# Improvement of Evaluation Method of Elderly Family Medical Product Design Based on AHP

Authors: Han Yue; Tian-Lu Zhu; Zheng-Jun Zhou; Tao Zhou
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

Due to the needs of an aging society, household medical products for the elderly are becoming increasingly important in everyday life. To improve the quality and scientificity of household medical product design for the elderly, this study uses the analytic hierarchy process to improve the evaluation method of household medical product design for the elderly and to promote the vigorous development of household medical products for the elderly. Based on previous research, firstly, this paper summarised the design elements of household medical products for the elderly using questionnaire research and used this to establish a hierarchical analysis model. Secondly, experts and the elderly were invited to rate the subcriteria layers, and the hierarchical analysis software Yaahp was used to calculate the weight values of each criterion layer to arrive at a ranking of the importance of the elements of elderly household medical product design. Finally, the accuracy of the results was verified by three examples of geriatric household blood glucose meters. In this study, the analytic hierarchy process (AHP) was introduced into the evaluation method of the design of household medical products for the elderly, which improved the evaluation system of the design of household medical products for the elderly and pointed out the direction of the design of household medical products for the elderly to continue to optimize and improve in the future. At the same time, it can also provide a reference for the design evaluation of similar products.


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## Body

## 1. Introduction

With the accelerating process of social aging in China, the overall elderly population in China shows a trend of large total and fast growth [1]. Under this general trend, the development of the country’s medical security system and medical products has received increasing attention from the state and the people. Compared with the rapid development of the medical industry, the design and development of home medical products for the elderly in China are relatively lagging [2]. In the research on the design of many household medical products, we can find that designers are often functionally oriented and tend to ignore other design elements of household medical products for the elderly. Therefore, in this study, the analytic hierarchy process (AHP) was introduced to improve the evaluation method for the design of household medical products for the elderly and provide designers concerning design elements more scientifically and reasonably, to improve the design quality of household medical products for the elderly and promote the development of household medical products for the elderly in China.According to public data from the National Bureau of Statistics, in 2017, the population of China over the age of 60 reached 240 million, accounting for 17.3% of the national population. By 2050, the aging level is expected to reach a staggering 31% [3]. With the continuous improvement of the health care awareness of the elderly, the traditional medical institution treatment model can no longer meet the needs of the growing elderly group [4]. Changes in healthcare paradigms have led to changes in people’s understanding of healthcare. In the early stage, most elderly patients completed the whole process from treatment to rehabilitation in the hospital, which led to increased treatment costs and longer periods. Modern medical services are increasingly family-oriented. Family therapy has gradually become a diversified and multilevel modern comprehensive medical system such as rehabilitation, nursing, and health care. Thus, the market is in urgent need of a design evaluation system for the elderly household products, while the development of the elderly household medical industry has both huge economic benefits and significant social benefits, the prospect is very broad. Research on medical product design has been conducted by many scholars from different perspectives (Table 1). Ding et al. pointed out in the article “Research on The Design Strategy of Health and Medical Product Service System Based on PCN Theory” [5]that medical products should take health service as the basic criterion and different design strategies should be made according to different scenarios. Wang et al. pointed out in the article “Modeling Design of Cervical and Cranial electromagnetic Therapy Instrument Based on Kano Model” [6]that the needs of both doctors and patients should be fully met and related medical products should be designed according to the needs of doctors and patients, to improve user satisfaction of medical device products. In the article “Research on the Design of household medical Products Based on the Emotional characteristics of the Elderly” [7], Zhu proposed to provide a reference for the design of household medical products for the elderly by analyzing the emotional characteristics of the elderly. In the paper “Research on the Design of household Medical Products Based on the Emotional Characteristics of the Elderly” [8], Qiao et al. proposed a reference for the design of household medical products based on the characteristics of new chemical materials. Through the review of the research of the above scholars, we can know that most of the research on the design of household medical products for the elderly is based on a single element as the key point, according to which the research and design of household medical products for the elderly are carried out. However, there are still deficiencies in the overall design evaluation of the elderly household medical products, and there is a lack of comprehensive design evaluation and design guidance for the elderly household medical products based on comprehensive analysis from all angles. Therefore, based on previous studies, this paper uses the analytic hierarchy process to improve the evaluation method of elderly household medical product design and to provide more scientific design elements for elderly household medical product reference. Firstly, this paper reviews the previous research on medical product design, concludes the shortcomings of the design evaluation of household medical products, and proposes the need for comprehensive evaluation and analysis of all design elements.Table 1
Literature review and analysis.
TitleAuthorMethodResearch on the Design Strategy of Health and Medical Product Service System Based on PCN TheoryDing et al.Analysis for different scenariosModeling Design of Cervical and Cranial Electromagnetic Therapy Instrument Based on Kano ModelWang et al.Analysis according to the needs of doctors and patientsResearch on the Design of Household Medical Products Based on the Emotional Characteristics of the ElderlyZhuThrough the analysis of emotional characteristicsResearch on Intelligent Medical Product Design Based on Molecular Sensing MaterialsQiao et al.Through material characteristic analysisSecondly, the classification of design elements is obtained through market research and questionnaire research, and the hierarchy analysis model is established. Then, by inviting experts and users to score, Yaahp software is used to calculate the weight of each design element, and the importance ranking is obtained, among which safety and comfort account for the highest weight. Finally, three types of blood glucose meters on the market were selected to verify the research results, and the results were consistent with the research results. It is concluded that the research method is scientific and reasonable.


