] According to the current position information and the end point position information, a return guide route is generated based on the electronic three-dimensional map and a preset path planning model.

[0044] send the return guide route to the smart wearable device.

[0045] In a second aspect, the present application further provides an electronic device, characterized in that comprising:

[0046] at least one memory;

[0047] at least one processor;

[0048] at least one program;

[0049] 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 the smart wearable device as described in any one of the embodiments of the first aspect.

[0050] In a third aspect, the present application further provides a computer readable storage medium, which stores computer executable signals, and the computer executable signals are used to execute the physical examination guidance method based on the smart wearable device as described in any one of the embodiments of the first aspect.

[0051] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0052] Additional aspects and advantages of the present application will become apparent and are in part summarized in the description of embodiments which follows, and in part will be apparent to those skilled in the art from the description of embodiments which follows, or can be learned by practice of the present application.

[0053] Figure 1 a flowchart of the physical examination guidance method based on the smart wearable device provided by the embodiments of the present application;

[0054] Figure 2 a flowchart of step S140 in the embodiments of the present application; Figure 1 ​

[0055] Figure 3 For this application Figure 2 Regarding the flowchart before step S220;

[0056] Figure 4 For this application Figure 1 Flowchart of the first part of step S150;

[0057] Figure 5 For this application Figure 1 Flowchart of the second part of step S150;

[0058] Figure 6 For this application Figure 1 Regarding the flowchart after step S160;

[0059] Figure 7 For this application Figure 1 Regarding the flowchart after step S170. DETAILED DESCRIPTION

[0060] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and are not to be construed as limiting the present application.

[0061] In the description of this application, it should be understood that descriptions involving orientations, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on this application.

[0062] In the description of this application, if there is a description of first or second, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0063] In the description of this application, unless otherwise clearly defined, terms such as setting, installing, and connecting should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this application based on the specific content of the technical solution.

[0064] In the field of medical examinations, the traditional physical examination process has many inconveniences. As people's health awareness increases, the demand for physical examinations is growing, and the number of physical examinations in major hospitals and physical examination institutions is increasing.

[0065] Currently, when a person undergoes a physical examination, he or she usually needs to hold a paper physical examination sheet and find the locations of various departments and wait in line by himself or herself. The layout of a hospital is often complex, and it is quite a challenge for a person who undergoes a physical examination for the first time to find the locations of various physical examination departments. This not only wastes a lot of time but also easily causes the person to feel anxious and tired. Meanwhile, due to the lack of real-time understanding of the queuing situation of various physical examination items, the person may spend too much waiting time on some items, resulting in low efficiency of the entire physical examination process. For example, the person may go to an item with a large number of people in line first and ignore an item with a small number of people in line and a short estimated time, thereby unnecessarily prolonging the physical examination time.

[0066] This traditional physical examination mode lacks effective guidance and management and cannot provide an optimal physical examination route and time arrangement for the person according to the real-time location of the person and the queuing situation of various items, which seriously affects the experience and efficiency of the person.

[0067] Based on this, the present application provides a physical examination guidance method based on a smart wearable device, an electronic device, and a storage medium to solve the above technical problems. The technical solutions provided by the present application are described in detail one by one as follows.

[0068] In a first aspect, with reference to Figure 1 The present application provides a physical examination guidance method based on a smart wearable device, applied to a physical examination management platform, which comprises the following steps:

[0069] Step S110: Obtain physical examination item information of a person undergoing a physical examination, 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 completed items and uncompleted items.

[0070] Step S120: Establish and maintain a communication connection with a smart wearable device, and send the physical examination item information to the corresponding smart wearable device.

[0071] Step S130: Obtain an electronic three-dimensional map, department location information of various physical examination items, average time consumption information, and current number information.

[0072] Step S140: According to the current number information of all physical examination items, the average time consumption information and the current number information of uncompleted items, obtain the predicted waiting time of each uncompleted item through a preset time calculation model.

[0073] Step S150: Receive current location information from the smart wearable device, and according to 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.

[0074] Step S160: send the physical examination guidance route to the smart wearable device.

[0075] Step S170: receive the completion feedback signal from the smart wearable device, and update the personal physical examination monitoring library.

