WO2023207678A1 - 酒精代谢检测方法、计算机设备及存储介质 - Google Patents
酒精代谢检测方法、计算机设备及存储介质 Download PDFInfo
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- WO2023207678A1 WO2023207678A1 PCT/CN2023/089006 CN2023089006W WO2023207678A1 WO 2023207678 A1 WO2023207678 A1 WO 2023207678A1 CN 2023089006 W CN2023089006 W CN 2023089006W WO 2023207678 A1 WO2023207678 A1 WO 2023207678A1
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- alcohol metabolism
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- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 title claims abstract description 343
- 230000004060 metabolic process Effects 0.000 title claims abstract description 201
- 238000001514 detection method Methods 0.000 title claims abstract description 56
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 14
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Classifications
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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
-
- 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
Definitions
- the invention relates to the field of data processing technology, and in particular to an alcohol metabolism detection method, computer equipment and storage medium.
- each individual's alcohol metabolism ability is different. That is, for multiple individuals who drink the same amount, alcohol will remain in the body for a shorter time in individuals with strong alcohol metabolism ability, and alcohol will remain in the body of individuals with weak alcohol metabolism ability for a shorter time. It remains in the body for a longer period of time. Therefore, for individuals with weak alcohol metabolizing ability, excessive drinking will cause harm to health.
- the present invention aims to solve at least one of the technical problems existing in the prior art.
- the present invention proposes an alcohol metabolism detection method, computer equipment and storage medium, which can obtain the alcohol metabolism speed in combination with the user's actual alcohol metabolism, thereby improving the accuracy of the alcohol metabolism speed.
- the method is applied to the server, and the method includes:
- a target alcohol metabolism rate is obtained according to a plurality of the first alcohol concentration data; wherein the target alcohol metabolism rate is used to characterize alcohol metabolism ability;
- the alcohol metabolism detection method has at least the following beneficial effects: through multiple first alcohol concentrations
- the degree data is calculated to obtain the target alcohol metabolism rate used to characterize the alcohol metabolism ability, thereby ensuring that the target alcohol metabolism rate is consistent with the individual's actual alcohol metabolism characteristics, thereby ensuring the accuracy of the alcohol metabolism grade.
- the target alcohol metabolism rate is obtained based on a plurality of the first alcohol concentration data, including:
- the calibrated alcohol metabolism rate is compared with the preset alcohol metabolism rate, the calibrated alcohol metabolism rate is processed according to the comparison result, and the target alcohol metabolism rate is obtained.
- using a plurality of the first alcohol concentration data in the sample data set that meet preset conditions as a test data set includes:
- N is a positive integer greater than 2;
- the calibration data set is used as the test data set.
- the method before obtaining the alcohol metabolism rate according to the plurality of first alcohol concentration data, the method further includes:
- it also includes:
- it also includes:
- the second alcohol metabolism level is obtained, and if the second alcohol metabolism level is smaller than the comparison level, a second prompt signal is generated.
- the method is applied to a client, and the client The end is used for communication connection with a wearable device, and the wearable device is used for collecting the first alcohol concentration data.
- the method includes:
- it also includes:
- the computer device includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor is used to implement:
- the storage medium is a computer-readable storage medium
- the computer-readable storage medium stores a computer program.
- the computer program is executed by a computer
- the computer is used to execute :
- Figure 1 is a schematic flow chart of an alcohol metabolism detection method applied to a server according to an embodiment of the present invention
- Figure 2 is another schematic flow chart of an alcohol metabolism detection method applied to a server according to an embodiment of the present invention
- Figure 3 is a schematic diagram of an alcohol metabolism trend chart according to an embodiment of the present invention.
- Figure 4 is another schematic flow chart of an alcohol metabolism detection method applied to a server according to an embodiment of the present invention.
- Figure 5 is another schematic flowchart of an alcohol metabolism detection method applied to a server according to an embodiment of the present invention.
- Figure 6 is another schematic flowchart of an alcohol metabolism detection method applied to a server according to an embodiment of the present invention.
- Figure 7 is another schematic flow chart of an alcohol metabolism detection method applied to the server according to an embodiment of the present invention.
- Figure 8 is a schematic flow chart of an alcohol metabolism detection method applied to a client according to an embodiment of the present invention.
- Figure 9 is another schematic flow chart of an alcohol metabolism detection method applied to a client according to an embodiment of the present invention.
- Figure 10 is a schematic diagram of a hardware structure of an embodiment of the present invention.
- orientation descriptions such as up, down, front, back, left, right, etc., are based on the orientation or position relationships shown in the drawings and are only In order to facilitate the description of the present invention and simplify the description, it is not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be construed as a limitation of the present invention.
- Artificial intelligence It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence; artificial intelligence is a branch of computer science, artificial intelligence Intelligence attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a manner similar to human intelligence. Research in this field includes robotics, language recognition, image recognition, natural language processing, and expert systems. Artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is also a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.
- Alcohol tester Also known as alcohol tester, it can be used by law enforcement traffic police to determine the amount of alcohol consumed by drinking drivers. It can also be used to detect the alcohol content in the breath exhaled by the human body on other occasions to avoid casualties and Significant damage to property can identify whether a driver is driving under the influence.
- Wearable device is a portable device that is worn directly on the body or is integrated into the user's clothing or accessories. Wearable devices are not just hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction.
- Electrochemical sensors work 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 electrode (or working electrode) and a counter electrode, separated by a thin electrolytic layer. The gas first reacts with the sensor through tiny capillary openings, then through a hydrophobic barrier layer, and finally reaches the electrode surface. This approach allows the appropriate amount of gas to react with the sensing electrode to form a sufficient electrical signal while preventing electrolyte from leaking out of the sensor.
- the first step is to perform relevant processing.
- the user's permission or consent is obtained, and the collection, use and processing of this data will comply with the relevant laws, regulations and standards of the relevant countries and regions.
- the embodiment of this application needs to obtain the user's sensitive personal information, it will obtain the user's separate permission or separate consent through a pop-up window or jump to a confirmation page. After clearly obtaining the user's separate permission or separate consent, it will then Obtain necessary user-related data for normal operation of the embodiment of the present application.
- an embodiment of the present application provides an alcohol metabolism detection method, which is applied to the server.
- the alcohol metabolism detection method includes but is not limited to steps S110 to S130.
- S130 Obtain basic information from the client, and obtain the first prompt signal based on the basic information and the target alcohol metabolism speed; where the basic information includes drinking type, drinking brand, alcohol concentration, drinking volume, food intake, water drinking volume, gender, and weight. , at least one of age.
- AI artificial intelligence
- Basic artificial intelligence technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation/interaction systems, mechatronics and other technologies.
- Artificial intelligence software technology mainly includes computer vision technology, robotics technology, biometric technology, speech processing technology, natural language processing technology, and machine learning/deep learning.
- the server can be an independent server, or can provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, and networks. Services, cloud communications, middleware services, domain name services, security services, content delivery network (Content Delivery Network, CDN), and the cloud server side of basic cloud computing services such as big data and artificial intelligence platforms.
- the server is used to transmit data with the client through a preset network protocol, and the client is used to communicate with the wearable device, such as through Bluetooth communication.
- wearable devices include smart watches, smart bracelets, smart glasses, etc. that can detect the first alcohol concentration data, which are not specifically limited in the embodiments of the present application.