## 2. Analytic Hierarchy Process

### 2.1. AHP Design Process

Analytic Hierarchy Process (AHP) is a research method proposed by American operations researcher Satty, which is widely used in various fields related to decision-making [9]. When the quantitative analysis of the importance of design elements and categories is more complicated, the introduction of AHP can more clearly deal with such multifeature comparison problems [10]. The model architecture process of AHP mainly includes selecting systems, extracting elements, AHP, constructing matrix, calculating weights, and drawing conclusions. The flow chart of AHP design is shown in Figure 1.Figure 1
Design flow of Analytic hierarchy process.


### 2.2. Constructing the Judgment Matrix Scale

According to the hierarchical structure proposed by Satty, we will analyze and compare the modeling design from the target layer, the criterion layer, and the scheme layer. For the construction method of the judgment matrix, we construct the judgment matrix according to Satty’s 1–9 scaling method [9]. For a certain target, the relevant elements are compared with each other. The scale value of the judgment matrix is shown in Table 2.Table 2
Judgment matrix scale.
Scale assignmentImportanceScale description (m and n)1Equally importantMetricm and metric n are equally important3Slightly importantMetricm is slightly more important than metric n5Clearly importantMetricm is significantly more important than metric n7Strongly importantMetricm is strongly more important than metric n9Absolutely importantMetricm is strongly more important than metric n2, 4, 6, 8MedianCompromise


