CN115024690A - Alcohol metabolism detection method, computer device and storage medium - Google Patents
Alcohol metabolism detection method, computer device and storage medium Download PDFInfo
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- CN115024690A CN115024690A CN202210435361.3A CN202210435361A CN115024690A CN 115024690 A CN115024690 A CN 115024690A CN 202210435361 A CN202210435361 A CN 202210435361A CN 115024690 A CN115024690 A CN 115024690A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4845—Toxicology, e.g. by detection of alcohol, drug or toxic products
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4866—Evaluating metabolism
Abstract
The invention discloses an alcohol metabolism detection method, computer equipment and a storage medium. The alcohol metabolism detection method applied to the server comprises the following steps: acquiring first alcohol concentration data from a client; obtaining a target alcohol metabolism speed according to the plurality of first alcohol concentration data; wherein the target alcohol metabolism rate is used for characterizing alcohol metabolism ability; acquiring basic information from the client, and obtaining a first prompt signal according to the basic information and the target alcohol metabolism speed; wherein the basic information includes at least one of a type of drinking, a brand of drinking, alcohol concentration, a drinking amount, a fasting state, a food intake, a drinking amount, a drinking state, a sex, a weight, and an age. The embodiment of the application can obtain the alcohol metabolism speed by combining the actual alcohol metabolism condition of the user, thereby improving the accuracy of the alcohol metabolism speed.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an alcohol metabolism detection method, computer equipment and a storage medium.
Background
At present, the alcohol metabolism ability of each individual is different for different individuals, that is, for a plurality of individuals with the same alcohol consumption, the retention time of alcohol in the individual with strong alcohol metabolism ability is short, and the retention time of alcohol in the individual with weak alcohol metabolism ability is long. Therefore, the excessive drinking of an individual with a weak alcohol metabolism may cause health risks.
In the related art, the alcohol metabolism ability of an individual is determined by calculating the time required for consuming a certain amount of alcohol by the user by substituting the individual drinking capacity, alcohol degree, sex, weight and other related information into a unified formula. However, the above method uses a unified calculation formula, that is, the method cannot correspond to the actual alcohol metabolism condition of the user, thereby causing the deviation of alcohol metabolism capability.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an alcohol metabolism detection method, computer equipment and a storage medium, which can obtain the alcohol metabolism speed by combining the actual alcohol metabolism condition of a user, thereby improving the accuracy of the alcohol metabolism speed.
The alcohol metabolism detection method according to the embodiment of the first aspect of the invention is applied to a server side, and comprises the following steps:
acquiring first alcohol concentration data from a client;
obtaining a target alcohol metabolism speed according to the plurality of first alcohol concentration data; wherein the target alcohol metabolism rate is used for characterizing alcohol metabolism ability;
acquiring basic information from the client, and acquiring a first prompt signal according to the basic information and the target alcohol metabolism speed; wherein the basic information includes at least one of a type of drinking, a brand of drinking, alcohol concentration, a drinking amount, a fasting state, a food intake, a drinking amount, a drinking state, a sex, a weight, and an age.
The alcohol metabolism detection method provided by the embodiment of the invention at least has the following beneficial effects: the target alcohol metabolism speed for representing the alcohol metabolism capability is obtained through calculation of the plurality of first alcohol concentration data, so that the target alcohol metabolism speed is guaranteed to accord with the actual alcohol metabolism characteristics of an individual, and the accuracy of the alcohol metabolism grade is further guaranteed.
According to some embodiments of the invention, the deriving a target alcohol metabolism rate from the plurality of first alcohol concentration data comprises:
performing data cleaning operation on the first alcohol concentration data to obtain a sample data set;
taking a plurality of first alcohol concentration data meeting preset conditions in the sample data set as a test data set;
fitting a plurality of first alcohol concentration data in the test data set to obtain a calibrated alcohol metabolism speed;
and comparing the calibrated alcohol metabolism speed with a preset alcohol metabolism speed, processing the calibrated alcohol metabolism speed according to a comparison result, and obtaining the target alcohol metabolism speed.
According to some embodiments of the invention, said taking a plurality of said first alcohol concentration data in said sample data set satisfying a preset condition as a test data set comprises:
taking N first alcohol concentration data in the sample data set as a calibration data set; wherein N is a positive integer greater than 2;
acquiring maximum alcohol data and final alcohol data in the calibration data set;
and if the maximum alcohol data and the final alcohol data are separated by a preset amount of the first alcohol concentration data, and the final alcohol data are smaller than a preset threshold value or the total sampling time length of all the first alcohol concentration data in the calibration data set is larger than a preset time length, taking the calibration data set as the test data set.