- the wearable device detects the first alcohol concentration data through a built-in electrochemical sensor.
- the client is used to obtain the user's first alcohol concentration data collected by the wearable device, and is used to forward the first alcohol concentration data to the server.
- the server obtains multiple first alcohol concentration data through the method described above, and calculates the user's alcohol metabolism per hour (ie, the target alcohol metabolism rate) based on the multiple first alcohol concentration data.
- the user's first alcohol metabolism level can be obtained according to the target alcohol metabolism speed, and the first alcohol metabolism level is used to characterize the user's alcohol metabolism ability.
- each speed zone corresponds to an alcohol metabolism level.
- the server compares the alcohol metabolism speed obtained according to the above method with multiple speed intervals to obtain the speed interval corresponding to the alcohol metabolism speed, and then uses the alcohol metabolism level corresponding to the speed interval as the first alcohol metabolism of the corresponding user grade.
- the speed intervals can be divided in advance according to the first alcohol metabolism levels of multiple test users, or the speed intervals can be divided in other ways, which is not specifically limited in the embodiments of the present application.
- Alcohol metabolism grade, B grade alcohol metabolism grade, D grade alcohol metabolism grade, E grade alcohol metabolism grade are divided according to the percentage lower than the verified alcohol metabolism speed.
- the server analyzes the ranking of the corresponding user's first alcohol metabolism speed among the alcohol metabolism speeds of all users through a preset ranking algorithm, and determines the alcohol metabolism level of the corresponding user based on the ranking. For example, users with a calibrated ranking of the top 25% are classified as level A alcohol metabolism, users with a calibrated ranking of 26% to 50% are classified as a level B alcohol metabolism, and users with a calibrated ranking of 51% to 75% are classified as a level C alcohol metabolism. Level, calibrated ranking of 76% to 100% of users is Level D Alcohol Metabolism, etc. class.
- the server sends the first alcohol metabolism level obtained according to the above method to the client, and the client displays the first alcohol metabolism level in the target mobile application, and/or displays the first alcohol metabolism level. Forwarded to the wearable device, allowing the user to quickly understand the current alcohol metabolism level from the target mobile application and/or wearable device.
- the target mobile application is installed in the client, and the client obtains the user's basic information through the user's typing operation in the target mobile application, and sends the basic information to the server.
- the basic information is information related to the alcohol metabolism rate.
- the basic information includes drinking type, drinking brand, alcohol concentration, drinking amount, food intake, water drinking amount, age, height, weight, fasting status, drinking water status, etc. at least one of them.
- the fasting state refers to whether the user drinks on an empty stomach
- the drinking state refers to whether the user drinks a lot of water. Perform correlation analysis on the calculated target alcohol metabolism speed through the above basic information, that is, analyze which information in the basic information affects the target alcohol metabolism speed, and obtain the relationship coefficient.
- the server confirms that the user's current drinking brand is brand A based on the basic information sent by the client, it generates a first prompt signal to remind the user to reduce drinking of brand A wine.
- the server also determines whether the currently obtained first alcohol concentration data can be used to calculate the alcohol metabolism speed based on basic information, for example, when the user drinks a lot of water before drinking or When drinking on an empty stomach, the first alcohol concentration data will deviate greatly from the alcohol concentration data under normal circumstances (without drinking a lot of water before drinking or drinking on an empty stomach). Therefore, the server can generate a prompt signal based on the basic information and send the prompt signal to the client. The client prompts the user based on the prompt signal that there may be an error in the current measurement and should test again later. And/or, the server corrects and compensates the obtained first alcohol concentration data based on basic information.
- the server can correct and compensate the first alcohol concentration data based on the amount of water consumed before drinking to ensure the accuracy of the first alcohol concentration data used to calculate the alcohol metabolism rate.
- the alcohol metabolism detection method provided by the embodiment of the present application calculates the target alcohol metabolism rate used to characterize the alcohol metabolism ability through multiple first alcohol concentration data, thereby ensuring that the target alcohol metabolism rate is in line with the actual alcohol metabolism characteristics of the individual, and thus The accuracy of the alcohol metabolism grade is guaranteed.
- step S130 includes but is not limited to sub-steps S210 to S230.
- a data cleaning operation is performed on the multiple obtained first alcohol concentration data to ensure the consistency and accuracy of the data in the sample data set. For example, perform any one or more operations such as discarding obviously erroneous data, completing missing data, and deduplicating data.
- Fitting processing of multiple first alcohol concentration data in the test data set for example: substituting multiple first alcohol concentration data filtered out from the sample data set into a preset linear regression model for analysis and processing, and obtaining the slope K value , and use the slope K value as the calibrated alcohol metabolism speed. Compare the calibrated alcohol metabolism rate with the preset alcohol metabolism rate.
- the comparison result indicates that the deviation value between the calibrated alcohol metabolism rate and the preset alcohol metabolism rate is within the preset range, then use the calibrated alcohol metabolism rate as the target alcohol metabolism rate; If the comparison result shows that the deviation value is not within the preset range, that is, there is an obvious error in the calibrated alcohol metabolism rate, then discard the calibrated alcohol metabolism rate, reacquire multiple first alcohol concentration data, or add the first alcohol concentration data in the test data set. quantity to recalculate the new calibrated alcohol metabolism rate. Compare the new calibrated alcohol metabolism speed with the preset alcohol metabolism speed according to the above method until the target alcohol metabolism speed is obtained.
- the preset alcohol metabolism rate is a basic value of the alcohol metabolism rate obtained based on actual applications, which can be adaptively adjusted based on actual applications, and is not specifically limited in the embodiments of this application. It can be understood that in the linear regression model, the multiple first alcohol concentration data are sorted from small to large according to the collection time.
- the preset conditions can be adaptively set according to actual application requirements, for example, according to calculation accuracy, calculation speed and other requirements, which are not specifically limited in the embodiments of the present application.
- the linear regression model may use a least squares linear regression model or other models, and the embodiments of the present application do not specifically limit this.
- the preset conditions can be set to the following two types:
- the preset condition is that multiple first alcohol concentration data at adjacent sampling times show a downward trend.
- the multiple first alcohol concentration data in the sample data set are sorted from small to large according to the sampling time to generate an alcohol metabolism trend graph.
- one set of alcohol concentration data sets includes two first alcohol concentration data at adjacent sampling moments. It is understandable that the multiple first alcohol concentration data in the sample data set are obtained at certain sampling intervals. Therefore, as time goes by, if the user does not continue to drink, his first alcohol concentration data should gradually reduce. On this basis, determine whether there is a continuous downward trend of the first alcohol concentration data in the sample data set through a preset linear gradient descent model or other methods, and use multiple first alcohol concentration data with a continuous downward trend as a test data set .
- the preset conditions include the following three points: first, the total amount of data in the data set is greater than 2; second, the first alcohol concentration data with the largest value in the data set (i.e., the maximum alcohol data) and the last one are obtained
- the first alcohol concentration data i.e., the final alcohol data
- the third point is that the value of the final alcohol data is less than or equal to the preset threshold, or all the first alcohol concentrations in the data set
- the total sampling time of the data is longer than the preset time.
- step S220 includes but is not limited to sub-steps S410 to S430.
