Oximeter collected data processing method and system

Abstract

The invention provides an oximeter collected data processing method and system.The method comprises the steps that when it is detected that an oximeter completes user detection in real time, real-time detection data uploaded by the oximeter are received in real time, and the real-time detection data comprise specific numerical values; according to a first preset rule, a corresponding first label is added to the real-time detection data, full scanning is carried out on the real-time detection data, a plurality of data subsets contained in the real-time detection data are detected in real time, and each data subset corresponds to one detection parameter; adding a corresponding second label to each data subset according to a second preset rule, and performing fusion processing on the first label and the second label to generate a corresponding fusion label in real time; and generating an encryption key matched with the real-time detection data in real time according to the fusion label, and encrypting the real-time detection data through the encryption key. According to the invention, encryption processing can be rapidly and effectively completed, and the user experience is correspondingly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for processing data collected by a blood oximeter. Background Art

[0002] With the advancement of science and technology and the rapid development of productivity, in order to be able to diagnose patients' diseases in a timely and effective manner, people have developed various types of medical equipment, and can collect pathological data corresponding to the patients in real time through medical equipment to complete subsequent diagnosis.

[0003] Among them, the oximeter is an instrument used to collect the patient's blood oxygen concentration. Specifically, in actual use, the oximeter will analyze the patient's blood oxygen concentration in real time by detecting parameters such as the patient's blood flow rate and pulse rate, so as to facilitate subsequent diagnosis.

[0004] Furthermore, after collecting and analyzing the patient's physical data, most of the existing blood oximeters directly store the physical data in a pre-set folder. However, during the storage process, since no corresponding confidentiality measures are set, the user's physical data is easily leaked, which correspondingly reduces the user's experience. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a method and system for processing data collected by a blood oximeter, so as to solve the problem that in the process of storing patient body data in the prior art, most of the data are directly stored in a pre-set folder without setting corresponding confidentiality measures, which makes the user's body data easy to leak.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A method for processing data collected by a blood oximeter, wherein the method comprises:

[0008] When it is detected in real time that the oximeter has completed the detection of the user, real-time detection data uploaded by the oximeter is received in real time, wherein the real-time detection data contains specific values;

[0009] According to a first preset rule, a corresponding first tag is added to the real-time detection data, and the real-time detection data is fully scanned to detect in real time a plurality of data subsets contained in the real-time detection data, each of the data subsets corresponding to a detection parameter;

[0010] According to a second preset rule, a corresponding second label is added to each of the data subsets, and the first label and the second label are fused to generate a corresponding fused label in real time;

[0011] An encryption key adapted to the real-time detection data is generated in real time according to the fusion tag, and the real-time detection data is encrypted by using the encryption key.

[0012] The beneficial effect of the present invention is that by receiving the real-time detection data uploaded by the oximeter in real time, the specific working content of the oximeter can be obtained accordingly. Based on this, in order to facilitate the subsequent encryption processing, the required key information can be further obtained. Based on this, the corresponding first label will be further generated according to the current real-time detection data. At the same time, the required second label can be further generated in real time according to the acquired data subset. On this basis, it is only necessary to fuse the current first label and the second label to further generate a fusion label for subsequent encryption and complete the subsequent encryption processing, so that the encryption and storage of the detection data can be completed quickly and effectively, data leakage can be avoided, and the user experience is correspondingly improved.

[0013] Furthermore, the step of adding a corresponding first label to the real-time detection data according to the first preset rule includes:

[0014] When the real-time detection data is acquired in real time, user information corresponding to the user is extracted in real time from a preset database;

[0015] Detecting in real time the data collection time and the data collection location corresponding to the real-time detection data, and extracting in real time the user name corresponding to the user from the user information;

[0016] The data collection time, the data collection location and the user name are fused to generate the first label accordingly.

[0017] Furthermore, the step of fusing the data collection time, the data collection location and the user name to generate the first label accordingly includes:

[0018] Detecting in real time a number of first letters corresponding to the user name, a number of second letters corresponding to the data collection location, and detecting in real time a number of first numbers corresponding to the data collection time;

[0019] Integrate and process a plurality of the first letters, a plurality of the second letters, and a plurality of the first numbers according to a preset arrangement rule to generate a corresponding initial acquisition data chain in real time;

[0020] The initial acquisition data chain is simplified in real time to generate a corresponding target acquisition data chain, and the target acquisition data chain is correspondingly set as the first label.