According to some embodiments of the invention, prior to said deriving alcohol metabolism rate from said plurality of said first alcohol concentration data, said method further comprises:
obtaining a sampling interval according to the first alcohol concentration data, and sending the sampling interval to a client;
and acquiring second alcohol concentration data returned by the client according to the sampling interval.
According to some embodiments of the invention, further comprising:
obtaining an early warning value according to the alcohol metabolism speed and a preset safety duration;
and sending the early warning value to a client.
According to some embodiments of the invention, further comprising:
obtaining a first alcohol metabolism grade according to the alcohol metabolism speed;
obtaining comparison grades according to the first alcohol metabolism grades;
and acquiring a second alcohol metabolism level, and if the second alcohol metabolism level is smaller than the comparison level, generating a second prompt signal.
The alcohol metabolism detection method according to the second aspect of the embodiment of the invention is applied to a client, the client is used for being in communication connection with a wearable device, the wearable device is used for collecting first alcohol concentration data, and the method comprises the following steps:
the method comprises the steps of obtaining the first alcohol concentration data from the wearable device, and sending the first alcohol concentration data to a server, so that the server executes the alcohol metabolism detection method according to any one of the first aspect.
According to some embodiments of the invention, further comprising:
acquiring a sampling interval;
generating an acquisition signal according to the sampling interval, and sending the acquisition signal to the wearable device;
acquiring second alcohol concentration data returned by the wearable equipment according to the acquired signal;
and sending the second alcohol concentration data to the server.
The computer device according to an embodiment of the third aspect of the present invention comprises a memory and a processor, wherein the memory has stored therein a computer program, which when executed by the processor is adapted to perform:
the alcohol metabolism assay of any one of the first aspect;
or, the alcohol metabolism test method according to any one of the second aspect.
A storage medium according to a fourth aspect of the present invention is a computer-readable storage medium storing a computer program for, when executed by a computer, executing:
the alcohol metabolism assay of any one of the first aspect;
or, the alcohol metabolism test method according to any one of the second aspect.
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 invention is further described with reference to the following figures and examples, in which:
FIG. 1 is a schematic flow chart of an alcohol metabolism detection method applied to a server according to an embodiment of the present invention;
FIG. 2 is another schematic flow chart of the alcohol metabolism detecting method applied to the server according to the embodiment of the invention;
FIG. 3 is a diagram illustrating a trend of alcohol metabolism according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart illustrating an alcohol metabolism detecting method applied to a server according to an embodiment of the present invention;
FIG. 5 is another schematic flow chart illustrating an alcohol metabolism detecting method applied to a server according to an embodiment of the present invention;
FIG. 6 is a schematic flow chart illustrating an alcohol metabolism detecting method applied to a server according to an embodiment of the present invention;
FIG. 7 is a schematic flow chart illustrating an alcohol metabolism detecting method applied to a server according to an embodiment of the present invention;
FIG. 8 is a flowchart illustrating an alcohol metabolism detection method applied to a client according to an embodiment of the present invention;
FIG. 9 is a schematic flow chart illustrating an alcohol metabolism detection method applied to a client according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a hardware structure according to an embodiment of the present invention.
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 or similar 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 accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality is one or more, the meaning of a plurality is two or more, and the above, below, exceeding, etc. are understood as excluding the present numbers, and the above, below, within, etc. are understood as including the present numbers. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
In the description of the present invention, reference to the description of the terms "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
First, several nouns are explained in this application:
artificial Intelligence (AI): is a new technical science for researching and developing theories, methods, technologies and application systems for simulating, extending and expanding human intelligence; artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produces a new intelligent machine that can react in a manner similar to human intelligence, and research in this field includes robotics, language recognition, image recognition, natural language processing, and expert systems, among others. The artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is also a theory, method, technique and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use the knowledge to obtain the best results.
Alcohol tester: the alcohol detector can be used for the law enforcement traffic police to specifically treat the drinking amount of a drunk driver, can also be used for detecting the alcohol content in gas exhaled by a human body in other occasions, avoids casualties and serious property loss, and can identify whether the driver drives after drinking.
A wearable device: a wearable device is a portable device that is worn directly on the body or integrated into the clothing or accessories of the user. The wearable device is not only a hardware device, but also realizes powerful functions through software support, data interaction and cloud interaction.