- N is a positive integer greater than 2;
- multiple first alcohol concentration data in the sample data set are screened through the three-point filtering conditions of the second preset condition, and multiple first alcohol concentration data that simultaneously meet the above three-point filtering conditions are used as the test data set. .
- a slope K value used to characterize the alcohol metabolism speed is obtained, and then the user's profile is obtained based on the slope K value and the method described in the above embodiment.
- the first level of alcohol metabolism It can be understood that the specific values of N, the preset number, and the preset duration can be adaptively adjusted according to actual application requirements, which are not specifically limited in the embodiments of the present application.
- the alcohol metabolism detection method before step S130, the alcohol metabolism detection method further includes steps S510 to S520.
- the server in order to obtain alcohol concentration data multiple times to improve the accuracy of alcohol metabolism rate calculation, the server is also used to generate a sampling interval based on the currently obtained alcohol concentration data (i.e., the first alcohol concentration data), and use the sampling interval interval sent to the client.
- the client regularly obtains new alcohol concentration data (i.e., the second alcohol concentration data) from the wearable device according to the sampling interval, and sends the new alcohol concentration data to the server, so that the server can calculate based on multiple alcohol concentration data.
- Obtain accurate alcohol metabolism rate thereby improving the accuracy of the first alcohol metabolism level.
- the alcohol metabolism detection method further includes steps S510 to S520.
- the server is also used to determine the relative safe length of time alcohol stays in the user's body based on the alcohol metabolism speed and the preset time limit. (i.e. the preset safety duration) to obtain the early warning value and send the early warning value to the client.
- the early warning value is used to represent the safe alcohol concentration corresponding to the user. That is, when the first alcohol concentration data is greater than the early warning value, it indicates that the user will need a longer time to consume all the alcohol in the body, and/or the user is currently in the body. The alcohol has exceeded the range that it can bear.
- the client generates a second prompt signal and/or controls the vibration of the wearable device to remind the user of the current possible risks.
- the alcohol metabolism detection method further includes steps S610 to S620.
- the first alcohol metabolism level of the corresponding user is obtained based on the calculated alcohol metabolism speed and the method described in any of the above embodiments.
- the server is also used to analyze multiple historical alcohol metabolism levels (ie, multiple first alcohol metabolism levels) to obtain an average level (ie, comparison level) used to characterize alcohol metabolism.
- an average level ie, comparison level
- the server When the user's current alcohol metabolism level (i.e., the second alcohol metabolism level) calculated according to the method described in any of the above embodiments is less than the comparison level, the server generates a second prompt signal and sends the second prompt signal to client.
- the client generates a pop-up prompt in the target mobile application based on the second prompt signal, and/or controls the wearable device to vibrate the prompt to remind the user that the current alcohol metabolism level fluctuates compared with historical data, that is, the current drinking operation may be risky. .
- the server can control the target mobile application of the client to display a check box asking whether the emergency contact needs to be notified through the second prompt signal. If the user chooses to notify an emergency contact to notify relevant relatives or friends to help, a reminder request is generated. According to the reminder request, the user's address information, time information, and risk information (including the corresponding user's first alcohol metabolism level, first alcohol concentration data, etc.) are sent to the preset emergency communication address to remind relevant relatives or friends. In order to facilitate relevant relatives or friends to provide corresponding help to the user based on the environmental abnormality prompt information, thereby improving the user's safety and user experience. Among them, the preset emergency communication address is the communication address of the emergency contact, and the communication address includes QQ information, WeChat account, mobile phone number, etc.
- the embodiment of the present application also provides another alcohol metabolism detection method.
- the alcohol metabolism detection method is applied to the client.
- the client is used to communicate with the wearable device, and the wearable device is used to collect the first alcohol concentration. data.
- the alcohol metabolism detection method includes steps:
- the alcohol metabolism detection method further includes the steps:
- the above-mentioned content in the embodiment of the alcohol metabolism detection method applied to the server is applicable to the embodiment of the alcohol metabolism detection method originally applied to the client.
- the functions specifically implemented by the embodiment of the alcohol metabolism detection method originally applied to the client are the same as
- the above-mentioned embodiments of the alcohol metabolism detection method applied to the server are the same, and the beneficial effects achieved are the same as those of the above-mentioned embodiments of the alcohol metabolism detection method applied to the server.
- An embodiment of the present application also provides a computer device, which includes: at least one processor, and a memory communicatively connected to the at least one processor.
- the memory stores instructions, and the instructions are executed by at least one processor, so that when at least one processor executes the instructions, the alcohol metabolism detection method applied to the server or the alcohol metabolism applied to the client is implemented as described in any of the above embodiments. Level calculation.
- Embodiments of the present application provide a computer-readable storage medium that stores computer-executable instructions.
- the computer-executable instructions are used to: execute the alcohol metabolism detection method applied to the server or applied to the client described in any of the above embodiments. Alcohol metabolism testing methods.
- the device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separate, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
- Embodiments of the present application also provide a wearable device.
- the wearable device includes: a memory, a processor, a program stored in the memory and executable on the processor, and a device for realizing connection and communication between the processor and the memory. Data bus, when the program is executed by the processor, the above alcohol concentration detection method is implemented.
- the wearable device can be any smart terminal including smart watches, smart bracelets, smart glasses, and smart clothing.
- Figure 10 illustrates the hardware structure of a wearable device according to another embodiment.
- the wearable device includes:
- the processor 1001 can be implemented by a general-purpose CPU (Central Processing Unit, central processing unit), a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute related programs to Implement the technical solutions provided by the embodiments of this application;
- a general-purpose CPU Central Processing Unit, central processing unit
- a microprocessor central processing unit
- an application specific integrated circuit Application Specific Integrated Circuit, ASIC
- ASIC Application Specific Integrated Circuit
- the memory 1002 can be implemented in the form of read-only memory (ReadOnlyMemory, ROM), static storage device, dynamic storage device, or random access memory (RandomAccessMemory, RAM).
- the memory 1002 can store operating systems and other application programs.
- the relevant program code is stored in the memory 1002, and is called by the processor 1001 to execute the alcohol concentration detection method of the embodiment of the present application;
- Communication interface 1004 is used to realize communication interaction between this device and other devices. Communication can be achieved through wired methods (such as USB, network cables, etc.) or wireless methods (such as mobile network, WIFI, Bluetooth, etc.);
- Bus 1005 which transmits information between various components of the device (such as processor 1001, memory 1002, input/output interface 1003, and communication interface 1004);
- the processor 1001, the memory 1002, the input/output interface 1003 and the communication interface 1004 implement communication connections between each other within the device through the bus 1005.
- Embodiments of the present application also provide a storage medium.
- the storage medium is a computer-readable storage medium for computer-readable storage.
- the storage medium stores one or more programs, and the one or more programs can be processed by one or more
- the device is executed to implement the above alcohol concentration detection method.
- memory can be used to store non-transitory software programs and non-transitory computer executable programs.
- the memory may include high-speed random access memory and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device.
- the memory may optionally include memory located remotely from the processor, and the remote memory may be connected to the processor via a network. Examples of the above-mentioned networks include but are not limited to the Internet, intranets, local area networks, mobile communication networks and combinations thereof.
- At least one (item) refers to one or more, and “plurality” refers to two or more.
