A medical equipment data acquisition device and method based on the Internet of Things

Abstract

The application provides a medical equipment data acquisition device and method based on the Internet of Things, wherein the device comprises: a listening module, which is used for listening to a medical equipment data acquisition request in a hospital area; an analysis module, which is used for analyzing a requestor, a medical equipment to be acquired and a request data type in the listened medical equipment data acquisition request; an acquisition module, which is used for acquiring the medical equipment data of the request data type through a preset Internet of Things node corresponding to the medical equipment to be acquired; and a return module, which is used for returning the medical equipment data to the requestor. The medical equipment data acquisition device based on the Internet of Things listens to the medical equipment data acquisition request in the hospital area, acquires the corresponding medical equipment data based on the Internet of Things and returns to the requestor, and thus the relevant staff of the medical equipment in the hospital area can remotely call the medical equipment data for viewing or using at any time, the work efficiency is improved, and the labor cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, in particular to a medical equipment data acquisition device and method based on Internet of Things. BACKGROUND

[0002] At present, the device data of some medical equipment put into use in hospital area cannot be remotely called for viewing or using at any time. For example, when medical staff wants to view the electrocardiogram information and electroencephalogram information of patients, they need to go to the site of patients to view the physical condition data monitored and obtained by medical equipment such as electrocardiogram monitor and electroencephalogram monitor used for patients; for another example, when the device maintenance personnel of medical equipment wants to view the running data of medical equipment for abnormal checking, they need to go to the site to connect medical equipment by PDA device to call the running data. In this way, it will lead to the decrease of the work efficiency of the relevant staff of medical equipment in hospital, and also increase the labor cost to some extent. Therefore, it is urgent to be solved. SUMMARY

[0003] One of the purposes of the present application is to provide a medical equipment data acquisition device and method based on Internet of Things, which listens to the medical equipment data acquisition request in hospital area, acquires the corresponding medical equipment data based on Internet of Things and returns to the requester, so that the relevant staff of medical equipment in hospital area can remotely call the medical equipment data for viewing or using at any time, which improves the work efficiency and reduces the labor cost.

[0004] The medical equipment data acquisition device based on Internet of Things provided by the embodiment of the present application comprises:

[0005] A listening module is used for listening to the medical equipment data acquisition request in hospital area;

[0006] An analysis module is used for analyzing the requester, the medical equipment to be acquired and the request data type in the listened medical equipment data acquisition request;

[0007] An acquisition module is used for acquiring the medical equipment data of the request data type through the preset Internet of Things node corresponding to the medical equipment to be acquired;

[0008] A return module is used for returning the medical equipment data to the requester.

[0009] Preferably, the medical equipment data acquisition request in hospital area comprises:

[0010] The medical equipment data acquisition request emitted by a plurality of health monitoring devices in hospital area is listened to;

[0011] And / or,

[0012] Listening to the medical equipment data collection request issued by the multiple device anomaly detection devices in the hospital campus;

[0013] and / or,

[0014] Listening to the medical equipment data collection request issued by the multiple medical staff terminal devices in the hospital campus;

[0015] and / or,

[0016] Listening to the medical equipment data collection request issued by the conference members in the multiple online conferences in progress in the hospital campus.

[0017] Preferably, listening to the medical equipment data collection request issued by the conference members in the multiple online conferences in progress in the hospital campus comprises:

[0018] Obtaining the conference speeches of the conference members;

[0019] Sorting the conference speeches according to the speaking order to obtain a speaking sequence;

[0020] Starting from the sequence starting point of the speaking sequence, sequentially traversing the conference speeches, at each traversal, extracting keywords from the traversed conference speeches to obtain a first keyword set, matching the first keyword set with a preset trigger keyword set, if the matching is consistent, stopping traversing the conference speeches, and obtaining a preset associated keyword set corresponding to the matching consistent trigger keyword set;

[0021] Extracting keywords from a preset number of conference speeches after the traversed conference speeches in the speaking sequence to obtain a second keyword set;

[0022] Matching the second keyword set with the associated keyword set, if the matching is consistent, obtaining a preset speech type corresponding to the matching consistent associated keyword set;

[0023] When the speech type is divergence, the conference speech corresponding to the matching consistent second keyword set is taken as a divergence speech;

[0024] When the speech type is supplement, the conference speech corresponding to the matching consistent second keyword set is taken as a supplement speech;

[0025] Respectively extracting semantics from the traversed conference speeches, the last divergence speech and each supplement speech in the speaking sequence to obtain multiple speech semantics;

[0026] Based on the speech semantics, determining the medical equipment data collection request;

[0027] Eliminating all conference speeches before the latter of the last divergence speech and the last supplement speech in the speaking sequence, after the elimination, continuing to traverse the remaining conference speeches.