An electrochemical sensor: electrochemical sensors operate by reacting with the gas being measured and producing an electrical signal proportional to the gas concentration. A typical electrochemical sensor consists of a sensing (or working) electrode and a counter electrode, separated by a thin electrolyte layer. The gas first reacts with the sensor through tiny capillary-type openings, then the hydrophobic barrier layer, and finally to the electrode surface. In this way, an appropriate amount of gas is allowed to react with the sensing electrode to form a sufficient electrical signal while preventing electrolyte from leaking out of the sensor.
In each embodiment of the present application, when data related to the user identity or characteristic, such as user information, user behavior data, user history data, and user location information, is processed, permission or consent of the user is obtained, and the data collection, use, and processing comply with relevant laws and regulations and standards of relevant countries and regions. In addition, when the embodiment of the present application needs to acquire sensitive personal information of a user, individual permission or individual consent of the user is obtained through a pop-up window or a jump to a confirmation page, and after the individual permission or individual consent of the user is definitely obtained, necessary user-related data for enabling the embodiment of the present application to operate normally is acquired.
Referring to fig. 1, the present application provides an alcohol metabolism testing method, which is applied to a server side and includes, but is not limited to, steps S110 to S130.
S110, acquiring first alcohol concentration data from a client;
s120, obtaining a target alcohol metabolism speed according to the plurality of first alcohol concentration data; wherein the target alcohol metabolism speed is used for representing the alcohol metabolism ability;
s130, acquiring basic information from a client, and obtaining a first prompt signal according to the basic information and the target alcohol metabolism speed; wherein the basic information includes at least one of type of drinking, brand of drinking, alcohol concentration, drinking amount, food intake, drinking amount, sex, body weight, and age.
It can be understood that the embodiment of the present application can acquire and process the related data based on the artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
It can be understood that the alcohol metabolism detection method provided in the embodiment of the present application is applied to a server, which may be an independent server, or a cloud server that provides basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, Network service, cloud communication, middleware service, domain name service, security service, a Content Delivery Network (CDN), big data, an artificial intelligence platform, and the like. The server is used for carrying out data transmission with the client through a preset network protocol, and the client is used for carrying out communication connection with the wearable device, for example, through Bluetooth communication connection. Wherein, wearable equipment is including intelligent wrist-watch, intelligent bracelet, the intelligent glasses etc. that can carry out first alcohol concentration data detection, does not do specific limit to this application embodiment. The wearable device detects the first alcohol concentration data through a built-in electrochemical sensor. The client is used for obtaining first alcohol concentration data of the user collected by the wearable device and forwarding the first alcohol concentration data to the server.
It can be understood that the server obtains a plurality of first alcohol concentration data by the above-described method, and calculates the alcohol metabolism amount per hour (i.e. the target alcohol metabolism speed) of the user according to the plurality of first alcohol concentration data. And obtaining a first alcohol metabolism level of the user according to the target alcohol metabolism speed, wherein the first alcohol metabolism level is used for representing the alcohol metabolism capability of the user.
It can be understood that a plurality of speed intervals are preset in the server, and each speed interval corresponds to one alcohol metabolism level. The server compares the alcohol metabolism speed obtained by the method with a plurality of speed intervals to obtain a speed interval corresponding to the alcohol metabolism speed, and therefore the alcohol metabolism level corresponding to the speed interval is used as the first alcohol metabolism level of the corresponding user. It is understood that the speed interval may be divided according to the first alcohol metabolism levels of a plurality of test users in advance, or may be divided in other manners, and the embodiment of the present application is not particularly limited.
Or comparing the alcohol metabolism speed with the currently verified alcohol metabolism speed of the human body, marking the user equal to the verified alcohol metabolism speed as a grade C alcohol metabolism level, dividing the grade A alcohol metabolism level and the grade B alcohol metabolism level according to the percentage exceeding the verified alcohol metabolism speed, and dividing the grade D alcohol metabolism level and the grade E alcohol metabolism level according to the percentage lower than the verified alcohol metabolism speed.
Or the server analyzes the ranking of the first alcohol metabolism speed of the corresponding user in the alcohol metabolism speeds of all users through a preset ranking algorithm, and determines the alcohol metabolism level of the corresponding user according to the ranking. For example, the first 25% of users ranked for a class A alcohol metabolism rating, the 26% to 50% of users ranked for a class B alcohol metabolism rating, the 51% to 75% of users ranked for a class C alcohol metabolism rating, and the 76% to 100% of users ranked for a class D alcohol metabolism rating are rated.