- “And/or” is used to describe the relationship between associated objects, indicating that there can be three relationships. For example, “A and/or B” can mean: only A exists, only B exists, and A and B exist simultaneously. , where A and B can be singular or plural. The character “/” generally indicates that the related objects are in an "or” relationship. “At least one of the following” or similar expressions thereof refers to any combination of these items, including any combination of a single item (items) or a plurality of items (items).
- At least one of a, b or c can mean: a, b, c, "a and b", “a and c", “b and c", or "a and b and c” ”, where a, b, c can be single or multiple.
- the disclosed devices and methods can be implemented in other ways.
- the device embodiments described above are only illustrative.
- the division of the above units is only a logical function division. In actual implementation, there may be other division methods.
- multiple units or components may be combined or may be Integrated into another system, or some features can be ignored, or not implemented.
- the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.
- the units described above as separate components may or may not be physically separated.
- the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
- each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit.
- the above integrated units can be implemented in the form of hardware or software functional units.
- Integrated units may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as independent products.
- the technical solution of the present application is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application.
- the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc. that can store programs. medium.
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- Investigating Or Analyzing Materials By The Use Of Fluid Adsorption Or Reactions (AREA)
Abstract
公开了一种酒精代谢检测方法、计算机设备及存储介质。应用于服务端的酒精代谢检测方法包括：从客户端获取第一酒精浓度数据（S110）；根据多个所述第一酒精浓度数据得到目标酒精代谢速度；其中，所述目标酒精代谢速度用于表征酒精代谢能力（S120）；从所述客户端获取基础信息，根据所述基础信息和所述目标酒精代谢速度得到第一提示信号；其中，所述基础信息包括饮酒类型、饮酒品牌、酒精浓度、饮酒量、空腹状态、进食量、喝水量、喝水状态、性别、体重、年龄中的至少一种（S130）。
Description
本发明涉及数据处理技术领域，尤其涉及一种酒精代谢检测方法、计算机设备及存储介质。
目前，对于不同个体来说，每个个体的酒精代谢能力均不相同，即对于饮酒量相同的多个个体，酒精在酒精代谢能力强的个体体内留存时间较短，酒精在酒精代谢能力弱的个体体内留存时间较长。因此，对于酒精代谢能力弱的个体，若其过渡饮酒，则会对健康造成危害。
相关技术中，通过将个体的饮酒量、酒精度数、用户性别、体重等相关信息代入统一的公式中，计算得到对应用户消耗一定量酒精所需的时间，从而确定该用户的酒精代谢能力。但是上述方法是使用统一的计算公式，即无法对应用户实际的酒精代谢情况，从而造成酒精代谢能力偏差。
发明内容
本发明旨在至少解决现有技术中存在的技术问题之一。为此，本发明提出一种酒精代谢检测方法、计算机设备及存储介质，能够结合用户的实际酒精代谢情况得到酒精代谢速度，从而提高了酒精代谢速度的准确性。
根据本发明的第一方面实施例的酒精代谢检测方法，所述方法应用于服务端，所述方法包括：
从客户端获取第一酒精浓度数据；
根据多个所述第一酒精浓度数据得到目标酒精代谢速度；其中，所述目标酒精代谢速度用于表征酒精代谢能力；
从所述客户端获取基础信息，根据所述基础信息和所述目标酒精代谢速度得到第一提示信号；其中，所述基础信息包括饮酒类型、饮酒品牌、酒精浓度、饮酒量、空腹状态、进食量、喝水量、喝水状态、性别、体重、年龄中的至少一种。
根据本发明实施例的酒精代谢检测方法，至少具有如下有益效果：通过多个第一酒精浓
度数据计算得到用于表征酒精代谢能力的目标酒精代谢速度，从而保证了该目标酒精代谢速度符合个体的实际酒精代谢特征，进而保证了酒精代谢等级的准确性。
根据本发明的一些实施例，所述根据多个所述第一酒精浓度数据得到目标酒精代谢速度，包括：
对多个所述第一酒精浓度数据进行数据清洗操作，以得到样本数据集；
将所述样本数据集中满足预设条件的多个所述第一酒精浓度数据作为测试数据集；
对所述测试数据集中的多个所述第一酒精浓度数据进行拟合处理，得到标定酒精代谢速度；
将所述标定酒精代谢速度与预设酒精代谢速度进行比较，根据比较结果对所述标定酒精代谢速度进行处理，并得到所述目标酒精代谢速度。
根据本发明的一些实施例，所述将所述样本数据集中满足预设条件的多个所述第一酒精浓度数据作为测试数据集，包括：
将所述样本数据集中的N个所述第一酒精浓度数据作为标定数据集；其中，N为大于2的正整数；
获取所述标定数据集中的最大酒精数据和最终酒精数据；
若所述最大酒精数据和所述最终酒精数据间隔预设数量的所述第一酒精浓度数据，且所述最终酒精数据小于预设阈值或所述标定数据集中所有所述第一酒精浓度数据的采样总时长大于预设时长，则将所述标定数据集作为所述测试数据集。
