CN211243385U - AI blood glucose meter - Google Patents
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- CN211243385U CN211243385U CN201921895355.6U CN201921895355U CN211243385U CN 211243385 U CN211243385 U CN 211243385U CN 201921895355 U CN201921895355 U CN 201921895355U CN 211243385 U CN211243385 U CN 211243385U
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Abstract
The utility model discloses an AI blood glucose meter, include: the detection module can be used for detecting and uploading blood sugar information of a user; the AI processing module sends out a corresponding processing signal according to the disease condition grade; the data interaction module is connected with the AI processing module and can receive the processing signals, and the data interaction module can send corresponding inquiry information to the user according to the corresponding processing signals and feed back corresponding data according to the reply of the user; the time detection module can detect the interaction time of the user and the data interaction module and sends a signal that the user stops interacting after the preset time that the user stops interacting with the data interaction module; and the emergency communication module is connected with the AI processing module and the data interaction module and identifies information of the AI processing module and the data interaction module, and can send emergency communication information to a third party according to a signal sent by the time detection module when the user stops interacting.
Description
Technical Field
The utility model belongs to the technical field of medical instrument, concretely relates to AI blood glucose meter.
Background
With the improvement of living conditions, the more and more the urban population suffers from the three highs, the more and more the disease becomes a chronic disease seriously harming human health. People usually go to a hospital to see a doctor when feeling untimely and can directly transmit the information of the disease to a doctor when seeing the doctor. In daily life, patients usually cannot transmit disease information without going to a hospital for a doctor, and a plurality of channels for knowing the disease information in real time are not available.
SUMMERY OF THE UTILITY MODEL
In view of this, the utility model provides an AI blood glucose meter can make the user in time know the information of falling ill to can also assist the user to contact the third party under emergency.
In order to solve the technical problem, the utility model provides an AI blood glucose meter, include: the detection module can be used for detecting and uploading blood sugar information of a user; the AI processing module can receive the blood sugar information and compare the blood sugar information with a preset value to judge the disease condition grade of the user, and the AI processing module sends out a corresponding processing signal according to the disease condition grade; the data interaction module is connected with the AI processing module and can receive the processing signal, and the data interaction module can send corresponding inquiry information to a user according to the corresponding processing signal and feed back corresponding data according to the reply of the user; the time detection module can detect the interaction time of the user and the data interaction module and sends a signal that the user stops interacting after the preset time that the user stops interacting with the data interaction module; and the emergency communication module is connected with the AI processing module and the data interaction module and identifies information of the AI processing module and the data interaction module, and can send emergency communication information to a third party according to a signal sent by the time detection module when the user stops interacting.
According to the utility model discloses AI blood glucose meter detects and uploads user's information through detection module, combine AI processing module and data interaction module, realize that the user is interactive with the intelligence of AI blood glucose meter, make the patient better know the information of falling ill of self, can carry out measures such as corresponding prevention, diagnosis, treatment according to the corresponding information of falling ill, and under the more serious condition of patient's testing result, AI blood glucose meter can also assist user or independently contact the third party according to the condition that corresponds, reduce the possibility that dangerous appears in the patient.
According to the utility model discloses an embodiment, the default is 3.0mmol/L-11.0mmol/L, AI processing module can be according to blood sugar information judges that user's state of an illness grade is ordinary grade or priority, and sends ordinary processing signal when the state of an illness grade is ordinary grade send priority processing signal when the state of an illness grade is the priority.
According to an embodiment of the present invention, the data interaction module is provided with general query information and priority query information, and the data interaction module sends out the general query information when receiving the general processing signal and sends out the priority query information when receiving the priority processing signal.
According to an embodiment of the present invention, the time detection module is connected to the AI processing module and identifies the AI processing module to determine the disease condition level of the user, when the disease condition level is normal, the time detection module sends a first stop signal when the user stops interacting with the data interaction module for a first preset time, and the AI processing module receives the first stop signal and stops working; when the disease condition level is the priority level, the time detection module sends a second stop signal when the user stops interacting with the data interaction module for a second preset time, and the emergency communication module receives the second stop signal and sends emergency communication information.