[0021] Furthermore, the step of adding a corresponding second label to each of the data subsets according to the second preset rule includes:

[0022] When the data subset is acquired in real time, the data subset is fully scanned to detect the target parameters contained in the data subset;

[0023] Performing real-time analysis on the target parameter to detect the parameter type corresponding to the target parameter in real time, and matching the target attribute value corresponding to the target parameter in a preset parameter database in real time according to the parameter type;

[0024] The second label is generated in real time according to the parameter type and the target attribute value.

[0025] Furthermore, the step of generating the second label in real time according to the parameter type and the target attribute value includes:

[0026] When the parameter type is acquired in real time, a target parameter format corresponding to the data subset is matched in real time according to the parameter type;

[0027] Extracting in real time a number of third letters contained in the target parameter format, and extracting in real time a number of second numbers contained in the target attribute value;

[0028] The third letters and the second numbers are integrated to generate corresponding target parameter data links in real time, and the target parameter data links are set as the second labels.

[0029] Furthermore, the step of fusing the first label and the second label to generate a corresponding fused label in real time includes:

[0030] When the first tag is acquired in real time, a first tag sequence corresponding to the first tag is detected in real time;

[0031] When the second tag is acquired in real time, a second tag sequence corresponding to the second tag is detected in real time;

[0032] The first tag sequence and the second tag sequence are fused to generate the fusion tag in real time.

[0033] Furthermore, the step of fusing the first tag sequence and the second tag sequence to generate the fusion tag in real time includes:

[0034] Performing forward maximum step word segmentation processing on the first tag sequence to split into a plurality of first sequence values, and adding a corresponding first identifier to each of the first sequence values;

[0035] Performing forward maximum step word segmentation processing on the second tag sequence to split into a number of second sequence values, and adding a corresponding second identifier to each of the second sequence values;

[0036] The first sequence values ​​and the second sequence values ​​are interspersed and fused according to the first identifier and the second identifier to generate a corresponding fusion sequence in real time, and the fusion tag is correspondingly generated according to the fusion sequence in real time.

[0037] The second aspect of the embodiment of the present invention proposes:

[0038] A blood oximeter data collection and processing system, wherein the system comprises:

[0039] A transmission module, for receiving real-time detection data uploaded by the oximeter when it is detected in real time that the oximeter has completed the detection of the user, wherein the real-time detection data contains specific values;

[0040] A scanning module, used for adding a corresponding first tag to the real-time detection data according to a first preset rule, and performing a full scan on the real-time detection data to detect in real time a plurality of data subsets contained in the real-time detection data, each of the data subsets corresponding to a detection parameter;

[0041] A fusion module, used for adding a corresponding second label to each of the data subsets according to a second preset rule, and fusing the first label and the second label to generate a corresponding fused label in real time;

[0042] The encryption module is used to generate an encryption key adapted to the real-time detection data in real time according to the fusion tag, and encrypt the real-time detection data by using the encryption key.

[0043] Furthermore, the scanning module is specifically used for:

[0044] When the real-time detection data is acquired in real time, user information corresponding to the user is extracted in real time from a preset database;

[0045] Detecting in real time the data collection time and the data collection location corresponding to the real-time detection data, and extracting in real time the user name corresponding to the user from the user information;

[0046] The data collection time, the data collection location and the user name are fused to generate the first label accordingly.

[0047] Furthermore, the scanning module is specifically used for:

[0048] Detecting in real time a number of first letters corresponding to the user name, a number of second letters corresponding to the data collection location, and detecting in real time a number of first numbers corresponding to the data collection time;

[0049] Integrate and process a plurality of the first letters, a plurality of the second letters, and a plurality of the first numbers according to a preset arrangement rule to generate a corresponding initial acquisition data chain in real time;

[0050] The initial acquisition data chain is simplified in real time to generate a corresponding target acquisition data chain, and the target acquisition data chain is correspondingly set as the first label.