[0028] Preferably, the medical device data collection request is determined based on the speech semantics of the speech, comprising:

[0029] determining a first medical device data requirement based on the speech semantics of the traversed conference speech;

[0030] performing requirement correction on the first medical device data requirement based on the speech semantics of the last divergent speech in the speech sequence to obtain a medical device data correction requirement;

[0031] determining a second medical device data requirement based on the speech semantics of each supplementary speech;

[0032] generating the medical device data collection request based on the medical device data correction requirement and the second medical device data requirement.

[0033] Preferably, the medical device data of the requested data type is collected through a preset Internet of Things node corresponding to the medical device to be collected, comprising:

[0034] inquiring the node condition of the Internet of Things node based on a preset node condition inquiry template to obtain the node condition returned by the Internet of Things node;

[0035] performing feature extraction on the node condition to obtain a condition feature set;

[0036] obtaining a preset index condition feature set corresponding to the Internet of Things node;

[0037] matching the condition feature set with the index condition feature set to obtain a matching degree;

[0038] if the matching degree is greater than or equal to a preset matching degree threshold, collecting the medical device data of the requested data type through the Internet of Things node.

[0039] Preferably, the medical device data is returned to the requester, comprising:

[0040] obtaining a preset data preference of the requester corresponding to the requested data type;

[0041] performing preprocessing on the medical device data based on the data preference to obtain a preprocessing result;

[0042] performing data packaging on the preprocessing result to obtain a data package;

[0043] returning the data package to the requester.

[0044] The medical device data collection method based on the Internet of Things provided by the embodiment of the application comprises:

[0045] Step S1: listening to a medical device data collection request in a hospital area;

[0046] Step S2: parsing the requestor, the medical device to be collected, and the request data type in the monitored medical device data collection request;

[0047] Step S3: collecting the medical device data of the request data type through the preset Internet of Things node corresponding to the medical device to be collected;

[0048] Step S4: returning the medical device data to the requestor.

[0049] Preferably, the medical device data collection request in the hospital campus is monitored, including:

[0050] Monitoring the medical device data collection request issued by the plurality of health monitoring devices in the hospital campus;

[0051] And / or,

[0052] Monitoring the medical device data collection request issued by the plurality of device anomaly detection devices in the hospital campus;

[0053] And / or,

[0054] Monitoring the medical device data collection request issued by the plurality of medical staff terminal devices in the hospital campus;

[0055] And / or,

[0056] Monitoring the medical device data collection request issued by the conference members in the plurality of online conferences being held in the hospital campus.

[0057] Preferably, the medical device data collection request issued by the conference members in the plurality of online conferences being held in the hospital campus is monitored, including:

[0058] Obtaining the conference speech of the conference members;

[0059] Sorting the conference speeches according to the speaking order to obtain a speaking sequence;

[0060] Traversing the conference speeches in sequence from the sequence starting point of the speaking sequence, and extracting keywords from the traversed conference speeches each time to obtain a first keyword set, and matching the first keyword set with a preset trigger keyword set, if the matching is consistent, stopping traversing the conference speeches, and obtaining a preset associated keyword set corresponding to the trigger keyword set matched;

[0061] Extracting keywords from the preset number of conference speeches after the traversed conference speeches in the speaking sequence to obtain a second keyword set;

[0062] Matching the second keyword set with the associated keyword set, if the matching is consistent, obtaining a preset speech type corresponding to the associated keyword set matched;

[0063] When the speech type is a divergence, the conference speech corresponding to the matched second keyword set is taken as a divergence speech;

[0064] When the speech type is a supplement, the conference speech corresponding to the matched second keyword set is taken as a supplement speech;

[0065] The semantic of the conference speech, the last divergence speech in the speech sequence and each supplement speech is extracted respectively, and a plurality of speech semantics is obtained;

[0066] Based on the speech semantics, a medical device data collection request is determined;

[0067] All conference speeches before the latter of the last divergence speech and the last supplement speech in the speech sequence are removed, and after the removal, the remaining conference speeches are continuously traversed.