According to an embodiment of the present invention, the first predetermined time is 15s to 30s, and the second predetermined time is 30s to 60 s.
According to the utility model discloses an embodiment, urgent communication module is 4G communication module or 5G communication module.
According to an embodiment of the present invention, the AI processing module is a processor integrated within the AI glucose meter.
According to the utility model discloses an embodiment, AI processing module is for establishing the APP at the removal end.
According to the utility model discloses an embodiment, AI blood glucose meter still includes: the AI processing module can read the illness state information in the data storage module and compare the illness state information with the information detected by the detection module.
According to the utility model discloses an embodiment, AI blood glucose meter still includes automatic learning module, automatic learning module with the data storage module links to each other, automatic learning module is in the data information that detection module detected does during the data information that does not store in the data storage module, will detection information storage extremely the data storage module.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic structural diagram of an AI blood glucose meter according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of an AI chronic disease management method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Reference numerals:
an AI blood glucose meter 100;
a detection module 10; an AI processing module 20; a data interaction module 30; a time detection module 40; an emergency communication module 50; a data storage module 60; an auto-learning module 70;
an electronic device 300;
a memory 310; an operating system 311; an application 312;
a processor 320; a network interface 330; an input device 340; a hard disk 350; a display device 360.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present invention, and should not be construed as limiting the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", and the like, indicate the orientation or positional relationship indicated based on the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore, should not be construed as limiting the present invention. Furthermore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The AI blood glucose meter 100 according to an embodiment of the present invention will be described first with reference to the drawings.
As shown in fig. 1, an AI blood glucose meter 100 according to an embodiment of the present invention includes: a detection module 10, an AI processing module 20, a data interaction module 30, a time detection module 40, and an emergency communication module 50.
Specifically, the detection module 10 can be used to detect and upload blood glucose information of a user, the AI processing module 20 can receive the blood glucose information and compare the blood glucose information with a preset value to determine an illness state level of the user, the AI processing module 20 sends a corresponding processing signal according to the illness state level, the data interaction module 30 is connected with the AI processing module 20 and can receive the processing signal, the data interaction module 30 can send corresponding query information to the user according to the corresponding processing signal and feed back corresponding data according to a reply of the user, the time detection module 40 can detect an interaction time of the user with the data interaction module 30 and send a signal that the user stops interacting after a predetermined time when the user stops interacting with the data interaction module 30, the emergency communication module 50 is connected with the AI processing module 20 and the data interaction module 30 and identifies information of the AI processing module 20 and the data interaction module 30, the emergency communication module 50 can send emergency communication information to a third party according to the signal of stopping the interaction of the user sent by the time detection module 40.
In other words, according to the utility model discloses AI blood glucose meter 100 mainly comprises detection module 10, AI processing module 20, data interaction module 30, time detection module 40 and emergency communication module 50 a host computer structure, wherein, detection module 10 can be used for carrying out blood glucose test, and upload the testing result to AI processing module 20, AI processing module can carry out the analysis to user's blood glucose testing result, judge whether user's blood glucose is normal, classify the judged result according to the difference of state of an illness grade, and send corresponding processing signal. The data interaction module 30 can send corresponding query information to the user according to different processing signals, and after the user replies, feed back corresponding information according to the reply information of the user, such as pushing corresponding knowledge, suggestions and related articles or links. The time detection module 40 may detect the time when the user interacts with the AI processing module 20, and after the user stops communicating with the AI processing module 20 for a certain time, determine that the user has finished the detection or other emergency situations occur, and then make corresponding feedback. The emergency communication module 50 may send emergency communication information when determining that the user is in an emergency, and contact a preset third party, so as to reduce the occurrence of danger.
From this, according to the utility model discloses AI blood glucose meter detects and uploads user's information through detection module, combine AI processing module and data interaction module, realize that the intelligence of user and AI blood glucose meter is interactive, make the sick information of patient's better understanding self, can carry out measures such as prevention, diagnosis, treatment that correspond according to corresponding sick information, and under the more serious condition of patient's testing result, AI blood glucose meter can also assist user or independently contact the third party according to the condition that corresponds, reduce the dangerous possibility of patient appearance.