[0051] Furthermore, the fusion module is specifically used for:

[0052] When the data subset is acquired in real time, the data subset is fully scanned to detect the target parameters contained in the data subset;

[0053] Performing real-time analysis on the target parameter to detect the parameter type corresponding to the target parameter in real time, and matching the target attribute value corresponding to the target parameter in a preset parameter database in real time according to the parameter type;

[0054] The second label is generated in real time according to the parameter type and the target attribute value.

[0055] Furthermore, the fusion module is specifically used for:

[0056] When the parameter type is acquired in real time, a target parameter format corresponding to the data subset is matched in real time according to the parameter type;

[0057] Extracting in real time a number of third letters contained in the target parameter format, and extracting in real time a number of second numbers contained in the target attribute value;

[0058] The third letters and the second numbers are integrated to generate corresponding target parameter data links in real time, and the target parameter data links are set as the second labels.

[0059] Furthermore, the fusion module is specifically used for:

[0060] When the first tag is acquired in real time, a first tag sequence corresponding to the first tag is detected in real time;

[0061] When the second tag is acquired in real time, a second tag sequence corresponding to the second tag is detected in real time;

[0062] The first tag sequence and the second tag sequence are fused to generate the fusion tag in real time.

[0063] Furthermore, the fusion module is specifically used for:

[0064] Performing forward maximum step word segmentation processing on the first tag sequence to split into a plurality of first sequence values, and adding a corresponding first identifier to each of the first sequence values;

[0065] Performing forward maximum step word segmentation processing on the second tag sequence to split into a number of second sequence values, and adding a corresponding second identifier to each of the second sequence values;

[0066] The first sequence values ​​and the second sequence values ​​are interspersed and fused according to the first identifier and the second identifier to generate a corresponding fusion sequence in real time, and the fusion tag is correspondingly generated according to the fusion sequence in real time.

[0067] The third aspect of the embodiment of the present invention proposes:

[0068] A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for processing blood oximeter collected data when executing the computer program.

[0069] The fourth aspect of the embodiments of the present invention proposes:

[0070] A readable storage medium stores a computer program, wherein when the program is executed by a processor, the method for processing the data collected by the oximeter as described above is implemented.

[0071] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A flow chart of a method for processing blood oximeter data collected in accordance with a first embodiment of the present invention;

[0073] Figure 2 This is a structural block diagram of a blood oximeter data collection and processing system provided in the third embodiment of the present invention.

[0074] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0075] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0076] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0077] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0078] See also Figure 1 , which shows the blood oximeter data collection processing method provided by the first embodiment of the present invention. The blood oximeter data collection processing method provided by this embodiment can quickly and effectively complete the encryption and storage of the collected data, which correspondingly improves the user experience.

[0079] Specifically, this embodiment provides:

[0080] A method for processing blood oximeter collected data, specifically comprising the following steps:

[0081] Step S10, when it is detected in real time that the oximeter has completed the detection of the user, real-time detection data uploaded by the oximeter is received in real time, wherein the real-time detection data contains specific values;

[0082] Step S20, adding a corresponding first tag to the real-time detection data according to a first preset rule, and performing a full scan on the real-time detection data to detect in real time a plurality of data subsets contained in the real-time detection data, each of the data subsets corresponding to a detection parameter;

[0083] Step S30, adding a corresponding second label to each of the data subsets according to a second preset rule, and fusing the first label and the second label to generate a corresponding fused label in real time;

[0084] Step S40: generating an encryption key adapted to the real-time detection data in real time according to the fusion tag, and encrypting the real-time detection data using the encryption key.

[0085] Specifically, in this embodiment, it should be noted that in order to quickly and effectively complete the encryption processing of the collected data, it is necessary to obtain the working status of the oximeter and the data collected by the oximeter in real time in real time. It should be pointed out that in the actual use of the oximeter, the objects collected by the oximeter are different, and the corresponding collected data will not be the same. Based on this, in order to be able to specifically complete the encryption processing of the detection data corresponding to each collection, it is necessary to further obtain the corresponding information contained in the collected real-time detection data, so that the corresponding encryption processing can be completed in real time in combination with the characteristics of the collected data, so as to facilitate subsequent processing.

