Kano-FAST-FBS model fused elderly intelligent medicine box design method and system

Abstract

The invention discloses a Kano-FAST-FBS model fused elderly intelligent medicine box design method and system, and the method comprises the steps: obtaining a plurality of medicine demands of elderly users, carrying out the classification and priority sorting of the plurality of medicine demands through a Kano model, and determining the basic medicine demands according to the sorting result; basic medication requirements are converted into basic functions through an FAST model, and the basic functions are decomposed into multiple basic sub-functions according to decomposition characteristics; performing function-behavior-structure relation mapping on the basic sub-functions through an FBS model, determining a system design path and a medicine box basic structure according to a mapping result, generating a design scheme according to the system design path and the medicine box basic structure, generating a product model according to the design scheme, verifying the product model, and obtaining a final design finished product according to a verification result. The medicine taking requirements of the elderly can be accurately captured and converted into the function and structural design of the medicine box, the scientificity and applicability of the product are improved, and therefore the medicine taking experience is effectively improved, and the health risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of medicine box design, and in particular to an intelligent medicine box design method and system for the elderly population integrating the Kano-FAST-FBS model. Background Art

[0002] At present, with the accelerating global aging process, the coexistence of chronic diseases and multiple diseases in the elderly population has become more and more common, and the demand for drug management has increased accordingly. Research shows that the problems of multiple diseases coexisting and polypharmacy in the elderly are becoming increasingly prominent, and the risks of missed doses, wrong doses and drug interactions are also relatively high, which has hindered the control and treatment of the condition. Whether to take medicine correctly is of great significance to the treatment of the elderly's chronic diseases. At present, the research on intelligent medicine boxes mainly focuses on technical implementation and function design, especially in aspects such as based on STM32 single-chip microcontrollers and Internet of Things technology, and functions such as drug reminder, storage management and automatic distribution have been realized to solve the medication problems of the elderly population. However, existing intelligent medicine box products generally lack in-depth analysis of user needs in the design process, and there is a certain disconnect between product functions and actual needs. Therefore, how to accurately capture and transform user needs has become a key issue in the design of intelligent medicine boxes. Summary of the Invention

[0003] In view of the problems shown above, the present invention provides an intelligent medicine box design method and system for the elderly population integrating the Kano-FAST-FBS model to solve the problems that existing intelligent medicine box products generally lack in-depth analysis of user needs in the design process and there is a certain disconnect between product functions and actual needs mentioned in the background art.

[0004] An intelligent medicine box design method for the elderly population integrating the Kano-FAST-FBS model includes the following steps:

[0005] Obtain multiple medication needs of elderly users, classify and prioritize the multiple medication needs through the Kano model, and determine the basic medication needs according to the sorting results;

[0006] Convert the basic medication needs into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics;

[0007] Map the relationship between function, behavior and structure for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping results;

[0008] Generate a design plan according to the system design path and the basic structure of the medicine box, generate a product model according to the design plan and verify the product model, and obtain the final design product according to the verification results.

[0009] Preferably, to obtain multiple medication requirements of elderly users, classify and prioritize the multiple medication requirements through the Kano model, and determine the basic medication requirements according to the ranking results, including:

[0010] Obtain multiple medication requirements of elderly users and the user requirement attributes of each medication requirement through questionnaire surveys or user interviews;

[0011] Formulate multiple requirement characteristics and determine the membership degree of each requirement characteristic for each user requirement attribute through questionnaire surveys;

[0012] Through the Kano model, determine the response intensity of users for each user requirement attribute according to the membership degree of each requirement characteristic for each user requirement attribute, prioritize the multiple medication requirements according to the response intensity, and classify the user requirement attributes with the same requirement characteristics;

[0013] Identify the first N medication requirements in the ranking results as the basic medication requirements of elderly users.

[0014] Preferably, transform the basic medication requirements into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics, including:

[0015] Through the FAST model, determine the requirement domain of elderly users according to the basic medication requirements, determine the functional application parameters of the requirement domain, and determine the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters of the requirement domain according to the functional application parameters;

[0016] Determine the key functional domain according to the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters, obtain the functional description parameters of the key functional domain, and determine the basic functions of the medicine box according to the functional description parameters;

[0017] Obtain the functional combination logic parameters of each basic function of the medicine box, and determine the functional chain according to the functional combination logic parameters;

[0018] Based on the functional chain, determine the upper and lower functional relationship parameters of each basic function of the medicine box, and decompose the basic function into multiple basic sub-functions according to the upper and lower functional relationship parameters.