It can be understood that the server sends the first alcohol metabolism level obtained according to the method to the client, and the client displays the first alcohol metabolism level in the target mobile application and/or forwards the first alcohol metabolism level to the wearable device, so that the user can quickly know the current alcohol metabolism level from the target mobile application and/or the wearable device.
It can be understood that the client has the target mobile application installed therein, and the client obtains the basic information of the user through the key-in operation of the user in the target mobile application and sends the basic information to the server. The basic information is information related to alcohol metabolism speed, for example, the basic information includes at least one of a type of drinking, a brand of drinking, alcohol concentration, a drinking amount, a food intake amount, a drinking amount, an age, a height, a weight, a fasting state, a drinking state, and the like. Wherein, the fasting state indicates whether the user drinks wine on fasting, and the drinking state indicates whether the user drinks a large amount of water. And performing correlation analysis on the calculated target alcohol metabolism speed through the basic information, namely analyzing the influence of the target alcohol metabolism speed on which information in the basic information is influenced, and obtaining a relation coefficient. For example, through big data analysis, the user has found that when drinking brand a wine, the target alcohol metabolism rate is lower than the target alcohol metabolism rate calculated when drinking other brands of wine. Therefore, for the health of the user, when the server confirms that the current drinking brand of the user is brand A according to the basic information sent by the client, a first prompt signal is generated to remind the user to reduce the drinking of brand A.
It is to be understood that, in other embodiments, the server determines whether the currently acquired first alcohol concentration data can be used for calculating the alcohol metabolism rate according to the basic information, for example, when the user has a heavy drinking phenomenon or a fasting drinking phenomenon before drinking, the first alcohol concentration data will have a large deviation from the alcohol concentration data in a normal condition (no heavy drinking or fasting drinking before drinking). Therefore, the server side can generate a prompt signal according to the basic information and send the prompt signal to the client side, and the client side prompts a user that an error phenomenon possibly exists in current measurement according to the prompt signal and the measurement should be conducted later. And/or the server performs correction compensation on the acquired first alcohol concentration data according to the basic information, for example, when the user drinks a large amount of water before drinking, the acquired first alcohol concentration data is lower than that acquired under normal conditions (drinking water before drinking). Therefore, the server can correct and compensate the first alcohol concentration data according to the drinking water amount before drinking so as to ensure the accuracy of the first alcohol concentration data for calculating the alcohol metabolism speed.
According to the alcohol metabolism detection method provided by the embodiment of the application, the target alcohol metabolism speed for representing the alcohol metabolism capacity is obtained through calculation of the plurality of first alcohol concentration data, so that the target alcohol metabolism speed is ensured to accord with the actual alcohol metabolism characteristic of an individual, and the accuracy of the alcohol metabolism grade is further ensured.
Referring to fig. 2, in some embodiments, step S130 includes, but is not limited to, sub-steps S210-S230.
S210, performing data cleaning operation on the plurality of first alcohol concentration data to obtain a sample data set;
s220, taking a plurality of first alcohol concentration data meeting preset conditions in the sample data set as a test data set;
s230, fitting a plurality of first alcohol concentration data in the test data set to obtain a calibrated alcohol metabolism speed;
s240, comparing the calibrated alcohol metabolism speed with a preset alcohol metabolism speed, processing the calibrated alcohol metabolism speed according to a comparison result, and obtaining a target alcohol metabolism speed.
Specifically, data cleaning operation is performed on the acquired first alcohol concentration data to ensure the consistency and accuracy of data in the sample data set. For example, any one or more of discarding the data with significant errors, completing the missing data, and removing the duplicate data may be performed. And carrying out data screening operation on a plurality of first alcohol concentration data in the sample data set according to preset conditions, thereby screening an effective test data set which can be used for calculating alcohol metabolism speed. Fitting a plurality of first alcohol concentration data in the test data set, for example: and substituting a plurality of first alcohol concentration data screened from the sample data set into a preset linear regression model for analysis processing to obtain a slope K value, and taking the slope K value as a calibrated alcohol metabolism speed. Comparing the calibrated alcohol metabolism speed with a preset alcohol metabolism speed, and if the comparison result shows that the deviation value of the calibrated alcohol metabolism speed and the preset alcohol metabolism speed is within a preset range, taking the calibrated alcohol metabolism speed as a target alcohol metabolism speed; and if the comparison result shows that the deviation value is not in the preset range, namely the calibrated alcohol metabolism speed is obviously wrong, discarding the calibrated alcohol metabolism speed, and obtaining a plurality of first alcohol concentration data again or increasing the number of the first alcohol concentration data in the test data set so as to recalculate to obtain a new calibrated alcohol metabolism speed. And comparing the new calibrated alcohol metabolism speed with a preset alcohol metabolism speed according to the method until the target alcohol metabolism speed is obtained. The preset alcohol metabolism speed is an alcohol metabolism speed basic value obtained according to actual application, and can be adaptively adjusted according to the actual application, and the embodiment of the application is not particularly limited. It is understood that, in the linear regression model, the plurality of first alcohol concentration data are sequentially ordered from small to large according to the collection time.