[0076] 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 thereon, which records the completed items and the 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 physical examination item content at any time through the smart wearable device. The platform obtains an electronic three-dimensional map, department location information, average time consumption information, and current number information of each physical examination item. According to the average time consumption information and the current number information of the uncompleted items, and comprehensively considering the current number information of all physical examination items, the overall operation load of the hospital at the current time point can be better reflected. Through a preset time calculation model, the predicted waiting time of each uncompleted item is calculated. The platform receives the current location information of the examinee fed back from the smart wearable device, combines 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, so that 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 keep track of the physical examination progress. With the help of the time calculation model, the waiting time of each uncompleted item is predicted according to the average time consumption and the current number information, and then the route to the item department with the shortest waiting time is planned, so that the examinee can preferentially select the item with less queue number and shorter time consumption for physical examination, effectively avoiding wasting too much time in queuing, greatly improving the overall efficiency of physical examination, shortening the total physical examination time, and improving the experience of the examinee. At the same time, by obtaining the electronic three-dimensional map and the location information of each department, the guidance route is generated by using the path planning model and sent to the smart wearable device, so that the examinee can clearly know the route to each physical examination department, greatly reducing the difficulty of finding the department in the complex environment of the hospital, and saving the time spent in finding the department.

[0077] It should be noted that the smart wearable device is used to realize the physical examination guidance function, and 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., which is not limited in the present application.

[0078] Reference Figure 2 It can be understood that in step S140, the following steps can be understood but are not limited to:

[0079] Step S210: Obtain the current time.

[0080] Step S220: Obtain the queuing correction coefficient according to the current time and a preset first correspondence table; wherein the first correspondence table is used to represent the correspondence relationship between different time periods and different queuing correction coefficients, and the first correspondence table corresponding to each physical examination item is different.

[0081] Step S230: Obtain the predicted waiting time of each unfinished item through a preset time estimation model according to the queuing correction coefficient of all the physical examination items and the current number of people information, the queuing correction coefficient corresponding to the unfinished item, the average time consumption information and the current number of people information.

[0082] In steps S210 to S230, the physical examination management platform first accurately obtains the current time information. The platform consults the first correspondence table corresponding to each physical examination item according to the obtained current time. Since the busy degree of different physical examination items is different in different time periods, each item has a dedicated first correspondence table. The correspondence table records in detail the correspondence relationship between different time periods and different queuing correction coefficients. For example, for the blood routine examination item, the corresponding queuing correction coefficient may be 1.2 in the time period of 8:00-9:00 in the morning, and the corresponding queuing correction coefficient may be 0.8 in the time period of 2:00-3:00 in the afternoon. The platform combines the obtained queuing correction coefficient, the average time consumption information corresponding to the unfinished item and the current number of people information, and substitutes them into the preset time estimation model to calculate the predicted waiting time of each unfinished item, thereby providing accurate time data support for subsequent physical examination route planning. Considering the influence of different time periods on the queuing situation of each physical examination item, the queuing correction coefficient is introduced to more accurately predict the waiting time in the actual scene. Compared with the simple estimation according to the average time consumption and the current number of people, this method fully considers the change of the queuing situation caused by the time factor, so that the prediction result is 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. In addition, more accurate predicted waiting time can enable the physical examination management platform to make more scientific and reasonable decisions when planning the physical examination route. The platform can arrange the examinees to go to the item department with the shortest waiting time according to the accurate predicted waiting time of each item, further improve the physical examination efficiency, reduce the examinees' stay time in the hospital, and improve the overall physical examination experience.

[0083] It can be understood that the time estimation model is:

[0084] ;

[0085] wherein P irepresents the predicted waiting time, T i represents the average time consumption information of the i-th unfinished project, N i represents the current number information of the i-th unfinished project, C i represents the queuing correction coefficient of the i-th unfinished project, N j represents the current number information of the j-th physical examination project, C j represents the queuing correction coefficient of the j-th physical examination project, ∑(N j * C j represents the N j * C j of all physical examination projects.

[0086] In step S310, this time estimation model not only considers the average time consumption, the current number and the queuing correction coefficient of the unfinished project itself, but also combines the relevant data of all physical examination projects. By incorporating the comprehensive busy degree factor of the overall project, the prediction of the waiting time of each unfinished project is more comprehensive and accurate.