[0068] Preferably, based on the speech semantics, the medical device data collection request is determined, comprising:

[0069] Based on the speech semantics of the traversed conference speech, a first medical device data requirement is determined;

[0070] Based on the speech semantics of the last divergence speech in the speech sequence, the first medical device data requirement is corrected, and a medical device data correction requirement is obtained;

[0071] Based on the speech semantics of each supplement speech, a second medical device data requirement is determined;

[0072] Based on the medical device data correction requirement and the second medical device data requirement, a medical device data collection request is generated.

[0073] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art upon examination of the following or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0074] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0075] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate the present application and explain the principles of the present application, and do not constitute a limitation of the present application. In the drawings:

[0076] Figure 1 is a schematic view of a medical device data collection device based on the Internet of Things in an embodiment of the present application;

[0077] Figure 2A schematic diagram of a medical equipment data acquisition method based on an Internet of Things in an embodiment of the present application. DETAILED DESCRIPTION

[0078] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, in which it should be understood that the preferred embodiments described herein are intended to serve only as an illustration and explanation of the present application, and are not intended to limit the present application.

[0079] An apparatus for acquiring medical equipment data based on an Internet of Things is provided in an embodiment of the present application, as shown in the accompanying drawings, comprising: Figure 1

[0080] A listening module 1 is configured to listen to a medical equipment data acquisition request in a hospital area.

[0081] An analysis module 2 is configured to analyze a requestor, a medical equipment to be acquired, and a data type to be requested in the listened medical equipment data acquisition request.

[0082] An acquisition module 3 is configured to acquire medical equipment data of the data type to be requested through a preset Internet of Things node corresponding to the medical equipment to be acquired.

[0083] A return module 4 is configured to return the medical equipment data to the requestor.

[0084] The working principle and beneficial effects of the above technical solution are as follows:

[0085] The present application is implemented in a platform form when applied. The platform is communicatively interfaced with each medical equipment in a hospital area to implement an Internet of Things setup. The platform is also communicatively interfaced with an intelligent terminal used by a medical equipment related staff in the hospital area, such as a mobile phone, a computer, and the like used by medical staff and medical equipment maintenance personnel, to monitor whether the staff sends a medical equipment data acquisition request based on the intelligent terminal. The requestor is a medical equipment data demand party, the medical equipment to be acquired is data of which medical equipment required by the requestor, and the data type to be requested is which type of data of the medical equipment to be acquired required by the requestor. For example, a medical staff A wants to view electrocardiogram information of a patient B, the requestor is the medical staff A, the medical equipment to be acquired is an electrocardiogram monitor used by the patient B, and the data type to be requested is the electrocardiogram information. When the platform acquires data, the medical equipment data of the data type to be requested is acquired through a preset Internet of Things node corresponding to the medical equipment to be acquired. The preset Internet of Things node is a communication node for communication between the platform and the medical equipment. After the acquisition is completed, the medical equipment data is returned to the requestor, and the requestor can view the data.

[0086] ​The application listens to the medical equipment data collection request in the hospital area, collects the corresponding medical equipment data based on the Internet of Things and returns to the requester. The relevant staff of the medical equipment in the hospital area can remotely call the medical equipment data at any time for viewing or use, which improves the work efficiency and reduces the labor cost.

[0087] In one embodiment, the medical equipment data collection request in the hospital area is listened to, including:

[0088] Listening to the medical equipment data collection request sent by the multiple health monitoring devices in the hospital area;

[0089] and / or,

[0090] Listening to the medical equipment data collection request sent by the multiple equipment anomaly detection devices in the hospital area;

[0091] and / or,

[0092] Listening to the medical equipment data collection request sent by the multiple medical staff terminal devices in the hospital area;

[0093] and / or,

[0094] Listening to the medical equipment data collection request sent by the conference members in the multiple online conferences in progress in the hospital area.