[0019] Preferably, map the relationship between function-behavior-structure for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping results, including:

[0020] Through the FBS model, perform F-B mapping on the basic sub-functions to obtain the behavior domain, and perform B-S mapping on the behavior domain to obtain the product structure domain;

[0021] Obtain multiple product sub - structures according to the product domain, and determine the system design path based on the technical features and structural principles of each product sub - structure;

[0022] Analyze the technical features and structural principles of each product sub - structure, and determine the structure aggregation boundary parameters according to the analysis results;

[0023] Optimize and aggregate multiple product sub - structures based on the structure aggregation boundary parameters to obtain the basic structure of the medicine box.

[0024] Preferably, generate a design plan according to the system design path and the basic structure of the medicine box, generate a product model according to the design plan and verify the product model, and obtain the final design product according to the verification results, including:

[0025] Generate structural design parameters according to the system design path and the basic structure of the medicine box, and obtain the preference parameters of elderly users for the shape, color and material of the medicine box;

[0026] Generate appearance design parameters according to the preference parameters, and perform integration processing based on the structural design parameters and the appearance design parameters to generate a design plan;

[0027] Generate a virtual 3D product model and a usage principle video according to the design plan, generate multiple product characteristic evaluation indicators, and comprehensively evaluate the design plan according to the multiple product characteristic evaluation indicators, the virtual 3D product model and the usage principle video;

[0028] Determine the items to be optimized according to the scoring results, optimize the design plan based on the items to be optimized to obtain an optimized plan, and obtain the final design product according to the optimized plan.

[0029] An intelligent medicine box design system for the elderly group integrating the Kano - FAST - FBS model, the system includes:

[0030] The first determination module is used to obtain multiple medication requirements of elderly users, classify and prioritize the multiple medication requirements through the Kano model, and determine the basic medication requirements according to the sorting results;

[0031] The decomposition module is used to transform the basic medication requirements into basic functions through the FAST model, and decompose the basic functions into multiple basic sub - functions according to the decomposition characteristics;

[0032] The second determination module is used to map the relationship between function - behavior - structure for the basic sub - functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping results;

[0033] A generation module, configured to generate a design plan according to a system design path and a basic structure of a medicine box, generate a product model according to the design plan and verify the product model, and obtain a final designed product according to a verification result.

[0034] Preferably, the first determination module includes:

[0035] An acquisition sub-module, configured to acquire multiple medication requirements of elderly users and user requirement attributes of each medication requirement through a questionnaire survey or user interviews.

[0036] A first determination sub-module, configured to formulate multiple requirement characteristics and determine the membership degree of each requirement characteristic to each user requirement attribute through a questionnaire survey.

[0037] A classification sub-module, configured to determine the reaction intensity of users to each user requirement attribute according to the membership degree of each requirement characteristic to each user requirement attribute through the Kano model, rank the multiple medication requirements according to the reaction intensity, and classify the user requirement attributes with the same requirement characteristic.

[0038] A confirmation sub-module, configured to confirm the first N medication requirements in the ranking result as the basic medication requirements of elderly users.

[0039] Preferably, the decomposition module includes:

[0040] A second determination sub-module, configured to determine the requirement domain of elderly users according to the basic medication requirements through the FAST model, determine the functional application parameters of the requirement domain, and determine the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters of the requirement domain according to the functional application parameters.

[0041] A third determination sub-module, configured to determine a key functional domain according to the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters, obtain the functional description parameters of the key functional domain, and determine the basic functions of the medicine box according to the functional description parameters.

[0042] A fourth determination sub-module, configured to obtain the functional combination logic parameters of each basic function of the medicine box and determine a functional chain according to the functional combination logic parameters.

[0043] A decomposition sub-module, configured to determine the superior and inferior functional relationship parameters of each basic function of the medicine box based on the functional chain, and decompose the basic functions into multiple basic sub-functions according to the superior and inferior functional relationship parameters.

[0044] Preferably, the second determination module includes:

[0045] A mapping sub-module, configured to perform F-B mapping on the basic sub-functions through the FBS model to obtain a behavior domain, and perform B-S mapping on the behavior domain to obtain a product structure domain.

[0046] The fifth determination sub-module is configured to obtain a plurality of product sub-structures according to the product structure domain, and determine the system design path based on the technical features and structural principles of each product sub-structure;

[0047] The sixth determination sub-module is configured to analyze the technical features and structural principles of each product sub-structure, and determine the structure aggregation boundary parameters according to the analysis results;

[0048] The optimization aggregation sub-module is configured to perform optimization aggregation on a plurality of product sub-structures based on the structure aggregation boundary parameters to obtain the basic structure of the medicine box.