It is understood that the preset condition may be adaptively set according to the actual application requirement, for example, adaptively set according to requirements such as calculation accuracy and calculation speed, and the embodiment of the present application is not particularly limited. Secondly, the linear regression model may be a least square normal linear regression model or other models, and the embodiment of the present application is not particularly limited.
In some embodiments, the preset conditions may be set as follows according to different requirements of actual applications:
first, referring to fig. 3, the preset condition is that a plurality of first alcohol concentration data of adjacent sampling times are in a descending trend. Specifically, a plurality of first alcohol concentration data in the sample data set are sequentially ordered from small to large according to sampling time so as to generate an alcohol metabolism trend graph. Calculating the change trends (namely slope values) of two first alcohol concentration data at adjacent sampling moments in the alcohol metabolism trend graph, and taking a plurality of groups of alcohol concentration data groups with negative slope values as target alcohol data. Wherein one group of the alcohol concentration data sets comprises two first alcohol concentration data of adjacent sampling moments. It can be understood that the plurality of first alcohol concentration data in the sample data set are obtained at regular sampling intervals, and therefore, the first alcohol concentration data of the user should gradually decrease as time goes on without the user continuously drinking alcohol. On the basis, whether first alcohol concentration data with a continuous descending trend exist in the sample data set is judged through a preset linear gradient descending model or other methods, and a plurality of first alcohol concentration data with the continuous descending trend are used as a test data set.
Secondly, the preset conditions include the following three points: first, the total amount of data in the dataset is greater than 2; at the second point, at least a preset amount of first alcohol concentration data are separated between the first alcohol concentration data with the maximum value (namely, the maximum alcohol data) in the data set and the last obtained first alcohol concentration data (namely, the final alcohol data); and thirdly, the value of the final alcohol data is smaller than or equal to a preset threshold, or the total sampling time length of all the first alcohol concentration data in the data set is larger than a preset time length. That is, referring to fig. 4, in some embodiments, step S220 includes, but is not limited to, substeps S410 through S430.
S410, taking N first alcohol concentration data in the sample data set as a calibration data set; wherein N is a positive integer greater than 2;
s420, acquiring maximum alcohol data and final alcohol data in the calibration data set;
and S430, if the maximum alcohol data and the final alcohol data are separated by a preset number of first alcohol concentration data, and the final alcohol data are smaller than a preset threshold or the total sampling duration of all the first alcohol concentration data in the calibration data set is larger than a preset duration, taking the calibration data set as a test data set.
Specifically, a plurality of first alcohol concentration data in the sample data set are screened through a three-point screening condition of a second preset condition, and the plurality of first alcohol concentration data which simultaneously meet the three-point screening condition are used as a test data set. The method includes fitting a plurality of first alcohol concentration data in the test data set to obtain a slope K value for representing alcohol metabolism speed, and further obtaining a first alcohol metabolism level of the user according to the slope K value and the method described in the above embodiment. It can be understood that the specific values of N, the preset number, and the preset duration may be adaptively adjusted according to the actual application requirements, and the embodiment of the present application is not specifically limited.
Referring to fig. 5, in some embodiments, the alcohol metabolism detection method further includes steps S510 to S520 before step S130.
S510, obtaining a sampling interval according to the first alcohol concentration data, and sending the sampling interval to a client;
and S520, acquiring second alcohol concentration data returned by the client according to the sampling interval.
Specifically, in order to acquire alcohol concentration data for multiple times to improve the accuracy of alcohol metabolism speed calculation, the server is further configured to generate a sampling interval according to the currently acquired alcohol concentration data (i.e., the first alcohol concentration data), and send the sampling interval to the client. The client acquires new alcohol concentration data (namely second alcohol concentration data) from the wearable device at regular time according to the sampling interval, and sends the new alcohol concentration data to the server, so that the server calculates accurate alcohol metabolism speed according to the plurality of alcohol concentration data, and accuracy of the first alcohol metabolism level is improved.