[0086] Further, after obtaining the required real-time detection data in real time through the above steps, the present invention will immediately add a corresponding first label to the current real-time detection data according to the pre-set first preset rule, that is, mark the corresponding characteristics. Further, since the current real-time detection data will contain a variety of different data at the same time, a number of data subsets will be generated accordingly, so that each data subset will only correspond to one parameter. Based on this, the present invention will further add a corresponding second label to each current data subset according to the pre-set second preset rule immediately, that is, mark the characteristics of each data subset. On this basis, in order to be able to complete the encryption processing of the current real-time detection data in a targeted manner, the present invention will further fuse the current first label and the second label to further generate the required fusion label, that is, to determine all the characteristics of the current real-time detection data, and can further generate an encryption key adapted to the current real-time detection data in real time according to the current fusion label. Preferably, the present invention will extract a number of numbers and letters from the current fusion label, and perform corresponding permutation and combination processing to generate a number of serial numbers, and randomly select a serial number to be used as the encryption key of the current real-time detection data. The above method can quickly and effectively complete the encryption and storage processing of the detection data, thereby avoiding data leakage and correspondingly improving the user experience.

[0087] Second embodiment

[0088] Furthermore, the step of adding a corresponding first label to the real-time detection data according to the first preset rule includes:

[0089] When the real-time detection data is acquired in real time, user information corresponding to the user is extracted in real time from a preset database;

[0090] Detecting in real time the data collection time and the data collection location corresponding to the real-time detection data, and extracting in real time the user name corresponding to the user from the user information;

[0091] The data collection time, the data collection location and the user name are fused to generate the first label accordingly.

[0092] Furthermore, the step of fusing the data collection time, the data collection location and the user name to generate the first label accordingly includes:

[0093] Detecting in real time a number of first letters corresponding to the user name, a number of second letters corresponding to the data collection location, and detecting in real time a number of first numbers corresponding to the data collection time;

[0094] Integrate and process a plurality of the first letters, a plurality of the second letters, and a plurality of the first numbers according to a preset arrangement rule to generate a corresponding initial acquisition data chain in real time;

[0095] The initial acquisition data chain is simplified in real time to generate a corresponding target acquisition data chain, and the target acquisition data chain is correspondingly set as the first label.

[0096] Furthermore, the step of adding a corresponding second label to each of the data subsets according to the second preset rule includes:

[0097] When the data subset is acquired in real time, the data subset is fully scanned to detect the target parameters contained in the data subset;

[0098] Performing real-time analysis on the target parameter to detect the parameter type corresponding to the target parameter in real time, and matching the target attribute value corresponding to the target parameter in a preset parameter database in real time according to the parameter type;

[0099] The second label is generated in real time according to the parameter type and the target attribute value.

[0100] Furthermore, the step of generating the second label in real time according to the parameter type and the target attribute value includes:

[0101] When the parameter type is acquired in real time, a target parameter format corresponding to the data subset is matched in real time according to the parameter type;

[0102] Extracting in real time a number of third letters contained in the target parameter format, and extracting in real time a number of second numbers contained in the target attribute value;

[0103] The third letters and the second numbers are integrated to generate corresponding target parameter data links in real time, and the target parameter data links are set as the second labels.

[0104] Furthermore, the step of fusing the first label and the second label to generate a corresponding fused label in real time includes:

[0105] When the first tag is acquired in real time, a first tag sequence corresponding to the first tag is detected in real time;

[0106] When the second tag is acquired in real time, a second tag sequence corresponding to the second tag is detected in real time;

[0107] The first tag sequence and the second tag sequence are fused to generate the fusion tag in real time.

[0108] Furthermore, the step of fusing the first tag sequence and the second tag sequence to generate the fusion tag in real time includes:

[0109] Performing forward maximum step word segmentation processing on the first tag sequence to split into a plurality of first sequence values, and adding a corresponding first identifier to each of the first sequence values;

[0110] Performing forward maximum step word segmentation processing on the second tag sequence to split into a number of second sequence values, and adding a corresponding second identifier to each of the second sequence values;

[0111] The first sequence values ​​and the second sequence values ​​are interspersed and fused according to the first identifier and the second identifier to generate a corresponding fusion sequence in real time, and the fusion tag is correspondingly generated according to the fusion sequence in real time.