[0049] Preferably, the generation module includes:

[0050] The first generation sub-module is configured to generate structure design parameters according to the system design path and the basic structure of the medicine box, and obtain the preference parameters of the elderly users for the shape, color, and material of the medicine box;

[0051] The second generation sub-module is configured to generate appearance design parameters according to the preference parameters, and perform integration processing based on the structure design parameters and the appearance design parameters to generate a design scheme;

[0052] The evaluation sub-module is configured to generate a virtual 3D product model and a usage principle video according to the design scheme, generate a plurality of product characteristic evaluation indicators, and comprehensively evaluate the design scheme according to the virtual 3D product model and the usage principle video through the plurality of product characteristic evaluation indicators;

[0053] The optimization sub-module is configured to determine the items to be optimized according to the scoring results, optimize the design scheme based on the items to be optimized to obtain an optimized scheme, and obtain the final design finished product according to the optimized scheme.

[0054] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in the written specification and the drawings.

[0055] The technical solutions of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0056] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention.

[0057] Figure 1 It is a working flow chart of a design method for an intelligent medicine box for the elderly population that integrates the Kano-FAST-FBS model provided by the present invention;

[0058] Figure 2 Another workflow diagram of the design method of an intelligent medicine box for the elderly group integrating the Kano-FAST-FBS model provided by the present invention;

[0059] Figure 3 Schematic structural diagram of a design system of an intelligent medicine box for the elderly group integrating the Kano-FAST-FBS model provided by the present invention;

[0060] Figure 4 Schematic structural diagram of the generation module in a design system of an intelligent medicine box for the elderly group integrating the Kano-FAST-FBS model provided by the present invention. Detailed implementation manners

[0061] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Among the following exemplary embodiments, the described implementation manners do not represent all implementation manners consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0062] At present, with the acceleration of the global aging process, the coexistence of chronic diseases and multiple diseases in the elderly group has become more and more common, and the demand for drug management has increased accordingly. Research shows that the problems of coexistence of multiple diseases and multiple drug use in the elderly are becoming increasingly prominent, and the risks of missed doses, wrong doses, and drug interactions are relatively large, which has hindered the control and treatment of the condition. Whether to take medicine correctly is of great significance for the treatment of the elderly's chronic diseases. At present, the research on intelligent medicine boxes mainly focuses on technical implementation and functional design, especially in aspects based on STM32 single-chip microcomputers, Internet of Things technology, etc., and functions such as drug reminder, storage management, and automatic distribution have been realized to solve the drug use problems of the elderly group. However, in the design process of existing intelligent medicine box products, there is generally a lack of in-depth analysis of user needs, and there is a certain disconnection between product functions and actual needs. Therefore, how to accurately capture and transform user needs has become a key issue in the design of intelligent medicine boxes. To solve the above problems, this embodiment discloses a design method of an intelligent medicine box for the elderly group integrating the Kano-FAST-FBS model.

[0063] A design method of an intelligent medicine box for the elderly group integrating the Kano-FAST-FBS model, as Figure 1 shown, includes the following steps:

[0064] Step S101, obtain multiple medication needs of elderly users, classify and prioritize the multiple medication needs through the Kano model, and determine the basic medication needs according to the sorting results;

[0065] Step S102: Convert the basic medication requirements into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics;

[0066] Step S103: Map the relationships between functions, behaviors, and structures for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping results;

[0067] Step S104: Generate a design plan according to the system design path and the basic structure of the medicine box, generate a product model according to the design plan and verify the product model, and obtain the final design product according to the verification results.

[0068] In this embodiment, multiple medication requirements are expressed as multiple requirements of elderly users during the medication process, such as: medication reminder, drug classification, etc.;

[0069] The working principle of the above technical solution is: Obtain multiple medication requirements of elderly users, classify and prioritize the multiple medication requirements through the Kano model, and determine the basic medication requirements according to the ranking results; convert the basic medication requirements into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics; map the relationships between functions, behaviors, and structures for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping results; generate a design plan according to the system design path and the basic structure of the medicine box, generate a product model according to the design plan and verify the product model, and obtain the final design product according to the verification results.

[0070] The beneficial effects of the above technical solution are: By integrating the KanO-FAST-FBS model, an integrated innovation design method for intelligent medicine boxes is proposed, which can accurately capture the medication requirements of the elderly population, transform them into the functional and structural design of the medicine box, improve the scientificity and applicability of the product, thereby effectively improving the medication experience, reducing health risks, and solving the problem that existing intelligent medicine box products generally lack in-depth analysis of user needs and there is a certain disconnection between product functions and actual needs in the design process of the existing technology.