根据本发明的一些实施例，在所述根据多个所述第一酒精浓度数据得到酒精代谢速度之前，所述方法还包括：
根据所述第一酒精浓度数据得到采样间隔，将所述采样间隔发送给客户端；
获取所述客户端根据所述采样间隔返回的第二酒精浓度数据。
根据本发明的一些实施例，还包括：
根据所述酒精代谢速度和预设安全时长得到预警值；
将所述预警值发送给客户端。
根据本发明的一些实施例，还包括：
根据所述酒精代谢速度得到第一酒精代谢等级；
根据多个所述第一酒精代谢等级得到比对等级；
获取第二酒精代谢等级，若第二酒精代谢等级小于所述比对等级，则生成第二提示信号。
根据本发明的第二方面实施例的酒精代谢检测方法，所述方法应用于客户端，所述客户
端用于与可穿戴设备通信连接，所述可穿戴设备用于采集第一酒精浓度数据，所述方法包括：
从所述可穿戴设备获取所述第一酒精浓度数据，并将所述第一酒精浓度数据发送给服务端，以使所述服务端执行如第一方面任一项所述的酒精代谢检测方法。
根据本发明的一些实施例，还包括：
获取采样间隔；
根据所述采样间隔生成获取信号，并将所述获取信号发送给所述可穿戴设备；
获取所述可穿戴设备根据所述获取信号返回的第二酒精浓度数据；
将所述第二酒精浓度数据发送给所述服务端。
根据本发明的第三方面实施例的计算机设备，所述计算机设备包括存储器和处理器，其中，所述存储器中存储有计算机程序，所述计算机程序被所述处理器执行时所述处理器用于执行：
如第一方面任一项所述的酒精代谢检测方法；
或，如第二方面任一项所述的酒精代谢检测方法。
根据本发明的第四方面实施例的存储介质，所述存储介质为计算机可读存储介质，所述计算机可读存储有计算机程序，在所述计算机程序被计算机执行时，所述计算机用于执行：
如第一方面任一项所述的酒精代谢检测方法；
或，如第二方面任一项所述的酒精代谢检测方法。
本发明的附加方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本发明的实践了解到。
下面结合附图和实施例对本发明做进一步的说明，其中：
图1为本发明实施例应用于服务端的酒精代谢检测方法的一流程示意图；
图2为本发明实施例应用于服务端的酒精代谢检测方法的另一流程示意图；
图3为本发明实施例酒精代谢趋势图的一示意图；
图4为本发明实施例应用于服务端的酒精代谢检测方法的另一流程示意图；
图5为本发明实施例应用于服务端的酒精代谢检测方法的另一流程示意图；
图6为本发明实施例应用于服务端的酒精代谢检测方法的另一流程示意图；
图7为本发明实施例应用于服务端的酒精代谢检测方法的另一流程示意图；
图8为本发明实施例应用于客户端的酒精代谢检测方法的一流程示意图；
图9为本发明实施例应用于客户端的酒精代谢检测方法的另一流程示意图；
图10为本发明实施例的一硬件结构示意图。
下面详细描述本发明的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，仅用于解释本发明，而不能理解为对本发明的限制。
在本发明的描述中，需要理解的是，涉及到方位描述，例如上、下、前、后、左、右等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。
在本发明的描述中，若干的含义是一个以上，多个的含义是两个以上，大于、小于、超过等理解为不包括本数，以上、以下、以内等理解为包括本数。如果有描述到第一、第二只是用于区分技术特征为目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量或者隐含指明所指示的技术特征的先后关系。
本发明的描述中，除非另有明确的限定，设置、安装、连接等词语应做广义理解，所属技术领域技术人员可以结合技术方案的具体内容合理确定上述词语在本发明中的具体含义。
本发明的描述中，参考术语“一个实施例”、“一些实施例”、“示意性实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
首先，对本申请中涉及若干名词进行解释：
人工智能(artificial intelligence，AI)：是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学；人工智能是计算机科学的一个分支，人工智能企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器，该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等。人工智能可以对人的意识、思维的信息过程的模拟。人工智能还是利用数字计算机或者数字计算机控制的机器模拟、延伸和扩展人的智能，感知环境、获取知识并使用知识获得最佳结果的理论、方法、技术及应用系统。
酒精测试仪：又称酒精检测仪，是可供执法交警用来对饮酒司机的饮酒多少来进行具体的处理，也可以用来在其他场合进行检测人体呼出的气体中酒精含量，避免人员伤亡和财产的重大损失，可以鉴别司机是否酒后驾车。
可穿戴设备：可穿戴设备是一种直接穿在身上或是整合到用户的衣服或配件的一种便携式设备。可穿戴设备不仅仅是一种硬件设备，更是通过软件支持以及数据交互、云端交互来实现强大的功能。
电化学传感器：电化学传感器通过与被测气体发生反应并产生与气体浓度成正比的电信号来工作。典型的电化学传感器由传感电极(或工作电极)和反电极组成，并由一个薄电解层隔开。气体首先通过微小的毛管型开孔与传感器发生反应，然后是疏水屏障层，最终到达电极表面。采用这种方法可以允许适量气体与传感电极发生反应，以形成充分的电信号，同时防止电解质漏出传感器。
需要说明的是，在本申请的各个具体实施方式中，当涉及到需要根据用户信息、用户行为数据，用户历史数据以及用户位置信息等与用户身份或特性相关的数据进行相关处理时，都会先获得用户的许可或者同意，而且，对这些数据的收集、使用和处理等，都会遵守相关国家和地区的相关法律法规和标准。此外，当本申请实施例需要获取用户的敏感个人信息时，会通过弹窗或者跳转到确认页面等方式获得用户的单独许可或者单独同意，在明确获得用户的单独许可或者单独同意之后，再获取用于使本申请实施例能够正常运行的必要的用户相关数据。
参照图1，本申请实施例提供了一种酒精代谢检测方法，该酒精代谢检测方法应用于服务端，该酒精代谢检测方法包括但不限于有步骤S110至S130。
S110、从客户端获取第一酒精浓度数据；
S120、根据多个第一酒精浓度数据得到目标酒精代谢速度；其中，目标酒精代谢速度用于表征酒精代谢能力；
S130、从客户端获取基础信息，根据基础信息和目标酒精代谢速度得到第一提示信号；其中，基础信息包括饮酒类型、饮酒品牌、酒精浓度、饮酒量、进食量、喝水量、性别、体重、年龄中的至少一种。
可以理解的是，本申请实施例可以基于人工智能技术对相关的数据进行获取和处理。其中，人工智能(Artificial Intelligence，AI)是利用数字计算机或者数字计算机控制的机器模拟、延伸和扩展人的智能，感知环境、获取知识并使用知识获得最佳结果的理论、方法、技术及应用系统。
人工智能基础技术一般包括如传感器、专用人工智能芯片、云计算、分布式存储、大数据处理技术、操作/交互系统、机电一体化等技术。人工智能软件技术主要包括计算机视觉技术、机器人技术、生物识别技术、语音处理技术、自然语言处理技术以及机器学习/深度学习等几大方向。
可以理解的是，本申请实施例提供的酒精代谢检测方法应用于服务端，该服务端可以是独立的服务端，也可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服务、安全服务、内容分发网络(Content Delivery Network，CDN)、以及大数据和人工智能平台等基础云计算服务的云服务端。该服务端用于与客户端通过预设的网络协议进行数据传输，客户端用于与可穿戴设备进行通信连接，例如通过蓝牙通信连接。其中，可穿戴设备包括能够进行第一酒精浓度数据检测的智能手表、智能手环、智能眼镜等，对此本申请实施例不作具体限定。可穿戴设备通过内置的电化学传感器对第一酒精浓度数据进行检测。客户端用于获取可穿戴设备所采集的用户的第一酒精浓度数据，并用于将该第一酒精浓度数据转发给服务端。