[0095] The working principle and beneficial effects of the above technical solutions are:

[0096] The types of the requestors are four: the first type is a health monitoring device. The health monitoring device is a device for monitoring whether the physical condition of a patient is normal. When the health monitoring device performs health monitoring, it needs to call physical condition data monitored by a physical condition monitoring instrument used by the patient (for example, the monitoring device needs to monitor whether the heart rate of the patient is within a normal range, and thus needs to call data measured by a heart rate instrument used by the patient), and sends a medical device data collection request by itself when the data needs to be called. The second type is a device anomaly detection device. The device anomaly detection device is a device for detecting whether a medical device is abnormal. The device anomaly detection device is usually used by a medical device maintenance personnel. When the device anomaly detection device performs device anomaly detection, it needs to call running data of the device (for example, running voltage and current of the medical device), and the medical device maintenance personnel inputs a medical device data collection request based on the device anomaly detection device when the data needs to be called. The third type is a medical staff terminal device. The medical staff terminal device can be a mobile phone used by medical staff. When the medical staff needs to call medical device data, the medical staff inputs a medical device data collection request based on the medical staff terminal device. The fourth type is an online conference. When a discussion conference on how to treat a patient is held in a hospital, some information about the patient is used as a situation introduction (for example, the heart rate and blood pressure of the patient are called), and thus conference members in the conference need to call data collected by related medical devices. Therefore, when the platform performs medical device data collection request listening, it can listen to whether the four types of requestors send the request.

[0097] The embodiment of the present application introduces four types of requestors, listens to whether the requestors send medical device data collection requests, improves the comprehensiveness of medical device data collection request listening, and improves the applicability of the system to the use of a hospital area.

[0098] In one embodiment, the medical device data collection request sent by the conference members in the multiple online conferences being performed in the hospital area is listened to, and the method comprises the following steps.

[0099] Obtaining a conference speech of the conference member;

[0100] Sorting the conference speeches according to the speaking order to obtain a speaking sequence;

[0101] Traversing the conference speeches in sequence from the sequence starting point of the speaking sequence, extracting a first keyword set from the conference speeches traversed each time, matching the first keyword set with a preset trigger keyword set, stopping the traversal of the conference speeches if the matching is consistent, and obtaining a preset associated keyword set corresponding to the trigger keyword set matched.

[0102] Extracting keywords from a preset number of conference speeches after the conference speeches traversed in the speaking sequence to obtain a second keyword set;

[0103] matching the second keyword set with the associated keyword set, if the matching is consistent, obtaining a preset speech type corresponding to the associated keyword set matched with the second keyword set;

[0104] when the speech type is divergence, taking the conference speech corresponding to the second keyword set matched as divergence speech;

[0105] when the speech type is supplement, taking the conference speech corresponding to the second keyword set matched as supplement speech;

[0106] respectively extracting semantics of the conference speech, the last divergence speech and each supplement speech in the speech sequence, obtaining a plurality of speech semantics;

[0107] determining a medical device data collection request based on the speech semantics;

[0108] eliminating all conference speeches before the latter of the last divergence speech and the last supplement speech in the speech sequence, and continuing to traverse the remaining conference speeches after the elimination.

[0109] The working principle and beneficial effects of the above technical solutions are:

[0110] During the conference, when the medical device data needs to be retrieved, the conference needs to be paused, and a conference member needs to be arranged by the conference host to retrieve the medical device data, which is relatively cumbersome. In addition, the conference member may be outdoors or off duty and does not carry a device with medical device data retrieval authority. Therefore, the medical device data required during the conference can be adaptively determined based on the conference speeches of the conference members.

[0111] The conference speech is text converted from the speech of the conference member in the online conference. When the conference speech is keyword extracted, the keyword combination of the text is extracted to form a keyword set. The preset trigger keyword set is formed by the keyword combination of the conference speech representing the medical device data retrieval demand of the conference member in advance. The preset associated keyword set corresponding to the trigger keyword set is formed by the keyword combination of the conference speech representing the divergence of the medical device data retrieval demand of the conference member represented by the trigger keyword set. The preset speech type corresponding to the associated keyword set is divided into divergence and supplement. The divergence is the divergence of the medical device data retrieval demand of the conference member represented by the trigger keyword set. The supplement is the supplement of the medical device data retrieval demand of the conference member represented by the trigger keyword set. The preset number is a constant.