[0087] In the formula, the calculation related to other projects (i.e., ∑(N j *C j ) is to consider the relative weight. The N i *C i alone reflects the influence of the current queuing number and the queuing correction coefficient of the i-th project on its time. However, in the actual physical examination scene, the waiting time of each project is not isolated. When calculating the predicted time of a project, considering the sum of N j *C j of all projects can balance the mutual influence among projects as a whole. The model operates based on the data of all physical examination projects, which can better reflect the overall operation load of the hospital at the current time point. For example, if the hospital as a whole is in a busy state, the queuing numbers of multiple projects are all large (N j is large) and the queuing correction coefficient (C i ) also shows that the time consumption increases, then the sum will be large. In the formula, when the 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, and the influence of the busy degree of the entire hospital physical examination process on the time of a single project is comprehensively reflected, avoiding isolated calculation of the time of a single project. This is helpful for 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 personnel in each department, avoid the situation that some departments are overcrowded while some departments are idle, and improve the accuracy and rationality of the prediction.

[0088] Referring to Figure 3It can be understood that before step S220, the following steps can also be included, but are not limited to:

[0089] Step S410: Obtain historical data information of each physical examination item; wherein, the historical data information includes historical time periods, multiple sets of corresponding historical person number information and historical time consumption information in each historical time period.

[0090] Step S420: Establish a correction model.

[0091] Step S430: Input the average time consumption information corresponding to the physical examination item, the historical person number information and the historical time consumption information corresponding to the same historical time period into the correction model to obtain multiple candidate correction coefficients.

[0092] Step S440: Perform weighted average processing on the multiple candidate correction coefficients to obtain a target correction coefficient; wherein, the weight of each candidate correction coefficient in the weighted average processing is generated according to the time generated by the corresponding historical person number information and the historical time consumption information.

[0093] Step S450: Establish a first comparison table according to the historical time periods and the corresponding target correction coefficients.

[0094] In steps S410 to S430, the physical examination management platform starts a data collection program to extract 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 person number information and historical time consumption information. A correction model for calculating correction coefficients is constructed. The 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 the present application. The average time consumption information corresponding to each physical examination item, and the historical person number information and the historical time consumption information corresponding to the same historical time period, are sequentially input into the established correction model.

[0095] In steps S440 to S450, the multiple candidate correction coefficients obtained are subjected to weighted average processing. In the weighted average process, the weight of each candidate correction coefficient is determined according to the time generated by the corresponding historical person number information and the historical time consumption information. The closer the time is to the present, the higher the corresponding weight is, because recent data can better reflect the current actual situation. For example, the weight of data in the past month will be higher than the weight of 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 sorts and associates the historical time periods and the corresponding target correction coefficients to establish a first comparison table.

[0096] Through analysis of a large amount of historical data, combined with the operation of the correction model and the weighted average processing, the influence of different time periods, different queue numbers and time consumption on the correction coefficient is fully considered. Compared with simple experience setting or single data reference, this way can more accurately determine the corresponding queue correction coefficient of each time period, thereby improving the accuracy of subsequent prediction of waiting time.

[0097] With reference 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 with the ultra-wideband positioning base stations at different positions of the physical examination center through the ultra-wideband positioning module. In the step of receiving the current position information from the smart wearable device in step S150, the following steps can be included but are not limited to:

[0098] Step S510: receiving a plurality of distance information sets from the smart wearable device; wherein the distance information set includes the base station identifier and the distance information between the corresponding ultra-wideband positioning base station and the base station identifier;

[0099] Step S520: calculating the current position information in the three-dimensional space according to the distance information set.