可以理解的是，服务端通过上述所描述的方法获取得到多个第一酒精浓度数据，并根据多个第一酒精浓度数据计算得到用户每小时的酒精代谢量(即目标酒精代谢速度)。根据该目标酒精代谢速度可得到用户的第一酒精代谢等级，该第一酒精代谢等级用于表征用户的酒精代谢能力。
可以理解的是，服务端中预设有多个速度区间，每一个速度区间与一个酒精代谢等级对应。服务端将根据上述方法得到的酒精代谢速度与多个速度区间进行比对，得到该酒精代谢速度所对应的速度区间，从而将该速度区间所对应的酒精代谢等级作为对应用户的第一酒精代谢等级。可以理解的是，预先可根据多个测试用户的第一酒精代谢等级对速度区间进行划分，或通过其他方式对速度区间进行划分，对此本申请实施例不作具体限定。
或者，将该酒精代谢速度与目前通过验证的人体酒精代谢速度进行比较，将等于该验证酒精代谢速度的用户标定为C级酒精代谢等级，并且，按超出该验证酒精代谢速度的百分比划分A级酒精代谢等级、B级酒精代谢等级，按低于该验证酒精代谢速度的百分比划分D级酒精代谢等级、E级酒精代谢等级。
或者，服务端通过预设的排名算法分析对应用户第一酒精代谢速度在所有用户的酒精代谢速度中的排名，根据该排名确定对应用户的酒精代谢等级。例如，标定排名为前25％的用于为A级酒精代谢等级，标定排名为26％至50％的用户为B级酒精代谢等级，标定排名为51％至75％的用户为C级酒精代谢等级，标定排名为76％至100％的用户为D级酒精代谢等
级。
可以理解的是，服务端将根据上述方法得到的第一酒精代谢等级发送给客户端，客户端在目标移动应用中对该第一酒精代谢等级进行显示，和/或将该第一酒精代谢等级转发给可穿戴设备，使得用户能够从目标移动应用和/或可穿戴设备中快速了解当前酒精代谢等级。
可以理解的是，客户端中安装有目标移动应用，客户端通过用户在目标移动应用中的键入操作获取用户的基础信息，并将该基础信息发送给服务端。其中，基础信息为与酒精代谢速度相关联的信息，例如基础信息包括饮酒类型、饮酒品牌、酒精浓度、饮酒量、进食量、喝水量、年龄、身高、体重、空腹状态、喝水状态等中的至少一种。其中，空腹状态指用户是否空腹饮酒，喝水状态指用户是否大量喝水。通过上述基础信息对计算得到的目标酒精代谢速度进行相关性分析，即分析目标酒精代谢速度受基础信息中哪些信息的影响，并得到关系系数。例如，通过大数据分析发现，该用户在饮用A品牌的酒时，目标酒精代谢速度低于饮用其他品牌酒时计算得到的目标酒精代谢速度。因此，为了用户健康，当服务端根据客户端发送的基础信息确认用户当前的饮酒品牌为A品牌时，生成第一提示信号，以提醒用户减少饮用A品牌的酒。
可以理解的是，在另一些实施例中，服务端还根据基础信息确定当前所获取的第一酒精浓度数据是否能够用于计算酒精代谢速度，例如，当用户在饮酒前存在大量喝水现象或空腹饮酒现象时，第一酒精浓度数据将会与正常情况下(饮酒前未大量喝水或未空腹饮酒)的酒精浓度数据存在较大偏差。因此，服务端可以根据基础信息生成提示信号，并将该提示信号发送给客户端，客户端根据该提示信号提示用户当前测量可能存在误差现象，应稍后再测。和/或，服务端根据基础信息对获取的第一酒精浓度数据进行修正补偿，例如，当用户在饮酒前存在大量喝水现象时，此时所获取的第一酒精浓度数据低于正常情况下(饮酒前未大量喝水)所获取的酒精浓度数据。因此，服务端可根据饮酒前的喝水量对第一酒精浓度数据进行修正补偿，以保证用于计算酒精代谢速度的第一酒精浓度数据的准确性。
本申请实施例提供的酒精代谢检测方法，通过多个第一酒精浓度数据计算得到用于表征酒精代谢能力的目标酒精代谢速度，从而保证了该目标酒精代谢速度符合个体的实际酒精代谢特征，进而保证了酒精代谢等级的准确性。
参照图2，在一些实施例中，步骤S130包括但不限于有子步骤S210至S230。
S210、对多个第一酒精浓度数据进行数据清洗操作，以得到样本数据集；
S220、将样本数据集中满足预设条件的多个第一酒精浓度数据作为测试数据集；
S230、对测试数据集中的多个第一酒精浓度数据进行拟合处理，得到标定酒精代谢速度；
S240、将标定酒精代谢速度与预设酒精代谢速度进行比较，根据比较结果对标定酒精代谢速度进行处理，并得到目标酒精代谢速度。
具体地，对获取得到的多个第一酒精浓度数据进行数据清洗操作，以保证样本数据集中数据的一致性和准确性。例如，进行丢弃存在明显错误数据、补全缺失数据、数据去重等任一种或多种操作。根据预设条件对样本数据集中的多个第一酒精浓度数据进行数据筛选操作，从而筛选出有效的、能够用于进行计算酒精代谢速度的测试数据集。对该测试数据集中的多个第一酒精浓度数据拟合处理，例如：将从样本数据集中筛选出的多个第一酒精浓度数据代入预设的线性回归模型中进行分析处理，得到斜率K值，将该斜率K值作为标定酒精代谢速度。将标定酒精代谢速度与预设酒精代谢速度进行比较，若比较结果表示标定酒精代谢速度与预设酒精代谢速度的偏差值在预设范围内，则将该标定酒精代谢速度作为目标酒精代谢速度；若比较结果表示该偏差值不在预设范围内，即该标定酒精代谢速度出现明显错误，则丢弃该标定酒精代谢速度，重新获取多个第一酒精浓度数据或增加测试数据集中第一酒精浓度数据的数量，以重新计算得到新的标定酒精代谢速度。根据上述方法将该新的标定酒精代谢速度与预设酒精代谢速度进行比较，直至得到目标酒精代谢速度。其中，预设酒精代谢速度为根据实际应用获取得到的酒精代谢速度基础值，其可以根据实际应用进行适应性调整，本申请实施例不作具体限定。可以理解的是，在线性回归模型中，多个第一酒精浓度数据根据采集时刻从小到大依次排序。
可以理解的是，预设条件可根据实际应用需求进行适应性设置，例如根据计算精度、计算速度等需求进行适应性设置，对此本申请实施例不作具体限定。其次，线性回归模型可选用最小二乘法线性回归模型或其他模型，对此本申请实施例也不作具体限定。
在一些实施例中，根据实际应用需求的不同，可将预设条件设置为如下两种：
第一种，参照图3，预设条件为相邻采样时间的多个第一酒精浓度数据呈下降趋势。具体地，将样本数据集中的多个第一酒精浓度数据按采样时刻从小到大依次排序，以生成酒精代谢趋势图。计算该酒精代谢趋势图中相邻采样时刻的两个第一酒精浓度数据的变化趋势(即斜率值)，将斜率值为负数的多组酒精浓度数据组作为目标酒精数据。其中，一组酒精浓度数据组包括相邻采样时刻的两个第一酒精浓度数据。可理解的是，样本数据集中的多个第一酒精浓度数据为间隔一定的采样间隔获取得到，因此，随着时间的推移，在用户未持续饮酒的情况下，其第一酒精浓度数据应逐渐降低。在此基础上，通过预设的线性梯度下降模型或其他方法判断样本数据集中是否存在连续下降趋势的第一酒精浓度数据，并将存在连续下降趋势的多个第一酒精浓度数据作为测试数据集。
第二种，预设条件包括如下三点：第一点，数据集中的总数据量大于2；第二点，数据集中数值最大的第一酒精浓度数据(即最大酒精数据)和最后一个获取得到的第一酒精浓度数据(即最终酒精数据)之间至少间隔预设数量的第一酒精浓度数据；第三点，最终酒精数据的数值小于或等于预设阈值，或数据集中所有第一酒精浓度数据的采样总时长大于预设时长。即参照图4，在一些实施例中，步骤S220包括但不限于有子步骤S410至S430。
S410、将样本数据集中的N个第一酒精浓度数据作为标定数据集；其中，N为大于2的正整数；
S420、获取标定数据集中的最大酒精数据和最终酒精数据；
S430、若最大酒精数据和最终酒精数据间隔预设数量的第一酒精浓度数据，且最终酒精数据小于预设阈值或标定数据集中所有第一酒精浓度数据的采样总时长大于预设时长，则将标定数据集作为测试数据集。