[0071] In this embodiment, after determining the basic medication requirements, it further includes:

[0072] Determine the operation elements and functional attributes of each basic medication requirement, and construct an operation network based on the operation elements and functional attributes, where the operation elements of the same type of function share one operation node;

[0073] Randomly screen multiple pieces of historical usage data of the elderly for the intelligent medicine box through the operation network, perform operation node matching on the historical usage data, and obtain the matching results;

[0074] Determine the necessary function attributes and the expected function attributes according to the matching results, and obtain the classification operation elements in the operation nodes corresponding to the necessary function attributes and the expected function attributes;

[0075] Obtaining a response level description parameter and a response state description parameter of each classification operation element, and determining a response effect evaluation parameter of each classification operation element based on the response level description parameter and the response state description parameter;

[0076] Determine the evaluation baseline level based on the response effect evaluation parameters of each classified operation element, and determine the operational level requirements of each classified operation element based on the evaluation baseline level;

[0077] Determine the average user response load and the average user response probability of each classified operation element according to the operation level requirement of each classified operation element;

[0078] Evaluate the demand response potential of each classified operation element based on the average user response load and average user response probability of each classified operation element;

[0079] Determine the functional contribution value of each classified operation element according to the demand response potential of each classified operation element and the response quality of the operation result of the classified operation element;

[0080] Determine the retention attributes of each classified operation element based on the functional contribution value, wherein the retention attributes include: must be retained, recommended to be retained, with a small probability of being retained, and no need to be retained;

[0081] Screening out the first basic medication requirement that is determined to be in a retention state and the second basic medication requirement that is determined to be in a non-retention state according to the retention attribute of each classification operation element;

[0082] The first basic medication requirement is used as the reference medication requirement for basic function transformation.

[0083] The beneficial effects of the above technical solution are: by dividing the basic medication needs according to functional uniformity to screen out the final retained medication needs and preferred medication needs, it can not only ensure the simplicity of control of the user's operation level but also maximize the reduction of the user's usage load, thereby improving practicality and user experience.

[0084] In one embodiment, the step of obtaining multiple medication needs of an elderly user, classifying and prioritizing the multiple medication needs using a Kano model, and determining basic medication needs based on the ranking results includes:

[0085] Obtain multiple medication needs of elderly users and the user demand attributes of each medication need through questionnaire surveys or user interviews;

[0086] Formulate multiple demand characteristics and determine the membership degree of each demand characteristic for each user demand attribute through a questionnaire survey;

[0087] According to the Kano model, determine the reaction intensity of users for each user demand attribute based on the membership degree of each demand characteristic for each user demand attribute, prioritize multiple medication demands according to the reaction intensity, and classify the user demand attributes with the same demand characteristic;

[0088] Identify the top N medication demands in the sorting result as the basic medication demands of elderly users.

[0089] In this embodiment, multiple demand characteristics include: basic demands, expected demands, indifferent demands, reverse demands, etc.;

[0090] In this embodiment, N can be 5.

[0091] The beneficial effects of the above technical solution are: By calculating the membership degree and then prioritizing the medication demands, reasonable medication demands can be selected according to the emotional rejection and acceptance of elderly users, ensuring reliability and adaptability.

[0092] In this embodiment, each demand characteristic can be expressed as R, where R = (r1, r2, r3, r4, r5), and r1 to r5 respectively represent the membership degrees of each demand characteristic for multiple user demand attributes. The membership degree rij is

[0093]

[0094] where f ij represents the frequency of demand classification of all surveyed users under the i-th user demand characteristic, and j represents the number of surveyed demand characteristics;

[0095] In this embodiment, according to the Kano model, determining the reaction intensity of users for each user demand attribute based on the membership degree of each demand characteristic for each user demand attribute includes:

[0096] According to the Kano model, determine the first influence degree of users for having each user demand attribute and the second influence degree of users for not having each user demand attribute based on the membership degree of each demand characteristic for each user demand attribute;

[0097] Determine the satisfaction coefficient and dissatisfaction coefficient of users for each user demand attribute according to the first influence degree and the second influence degree;

[0098] Determine the demand sensitivity of users for each user demand attribute according to the satisfaction coefficient and the dissatisfaction coefficient;

[0099] Quantify the demand sensitivity to determine the response intensity of users to each user demand attribute.

[0100] In this embodiment, the satisfaction coefficient and the dissatisfaction coefficient are respectively:

[0101]

[0102] Among them, S i represents the influence degree of user satisfaction when having a certain demand attribute, and DS i represents the influence degree of user satisfaction when not having a certain demand attribute. The value of the satisfaction coefficient is proportional to the satisfaction of user demands. The larger the absolute value, the higher the user satisfaction or dissatisfaction;

[0103] Combine the user's satisfaction and dissatisfaction to obtain the demand sensitivity:

[0104]

[0105] The beneficial effects of the above technical solution are as follows: By introducing the satisfaction coefficient for evaluation, it is possible to more intuitively and quantitatively determine the response intensity of users to each user demand attribute, ensuring the objectivity and rationality of the evaluation.