According to the utility model discloses an embodiment, the default is 3.0mmol/L-11.0mmol/L, and AI processing module 20 can judge that user's state of an illness grade is ordinary level or priority according to blood sugar information to send ordinary processing signal when the state of an illness grade is ordinary level, send priority processing signal when the state of an illness grade is the priority.
Optionally, the data interaction module 30 is provided with general query information and priority query information, and the data interaction module 30 sends out the general query information when receiving the general processing signal and sends out the priority query information when receiving the priority processing signal.
In some embodiments of the present invention, the time detection module 40 is connected to the AI processing module 20 and identifies the AI processing module 20 to determine the disease condition level of the user, when the disease condition level is a normal level, the time detection module 40 sends a first stop signal when the user stops interacting with the data interaction module 30 for a first preset time, and the AI processing module 20 receives the first stop signal and stops working; when the disease level is the priority level, the time detection module 40 sends a second stop signal when the user stops interacting with the data interaction module 30 for a second preset time, and the emergency communication module sends emergency communication information according to the received second stop signal. Wherein the first preset time is 15s-30s, and the second preset time is 30s-60 s.
According to an embodiment of the present invention, the emergency communication module 50 is a 4G communication module 50 or a 5G communication module 50. The AI processing module 20 is a processor integrated in the AI blood glucose meter 100, and may also be an APP provided on the mobile terminal.
In other embodiments of the present invention, the AI blood glucose meter 100 further comprises: a data storage module 60 and an automatic learning module 70, wherein the data storage module 60 can store the disease condition information of the user, and the AI processing module 20 can read the disease condition information in the data storage module 60 and compare the disease condition information with the information detected by the detection module 10. The automatic learning module 70 is connected to the data storage module 60, and when the data information detected by the detection module 10 is data information that is not stored in the data storage module 60, the automatic learning module 70 stores the detected information in the data storage module 60.
The following describes in detail an AI chronic disease management method of the AI blood glucose meter 100 according to an embodiment of the present invention in use with reference to the drawings.
As shown in fig. 2, the AI chronic disease management method according to the embodiment of the present invention includes the following steps:
and S1, detecting and uploading the detected value of the patient chronic disease information.
S2, comparing the detection value with a preset value, judging the disease level of the patient to be a common level or a priority level, executing the step S3 when the disease level is the common level, and executing the step S4 when the disease level is the priority level.
S3, pushing common inquiry information to the patient, identifying whether response information of the patient to the common inquiry information exists or not after the common inquiry information is pushed to the patient, if yes, replying the corresponding question of the patient according to the response information, and if no response exists within a first preset time, finishing the identification.
S4, triggering a warning signal, pushing priority inquiry information to the patient after triggering the warning signal, identifying whether reply information of the patient to the priority inquiry information exists or not after pushing the priority inquiry information to the patient, if yes, determining whether to contact a third party or not according to the reply information, and if no reply exists within second preset time, automatically contacting the third party.
In other words, according to the utility model discloses AI chronic disease management method can be after detecting the patient, with patient's chronic disease information upload to server, judge whether normal according to the testing result of preset instruction by the server to according to the testing result of testing result to the patient propelling movement different information, for example when patient's testing result is normal, then to the ordinary inquiry information of patient propelling movement, for example diet condition, motion condition etc. problem, according to corresponding problem of the reply propelling movement of patient or answer again. When the server judges that the detection result of the patient is serious, the server triggers warning information, firstly, the server sends problems under emergency situations to the patient according to the warning information, such as whether the patient has symptoms such as headache and the like, and automatically judges whether a third party is required to be contacted according to the response of the patient, such as third party contact information reserved by a hospital or the patient and the like, and when the patient does not respond within a preset time, the server can automatically contact the third party to avoid danger of the patient.
Wherein need explain, according to the utility model discloses in the AI chronic disease management method, can realize the patient to the understanding of chronic disease information through server and the data interaction who removes end and detector completely, the patient passes through the detector promptly and detects chronic disease information, passes through to remove the end or directly uploads the testing result to the server, and the server receives and carries out relevant operation automatically after the chronic disease information. When the patient's problem or the chronic disease information is a problem that the server cannot automatically recognize or process, the server can contact the relevant technical personnel through the background to manually answer, and the patient can also know the patient's own chronic disease information.