[0112] The application sets the trigger keyword set as {“call” “bed” “patient” and “ECG”} in implementation, for example, if the first keyword set matches, it means that the conference member proposes to call the ECG information of a certain bed patient. However, the conference member may make a different opinion and / or supplement the opinion, therefore, the association keyword set is set as {“ECG” “see later”}, if the second keyword set of the subsequent speech matches, it means that the conference member makes a different opinion of calling the ECG information later, and the speech type is different. The association keyword set can also be set as {“also” “his” and “EEG”}, if the second keyword set of the subsequent speech matches, it means that the conference member makes a supplementary opinion of also calling the EEG information of the bed patient, and the speech type is supplementary.

[0113] Generally, after the different opinion is made, a new different opinion may be made subsequently, and the last different opinion made is the opinion without difference among the conference members, which can be used as the decision opinion of calling the medical equipment data, and used for correcting the original opinion represented by the conference speech traversed. Each point of the supplementary speech can be used as the decision opinion of calling the medical equipment data. Therefore, the semantic extraction is performed on the conference speech traversed, the last different speech in the speech sequence and each supplementary speech, respectively, to obtain multiple speech semantics, and the medical equipment data collection request is determined based on the speech semantics.

[0114] In addition, in order to save traversal resources, all conference speeches before the latter of the last different speech and the last supplementary speech in the speech sequence are the discussion stage of the medical equipment data calling opinion and the different / supplementary opinion making, and are excluded before the traversal of the conference speech is continued.

[0115] The embodiment of the application adaptively determines the medical equipment data collection request of calling the medical equipment data in the conference process based on the conference speech of the conference member, without temporarily suspending the conference to arrange a conference member to call, improves the conference efficiency, and when the data is adaptively called, the output is performed along with the conversation of the conference member, so that the conference member can view, and the user experience is improved.

[0116] In one embodiment, the medical equipment data collection request is determined based on the speech semantics, including:

[0117] The first medical equipment data demand is determined based on the speech semantics of the conference speech traversed;

[0118] The first medical equipment data demand is corrected based on the speech semantics of the last different speech in the speech sequence, to obtain the medical equipment data correction demand;

[0119] The second medical equipment data demand is determined based on the speech semantics of each supplementary speech;

[0120] generate the medical equipment data collection request based on the medical equipment data revision requirement and the second medical equipment data requirement.

[0121] The working principle and beneficial effects of the above technical solution are:

[0122] The first medical equipment data requirement is a retrieval requirement before the meeting member proposes a difference / supplementary opinion, which is determined based on the speech semantics of the traversed meeting speech, for example: the speech semantics of the traversed meeting speech is "adjust the electrocardiogram information of the patient in bed 302", and the first medical equipment data requirement is the electrocardiogram information monitored by the electrocardiogram monitor used by the patient in bed 302. The speech semantics of the last difference speech revises the first medical equipment data requirement, for example: the speech semantics of the last difference speech is "review the electrocardiogram information later", and the first medical equipment data requirement is revised to be a blank requirement. Based on the speech semantics of each supplementary speech, the second medical equipment data requirement is determined, for example: the speech semantics of the supplementary speech is "review his electroencephalogram information again", and the second medical equipment data requirement is the electroencephalogram information monitored by the electroencephalogram monitor used by the patient in bed 302. Based on the medical equipment data revision requirement and the second medical equipment data requirement, the medical equipment data collection request is generated, for example: the electrocardiogram information monitored by the electrocardiogram monitor used by the patient in bed 302 and the electroencephalogram information monitored by the electroencephalogram monitor used by the patient in bed 302 are collected.

[0123] The embodiment of the application generates a medical equipment data collection request based on speech semantics, improving the accuracy of medical equipment data collection request determination.

[0124] In one embodiment, the medical equipment data of the request data type is collected by the preset Internet of Things node corresponding to the to-be-collected medical equipment, including:

[0125] Inquire about the node condition of the Internet of Things node based on the preset node condition inquiry template, and obtain the node condition returned by the Internet of Things node;

[0126] Extract features from the node condition to obtain a condition feature set;

[0127] Obtain a preset index condition feature set corresponding to the Internet of Things node;

[0128] Match the condition feature set with the index condition feature set to obtain a matching degree;

[0129] If the matching degree is greater than or equal to a preset matching degree threshold, collect the medical equipment data of the request data type through the Internet of Things node.