### 2.3. Construction of Judgment Matrix and Calculation of Weight Values

FThe judgment matrix is constructed by comparing the elements of the evaluation indicators in each tier with each other. The judgment matrix is also an important basis for the weighting calculation. For the 1-level evaluation indicator layer U1, the 2-level evaluation indicators U11, C12,…, U1n are assigned a certain value according to their importance after comparing their importance, and the assigned value is labeled as aij (i, j = 1, 2,…, n), where aij represents the importance value of factors i and j relative to the target, and n is the number of indicators. The value of aij is usually given by experts in the field or based on data from a questionnaire and has aij x aji = 1. Through the above judgment matrix, the weight value of each indicator is the eigenvector corresponding to the maximum eigenvalue of the judgment matrix, and the square root method is used to calculate the weight value of the judgment matrix. By pairwise comparison of level 2 evaluation indexes, the following judgment matrix is obtained:(1)A=1a12⋯a1i⋯a1j⋯a1na211⋯a2i⋯a2j⋯a2n⋮⋮⋮⋮⋮⋮⋮⋮ai1ai2⋯1⋯aij⋯ain⋮⋮⋮⋮⋮⋮⋮⋮aj1aj2⋯aji⋯1⋯ajn⋮⋮⋮⋮⋮⋮⋮⋮an1an2⋯ani⋯anj⋯1=aijn×n.The weight value is represented byw, and the software Yaahp is used in this study to calculate the weight value. The specific steps are as follows:(1)
Firstly, an AHP hierarchy diagram is established based on the primary and secondary evaluation indicators.(2)
Data input was carried out. The data were scored by experts and compared with the 9-point scale. Consistency <0.1 is required during data entry. If it is not satisfied, data will be readjusted.(3)
Click to calculate the result.


### 2.4. Consistency Test

To ensure the scientificity and standardization of evaluation, it is necessary to test the consistency of evaluation results. CI is the consistency index, CR is the consistency ratio, and RI is the random consistency index. See Formula (2) for calculating consistency index and Formula (3) for calculating consistency ratio.The average random consistency index RI was searched, and the specific value is shown in Table3. Where λmax is the maximum eigenvalue in matrix A. When CR ≤ 0.1, it is considered that the results of hierarchical total ordering meet the consistency judgment, otherwise, the judgment matrix needs to be adjusted or reconstructed until the total ordering meets the consistency judgment.Table 3
Consistency index of average random number.
n123456789101112RI000.520.891.121.261.261.411.461.491.521.54


## 2.1. AHP Design Process

Analytic Hierarchy Process (AHP) is a research method proposed by American operations researcher Satty, which is widely used in various fields related to decision-making [9]. When the quantitative analysis of the importance of design elements and categories is more complicated, the introduction of AHP can more clearly deal with such multifeature comparison problems [10]. The model architecture process of AHP mainly includes selecting systems, extracting elements, AHP, constructing matrix, calculating weights, and drawing conclusions. The flow chart of AHP design is shown in Figure 1.Figure 1
Design flow of Analytic hierarchy process.


## 2.2. Constructing the Judgment Matrix Scale

According to the hierarchical structure proposed by Satty, we will analyze and compare the modeling design from the target layer, the criterion layer, and the scheme layer. For the construction method of the judgment matrix, we construct the judgment matrix according to Satty’s 1–9 scaling method [9]. For a certain target, the relevant elements are compared with each other. The scale value of the judgment matrix is shown in Table 2.Table 2
Judgment matrix scale.
Scale assignmentImportanceScale description (m and n)1Equally importantMetricm and metric n are equally important3Slightly importantMetricm is slightly more important than metric n5Clearly importantMetricm is significantly more important than metric n7Strongly importantMetricm is strongly more important than metric n9Absolutely importantMetricm is strongly more important than metric n2, 4, 6, 8MedianCompromise


## 2.3. Construction of Judgment Matrix and Calculation of Weight Values

FThe judgment matrix is constructed by comparing the elements of the evaluation indicators in each tier with each other. The judgment matrix is also an important basis for the weighting calculation. For the 1-level evaluation indicator layer U1, the 2-level evaluation indicators U11, C12,…, U1n are assigned a certain value according to their importance after comparing their importance, and the assigned value is labeled as aij (i, j = 1, 2,…, n), where aij represents the importance value of factors i and j relative to the target, and n is the number of indicators. The value of aij is usually given by experts in the field or based on data from a questionnaire and has aij x aji = 1. Through the above judgment matrix, the weight value of each indicator is the eigenvector corresponding to the maximum eigenvalue of the judgment matrix, and the square root method is used to calculate the weight value of the judgment matrix. By pairwise comparison of level 2 evaluation indexes, the following judgment matrix is obtained:(1)A=1a12⋯a1i⋯a1j⋯a1na211⋯a2i⋯a2j⋯a2n⋮⋮⋮⋮⋮⋮⋮⋮ai1ai2⋯1⋯aij⋯ain⋮⋮⋮⋮⋮⋮⋮⋮aj1aj2⋯aji⋯1⋯ajn⋮⋮⋮⋮⋮⋮⋮⋮an1an2⋯ani⋯anj⋯1=aijn×n.The weight value is represented byw, and the software Yaahp is used in this study to calculate the weight value. The specific steps are as follows:(1)
Firstly, an AHP hierarchy diagram is established based on the primary and secondary evaluation indicators.(2)
Data input was carried out. The data were scored by experts and compared with the 9-point scale. Consistency <0.1 is required during data entry. If it is not satisfied, data will be readjusted.(3)
Click to calculate the result.