[0100] In steps S510 to S520, when the examinee wears the smart wearable device and enters the physical examination center, the ultra-wideband positioning module in the smart wearable device automatically starts the search function. The module continuously sends ultra-wideband signals of a specific frequency to scan the ultra-wideband positioning base stations pre-deployed in different positions of the physical examination center. The smart wearable device periodically receives signals from the ultra-wideband positioning base stations through the ultra-wideband positioning module that has established a connection. Based on the time of flight (TOF) principle of the ultra-wideband positioning technology, the smart wearable device calculates the time experienced by the signal from the base station to be received by itself, and then converts the distance between each base station. After each reception is completed, the smart wearable device integrates the distance information obtained with the corresponding base station identifier to form a distance information set. For example, the distance information set may be in the form of [base station A, 5 meters; base station B, 8 meters; base station C, 6 meters]. Multiple such distance information sets are continuously sent to the physical examination management platform. After receiving multiple distance information sets from the smart wearable device, the physical examination management platform uses a specific algorithm to solve the position. In a three-dimensional space, the trilateration method or the multilateration method is usually used. Taking the trilateration method as an example, assuming that the coordinates of the three ultra-wideband positioning base stations are (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3), and the distances between the smart wearable device and the three base stations are d1, d2, and d3, respectively. Then, by constructing an equation set, the coordinates (x, y, z) of the smart wearable device in the three-dimensional space, i.e., the current position information of the examinee, are obtained. If there are more distance information sets, the multilateration method uses more distance information of the base stations to perform more accurate position calculation, further improving the positioning accuracy.

[0101] The 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 position of the examinee in the physical examination center, including the floor, room number, and even the specific direction. Even in areas with high personnel density or more signal shielding, such as elevators, corridor corners, etc., the ultra-wideband positioning module can still accurately calculate the position of the examinee through the signal interaction of multiple base stations, ensuring the stability of the physical examination guidance. For example, in the complex floor structure and numerous department layout of a large physical examination center, the examinee can be accurately guided to the next physical examination department, avoiding getting lost or taking the wrong road due to inaccurate positioning, greatly saving the time spent by the examinee in searching for the department.

[0102] Reference Figure 5 It can be understood that the step of "generating a physical examination guidance route based on the electronic three-dimensional map and the pre-set path planning model according to the current position information and the department position information corresponding to the unfinished project with the shortest predicted waiting time" in step S150 can include but is not limited to the following steps:

[0103] Step S610: Sending the unfinished item with the shortest predicted waiting time to the smart wearable device, waiting for the examinee to confirm the next recommended physical examination item;

[0104] Step S620: In response to the confirmation instruction from the smart wearable device, the unfinished item with the shortest predicted waiting time is selected as the target physical examination item;

[0105] Step S630: responding to the cancellation instruction from the smart wearable device, obtaining a selection instruction generated by the examinee's selection from the unfinished items, and using the physical examination item corresponding to the selection instruction as the target physical examination item;

[0106] 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.

[0107] In steps S610 to S630, after calculating the predicted waiting time for each uncompleted medical examination item, the medical examination management platform selects the uncompleted item with the shortest predicted waiting time. The platform then sends this information to the smart wearable device, which then notifies the examinee of the next recommended medical examination item through a pop-up window, vibration, or voice prompt, waiting for the examinee to confirm. For example, the smart wearable device screen may display a prompt: "We recommend a blood test next. This item has the shortest predicted waiting time. Are you sure you want to proceed?" After the examinee views the prompt on the smart wearable device and agrees to proceed with the recommended examination, they issue a confirmation instruction on the device. Upon receiving the confirmation instruction, the smart wearable device immediately transmits it to the medical examination management platform. In response to this confirmation instruction, the platform officially designates the uncompleted item with the shortest predicted waiting time as the target medical examination item, clarifying the target direction for subsequent route planning. If the examinee has personal reasons (such as preferring a specific examination first, having questions about the recommended item, etc.), they can issue a cancellation instruction on the smart wearable device. The smart wearable device sends a cancellation command to the medical examination management platform, which then initiates the autonomous selection process. The examinee can use the smart wearable device to select the medical examination item they wish to perform first from a list of uncompleted items displayed in the personal medical examination monitoring library, generating a selection command. The smart wearable device transmits this selection command to the platform, which responds by selecting the medical examination item corresponding to the selection command as the target medical examination item.

[0108] In step S640, the physical examination management platform obtains the current position information of the examinee and the department position information corresponding to the determined target physical examination item. Based on the preloaded electronic three-dimensional map, a preset path planning model is called. The path planning model takes the current position as the starting point and the department position of the target physical examination item as the end point, 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, i.e., the physical examination guide route, through an algorithm.