[0130] The working principle and beneficial effects of the above technical solution are:

[0131] The preset node condition inquiry template is provided with a plurality of inquiry rules for inquiring about the load condition of the Internet of Things node, such as inquiring about the number of tasks being performed by the Internet of Things node for data collection and inquiring about the throughput of the Internet of Things node. Correspondingly, the node condition returned by the Internet of Things node after the node condition inquiry of the Internet of Things node is the node load condition, such as the number of tasks being performed for data collection being 3 and the throughput being 1280 bps. The preset index condition feature set corresponding to the Internet of Things node is formed by pre-setting an index condition feature combination representing the node load condition in which the Internet of Things node can perform data communication collection in the best state, and the index condition feature is, for example, the number of tasks being performed for data collection being 2 and the throughput being 3000 bps. The condition feature set and the index condition feature set are matched, and if the matching degree is greater than or equal to a preset matching degree threshold, it is indicated that the collection opportunity is appropriate, and the medical device data is collected through the Internet of Things node.

[0132] In the embodiment of the application, the load condition of the Internet of Things node is inquired about when the medical device data is collected through the Internet of Things node, and whether the collection is appropriate is determined based on the load condition, so as to avoid the situation that the node load is too high caused by direct collection, and the stability of the operation of the Internet of Things node is improved.

[0133] In one embodiment, the medical device data is returned to the requester, including:

[0134] A preset data preference of the requester corresponding to the requested data type is obtained;

[0135] The medical device data is preprocessed based on the data preference to obtain a preprocessing result;

[0136] The preprocessing result is packaged to obtain a data packet;

[0137] The data packet is returned to the requester.

[0138] The working principle and beneficial effects of the above technical solution are:

[0139] The preset data preference of the requester corresponding to the requested data type is a pre-set use preference of the data of the requester corresponding to the requested data type, and correspondingly, for example, the health monitoring device needs to extract the maximum and minimum heart rates in a certain period of time, and the data preference is to extract the maximum and minimum heart rates, and for another example, the device anomaly detection device needs to extract the error records during the operation of the medical device, and the data preference is to extract the error records. Therefore, the medical device data can be preprocessed based on the data preference and packaged, and then returned to the requester, which increases the use efficiency of the medical device data used by the requester, and is also more humanized.

[0140] The data preference can be set by a medical device related staff, and target data can also be obtained from a big data platform, and the target data is determined based on the target data, for example: obtaining target data of health monitoring basis and principle in the official specification of the health monitoring device, and determining the data preference based on the target data, and for another example: obtaining target data of device abnormality detection basis and principle in the official specification of the device abnormality detection device, and determining the data preference based on the target data. Wherein, the target data obtained from the big data platform comprises: respectively obtaining a credit value of the big data platform and a guarantee value of the big data platform guaranteeing the target data; the credit value represents the overall quality of the data provided by the big data platform in history, and the higher the credit value, the better the overall quality; the big data platform needs to guarantee the target data before providing the target data, and the greater the guarantee value, the greater the guarantee strength; based on the credit value and the guarantee value, a first determination index is calculated, and the calculation formula is as follows: Wherein, is the first determination index, m and n are preset weight values, D is the credit value, and H is the guarantee value; if the first determination index is greater than or equal to a preset first determination index threshold, a plurality of historical credibility of the source of the target data is obtained; the first determination index threshold is a constant, for example: 90; the historical credibility is the credibility in history of the source, for example: the website credibility of the official website of the health monitoring device; based on the plurality of historical credibility, a second determination index is calculated, and the calculation formula is as follows: Wherein, is the second determination index, Q P is the Pth historical credibility, and K is the total number of historical credibility; if the second determination index is greater than or equal to a preset second determination index, the target data is obtained. The second determination index is a constant, for example: 95. First, the credit and guarantee verification is carried out, and if the verification fails, the target data is not obtained and the next step verification is not carried out, so that the verification efficiency is improved; when the credit and guarantee verification is passed, the credibility verification of the source of the target data is carried out again, so that the reliability of the obtained target data is fully guaranteed, and the applicability of obtaining the target data from the big data platform is improved.

[0141] The embodiment of the application provides a medical device data acquisition method based on an Internet of Things, as shown in Figure 2 , comprising:

[0142] Step S1: listening to a medical device data acquisition request in a hospital area;

[0143] Step S2: analyzing a request party, a to-be-acquired medical device and a request data type in the listened medical device data acquisition request;

[0144] Step S3: acquiring medical device data of the request data type through a preset Internet of Things node corresponding to the to-be-acquired medical device;

[0145] Step S4: returning the medical device data to the requester.