From this, according to the utility model discloses AI chronic disease management method, after the patient detected chronic disease information, can upload and discern relevant information automatically, carry out the information interaction with the patient according to the identification result, strengthen the patient to the understanding and the notice of self chronic disease information to can help the patient contact the third party under emergency, realize the comprehensive management to patient's chronic disease, reduce the emergence of dangerous situation.
According to the utility model discloses an embodiment, in step S1, the chronic disease information includes blood sugar, blood pressure and blood lipid, that is to say, can detect patient' S chronic disease information through blood glucose meter, sphygmomanometer and lipid-lowering instrument to the information that will detect and obtain uploads. Therefore, the comprehensive arrangement of the information of the plurality of chronic diseases can facilitate the patients to know the plurality of chronic diseases, and the use is more convenient.
The following describes in detail an AI chronic disease management method according to an embodiment of the present invention, taking chronic disease information as blood glucose information as an example.
In some embodiments of the present invention, the preset value is 3.0mmol/L to 11.0mmol/L, and when the detection value is greater than the preset value range or smaller than the preset value range, the disease level is determined as priority; and when the detection value is within the preset value range, judging the disease condition level to be a common level.
That is, when the chronic disease information is blood sugar information, a preset value, for example, 3.0mmol/L-11.0mmol/L, may be preset by the system, and the blood sugar value is a normal blood sugar value of a person under normal conditions, and when the detected value is within a preset value range, the server determines that the blood sugar of the patient is normal, determines the disease level as a normal level, sends general query information, for example, diet, exercise, and medication conditions to the patient, automatically determines whether there is any problem according to the response information of the patient, and pushes a corresponding recipe and exercise method, for example, links a third party to eat, a medication service, an accompanying visit, and the like.
When the blood sugar value is smaller than the preset value, the blood sugar of the patient is relatively low, the possibility of hypoglycemia exists, when the blood sugar value is larger than the preset value, the blood sugar value of the patient is relatively high, the possibility of hyperglycemia exists, under the two conditions, the server considers that the blood sugar of the patient is in an abnormal state, judges the disease level as priority, and sends priority inquiry information to the patient.
In the actual use process, the preset values can be further subdivided, for example, the hypoglycemia condition can be further layered, and the method specifically comprises the following steps:
(1) blood glucose alert value: the blood sugar is less than or equal to 3.9mmol/L, in the case, the patient needs to take quick-acting carbohydrate and adjust the dosage of the blood sugar reduction scheme, and the server can provide relevant suggestions for the patient according to the detection result and the inquiry condition of the patient;
(2) clinically significant hypoglycemia: the blood sugar is less than 3.0mmol/L, and in the condition, the server prompts the patient to have serious and clinically significant hypoglycemia;
(3) severe hypoglycemia: blood glucose < 2.0mmol/L, which range of blood glucose values has no specific blood glucose limit, in which case the patient may be accompanied by severe cognitive dysfunction and hypoglycemia that requires additional measures to help recovery, in which case the server may contact the third party urgently, reducing the risk.
The hyperglycemic condition can be further classified, and specifically includes:
(1) the control can be as follows: fasting glucose is <7mmol/L and postprandial glucose is <10mmol/L, in which case the server may recommend that the patient does not require human intervention on blood glucose;
(2) low risk situation: fasting blood glucose is between 7mmol/L and 11mmol/L, or postprandial blood glucose is between 10mmol/L and 14mmol/L, in which case the server may recommend that the patient be handled by the community physician alone;
(3) in the middle critical situation: fasting blood glucose is between 11mmol/L and 14mmol/L, or postprandial blood glucose is between 14mmol/L and 18mmol/L, in which case the server may recommend treatment by community physicians under the direction of specialist physicians;
(4) high-risk situations: fasting glucose is >14mmol/L, or postprandial glucose is >18mmol/L, in which case the server may recommend treatment, outpatient adjustment or hospitalization by a specialist.