具体地，通过第二种预设条件的三点筛选条件对样本数据集中的多个第一酒精浓度数据进行筛选，将同时满足上述三点筛选条件的多个第一酒精浓度数据作为测试数据集。通过对该测试数据集中的多个第一酒精浓度数据进行拟合处理，得到用于表征酒精代谢速度的斜率K值，进而根据该斜率K值和如上述实施例所描述的方法得到该用户的第一酒精代谢等级。可以理解的是，N、预设数量、预设时长的具体取值可以根据实际应用需求进行适应性调整，对此本申请实施例不作具体限定。
参照图5，在一些实施例中，在步骤S130之前，该酒精代谢检测方法还包括步骤S510至S520。
S510、根据第一酒精浓度数据得到采样间隔，将采样间隔发送给客户端；
S520、获取客户端根据采样间隔返回的第二酒精浓度数据。
具体地，为了多次获取酒精浓度数据，以提高酒精代谢速度计算的准确性，服务端还用于根据当前所获取的酒精浓度数据(即第一酒精浓度数据)生成采样间隔，并将该采样间隔发送给客户端。客户端根据该采样间隔定时从可穿戴设备中获取新的酒精浓度数据(即第二酒精浓度数据)，并将新的酒精浓度数据发送给服务端，以使服务端根据多个酒精浓度数据计算得到准确的酒精代谢速度，进而提高第一酒精代谢等级的准确性。
参照图6，在一些实施例中，该酒精代谢检测方法还包括步骤S510至S520。
S610、根据酒精代谢速度和预设安全时长得到预警值；
S620、将预警值发送给客户端。
具体地，服务端还用于根据酒精代谢速度和预设的酒精在用户体内停留的相对安全时长
(即预设安全时长)得到预警值，并将该预警值发送给客户端。其中，预警值用于表征对应用户安全的酒精浓度，即当第一酒精浓度数据大于该预警值时，表明该用户需要较长的时间才能消耗完体内的酒精，和/或该用户当前体内的酒精已超过其所能承受的范围，此时客户端生成第二提示信号和/或控制可穿戴设备震动，以提醒用户当前可能存在的风险。
参照图7，在一些实施例中，该酒精代谢检测方法还包括步骤S610至S620。
S710、根据酒精代谢速度得到第一酒精代谢等级；
S720、根据多个所述第一酒精代谢等级得到比对等级；
S730、获取第二酒精代谢等级，若第二酒精代谢等级小于所述比对等级，则生成第二提示信号。
具体地，根据计算得到的酒精代谢速度和如上述任一实施例所描述的方法得到对应用户的第一酒精代谢等级。服务端还用于对多个历史酒精代谢等级(即多个第一酒精代谢等级)进行分析，以得到用于表征酒精代谢的平均等级(即比对等级)。当根据如上述任一实施例所描述的方法计算得到用户当前的酒精代谢等级(即第二酒精代谢等级)小于比对等级时，服务器生成第二提示信号，并将该第二提示信号发送给客户端。客户端根据该第二提示信号在目标移动应用中进行弹窗提示，和/或控制可穿戴设备进行震动提示，以提醒用户当前酒精代谢等级较历史数据存在波动，即当前的饮酒操作可能存在风险。
可以理解的是，当根据如上述方法确定用户可能存在风险时，服务端可通过第二提示信号控制客户端的目标移动应用显示一个是否需要通知紧急联系人的选框。若用户选择需要通知紧急联系人，以通知相关亲人或朋友来帮助，则生成提醒请求。根据提醒请求将该用户的地址信息、时间信息、风险信息(包括对应用户的第一酒精代谢等级、第一酒精浓度数据等信息)发送至预先设置的紧急通讯地址，以提醒相关亲人或朋友，以便于相关亲人或朋友根据环境异常提示信息对用户做出对应的帮助，从而提高用户的安全性和使用体验感。其中，预先设置的紧急通讯地址为紧急联系人的通讯地址，且通讯地址包括QQ信息、微信账号、手机号码等。
参照图8，本申请实施例还提供了另一种酒精代谢检测方法，该酒精代谢检测方法应用于客户端，客户端用于与可穿戴设备通信连接，可穿戴设备用于采集第一酒精浓度数据。该酒精代谢检测方法包括步骤：
S810、从可穿戴设备获取第一酒精浓度数据；
S820、将第一酒精浓度数据发送给服务端，以使服务端执行如上述任一实施例所描述的酒精代谢检测方法。
参照图9，在一些实施例中，该酒精代谢检测方法还包括步骤：
S910、获取采样间隔；
S920、根据采样间隔生成获取信号，并将获取信号发送给可穿戴设备；
S930、获取可穿戴设备根据获取信号返回的第二酒精浓度数据；
S940、将第二酒精浓度数据发送给服务端。
可见，上述应用于服务端的酒精代谢检测方法实施例中的内容均适用于本应用于客户端的酒精代谢检测方法的实施例中，本应用于客户端的酒精代谢检测方法实施例所具体实现的功能与上述应用于服务端的酒精代谢检测方法实施例相同，并且达到的有益效果与上述应用于服务端的酒精代谢检测方法实施例所达到的有益效果也相同。
本申请实施例还提供了一种计算机设备，该计算机设备包括：至少一个处理器，以及与至少一个处理器通信连接的存储器。其中，存储器存储有指令，指令被至少一个处理器执行，以使至少一个处理器执行该指令时实现如上述任一实施例所描述的应用于服务端的酒精代谢检测方法或应用于客户端的酒精代谢等级计算。
本申请实施例提供了一种计算机可读存储介质，存储有计算机可执行指令，计算机可执行指令用于：执行上述任一实施例所描述的应用于服务端的酒精代谢检测方法或应用于客户端的酒精代谢检测方法。
以上所描述的装置实施例仅仅是示意性的，其中作为分离部件说明的单元可以是或者也可以不是物理上分开的，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。
本申请实施例还提供了一种可穿戴设备，可穿戴设备包括：存储器、处理器、存储在存储器上并可在处理器上运行的程序以及用于实现处理器和存储器之间的连接通信的数据总线，程序被处理器执行时实现上述酒精浓度检测方法。该可穿戴设备可以为包括智能手表、智能手环、智能眼镜和智能服饰等任意智能终端。
参照图10，图10示意了另一实施例的可穿戴设备的硬件结构，可穿戴设备包括：
处理器1001，可以采用通用的CPU(Central ProcessingUnit，中央处理器)、微处理器、应用专用集成电路(ApplicationSpecificIntegratedCircuit，ASIC)、或者一个或多个集成电路等方式实现，用于执行相关程序，以实现本申请实施例所提供的技术方案；
存储器1002，可以采用只读存储器(ReadOnlyMemory，ROM)、静态存储设备、动态存储设备或者随机存取存储器(RandomAccessMemory，RAM)等形式实现。存储器1002可以存储操作系统和其他应用程序，在通过软件或者固件来实现本说明书实施例所提供的技术方案时，
相关的程序代码保存在存储器1002中，并由处理器1001来调用执行本申请实施例的酒精浓度检测方法；
输入/输出接口1003，用于实现信息输入及输出；
通信接口1004，用于实现本设备与其他设备的通信交互，可以通过有线方式(例如USB、网线等)实现通信，也可以通过无线方式(例如移动网络、WIFI、蓝牙等)实现通信；
总线1005，在设备的各个组件(例如处理器1001、存储器1002、输入/输出接口1003和通信接口1004)之间传输信息；
其中处理器1001、存储器1002、输入/输出接口1003和通信接口1004通过总线1005实现彼此之间在设备内部的通信连接。
本申请实施例还提供了一种存储介质，存储介质为计算机可读存储介质，用于计算机可读存储，存储介质存储有一个或者多个程序，一个或者多个程序可被一个或者多个处理器执行，以实现上述酒精浓度检测方法。
存储器作为一种非暂态计算机可读存储介质，可用于存储非暂态软件程序以及非暂态性计算机可执行程序。此外，存储器可以包括高速随机存取存储器，还可以包括非暂态存储器，例如至少一个磁盘存储器件、闪存器件、或其他非暂态固态存储器件。在一些实施方式中，存储器可选包括相对于处理器远程设置的存储器，这些远程存储器可以通过网络连接至该处理器。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