[0146] In one embodiment, the medical device data collection request in the hospital campus is monitored, including:

[0147] The medical device data collection request from the plurality of health monitoring devices in the hospital campus is monitored;

[0148] and / or,

[0149] The medical device data collection request from the plurality of device anomaly detection devices in the hospital campus is monitored;

[0150] and / or,

[0151] The medical device data collection request from the plurality of medical staff terminal devices in the hospital campus is monitored;

[0152] and / or,

[0153] The medical device data collection request from the conference members in the plurality of online conferences in progress in the hospital campus is monitored.

[0154] In one embodiment, the medical device data collection request from the conference members in the plurality of online conferences in progress in the hospital campus is monitored, including:

[0155] Obtaining the conference speeches of the conference members;

[0156] Sorting the conference speeches according to the speaking order to obtain a speech sequence;

[0157] Traversing the conference speeches in sequence from the sequence starting point of the speech sequence, and each time the conference speech is traversed, keyword extraction is performed on the conference speech to obtain a first keyword set, and the first keyword set is matched with a preset trigger keyword set, if the matching is consistent, the traversal of the conference speeches is stopped, and a preset associated keyword set corresponding to the matching consistent trigger keyword set is obtained;

[0158] Keyword extraction is performed on the preset number of conference speeches after the conference speeches traversed in the speech sequence to obtain a second keyword set;

[0159] Matching the second keyword set with the associated keyword set, if the matching is consistent, a preset speech type corresponding to the matching consistent associated keyword set is obtained;

[0160] When the speech type is divergence, the conference speech corresponding to the matching consistent second keyword set is taken as a divergence speech;

[0161] When the speech type is supplement, the conference speech corresponding to the matching consistent second keyword set is taken as a supplement speech;

[0162] respectively, to obtain a plurality of speech semantics;

[0163] determine the medical equipment data acquisition request based on the speech semantics;

[0164] remove all conference speeches before the latter of the last divergent speech and the last supplementary speech in the speech sequence, and continue to traverse the remaining conference speeches after the removal.

[0165] In one embodiment, determining the medical equipment data acquisition request based on the speech semantics comprises:

[0166] determine a first medical equipment data requirement based on the speech semantics of the traversed conference speeches;

[0167] perform requirement correction on the first medical equipment data requirement based on the speech semantics of the last divergent speech in the speech sequence to obtain a medical equipment data corrected requirement;

[0168] determine a second medical equipment data requirement based on the speech semantics of each supplementary speech;

[0169] generate the medical equipment data acquisition request based on the medical equipment data corrected requirement and the second medical equipment data requirement.

[0170] Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the spirit and scope of the present application. Thus, it is intended that the present application cover the modifications and changes as long as they come within the scope of the claims of the present application and their equivalents.

Claims

1. An Internet of Things based medical device data acquisition apparatus, characterized by, The method comprises the steps of: monitoring a medical device data collection request in a hospital campus; analyzing the request party, the medical device to be collected, and the request data type in the monitored medical device data collection request; collecting the medical device data of the request data type through the preset Internet of Things node corresponding to the medical device to be collected; returning the medical device data to the request party; monitoring a medical device data collection request in a hospital campus, comprising: monitoring a medical device data collection request issued by a conference member in a plurality of ongoing online conferences in a hospital campus; monitoring a medical device data collection request issued by a conference member in a plurality of ongoing online conferences in a hospital campus, comprising: obtaining conference speeches of the conference member; sorting the conference speeches according to the speaking order to obtain a speaking sequence; traversing the conference speeches from the beginning of the speaking sequence, and extracting keywords from the conference speeches in each traversal to obtain a first keyword set, and matching the first keyword set with a preset trigger keyword set, if the matching is consistent, stopping traversing the conference speeches, and obtaining a preset associated keyword set corresponding to the matching consistent trigger keyword set; extracting keywords from a preset number of conference speeches after the conference speeches in the speaking sequence to obtain a second keyword set; matching the second keyword set with the associated keyword set, if the matching is consistent, obtaining a preset speaking type corresponding to the matching consistent associated keyword set; when the speaking type is divergence, taking the conference speech corresponding to the matching consistent second keyword set as a divergence speech; when the speaking type is supplement, taking the conference speech corresponding to the matching consistent second keyword set as a supplementary speech; respectively extracting semantics from the conference speeches, the last divergence speech in the speaking sequence, and each supplementary speech to obtain a plurality of speech semantics; determining a medical device data collection request based on the speech semantics; excluding all conference speeches before the latter of the last divergence speech and the last supplementary speech in the speaking sequence, and continuing to traverse the remaining conference speeches after the exclusion; determining a medical device data collection request based on the speech semantics, comprising: determining a first medical device data requirement based on the speech semantics of the conference speeches; correcting the first medical device data requirement based on the speech semantics of the last divergence speech in the speaking sequence to obtain a medical device data correction requirement; determining a second medical device data requirement based on the speech semantics of each supplementary speech; generating a medical device data collection request based on the medical device data correction requirement and the second medical device data requirement.