Referring to fig. 6, in some embodiments, the alcohol metabolism detection method further includes steps S510 to S520.
S610, obtaining an early warning value according to the alcohol metabolism speed and the preset safety duration;
and S620, sending the early warning value to the client.
Specifically, the server is further configured to obtain an early warning value according to the alcohol metabolism speed and a preset relative safe duration (i.e., a preset safe duration) during which the alcohol stays in the user, and send the early warning value to the client. The early warning value is used for representing the safe alcohol concentration of the corresponding user, namely when the first alcohol concentration data is larger than the early warning value, the fact that the user can consume alcohol in the body for a long time is indicated, and/or the current in-vivo alcohol of the user exceeds the tolerable range of the user, at the moment, the client generates a second prompt signal and/or controls the wearable device to vibrate so as to remind the user of the risk which possibly exists currently.
Referring to fig. 7, in some embodiments, the alcohol metabolism detection method further includes steps S610 to S620.
S710, obtaining a first alcohol metabolism grade according to the alcohol metabolism speed;
s720, obtaining comparison grades according to the first alcohol metabolism grades;
and S730, obtaining a second alcohol metabolism level, and if the second alcohol metabolism level is smaller than the comparison level, generating a second prompt signal.
Specifically, a first alcohol metabolism level corresponding to the user is obtained according to the calculated alcohol metabolism rate and the method as described in any of the above embodiments. The server is further configured to analyze the plurality of historical alcohol metabolism levels (i.e., the plurality of first alcohol metabolism levels) to obtain an average level (i.e., a comparison level) for characterizing alcohol metabolism. When the current alcohol metabolism level (i.e. the second alcohol metabolism level) of the user is calculated to be smaller than the comparison level according to the method described in any of the above embodiments, the server generates a second prompt signal and sends the second prompt signal to the client. The client performs pop-up window prompting in the target mobile application according to the second prompting signal, and/or controls the wearable device to perform vibration prompting so as to remind a user that the current alcohol metabolism level fluctuates compared with historical data, namely that the current alcohol drinking operation may have risks.
It is understood that when it is determined that the user may be at risk according to the above method, the server may control the target mobile application of the client to display a selection box indicating whether the emergency contact needs to be notified or not through the second prompt signal. If the user selects to notify the emergency contact to notify the relevant relatives or friends for help, a reminder request is generated. And sending the address information, the time information and the risk information (including information such as a first alcohol metabolism level and a first alcohol concentration data of the corresponding user) of the user to a preset emergency communication address according to the reminding request so as to remind relevant relatives or friends, so that the relevant relatives or friends can make corresponding help for the user according to the environmental abnormity prompting information, and the safety and the use experience of the user are improved. The preset emergency communication address is a communication address of an emergency contact, and the communication address comprises QQ information, a WeChat account number, a mobile phone number and the like.
Referring to fig. 8, an embodiment of the present application further provides another alcohol metabolism detection method, where the alcohol metabolism detection method is applied to a client, the client is used for being in communication connection with a wearable device, and the wearable device is used for acquiring first alcohol concentration data. The alcohol metabolism detection method comprises the following steps:
s810, acquiring first alcohol concentration data from wearable equipment;
s820, sending the first alcohol concentration data to the server, so that the server performs the alcohol metabolism detection method described in any of the above embodiments.
Referring to fig. 9, in some embodiments, the alcohol metabolism testing method further comprises the steps of:
s910, acquiring a sampling interval;
s920, generating an acquisition signal according to the sampling interval, and sending the acquisition signal to wearable equipment;
s930, acquiring second alcohol concentration data returned by the wearable device according to the acquired signal;
and S940, sending the second alcohol concentration data to a server.
It can be seen that, the content of the above-mentioned embodiment of the method for detecting alcohol metabolism applied to the server is all applicable to the embodiment of the method for detecting alcohol metabolism applied to the client, and the functions specifically implemented by the embodiment of the method for detecting alcohol metabolism applied to the client are the same as those of the above-mentioned embodiment of the method for detecting alcohol metabolism applied to the server, and the beneficial effects achieved by the embodiment of the method for detecting alcohol metabolism applied to the server are also the same as those achieved by the above-mentioned embodiment of the method for detecting alcohol metabolism applied to the server.