[0112] In addition, in this embodiment, it is also necessary to explain that after the required real-time detection data is obtained in real time through the above steps, in order to objectively and effectively generate the first label adapted to the current real-time detection data, preferably, the present invention will bind the current real-time detection data to the current user. Specifically, the present invention will further detect the user information corresponding to the current user in the existing database in real time. Based on this, the user name corresponding to the current user can be further extracted from the current user information in real time. At the same time, the present invention will also synchronously extract the corresponding data collection time and data collection location in real time from the above real-time detection data. It should be pointed out that since the above three parameters are unique, they can objectively reflect the characteristics of the current real-time detection data. Based on this, the present invention will further extract several first letters contained in the current user name, several second letters contained in the current data collection location, and similarly, several first numbers contained in the current data collection time. Based on this, the present invention will further integrate the current several first letters, several second letters and several first numbers according to the arrangement rule of "first letter-first number-second letter", and can generate the required initial collection data chain accordingly. Similarly, the initial collection data chain is also unique. Specifically, for ease of understanding, for example, the initial acquisition data link can be "zhangsan-2024.10.10-jiangxi", wherein, in order to further reduce the subsequent data processing amount, the present invention will further perform real-time simplification processing on the current initial acquisition data link. Specifically, for ease of understanding, for example, the corresponding target acquisition data link generated after simplified processing can be "zs-24.10.10-jx". Based on this, the current real-time generated target acquisition data link can be directly set as the first label of the current real-time detection data for subsequent processing.

[0113] Furthermore, after the first label is obtained in real time through the above steps, several data subsets corresponding to the current real-time detection data will be further detected. Similarly, the present invention will further parse and process each current data subset. Preferably, the present invention will first detect the target parameter corresponding to the current data subset. At the same time, the parameter type corresponding to the current target parameter can be synchronously detected. Specifically, the parameter types disclosed in the present invention include blood pressure, blood flow velocity, pulse beats and other types. It should be pointed out that since each parameter contains a corresponding characteristic, that is, contains a corresponding attribute, based on this, the present invention will further detect the target attribute value corresponding to the current target parameter. At the same time, in order to facilitate subsequent processing, the present invention will further detect the target parameter format corresponding to the current target parameter in real time according to the current parameter type. Based on this, the present invention will further detect several third letters corresponding to the current target parameter format and several second digits corresponding to the current target attribute value. Based on this, the current third letters and the current second digits are also integrated to further generate the required target parameter data chain, and the current target parameter data chain can be directly set to the required second label. Based on this, in order to fully complete the subsequent encryption processing, the present invention will further fuse the current first label and the second label. Preferably, in the actual fusion process, the first label sequence contained in the current first label will be detected accordingly. Similarly, the second label sequence contained in the current second label will be detected accordingly. Based on this, corresponding forward compensation maximum word segmentation processing is performed respectively to split them into several first sequence values ​​and several second sequence values. On this basis, the corresponding first identifier and second identifier are added respectively, and further according to the correspondence between the current first identifier and the second identifier, the current several first sequence values ​​and several second sequence values ​​are interspersed and fused, so as to finally obtain the required fusion sequence, and the above-mentioned fusion label can be further generated according to the fusion sequence to facilitate subsequent processing.

[0114] See also Figure 2 , the third embodiment of the present invention provides:

[0115] A blood oximeter data collection and processing system, wherein the system comprises:

[0116] A transmission module, for receiving real-time detection data uploaded by the oximeter when it is detected in real time that the oximeter has completed the detection of the user, wherein the real-time detection data contains specific values;

[0117] A scanning module, used for adding a corresponding first tag to the real-time detection data according to a first preset rule, and performing a full scan on the real-time detection data to detect in real time a plurality of data subsets contained in the real-time detection data, each of the data subsets corresponding to a detection parameter;

[0118] A fusion module, used for adding a corresponding second label to each of the data subsets according to a second preset rule, and fusing the first label and the second label to generate a corresponding fused label in real time;

[0119] The encryption module is used to generate an encryption key adapted to the real-time detection data in real time according to the fusion tag, and encrypt the real-time detection data by using the encryption key.