应当理解，在本申请中，“至少一个(项)”是指一个或者多个，“多个”是指两个或两个以上。“和/或”，用于描述关联对象的关联关系，表示可以存在三种关系，例如，“A和/或B”可以表示：只存在A，只存在B以及同时存在A和B三种情况，其中A，B可以是单数或者复数。字符“/”一般表示前后关联对象是一种“或”的关系。“以下至少一项(个)”或其类似表达，是指这些项中的任意组合，包括单项(个)或复数项(个)的任意组合。例如，a，b或c中的至少一项(个)，可以表示：a，b，c，“a和b”，“a和c”，“b和c”，或“a和b和c”，其中a，b，c可以是单个，也可以是多个。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，上述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
上述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括多指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例的方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，简称ROM)、随机存取存储器(Random Access Memory，简称RAM)、磁碟或者光盘等各种可以存储程序的介质。
以上参照附图说明了本申请实施例的优选实施例，并非因此局限本申请实施例的权利范围。本领域技术人员不脱离本申请实施例的范围和实质内所作的任何修改、等同替换和改进，均应在本申请实施例的权利范围之内。
Claims (10)
- 酒精代谢检测方法，其特征在于，所述方法应用于服务端，所述方法包括：从客户端获取第一酒精浓度数据；根据多个所述第一酒精浓度数据得到目标酒精代谢速度；其中，所述目标酒精代谢速度用于表征酒精代谢能力；从所述客户端获取基础信息，根据所述基础信息和所述目标酒精代谢速度得到第一提示信号；其中，所述基础信息包括饮酒类型、饮酒品牌、酒精浓度、饮酒量、空腹状态、进食量、喝水量、喝水状态、性别、体重、年龄中的至少一种。
- 根据权利要求1所述的酒精代谢检测方法，其特征在于，所述根据多个所述第一酒精浓度数据得到目标酒精代谢速度，包括：对多个所述第一酒精浓度数据进行数据清洗操作，以得到样本数据集；将所述样本数据集中满足预设条件的多个所述第一酒精浓度数据作为测试数据集；对所述测试数据集中的多个所述第一酒精浓度数据进行拟合处理，得到标定酒精代谢速度；将所述标定酒精代谢速度与预设酒精代谢速度进行比较，根据比较结果对所述标定酒精代谢速度进行处理，并得到所述目标酒精代谢速度。
- 根据权利要求2所述的酒精代谢检测方法，其特征在于，所述将所述样本数据集中满足预设条件的多个所述第一酒精浓度数据作为测试数据集，包括：将所述样本数据集中的N个所述第一酒精浓度数据作为标定数据集；其中，N为大于2的正整数；获取所述标定数据集中的最大酒精数据和最终酒精数据；若所述最大酒精数据和所述最终酒精数据间隔预设数量的所述第一酒精浓度数据，且所述最终酒精数据小于预设阈值或所述标定数据集中所有所述第一酒精浓度数据的采样总时长大于预设时长，则将所述标定数据集作为所述测试数据集。
- 根据权利要求1所述的酒精代谢检测方法，其特征在于，在所述根据多个所述第一酒精浓度数据得到酒精代谢速度之前，所述方法还包括：根据所述第一酒精浓度数据得到采样间隔，将所述采样间隔发送给客户端；获取所述客户端根据所述采样间隔返回的第二酒精浓度数据。
- 根据权利要求1至4任一项所述的酒精代谢检测方法，其特征在于，还包括：根据所述酒精代谢速度和预设安全时长得到预警值；将所述预警值发送给客户端。
- 根据权利要求1至4任一项所述的酒精代谢检测方法，其特征在于，还包括：根据所述酒精代谢速度得到第一酒精代谢等级；根据多个所述第一酒精代谢等级得到比对等级；获取第二酒精代谢等级，若第二酒精代谢等级小于所述比对等级，则生成第二提示信号。
- 酒精代谢检测方法，其特征在于，所述方法应用于客户端，所述客户端用于与可穿戴设备通信连接，所述可穿戴设备用于采集第一酒精浓度数据，所述方法包括：从所述可穿戴设备获取所述第一酒精浓度数据；将所述第一酒精浓度数据发送给服务端，以使所述服务端执行如权利要求1至6任一项所述的酒精代谢检测方法。
- 根据权利要求7所述的酒精代谢检测方法，其特征在于，还包括：获取采样间隔；根据所述采样间隔生成获取信号，并将所述获取信号发送给所述可穿戴设备；获取所述可穿戴设备根据所述获取信号返回的第二酒精浓度数据；将所述第二酒精浓度数据发送给所述服务端。
- 一种计算机设备，其特征在于，所述计算机设备包括存储器和处理器，其中，所述存储器中存储有计算机程序，所述计算机程序被所述处理器执行时所述处理器用于执行：如权利要求1至6中任一项所述的酒精代谢检测方法；或，如权利要求7或8所述的酒精代谢检测方法。
- 一种存储介质，所述存储介质为计算机可读存储介质，其特征在于，所述计算机可读存储有计算机程序，在所述计算机程序被计算机执行时，所述计算机用于执行：如权利要求1至6中任一项所述的酒精代谢检测方法；或，如权利要求7或8所述的酒精代谢检测方法。
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| 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 (zh) * | 2016-04-22 | 2016-09-07 | 深圳还是威健康科技有限公司 | 测量酒精浓度的可穿戴设备及其方法 |
| CN111272988A (zh) * | 2020-02-27 | 2020-06-12 | 广州逆熵电子科技有限公司 | 一种酒精浓度预测方法、系统及酒精降解评估仪 |
| CN211022622U (zh) * | 2019-06-03 | 2020-07-17 | 陕西理工大学 | 一种新型酒精检测提醒腕带 |
| CN111671408A (zh) * | 2020-07-07 | 2020-09-18 | 方滨 | 一种用户饮酒安全监护方法、用户终端、服务器 |
| CN115024690A (zh) * | 2022-04-24 | 2022-09-09 | 深圳市华盛昌科技实业股份有限公司 | 酒精代谢检测方法、计算机设备及存储介质 |
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Patent Citations (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 (zh) * | 2016-04-22 | 2016-09-07 | 深圳还是威健康科技有限公司 | 测量酒精浓度的可穿戴设备及其方法 |
| CN211022622U (zh) * | 2019-06-03 | 2020-07-17 | 陕西理工大学 | 一种新型酒精检测提醒腕带 |
| CN111272988A (zh) * | 2020-02-27 | 2020-06-12 | 广州逆熵电子科技有限公司 | 一种酒精浓度预测方法、系统及酒精降解评估仪 |
| CN111671408A (zh) * | 2020-07-07 | 2020-09-18 | 方滨 | 一种用户饮酒安全监护方法、用户终端、服务器 |
| CN115024690A (zh) * | 2022-04-24 | 2022-09-09 | 深圳市华盛昌科技实业股份有限公司 | 酒精代谢检测方法、计算机设备及存储介质 |
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