An embodiment of the present application further provides a computer device, where the computer device includes: at least one processor, and a memory communicatively coupled to the at least one processor. The storage stores instructions that are executed by the at least one processor, so that when the at least one processor executes the instructions, the at least one processor implements the alcohol metabolism detection method applied to the server or the alcohol metabolism level calculation applied to the client as described in any of the above embodiments.
An embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions for: the alcohol metabolism detection method applied to the server or the alcohol metabolism detection method applied to the client, which is described in any of the above embodiments, is performed.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
An embodiment of the present application further provides a wearable device, and the wearable device includes: the alcohol concentration detection device comprises a memory, a processor, a program stored on the memory and capable of running on the processor, and a data bus for realizing connection communication between the processor and the memory, wherein the program realizes the alcohol concentration detection method when being executed by the processor. This wearable equipment can be for including arbitrary intelligent terminal such as intelligent wrist-watch, intelligent bracelet, intelligent glasses and intelligent dress.
Referring to fig. 10, fig. 10 illustrates a hardware structure of a wearable device of another embodiment, the wearable device including:
the processor 1001 may be implemented by a general-purpose CPU (central processing unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits, and is configured to execute a relevant program to implement the technical solution provided in the embodiment of the present application;
the memory 1002 may be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a Random Access Memory (RAM). The memory 1002 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present disclosure is implemented by software or firmware, the relevant program codes are stored in the memory 1002 and called by the processor 1001 to execute the alcohol concentration detection method according to the embodiments of the present disclosure;
an input/output interface 1003 for implementing information input and output;
the communication interface 1004 is used for realizing communication interaction between the device and other devices, and can realize communication in a wired manner (for example, USB, network cable, etc.) or in a wireless manner (for example, mobile network, WIFI, bluetooth, etc.);
a bus 1005 that transfers information between various components of the device, such as the processor 1001, memory 1002, input/output interface 1003, and communication interface 1004;
wherein the processor 1001, the memory 1002, the input/output interface 1003 and the communication interface 1004 realize communication connections with each other inside the apparatus through a bus 1005.
The embodiment of the present application further provides a storage medium, which is a computer-readable storage medium for computer-readable storage, where the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to implement the above alcohol concentration detection method.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the above-described division of units is only one type of division of logical functions, 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.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing programs, 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 preferred embodiments of the present application have been described above with reference to the accompanying drawings, and the scope of the claims of the embodiments of the present application is not limited thereto. Any modifications, equivalents and improvements that may occur to those skilled in the art without departing from the scope and spirit of the embodiments of the present application are intended to be within the scope of the claims of the embodiments of the present application.
Claims (10)
1. The alcohol metabolism detection method is applied to a server side, and comprises the following steps:
acquiring first alcohol concentration data from a client;
obtaining a target alcohol metabolism speed according to the plurality of first alcohol concentration data; wherein the target alcohol metabolism rate is used for characterizing alcohol metabolism ability;
acquiring basic information from the client, and acquiring a first prompt signal according to the basic information and the target alcohol metabolism speed; wherein the basic information includes at least one of a type of drinking, a brand of drinking, alcohol concentration, a drinking amount, a fasting state, a food intake, a drinking amount, a drinking state, a sex, a weight, and an age.
2. The alcohol metabolism detection method according to claim 1, wherein obtaining a target alcohol metabolism rate from the plurality of first alcohol concentration data includes:
performing data cleaning operation on the first alcohol concentration data to obtain a sample data set;
taking a plurality of first alcohol concentration data meeting preset conditions in the sample data set as a test data set;
fitting a plurality of first alcohol concentration data in the test data set to obtain a calibrated alcohol metabolism speed;
and comparing the calibrated alcohol metabolism speed with a preset alcohol metabolism speed, processing the calibrated alcohol metabolism speed according to a comparison result, and obtaining the target alcohol metabolism speed.
3. The alcohol metabolism detection method according to claim 2, wherein the using a plurality of the first alcohol concentration data satisfying a preset condition in the sample data set as a test data set comprises:
taking N first alcohol concentration data in the sample data set as a calibration data set; wherein N is a positive integer greater than 2;
acquiring maximum alcohol data and final alcohol data in the calibration data set;
and if the maximum alcohol data and the final alcohol data are separated by a preset amount of the first alcohol concentration data, and the final alcohol data are smaller than a preset threshold value or the total sampling time length of all the first alcohol concentration data in the calibration data set is larger than a preset time length, taking the calibration data set as the test data set.