On the basis of presetting the preset value, the server can perform real-time feedback according to the detection result of the patient, when the disease condition level of the patient is judged to be a common level, common inquiry information is pushed to the patient, whether reply information is received or not is identified, if the reply information is received, reply is performed according to the reply information, and the reply content is sent to the patient. And if the reply message is not received within the first preset time, automatically ending the recognition state.
When receiving the reply information, the AI can automatically divide the information and forward the information to the corresponding answering personnel according to the identified consultation information.
According to an embodiment of the present invention, in step S3, the general query information includes: diet information, exercise information and medication, and general inquiry information can be adjusted and modified according to requirements.
Optionally, in step S3, the first preset time is 15S-30S. That is, when the patient's disease level is judged to be normal, the mobile terminal or other device sends a normal inquiry message to the patient, and if the patient does not reply after 15s-30s, the server automatically disconnects the contact with the patient, and the diagnosis and management of the chronic disease information are finished.
According to an embodiment of the present invention, in step S4, the priority query information includes: physical comfort information and medical history information, it should be noted that the priority query information can be adjusted and modified as needed.
In some embodiments of the present invention, in step S4, the second predetermined time is 30S to 60S.
Optionally, in step S4, the third party is a family member of the patient, a family doctor or a hospital.
That is, when the detected value of the detected chronic disease information is lower or higher than a preset value, for example, when a high-risk situation occurs, the server automatically triggers a serious warning message, and sends a priority inquiry message, for example, asking whether there is a problem such as dizziness, headache, etc. The patient sends the reply information, the database can judge the specific situation according to the question and answer result, trigger to family doctor, doctor to actively contact the patient, or directly link 120, and can trigger the function of up-down transfer to transfer the patient information from the primary hospital to the superior hospital. If the patient does not reply after 30-60 s, a warning message is triggered, and a WeChat or telephone alarm can be triggered to give family doctors or relatives of the patient.
In addition, according to the utility model discloses in the AI chronic disease management method of embodiment, the chronic disease information still can be blood pressure or blood lipid, when the chronic disease information is blood pressure, can carry out the management of chronic disease according to how to define blood pressure anomaly.
Specifically, the blood pressure abnormality includes hypotension and hypertension, the hypotension means that the blood pressure of the patient is less than 90/60mmhg, and the specific cases of the hypertension are shown in the following table 1:
TABLE 1 Classification of conditions of different blood pressure values
| Categories | Systolic pressure (mmhg) | Diastolic pressure (mmhg) |
| Ideal blood pressure | <120 and | <80 |
| normal high value | 120 to 139 and (or) | 80～89 |
| Hypertension (hypertension) | Not less than 140 and (or) | ≥90 |
| 1 st hypertension (mild) | 140 to 159 and (or) | 90～99 |
| Grade 2 hypertension (moderate) | 160 to 179 sum (or) | 100～109 |
| Grade 3 hypertension (severe) | Not less than 180 and (or) | ≥110 |
When the hypertension patient has continuous low pressure, under the condition, the server reminds the patient of needing to seek medical attention in time, when the blood pressure detection value of the patient is under the conditions of ideal blood pressure and normal high value, intervention is not needed, when the systolic pressure of the blood pressure detection value is 140-159 and/or the diastolic pressure is 90-99 mmhg, the server judges that the patient is the 1-grade high blood pressure, and the patient is recommended to be treated by a community doctor independently; when the systolic pressure of the blood pressure detection value is 160-179 mmhg or the diastolic pressure is 100-109 mmhg, the server judges that the patient is the level 2 high blood pressure, and the patient is recommended to be treated by a community doctor under the guidance of a specialist; when the systolic pressure of the blood pressure detection value is more than or equal to 180mmhg or the diastolic pressure is more than or equal to 110mmhg, the server judges that the patient is the 3-grade high blood pressure, and the diagnosis and treatment by a specialist, the adjustment of a treatment scheme by an outpatient service or hospitalization are recommended.
According to an embodiment of the present invention, step S1 further includes: judging whether the patient' S chronic disease information is stored in the database, if so, executing steps S2-S4, and if not, further comprising: and S5, storing the chronic disease information of the patient into a database. The intelligent analysis can be carried out through the database, corresponding questions are inquired for the patient according to the comparison and judgment results, and different questions are triggered by different detection results, such as common inquiry information and priority inquiry information.