## 2.4. Consistency Test

To ensure the scientificity and standardization of evaluation, it is necessary to test the consistency of evaluation results. CI is the consistency index, CR is the consistency ratio, and RI is the random consistency index. See Formula (2) for calculating consistency index and Formula (3) for calculating consistency ratio.The average random consistency index RI was searched, and the specific value is shown in Table3. Where λmax is the maximum eigenvalue in matrix A. When CR ≤ 0.1, it is considered that the results of hierarchical total ordering meet the consistency judgment, otherwise, the judgment matrix needs to be adjusted or reconstructed until the total ordering meets the consistency judgment.Table 3
Consistency index of average random number.
n123456789101112RI000.520.891.121.261.261.411.461.491.521.54


## 3. Evaluation of Elderly Household Medical Products based on AHP

### 3.1. Analysis of Design Elements

An elderly group is a special group, so the products aimed at the elderly group should also meet this particularity, that is, product design evaluation needs to meet the needs of the elderly group to the greatest extent [9]. Sociological research shows that the needs of the elderly group are divided into three dimensions, namely, the dimension of physiological needs, the dimension of social needs, and the dimension of cultural needs [10]. Objectively and physiologically, the three needs will show commonalities with the changes in the elderly group, which shows that each need can affect each other although they are located at different angles. Meyer pointed out that the process of aging should not be a biological process, but a process of change in which the subject participates in the realization of social behavior and social obligations [11]. The changing process of social aging will inevitably show differences in different environments. The social environment and objective environment can have a direct impact on the elderly group, and this impact is manifested in product design in the form of aesthetics, functionality, and practicality of the product.(1)
Aesthetics. The aesthetics of elderly household medical products is one of the important factors in their design. Therefore, the design needs to meet the psychological and physiological needs of the elderly. At present, the elderly household medical products on the market, such as blood pressure monitors and blood glucose meters, have problems such as cold shape, chaotic colors, and lack of humanization are ignoring the emotional needs of the elderly. We classify the design elements that are mainly considered for the appearance of elderly home medical products into four elements: shape, color, material, and decoration. The shape should be mainly streamlined, the color types should be simplified, and the aesthetics of the materials should take into account both visual and tactile sensations. The products of the elderly group, it is more inclined to use simple, warm, green, and environmentally friendly materials. The decoration is simple and easy to understand.(2)
Functionality. The functions of elderly products are mainly in the form of monitoring, communication, prompting, and remote control. The monitoring function is responsible for monitoring various data of the elderly group, the communication function is used to communicate with the elderly group and their families and the external environment, the prompt function is responsible for reminding the elderly group to fix their behavior, and the remote control function is for the elderly group with inconvenience and is used to help or replace the elderly mobile products.(3)
Practicality. The practical design is to measure the product value from the attributes of safety, comfort, reliability, and durability through accurate positioning of product functions. The measurement principle is based on the realization degree of product functionality. Medical products may not be of practical value due to their service life, usage environment, or operation methods. At the same time, the practicability of elderly products should also include the exclusion of idle functions of products. At present, the existing functions of elderly household products on the market are very different from the actual application for elderly groups. Most of the products have excess functions and auxiliary functions are idle, resulting in resource shortages and wasteful and meaningless output.