4. The alcohol metabolism test method according to claim 1, wherein, before the obtaining of the alcohol metabolism rate from the plurality of first alcohol concentration data, the method further comprises:
obtaining a sampling interval according to the first alcohol concentration data, and sending the sampling interval to a client;
and acquiring second alcohol concentration data returned by the client according to the sampling interval.
5. The alcohol metabolism test method according to any one of claims 1 to 4, further comprising:
obtaining an early warning value according to the alcohol metabolism speed and a preset safety duration;
and sending the early warning value to a client.
6. The alcohol metabolism test method according to any one of claims 1 to 4, further comprising:
obtaining a first alcohol metabolism grade according to the alcohol metabolism speed;
obtaining comparison grades according to the first alcohol metabolism grades;
and acquiring a second alcohol metabolism level, and if the second alcohol metabolism level is smaller than the comparison level, generating a second prompt signal.
7. The alcohol metabolism detection method is applied to a client, the client is used for being in communication connection with a wearable device, the wearable device is used for collecting first alcohol concentration data, and the method comprises the following steps:
obtaining the first alcohol concentration data from the wearable device;
transmitting the first alcohol concentration data to a server, so that the server executes the alcohol metabolism testing method according to any one of claims 1 to 6.
8. The alcohol metabolism detection method according to claim 7, further comprising:
acquiring a sampling interval;
generating an acquisition signal according to the sampling interval, and sending the acquisition signal to the wearable device;
acquiring second alcohol concentration data returned by the wearable equipment according to the acquired signal;
and sending the second alcohol concentration data to the server.
9. A computer device, characterized in that the computer device comprises a memory and a processor, wherein the memory has stored therein a computer program, and the processor is adapted to perform, when the computer program is executed by the processor:
the alcohol metabolism assay of any one of claims 1 to 6;
or, the alcohol metabolism test method according to claim 7 or 8.
10. A storage medium that is a computer-readable storage medium, wherein the computer-readable stores a computer program that, when executed by a computer, the computer is operable to perform:
the alcohol metabolism test method according to any one of claims 1 to 6;
or, the alcohol metabolism test method according to claim 7 or 8.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210435361.3A CN115024690A (en) | 2022-04-24 | 2022-04-24 | Alcohol metabolism detection method, computer device and storage medium |
| PCT/CN2023/089006 WO2023207678A1 (en) | 2022-04-24 | 2023-04-18 | Alcohol metabolism detection method, computer device, and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210435361.3A CN115024690A (en) | 2022-04-24 | 2022-04-24 | Alcohol metabolism detection method, computer device and storage medium |
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| CN115024690A true CN115024690A (en) | 2022-09-09 |
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| CN202210435361.3A Pending CN115024690A (en) | 2022-04-24 | 2022-04-24 | Alcohol metabolism detection method, computer device and storage medium |
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| WO (1) | WO2023207678A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023207678A1 (en) * | 2022-04-24 | 2023-11-02 | 深圳市华盛昌科技实业股份有限公司 | Alcohol metabolism detection method, computer device, and storage medium |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140365142A1 (en) * | 2013-06-11 | 2014-12-11 | Antimatter Research, Inc. | Wearable Blood Alcohol Measuring Device |
| CN105929144A (en) * | 2016-04-22 | 2016-09-07 | 深圳还是威健康科技有限公司 | Wearable device for measuring alcohol concentration and method thereof |
| CN211022622U (en) * | 2019-06-03 | 2020-07-17 | 陕西理工大学 | Novel alcohol detection reminding wrist strap |
| CN111272988B (en) * | 2020-02-27 | 2021-04-02 | 广州逆熵电子科技有限公司 | Alcohol concentration prediction method and system and alcohol degradation assessment instrument |
| CN111671408B (en) * | 2020-07-07 | 2023-05-30 | 方滨 | User drinking safety monitoring method, user terminal and server |
| CN115024690A (en) * | 2022-04-24 | 2022-09-09 | 深圳市华盛昌科技实业股份有限公司 | Alcohol metabolism detection method, computer device and storage medium |
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- 2022-04-24 CN CN202210435361.3A patent/CN115024690A/en active Pending
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2023207678A1 (en) * | 2022-04-24 | 2023-11-02 | 深圳市华盛昌科技实业股份有限公司 | Alcohol metabolism detection method, computer device, and storage medium |
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