[0106] In one embodiment, as Figure 2 shown, the basic medication needs are transformed into basic functions through the FAST model, and the basic functions are decomposed into multiple basic sub-functions according to the decomposition characteristics, including:

[0107] Step S201: Determine the demand domain of elderly users according to the basic medication needs through the FAST model, determine the function application parameters of the demand domain, and determine the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters of the demand domain according to the function application parameters;

[0108] Step S202: Determine the key function domain according to the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters, obtain the function description parameters of the key function domain, and determine the basic functions of the medicine box according to the function description parameters;

[0109] Step S203: Obtain the function combination logic parameters of each basic function of the medicine box, and determine the function chain according to the function combination logic parameters;

[0110] Step S204: Determine the superior and inferior function relationship parameters of each basic function of the medicine box based on the function chain, and decompose the basic functions into multiple basic sub-functions according to the superior and inferior function relationship parameters.

[0111] In this embodiment, the demand domains of elderly users can be divided into four categories: basic demands, attractive demands, expected demands, and indifferent demands. Among them, the basic demands include: (automatic medicine dispensing, power reminder, timing reminder, emergency contact, remaining quantity reminder, safety lock); the expected demands include: (medicine taking confirmation, adjustable volume, convenient operation, intuitive interaction interface, notification of missed doses, information sharing); the attractive demands include: (remote control, personalized reminder); the indifferent demands include: (real-time monitoring, voice guidance).

[0112] After abstracting, classifying, and mapping the demand domains, they are transformed into function domains: The function domain corresponding to the basic demands is: F1 = Comprehensive Reminder = (timing reminder, power reminder, remaining quantity reminder, personalized reminder, notification of missed doses, adjustable volume);

[0113] The function domain corresponding to the expected demands is: F2 = Automatic Medicine Dispensing = (medicine storage, automatic dispensing);

[0114] The function domain corresponding to the attractive demands is: F3 = Safety System = (safety lock, emergency contact, medicine taking confirmation);

[0115] The function domain corresponding to the indifferent demands is: F4 = Intelligent Interaction = (information sharing, intuitive interaction interface, remote control, convenient operation).

[0116] The structure domain of the intelligent medicine box is obtained by solving the F-B-S mapping, where:

[0117] The structure domain corresponding to the basic demands is: S1 = (LED indicator, speaker, power monitoring module, sensing device, control system, storage module, touch screen interface, user-end APP);

[0118] The function domain corresponding to the expected demands is: S2 = (modular medicine dispensing tube, rotating cylinder, user-end APP, control system, rotating mechanism, medicine pushing device, temporary medicine storage bin);

[0119] The function domain corresponding to the attractive demands is: S3 = (medicine box cover, electronic control lock, temporary medicine storage bin, sensing device, user-end APP, storage module, control system, communication module, emergency button, touch screen interface);

[0120] The function domain corresponding to the indifferent demands is: S4 = (communication module, user-end APP, control system, touch screen interface);

[0121] By mapping each function - behavior - structure, the complex functions of the intelligent medicine box for the elderly group can be effectively split, which is convenient for design, implementation, and optimization, thereby improving the practicality and safety of the intelligent medicine box among elderly users.

[0122] The beneficial effects of the above technical solution are as follows: By performing function decomposition, the large function can be decomposed into multiple basic sub-functions for the function setting of the medicine box, ensuring the user experience and practicality.

[0123] In one embodiment, the relationship mapping between function, behavior, and structure is carried out for the basic sub-functions through the FBS model, and the system design path and the basic structure of the medicine box are determined according to the mapping results, including:

[0124] Perform F-B mapping on the basic sub-functions through the FBS model to obtain the behavior domain, and perform B-S mapping on the behavior domain to obtain the product structure domain;

[0125] Obtain multiple product sub-structures according to the product structure domain, and determine the system design path according to the technical features and structural principles of each product sub-structure;

[0126] Analyze the technical features and structural principles of each product sub-structure, and determine the structure aggregation boundary parameters according to the analysis results;

[0127] Optimize and aggregate multiple product sub-structures based on the structure aggregation boundary parameters to obtain the basic structure of the medicine box.