[0120] Furthermore, the scanning module is specifically used for:

[0121] When the real-time detection data is acquired in real time, user information corresponding to the user is extracted in real time from a preset database;

[0122] Detecting in real time the data collection time and the data collection location corresponding to the real-time detection data, and extracting in real time the user name corresponding to the user from the user information;

[0123] The data collection time, the data collection location and the user name are fused to generate the first label accordingly.

[0124] Furthermore, the scanning module is specifically used for:

[0125] Detecting in real time a number of first letters corresponding to the user name, a number of second letters corresponding to the data collection location, and detecting in real time a number of first numbers corresponding to the data collection time;

[0126] Integrate and process a plurality of the first letters, a plurality of the second letters, and a plurality of the first numbers according to a preset arrangement rule to generate a corresponding initial acquisition data chain in real time;

[0127] The initial acquisition data chain is simplified in real time to generate a corresponding target acquisition data chain, and the target acquisition data chain is correspondingly set as the first label.

[0128] Furthermore, the fusion module is specifically used for:

[0129] When the data subset is acquired in real time, the data subset is fully scanned to detect the target parameters contained in the data subset;

[0130] Performing real-time analysis on the target parameter to detect the parameter type corresponding to the target parameter in real time, and matching the target attribute value corresponding to the target parameter in a preset parameter database in real time according to the parameter type;

[0131] The second label is generated in real time according to the parameter type and the target attribute value.

[0132] Furthermore, the fusion module is specifically used for:

[0133] When the parameter type is acquired in real time, a target parameter format corresponding to the data subset is matched in real time according to the parameter type;

[0134] Extracting in real time a number of third letters contained in the target parameter format, and extracting in real time a number of second numbers contained in the target attribute value;

[0135] The third letters and the second numbers are integrated to generate corresponding target parameter data links in real time, and the target parameter data links are set as the second labels.

[0136] Furthermore, the fusion module is specifically used for:

[0137] When the first tag is acquired in real time, a first tag sequence corresponding to the first tag is detected in real time;

[0138] When the second tag is acquired in real time, a second tag sequence corresponding to the second tag is detected in real time;

[0139] The first tag sequence and the second tag sequence are fused to generate the fusion tag in real time.

[0140] Furthermore, the fusion module is specifically used for:

[0141] Performing forward maximum step word segmentation processing on the first tag sequence to split into a plurality of first sequence values, and adding a corresponding first identifier to each of the first sequence values;

[0142] Performing forward maximum step word segmentation processing on the second tag sequence to split into a number of second sequence values, and adding a corresponding second identifier to each of the second sequence values;

[0143] The first sequence values ​​and the second sequence values ​​are interspersed and fused according to the first identifier and the second identifier to generate a corresponding fusion sequence in real time, and the fusion tag is correspondingly generated according to the fusion sequence in real time.

[0144] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-described method for processing blood oximeter collected data when executing the computer program.

[0145] A fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for processing the data collected by the oximeter as described above is implemented.

[0146] In summary, the oximeter data collection processing method and system provided in the above embodiments of the present invention can quickly and effectively complete the encryption and storage of collected data, thereby correspondingly improving the user experience.

[0147] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0149] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0150] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0151] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0152] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for processing blood oximeter data collection, characterized in that: The method comprises: When it is detected in real time that the oximeter has completed the detection of the user, real-time detection data uploaded by the oximeter is received in real time, wherein the real-time detection data contains specific values; According to a first preset rule, a corresponding first tag is added to the real-time detection data, and the real-time detection data is fully scanned to detect in real time a plurality of data subsets contained in the real-time detection data, each of the data subsets corresponding to a detection parameter; According to a second preset rule, a corresponding second label is added to each of the data subsets, and the first label and the second label are fused to generate a corresponding fused label in real time; An encryption key adapted to the real-time detection data is generated in real time according to the fusion tag, and the real-time detection data is encrypted by using the encryption key.