[0109] In the above steps, the examinee is given the right to choose physical examination items independently, fully respecting the personal wishes of the examinee. The examinee can flexibly decide the physical examination order according to their own situation and needs, rather than passively accepting system recommendations. This interactive way enhances the examinee's sense of participation and control in the physical examination process, making the physical examination process more humanized and greatly improving the user experience. The clear target physical examination item determination method ensures that the path planning model can calculate the route based on accurate starting and ending points. Whether the target item is recommended by the system or selected by the examinee, the generated physical examination guide route can more accurately meet the actual needs of the examinee, avoiding route deviation caused by unclear targets, further improving physical examination efficiency, and reducing the examinee's walking time and unnecessary waiting time in the hospital.

[0110] Reference Figure 6 It can be understood that after step S160, the following steps are included, but not limited to:

[0111] Step S710: continuously obtaining current position information and determining the current walking direction according to the change of the current position information;

[0112] Step S720: generating a target walking direction according to the current walking direction, the current position information and the physical examination guide route;

[0113] Step S730: sending the target walking direction to the smart wearable device to display the target walking direction on the screen of the smart wearable device.

[0114] In steps S710-S730, the physical examination management platform keeps real-time communication connection with the smart wearable device, continuously receives the current position information fed back from the smart wearable device ultra-wideband positioning module. The platform can continuously update the latest position coordinates of the examinee according to the set time interval (such as once per second), determines the current walking direction of the examinee by using vector calculation method according to the continuously acquired at least two current position information. The platform compares and analyzes the determined current walking direction with the physical examination guide route. First, the nearest path point on the physical examination guide route from the current position is found, and then the target direction from the current position along the physical examination guide route is calculated according to the position information of the path point and the next path point. For example, if the physical examination guide route is a straight line to the right front at this point, and the current walking direction is left, the platform will comprehensively consider the current position, the current walking direction and the direction of the physical examination guide route, and calculate a corrected target walking direction to guide the examinee to return to the correct route. The physical examination management platform sends the generated target walking direction to the smart wearable device through wireless communication. After the smart wearable device receives the target walking direction information, it displays it in an intuitive way on its screen. For example, an arrow icon may be displayed, and the direction of the arrow is the target walking direction. At the same time, a text prompt such as "please turn right and walk in this direction" can be displayed to let the examinee clearly understand the next step of the walking direction.

[0115] By real-time acquisition of position information and dynamic adjustment of target walking direction, the deviation from the route that may occur in the walking process of the examinee can be corrected in time. Compared with the traditional static navigation guide, this real-time dynamic navigation method can better adapt to the actual walking situation of the examinee in the complex hospital environment, avoid getting lost or delaying the physical examination time due to temporary change of route or wrong direction, and greatly improve the accuracy of navigation.

[0116] Reference Figure 7 It can be understood that after step S170, the following steps can also be included, but are not limited to:

[0117] Step S810: When the unfinished items in the personal physical examination monitoring library are empty, the preset end position information is acquired.

[0118] Step S820: According to the current position information and the end position information, a return guide route is generated based on the electronic three-dimensional map through the preset path planning model.

[0119] Step S830: The return guide route is sent to the smart wearable device.

[0120] In steps S810 to S830, the physical examination management platform continuously monitors the state of the personal physical examination monitoring library. When the platform receives a completion feedback signal from the smart wearable device, it updates the corresponding physical examination item state in the personal physical examination monitoring library one by one. After each update, the platform automatically checks the list of incomplete items in the personal physical examination monitoring library. If it is found that the incomplete item is empty, it means that the examinee has completed all the scheduled physical examination items, at which time the subsequent return guidance flow is triggered. Once it is determined that the examinee has completed all the physical examination items, the physical examination management platform obtains the preset end position information from the pre-set database. The physical examination management platform combines the current examinee position information obtained from the smart wearable device and the end position information just obtained, and based on the electronic three-dimensional map, calls the preset path planning model to calculate an optimal route from the current position of the examinee to the end position, i.e. the return guidance route. After the smart wearable device receives the return guidance route information, it will present it to the examinee on its screen in a similar way to the display of the physical examination guidance route, such as through map markers, arrow indications and text explanations, to guide the examinee to successfully arrive at the end position. The smart wearable device directly provides a clear return guidance route, greatly saving the examinee's time, especially in the case of unfamiliarity with the hospital environment, avoiding the trouble caused by getting lost, and improving the overall convenience of the physical examination service.

[0121] In a second aspect, the present application also provides an electronic device, comprising: at least one memory; at least one processor; at least one program; the program is stored in the memory, and the processor executes the at least one program to implement the nurse terminal operation interface personalized display method according to any one of the first aspect.