When the database is established, information such as keywords, pictures, videos, related articles, recipes, motion schemes, suggestion schemes of corresponding diseases, training question and answer logics and the like of related chronic diseases can be input.
It should be noted that general query information and priority query information may be pushed to the patient through WeChat, telephone, community, and the like. And a user application platform can be established, such as a wechat robot (including public numbers, wechat groups and applets), a telephone robot (including short messages), a pc management end of the internet of things detection equipment, a cloud server and the like.
When the response information of the patient is identified, corresponding knowledge points or suggested schemes and the like can be fed back according to corresponding consultation information, for example, voice information or text information is identified, pictures are identified, key information can be extracted according to an identification result, and logic question answering is carried out on the extracted key information. When the logic question answering state is carried out, the database can be connected, and the corresponding condition triggered by the corresponding content is judged.
When the condition that the reply information cannot be identified occurs, the answer can be converted into manual work for answering, and the relevant consultation information can be input into the database to enable the AI to automatically learn.
In some embodiments of the present invention, after the reply message of the patient is identified, the reply message can be automatically replied and pushed, and the reply message can also be manually replied and pushed.
According to the utility model discloses an embodiment, when uploading patient's chronic disease information, can judge this patient's historical chronic disease information in the database, if have, then call out historical chronic disease information and compare real-time chronic disease information testing result with historical chronic disease information testing result. If not, the personal information of the patient is newly created.
In summary, the AI chronic disease management method according to the embodiment of the present invention has the following advantages:
(1) the Internet of things technology is applied to collect and manage the chronic disease information of the patient, and meanwhile, the artificial intelligence technology is introduced, so that the efficiency of preventing and controlling the risk factors of the high risk group with the chronic disease is effectively improved;
(2) can carry out remote monitoring to the patient, be convenient for carry out intervention treatment.
In addition, the embodiment of the present invention further provides a computer storage medium, where the computer storage medium includes one or more computer instructions, and when executed, the one or more computer instructions implement any one of the AI chronic disease management methods described above.
That is, the computer storage medium stores a computer program that, when executed by a processor, causes the processor to execute any of the AI lentimorous management methods described above.
As shown in fig. 3, an electronic device 300 according to an embodiment of the present invention includes a memory 310 and a processor 320, where the memory 310 is configured to store one or more computer instructions, and the processor 320 is configured to call and execute the one or more computer instructions, so as to implement any one of the methods described above.
That is, the electronic device 300 includes: a processor 320 and a memory 310, in which memory 310 computer program instructions are stored, wherein the computer program instructions, when executed by the processor, cause the processor 320 to perform any of the methods described above.
Further, as shown in fig. 3, the electronic device 300 further includes a network interface 330, an input device 340, a hard disk 350, and a display device 360.
The various interfaces and devices described above may be interconnected by a bus architecture. A bus architecture may be any architecture that may include any number of interconnected buses and bridges. Various circuits of one or more Central Processing Units (CPUs), represented in particular by processor 320, and one or more memories, represented by memory 310, are coupled together. The bus architecture may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like. It will be appreciated that a bus architecture is used to enable communications among the components. The bus architecture includes a power bus, a control bus, and a status signal bus, in addition to a data bus, all of which are well known in the art and therefore will not be described in detail herein.
The network interface 330 may be connected to a network (e.g., the internet, a local area network, etc.), and may obtain relevant data from the network and store the relevant data in the hard disk 350.
The input device 340 may receive various commands input by an operator and send the commands to the processor 320 for execution. The input device 340 may include a keyboard or a pointing device (e.g., a mouse, a trackball, a touch pad, a touch screen, or the like).
The display device 360 may display the result of the instructions executed by the processor 320.
The memory 310 is used for storing programs and data necessary for operating the operating system, and data such as intermediate results in the calculation process of the processor 320.
It will be appreciated that memory 310 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. The memory 310 of the apparatus and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 310 stores the following elements, executable modules or data structures, or a subset thereof, or an expanded set thereof: an operating system 311 and application programs 312.