[0128] The beneficial effects of the above technical solution are as follows: By optimizing and aggregating multiple product sub-structures to obtain the basic structure of the medicine box, the aggregation evaluation of the product structure can be carried out according to the structure aggregation conditions, which can not only ensure the structural practicality and aesthetics of the designed medicine box product, but also avoid the use conflicts of multiple functions, maximizing the practicality and reliability of the medicine box.

[0129] In one embodiment, generate a design plan according to the system design path and the basic structure of the medicine box, generate a product model according to the design plan and verify the product model, and obtain the final design product according to the verification results, including:

[0130] Generate structural design parameters according to the system design path and the basic structure of the medicine box, and obtain the preference parameters of elderly users for the shape, color, and material of the medicine box;

[0131] Generate appearance design parameters according to the preference parameters, and perform integration processing based on the structural design parameters and the appearance design parameters to generate a design plan;

[0132] Generate a virtual 3D product model and a usage principle video according to the design plan, generate multiple product characteristic evaluation indicators, and comprehensively evaluate the design plan according to the virtual 3D product model and the usage principle video through the multiple product characteristic evaluation indicators;

[0133] Determine the items to be optimized according to the scoring results, optimize the design plan based on the items to be optimized to obtain an optimized plan, and obtain the final design product according to the optimized plan.

[0134] In this embodiment, multiple product feature evaluation indicators may be: functionality, safety, interactivity, practicality, aesthetics, and innovation.

[0135] The beneficial effects of the above technical solution are as follows: By determining the appearance design parameters and structural design parameters to generate a design solution, it can not only ensure the acceptability of the structure by users but also take into account the appearance selection, further improving the usage experience of elderly users.

[0136] In one embodiment, this embodiment also discloses an intelligent medicine box design system for the elderly group integrating the Kano-FAST-FBS model, as Figure 3 shown. The system includes:

[0137] A first determination module 301, configured to obtain multiple medication needs of elderly users, classify and prioritize the multiple medication needs through the Kano model, and determine the basic medication needs according to the sorting result;

[0138] A decomposition module 302, configured to convert the basic medication needs into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics;

[0139] A second determination module 303, configured to perform a relationship mapping between function-behavior-structure for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping result;

[0140] A generation module 304, configured to generate a design solution according to the system design path and the basic structure of the medicine box, generate a product model according to the design solution and verify the product model, and obtain the final design finished product according to the verification result.

[0141] The working principle and beneficial effects of the above technical solution have been described in the method embodiment, and will not be elaborated here.

[0142] In one embodiment, the first determination module includes:

[0143] An acquisition sub-module, configured to obtain multiple medication needs of elderly users and the user need attributes of each medication need through questionnaire surveys or user interviews;

[0144] A first determination sub-module, configured to formulate multiple demand characteristics and determine the membership degree of each demand characteristic to each user need attribute through questionnaire surveys;

[0145] A classification sub-module, configured to determine the response intensity of a user to each user requirement attribute according to the membership degree of each requirement feature to each user requirement attribute through the Kano model, prioritize multiple medication requirements according to the response intensity, and classify user requirement attributes with the same requirement feature;

[0146] A confirmation sub-module, configured to confirm the first N medication requirements in the sorting result as the basic medication requirements of elderly users.

[0147] In one embodiment, the decomposition module includes:

[0148] A second determination sub-module, configured to determine the requirement domain of an elderly user through the FAST model according to the basic medication requirements, determine the functional application parameters of the requirement domain, and determine the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters of the requirement domain according to the functional application parameters;

[0149] A third determination sub-module, configured to determine the key functional domain according to the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters, obtain the functional description parameters of the key functional domain, and determine the basic functions of the medicine box according to the functional description parameters;

[0150] A fourth determination sub-module, configured to obtain the functional combination logic parameters of each basic function of the medicine box, and determine the functional chain according to the functional combination logic parameters;

[0151] A decomposition sub-module, configured to determine the superior and inferior function relationship parameters of each basic function of the medicine box based on the functional chain, and decompose the basic function into multiple basic sub-functions according to the superior and inferior function relationship parameters.

[0152] In one embodiment, the second determination module includes:

[0153] A mapping sub-module, configured to perform F-B mapping on the basic sub-functions through the FBS model to obtain the behavior domain, and perform B-S mapping on the behavior domain to obtain the product structure domain;

[0154] A fifth determination sub-module, configured to obtain multiple product sub-structures according to the product structure domain, and determine the system design path according to the technical features and structural principles of each product sub-structure;

[0155] A sixth determination sub-module, configured to analyze the technical features and structural principles of each product sub-structure, and determine the structure aggregation boundary parameters according to the analysis results;

[0156] An optimization aggregation sub-module, configured to perform optimization aggregation on multiple product sub-structures based on the structure aggregation boundary parameters to obtain the basic structure of the medicine box.