[0122] In the electronic device, the physical examination management platform obtains physical examination item information of a physical examinee, and constructs a personal physical examination monitoring library based on the physical examination item information, the personal physical examination monitoring library recording 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 physical examinee can know the physical examination item content at any time through the smart wearable device. The platform obtains an electronic three-dimensional map, department location information of each physical examination item, average time consumption information and current number information, calculates the predicted waiting time of each uncompleted item through a preset time calculation model according to the average time consumption information and the current number information of the uncompleted item corresponding to the uncompleted item. The platform receives the current position information of the physical examinee fed back from the smart wearable device, combines the department location information corresponding to the uncompleted item with the shortest predicted waiting time, generates a physical examination guide route based on the electronic three-dimensional map through a preset path planning model. The generated physical examination guide route is sent to the smart wearable device, so that the physical examinee can intuitively see the best route to the next physical examination department. When the physical 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 keep accurate tracking of the physical examination progress. With the help of the time calculation model, the average time consumption and the current number information are used to predict the waiting time of each uncompleted item, and then the route to the department of the item with the shortest waiting time is planned, so that the physical examinee can preferentially select the item with less queue number and shorter time consumption for physical examination, effectively avoiding wasting too much time in queuing, greatly improving the overall efficiency of physical examination, shortening the total physical examination time, and improving the experience of the physical examinee. At the same time, by obtaining the electronic three-dimensional map and the department location information, the guide route is generated by using the path planning model and sent to the smart wearable device, so that the physical examinee can clearly know the route to each physical examination department, greatly reducing the difficulty of finding the department in the complex environment of the hospital, and saving the time spent in finding the department.

[0123] The memory is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs, non-transitory computer executable programs and signals, such as program instructions / signals corresponding to the processing module in the embodiment of the 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 nurse terminal operation interface personalized display method of the above method embodiment.

[0124] The memory can include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function; and the data storage area can store related data of the nurse terminal operation interface personalized display method and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one disk storage device, a flash memory device or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processing module through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0125] One or more signals are stored in the memory, and when executed by one or more processors, perform the nurse terminal operation interface personalized display method in any method embodiment described above.

[0126] In a third aspect, the embodiments of the present application provide a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by one or more processors, and can make the one or more processors execute the nurse terminal operation interface personalized display method in the method embodiments described above.

[0127] The device embodiments described above are only schematic, wherein the units shown as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the present embodiment scheme.

[0128] From the description of the embodiments above, those skilled in the art can understand that all or some of the steps in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all of the 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 computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of 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 technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic 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, it is well known to those skilled in the art that communication media generally includes computer readable signals, data structures, program modules or other data in modulated data signals such as carrier waves or other transport mechanisms, and can include any information delivery medium.

[0129] It should be understood that in this application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, "A and / or B" can mean that there are three cases of only A, only B, and A and B at the same time, where A and B can be singular or plural. The character " / " generally represents that the associated objects before and after are in an "or" relationship. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least 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, and c can be single or multiple.

[0130] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the above units is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, apparatuses or units, and can be electrical, mechanical or other forms.

[0131] The units described above as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place or can be distributed to a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0132] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0133] If the integrated unit is realized 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 this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of 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 method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0134] The embodiments of the present application are described in detail above in combination with the drawings, but the present application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the purpose of the present application.