2. The method for processing blood oximeter data collection according to claim 1, characterized in that: The step of adding a corresponding first label to the real-time detection data according to a first preset rule comprises: When the real-time detection data is acquired in real time, user information corresponding to the user is extracted in real time from a preset database; Detecting in real time the data collection time and the data collection location corresponding to the real-time detection data, and extracting in real time the user name corresponding to the user from the user information; The data collection time, the data collection location and the user name are fused to generate the first label accordingly.

3. The method for processing blood oximeter data collection according to claim 2, characterized in that: The step of fusing the data collection time, the data collection location, and the user name to generate the first label accordingly includes: Detecting in real time a number of first letters corresponding to the user name, a number of second letters corresponding to the data collection location, and detecting in real time a number of first numbers corresponding to the data collection time; Integrate and process a plurality of the first letters, a plurality of the second letters, and a plurality of the first numbers according to a preset arrangement rule to generate a corresponding initial acquisition data chain in real time; The initial acquisition data chain is simplified in real time to generate a corresponding target acquisition data chain, and the target acquisition data chain is correspondingly set as the first label.

4. The method for processing blood oximeter data collection according to claim 3, characterized in that: The step of adding a corresponding second label to each of the data subsets according to the second preset rule comprises: When the data subset is acquired in real time, the data subset is fully scanned to detect the target parameters contained in the data subset; Performing real-time analysis on the target parameter to detect the parameter type corresponding to the target parameter in real time, and matching the target attribute value corresponding to the target parameter in a preset parameter database in real time according to the parameter type; The second label is generated in real time according to the parameter type and the target attribute value.

5. The method for processing blood oximeter data collection according to claim 4, characterized in that: The step of generating the second label in real time according to the parameter type and the target attribute value includes: When the parameter type is acquired in real time, a target parameter format corresponding to the data subset is matched in real time according to the parameter type; Extracting in real time a number of third letters contained in the target parameter format, and extracting in real time a number of second numbers contained in the target attribute value; The third letters and the second numbers are integrated to generate corresponding target parameter data links in real time, and the target parameter data links are set as the second labels.

6. The method for processing blood oximeter data collection according to claim 5, characterized in that: The step of fusing the first label and the second label to generate a corresponding fused label in real time includes: When the first tag is acquired in real time, a first tag sequence corresponding to the first tag is detected in real time; When the second tag is acquired in real time, a second tag sequence corresponding to the second tag is detected in real time; The first tag sequence and the second tag sequence are fused to generate the fusion tag in real time.

7. The method for processing blood oximeter data collection according to claim 6, characterized in that: The step of fusing the first tag sequence and the second tag sequence to generate the fusion tag in real time includes: Performing forward maximum step word segmentation processing on the first tag sequence to split into a plurality of first sequence values, and adding a corresponding first identifier to each of the first sequence values; Performing forward maximum step word segmentation processing on the second tag sequence to split into a number of second sequence values, and adding a corresponding second identifier to each of the second sequence values; The first sequence values ​​and the second sequence values ​​are interspersed and fused according to the first identifier and the second identifier to generate a corresponding fusion sequence in real time, and the fusion tag is correspondingly generated according to the fusion sequence in real time.

8. A blood oximeter data collection and processing system, characterized in that: The system comprises: A transmission module, for receiving real-time detection data uploaded by the oximeter when it is detected in real time that the oximeter has completed the detection of the user, wherein the real-time detection data contains specific values; A scanning module, used for adding a corresponding first tag to the real-time detection data according to a first preset rule, and performing a full scan on the real-time detection data to detect in real time a plurality of data subsets contained in the real-time detection data, each of the data subsets corresponding to a detection parameter; A fusion module, used for adding a corresponding second label to each of the data subsets according to a second preset rule, and fusing the first label and the second label to generate a corresponding fused label in real time; The encryption module is used to generate an encryption key adapted to the real-time detection data in real time according to the fusion tag, and encrypt the real-time detection data by using the encryption key.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for processing blood oximeter collected data as described in any one of claims 1 to 7 is implemented.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for processing blood oximeter collected data as claimed in any one of claims 1 to 7 is implemented.

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