[0157] In one embodiment, as Figure 4 shown, the generation module 304 includes:

[0158] The first generation sub-module 3041 is used to generate structure design parameters according to the system design path and the basic structure of the medicine box, and obtain the preference parameters of elderly users for the shape, color, and material of the medicine box;

[0159] The second generation sub-module 3042 is used to generate appearance design parameters according to the preference parameters, and perform integration processing based on the structure design parameters and the appearance design parameters to generate a design scheme;

[0160] The scoring sub-module 3043 is used to generate a virtual 3D product model and a usage principle video according to the design scheme, generate multiple product characteristic evaluation indicators, and comprehensively score the design scheme according to the virtual 3D product model and the usage principle video through the multiple product characteristic evaluation indicators;

[0161] The optimization sub-module 3044 is used to determine the items to be optimized according to the scoring results, optimize the design scheme based on the items to be optimized to obtain an optimized scheme, and obtain the final design finished product according to the optimized scheme.

[0162] Those skilled in the art should understand that the first and second in the present invention refer to different application stages.

[0163] After considering the specification and practicing the disclosure herein, those skilled in the art will readily conceive of other embodiments of the present disclosure. This application is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and examples are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0164] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A design method of an intelligent medicine box for the elderly that integrates the Kano-FAST-FBS model, characterized in that, Including the following steps: Obtain multiple medication needs of elderly users, classify and prioritize the multiple medication needs through the Kano model, and determine the basic medication needs according to the ranking results; Convert the basic medication needs into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics; Map the relationship between function, behavior, and structure for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping results; Generate a design plan based on the system design path and the basic structure of the medicine box, generate a product model according to the design plan and verify the product model, and obtain the final design product according to the verification results.

2. The intelligent medicine box design method for the elderly population integrating the Kano-FAST-FBS model according to claim 1, characterized in that The obtaining of multiple medication needs of elderly users, classifying and prioritizing the multiple medication needs through the Kano model, and determining the basic medication needs according to the ranking results include: Obtain multiple medication needs of elderly users and the user need attributes of each medication need through questionnaire surveys or user interviews; Formulate multiple demand characteristics and determine the membership degree of each demand characteristic to each user need attribute through questionnaire surveys; Determine the response intensity of users to each user need attribute through the Kano model according to the membership degree of each demand characteristic to each user need attribute, prioritize the multiple medication needs according to the response intensity, and classify the user need attributes with the same demand characteristic; Confirm the first N medication needs in the ranking results as the basic medication needs of elderly users.

3. The intelligent medicine box design method for the elderly group integrating the Kano-FAST-FBS model according to claim 1, wherein The converting of the basic medication needs into basic functions through the FAST model and decomposing the basic functions into multiple basic sub-functions according to the decomposition characteristics include: Determine the demand domain of elderly users through the FAST model according to the basic medication needs, determine the functional application parameters of the demand domain, and determine the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters of the demand domain according to the functional application parameters; Determine the key functional domain according to the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters, obtain the functional description parameters of the key functional domain, and determine the basic functions of the medicine box according to the functional description parameters; Obtain the functional combination logic parameters of each basic function of the medicine box, and determine the function chain according to the functional combination logic parameters; Based on the function chain, determine the upper and lower function relationship parameters of each basic function of the medicine box, and decompose the basic functions into multiple basic sub-functions according to the upper and lower function relationship parameters.

4. The intelligent medicine box design method for the elderly population integrating the Kano-FAST-FBS model according to claim 1, characterized in that, The mapping of the relationship between function, behavior, and structure for the basic sub-functions through the FBS model and determining the system design path and the basic structure of the medicine box according to the mapping results include: Obtain the behavior domain through F-B mapping of the basic sub-functions through the FBS model, and obtain the product structure domain through B-S mapping of the behavior domain; Obtain multiple product sub-structures according to the product structure domain, and determine the system design path according to the technical characteristics and structural principles of each product sub-structure; Analyze the technical characteristics and structural principles of each product sub-structure, and determine the structure aggregation boundary parameters according to the analysis results; Optimize and aggregate the multiple product sub-structures based on the structure aggregation boundary parameters to obtain the basic structure of the medicine box.