2. The medical device data collection apparatus based on the Internet of Things of claim 1, wherein, collecting the medical device data of the request data type through the preset Internet of Things node corresponding to the medical device to be collected, comprising: inquiring the node condition of the Internet of Things node based on the preset node condition inquiry template to obtain the node condition returned by the Internet of Things node; extracting features from the node condition to obtain a condition feature set; obtaining a preset index condition feature set corresponding to the Internet of Things node; matching the condition feature set with the index condition feature set to obtain a matching degree; If the matching degree is greater than or equal to the preset matching degree threshold, collecting, by the Internet of Things node, medical equipment data of the request data type.

3. The medical device data collection apparatus based on the Internet of Things of claim 1, wherein, Returning the medical equipment data to the requester, including: Obtaining a preset data preference of the requester corresponding to the request data type; Based on the data preference, pre-processing the medical equipment data to obtain a pre-processing result; Packing the pre-processing result into a data packet to obtain a data packet; Returning the data packet to the requester.

4. An Internet of Things-based medical device data acquisition method, characterized by, Including: Step S1: Listening to medical equipment data collection requests in the hospital campus; Step S2: Parsing the requester, the medical equipment to be collected, and the request data type in the medical equipment data collection request listened to; Step S3: Collecting, by the preset Internet of Things node corresponding to the medical equipment to be collected, medical equipment data of the request data type; Step S4: Returning the medical equipment data to the requester; Listening to medical equipment data collection requests in the hospital campus, including: Listening to medical equipment data collection requests issued by conference members in multiple online conferences being held in the hospital campus; Listening to medical equipment data collection requests issued by conference members in multiple online conferences being held in the hospital campus, including: Obtaining conference speeches of the conference members; Sorting the conference speeches according to the speaking order to obtain a speaking sequence; Starting from the sequence starting point of the speaking sequence, traversing the conference speeches one by one, and each time traversing the conference speeches, extracting keywords from the conference speeches to obtain a first keyword set, and matching the first keyword set with a preset trigger keyword set, if the matching is consistent, stopping traversing the conference speeches, and obtaining a preset associated keyword set corresponding to the matching consistent trigger keyword set; Extracting keywords from the preset number of conference speeches after the conference speeches traversed in the speaking sequence to obtain a second keyword set; Matching the second keyword set with the associated keyword set, if the matching is consistent, obtaining a preset speech type corresponding to the matching consistent associated keyword set; When the speech type is divergence, the conference speech corresponding to the matching consistent second keyword set is taken as a divergence speech; When the speech type is supplement, the conference speech corresponding to the matching consistent second keyword set is taken as a supplementary speech; Respectively extracting semantics from the conference speeches traversed, the last divergence speech in the speaking sequence, and each supplementary speech to obtain multiple speech semantics; Based on the speech semantics, determining the medical equipment data collection request; Eliminating all conference speeches before the latter of the last divergence speech and the last supplementary speech in the speaking sequence, and after the elimination, continuing to traverse the remaining conference speeches; Based on the speech semantics, determining the medical equipment data collection request, including: Based on the speech semantics of the conference speeches traversed, determining a first medical equipment data requirement; Based on the speech semantics of the last divergence speech in the speaking sequence, correcting the first medical equipment data requirement to obtain a medical equipment data correction requirement; Based on the speech semantics of each supplementary speech, determining a second medical equipment data requirement; Based on the medical equipment data correction requirement and the second medical equipment data requirement, generating the medical equipment data collection request.

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