Claims

1. A physical examination guiding method based on a smart wearable device, characterized in that, The application is applied to a physical examination management platform, and the physical examination guiding method comprises the following steps: Obtaining physical examination item information of a physical 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 for recording completed items and uncompleted items; Establishing and maintaining communication connection with a smart wearable device, and sending the physical examination item information to the corresponding smart wearable device; Obtaining an electronic three-dimensional map, department location information of each physical examination item, average time consumption information and current number information; According to the current number information of all the physical examination items, the average time consumption information and the current number information of the uncompleted items, a prediction waiting time of each uncompleted item is obtained through a preset time calculation model; Receiving current location information from the smart wearable device, and generating a physical examination guiding 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 uncompleted item with the shortest prediction waiting time; Sending the physical examination guiding route to the smart wearable device; Receiving a completion feedback signal from the smart wearable device, and updating the personal physical examination monitoring library; According to the current time and a preset first comparison table, a queuing correction coefficient is obtained; wherein the first comparison table is used for representing the corresponding relationship between different time periods and different queuing correction coefficients, and the first comparison table corresponding to each physical examination item is different; According to the queuing correction coefficient and the current number information of all the physical examination items, the queuing correction coefficient, the average time consumption information and the current number information of the uncompleted items, a prediction waiting time of each uncompleted item is obtained through a preset time calculation model; The time calculation model is: Before the step of obtaining the queuing correction coefficient according to the current time and a preset first comparison table, the following steps are further included: Obtaining historical data information of each physical examination item; wherein the historical data information comprises a historical time period, a plurality of sets of corresponding historical number information and historical time consumption information in each historical time period; ； wherein P i represents the predicted waiting time, T i represents the average time consumption information of the i-th unfinished project, N i represents the current number information of the i-th unfinished project, C i represents the queuing correction coefficient of the i-th unfinished project, N j represents the current number information of the j-th medical examination project, C j represents the queuing correction coefficient of the j-th medical examination project, ∑(N j * C j represents the sum of N j * C j of all medical examination projects. 2.The smart wear device-based physical examination guiding method according to claim 1, characterized in that, Establishing a correction model; Inputting the average time consumption information corresponding to the physical examination item, the historical number information corresponding to the same historical time period and the historical time consumption information into the correction model to obtain a plurality of candidate correction coefficients; Weighted average processing is performed on the plurality of candidate correction coefficients to obtain a target correction coefficient; wherein the weight of each candidate correction coefficient in the weighted average processing is obtained according to the time generated by the corresponding historical number information and the historical time consumption information; According to the historical time period and the corresponding target correction coefficient, the first comparison table is established. ​ ​ 3.The smart wear device based physical examination guiding method according to claim 1, characterized in that, The intelligent wearable device comprises an ultra-wideband positioning module, and the intelligent wearable device is connected with ultra-wideband positioning base stations at different positions of the physical examination center through the ultra-wideband positioning module. The current position information from the intelligent wearable device is received, comprising: A plurality of distance information sets from the intelligent wearable device are received; wherein the distance information set comprises a base station identifier and distance information between the ultra-wideband positioning base station corresponding to the base station identifier; According to the distance information set, the current position information in the three-dimensional space is calculated. 4.The smart wear device based physical examination guiding method according to claim 1, characterized in that, According to the current position information and the department position information corresponding to the unfinished project with the shortest predicted waiting time, a physical examination guide route is generated based on the electronic three-dimensional map through a preset path planning model, comprising: The unfinished project with the shortest predicted waiting time is sent to the intelligent wearable device to wait for the examinee to confirm the next recommended physical examination project; In response to the confirmation instruction from the intelligent wearable device, the unfinished project with the shortest predicted waiting time is taken as the target physical examination project; In response to the cancellation instruction from the intelligent wearable device, a selection instruction generated by the examinee from the unfinished project is obtained, and the physical examination project corresponding to the selection instruction is taken as the target physical examination project; According to the current position information and the department position information corresponding to the target physical examination project, a physical examination guide route is generated based on the electronic three-dimensional map through a preset path planning model. 5.The smart wear device based physical examination guiding method according to claim 1, characterized in that, After the step of sending the physical examination guide route to the intelligent wearable device, it further comprises: The current position information is continuously obtained, and the current walking direction is determined according to the change of the current position information; According to the current walking direction, the current position information and the physical examination guide route, a target walking direction is generated; The target walking direction is sent to the intelligent wearable device to display the target walking direction on the screen of the intelligent wearable device. 6.The smart wear device based physical examination guiding method according to claim 1, characterized in that, After the step of receiving the completion feedback signal from the intelligent wearable device to update the personal physical examination monitoring library, it further comprises: When the unfinished project in the personal physical examination monitoring library is empty, a preset terminal position information is obtained; According to the current position information and the terminal position information, a return guide route is generated based on the electronic three-dimensional map through a preset path planning model; The return guide route is sent to the intelligent wearable device.

7. An electronic device, comprising: Comprise: 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 realize the physical examination guide method based on the intelligent wearable device according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer executable signals, and the computer executable signals are used to execute the physical examination guide method based on the intelligent wearable device according to any one of claims 1 to 6.

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