The operating system 311 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs 312 include various application programs, such as a Browser (Browser), and are used for implementing various application services. A program for implementing the method according to an embodiment of the present invention may be included in the application 312.
The processor 320, when invoking and executing the application program and data stored in the memory 310, specifically, the application program or the instructions stored in the application program 312, dispersedly sends one of the first set and the second set to the node distributed by the other one of the first set and the second set, where the other one is dispersedly stored in at least two nodes; and performing intersection processing in a node-by-node manner according to the node distribution of the first set and the node distribution of the second set.
The method disclosed in the above embodiments of the present invention may be applied to the processor 320, or implemented by the processor 320. Processor 320 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 320. The processor 320 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, and may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present invention. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed by the embodiment of the present invention can be directly embodied as the execution of the hardware decoding processor, or the combination of the hardware and the software module in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 310, and the processor 320 reads the information in the memory 310 and completes the steps of the method in combination with the hardware.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
In particular, the processor 320 is also configured to read the computer program and execute any of the methods described above.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, each functional unit in the embodiments of the present invention may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) to perform some steps of the transceiving method according to various embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The foregoing is a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, a plurality of improvements and decorations can be made without departing from the principle of the present invention, and these improvements and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. An AI glucose meter, comprising:
the detection module can be used for detecting and uploading blood sugar information of a user;
the AI processing module can receive the blood sugar information and compare the blood sugar information with a preset value to judge the disease condition grade of the user, and the AI processing module sends out a corresponding processing signal according to the disease condition grade;
the data interaction module is connected with the AI processing module and can receive the processing signal, and the data interaction module can send corresponding inquiry information to a user according to the corresponding processing signal and feed back corresponding data according to the reply of the user;
the time detection module can detect the interaction time of the user and the data interaction module and sends a signal that the user stops interacting after the preset time that the user stops interacting with the data interaction module;
and the emergency communication module is connected with the AI processing module and the data interaction module and identifies information of the AI processing module and the data interaction module, and can send emergency communication information to a third party according to a signal sent by the time detection module when the user stops interacting.
2. The AI glucometer of claim 1, wherein the preset value is 3.0-11.0 mmol/L, the AI processing module is capable of determining, according to the blood glucose information, that a disease level of the user is a normal level or a priority level, and sending a normal processing signal when the disease level is the normal level, and sending a priority processing signal when the disease level is the priority level.
3. The AI glucose meter of claim 2, wherein the data interaction module is configured with general query information and priority query information, the data interaction module sending the general query information upon receiving the general processing signal and sending the priority query information upon receiving the priority processing signal.
4. The AI glucometer of claim 2, wherein the time detection module is connected to the AI processing module and identifies the AI processing module to determine the disease level of the user, and when the disease level is normal, the time detection module sends a first stop signal when the user stops interacting with the data interaction module for a first preset time, and the AI processing module receives the first stop signal and stops working;
when the disease condition level is the priority level, the time detection module sends a second stop signal when the user stops interacting with the data interaction module for a second preset time, and the emergency communication module receives the second stop signal and sends emergency communication information.
5. The AI glucose meter of claim 4, wherein the first predetermined time is 15s-30s and the second predetermined time is 30s-60 s.
6. The AI glucose meter of claim 1, wherein the emergency communication module is a 4G communication module or a 5G communication module.
7. The AI glucose meter of claim 1, wherein the AI processing module is a processor integrated within the AI glucose meter.
8. The AI glucose meter of claim 1, wherein the AI processing module is an APP located at the mobile terminal.
9. The AI glucose meter of claim 1, further comprising:
the AI processing module can read the illness state information in the data storage module and compare the illness state information with the information detected by the detection module.
10. The AI glucose meter of claim 9, further comprising:
the automatic learning module is connected with the data storage module, and when the data information detected by the detection module is data information which is not stored in the data storage module, the automatic learning module stores the detection information into the data storage module.
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| CN115607127A (en) * | 2022-10-31 | 2023-01-17 | 歌尔科技有限公司 | Wrist band device and blood pressure measuring method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115607127A (en) * | 2022-10-31 | 2023-01-17 | 歌尔科技有限公司 | Wrist band device and blood pressure measuring method |
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