5. The intelligent medicine box design method for the elderly population integrating the Kano-FAST-FBS model according to claim 1, wherein, Generating a design plan based on the system design path and the basic structure of the medicine box, generating a product model according to the design plan and validating the product model, and obtaining the final design product according to the validation result, including: Generating structural design parameters based on the system design path and the basic structure of the medicine box, and obtaining preference parameters of elderly users for the shape, color, and material of the medicine box; Generating appearance design parameters according to the preference parameters, and performing integration processing based on the structural design parameters and the appearance design parameters to generate a design plan; Generating a virtual 3D product model and a usage principle video according to the design plan, generating multiple product characteristic evaluation indicators, and comprehensively scoring the design plan according to the multiple product characteristic evaluation indicators based on the virtual 3D product model and the usage principle video; Determining the items to be optimized according to the scoring result, optimizing the design plan based on the items to be optimized to obtain an optimized plan, and obtaining the final design product according to the optimized plan.

6. An intelligent medicine box design system for the elderly population integrating the Kano-FAST-FBS model, characterized in that, The system includes: The first determination module is used to obtain multiple medication needs of elderly users, classify and prioritize the multiple medication needs through the Kano model, and determine the basic medication needs according to the ranking result; The decomposition module is used to convert the basic medication needs into basic functions through the FAST model, and decompose the basic functions into multiple basic sub-functions according to the decomposition characteristics; The second determination module is used to map the relationship between function-behavior-structure for the basic sub-functions through the FBS model, and determine the system design path and the basic structure of the medicine box according to the mapping result; The generation module is used to generate a design plan based on the system design path and the basic structure of the medicine box, generate a product model according to the design plan and validate the product model, and obtain the final design product according to the validation result.

7. The intelligent medicine box design system for the elderly population integrating the Kano-FAST-FBS model according to claim 6, characterized in that The first determination module includes: The acquisition sub-module is used to obtain multiple medication needs of elderly users and the user need attributes of each medication need through questionnaire surveys or user interviews; The first determination sub-module is used to formulate multiple demand characteristics and determine the membership degree of each demand characteristic for each user need attribute through questionnaire surveys; The classification sub-module is used to determine the response intensity of users for each user need attribute according to the membership degree of each demand characteristic for each user need attribute through the Kano model, prioritize the multiple medication needs according to the response intensity, and classify the user need attributes with the same demand characteristic; The confirmation sub-module is used to confirm the first N medication needs in the ranking result as the basic medication needs of elderly users.

8. The intelligent medicine box design system for the elderly population integrating the Kano-FAST-FBS model according to claim 6, wherein The decomposition module includes: The second determination sub-module is used to determine the demand domain of elderly users according to the basic medication needs through the FAST model, determine the functional application parameters of the demand domain, and determine the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters of the demand domain according to the functional application parameters; The third determination sub-module is used to determine the key functional domain according to the energy conversion flow parameters, material conversion flow parameters, and information conversion flow parameters, obtain the functional description parameters of the key functional domain, and determine the basic function of the medicine box according to the functional description parameters; The fourth determination sub-module is used to obtain the functional combination logic parameters of each basic function of the medicine box, and determine the function chain according to the functional combination logic parameters; The decomposition sub-module is used to determine the superior and inferior function relationship parameters of each basic function of the medicine box based on the function chain, and decompose the basic function into multiple basic sub-functions according to the superior and inferior function relationship parameters.

9. The intelligent medicine box design system for the elderly population integrating the Kano-FAST-FBS model according to claim 6, wherein The second determination module includes: The mapping sub-module is used to perform F-B mapping on the basic sub-functions through the FBS model to obtain the behavior domain, and perform B-S mapping on the behavior domain to obtain the product structure domain; The fifth determination sub-module is used to obtain multiple product sub-structures according to the product structure domain, and determine the system design path according to the technical features and structural principles of each product sub-structure; The sixth determination sub-module is used to analyze the technical features and structural principles of each product sub-structure, and determine the structure aggregation boundary parameters according to the analysis results; The optimization aggregation sub-module is used to perform optimization aggregation on multiple product sub-structures based on the structure aggregation boundary parameters to obtain the basic structure of the medicine box.

10. The intelligent medicine box design system for the elderly integrating the Kano-FAST-FBS model according to claim 6, characterized in that, The generation module includes: The first generation sub-module is used to generate structure design parameters according to the system design path and the basic structure of the medicine box, and obtain the preference parameters of the elderly users for the shape, color and material of the medicine box; The second generation sub-module is used to generate appearance design parameters according to the preference parameters, and perform integration processing based on the structure design parameters and the appearance design parameters to generate a design scheme; The scoring sub-module is used to generate a virtual 3D product model and a usage principle video according to the design scheme, generate multiple product characteristic evaluation indicators, and comprehensively score the design scheme according to the virtual 3D product model and the usage principle video through the multiple product characteristic evaluation indicators; The optimization sub-module is used to determine the items to be optimized according to the scoring results, optimize the design scheme based on the items to be optimized to obtain an optimized scheme, and obtain the final design finished product according to the optimized scheme.

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