### 3.2. Establishment of Hierarchical Model for Elderly Home Medical Products

Based on AHP to construct the design decision model requirements, the model is divided into the target layer, criterion layer, and scheme layer. First, we set the target layer as the design evaluation of elderly home medical products. Secondly, according to the analysis of the design evaluation elements above, we set the first layer of the criterion layer as aesthetics U1, functional U2, and practical U3. Next, we extract the design categories for the design elements of the first layer of the criterion layer as the second layer of the criterion layer, including a total of 12 design categories, which are set as U11 modeling, U12 color, U13 material, U14 decoration, U21 monitoring function, U22 communication function, U23 prompt function, U24 remote control function, U31 simplicity, U32 comfort, U33 durability, and U34 safety. The AHP design decision model is shown in Figure2.Figure 2
Decision model for elderly home medical product design.


### 3.3. Index Weight Solution

For the research at the standard level, we adopted the form of an audience questionnaire survey. Among them, we distributed a total of 50 questionnaires, and the survey objects were mainly from the elderly, scientific researchers, and medical staff. Considering that it is difficult for the elderly to understand the form of the judgment matrix and there are too many evaluation scales, the scoring model is adopted here for the importance of the elements in the second criterion layer. This clearly demonstrates the importance of each element in the elderly population. The most important metric is set to 1, the next most important metric is set to 2, and so on. The results of the user questionnaire are shown in Table4.Table 4
Questionnaire survey results.
Indicator importance1234Modeling1514129Color241475Material8111615Decorate3111521Monitoring function1514912Communication function142196Prompt function1381613Remote control function871619Simplicity051431Comfort182192Durability472217Safety281750According to the statistical results of the questionnaire survey, we scored the highest importance score in the questionnaire as 4 points and the lowest importance score as 1 point, and the importance ratio decreased gradually. We perform a weighted average of the scoring results and calculated the data (the decimal point is rounded off) to obtain the weight values of the first criterion layer indicators. For example, the calculation method of modeling score is15∗4+14∗3+12∗2+9∗1, the score is 135, and the calculation method of the color score is 24∗4+14∗3+7∗2+5∗1, and the score is 157, the modeling/color ratio is 135/157, which is about 0.8599. The rest of the calculation is the same, and the research results are brought into the AHP model, and all results obtained have passed the consistency test. The judgment result matrix and calculation weight of each level are shown in Tables 5–8.Table 5
Judgment matrix and weight of elderly home medical product design.
GU1U2U3WeightConsistent resultsU11.00000.77780.53850.24140.0000U21.28571.00000.69230.3103U31.8571.4441.00000.4483Table 6
Judgment matrix and weight of aesthetic.
AU11U12U13U14Weight resultsConsistent resultsU111.00000.85991.20541.40620.27000.0000U121.16301.00001.40181.63540.3140U130.82960.71341.00001.16670.2240U140.71110.61150.85711.00000.1920Table 7
Judgment matrix and weight of functionality.
AU21U22U23U24Weight resultsConsistent resultsU211.00000.92311.09101.26920.26400.0000U221.08331.00001.18181.37500.2860U230.91670.84621.00001.16350.2420U240.78790.72730.85951.00000.2080Table 8
Judgment matrix and weight of practicality.
AU31U32U33U34Weight resultsConsistent resultsU311.00000.47740.75510.42770.14800.0000U322.09461.00001.58160.89600.3100U331.32430.63231.00000.56650.1960U342.33781.11611.76531.00000.3460By normalizing each weight value of the second criterion layer, the second-level judgment matrix and weight of the criterion layer can be obtained, as shown in Figure3 and the importance ranking of criteria layer is shown in Table 9.Figure 3
Weights of the second hierarchy.Table 9
Design element index comprehensive weight sorting.
Target layerPrimary indexSecondary indexWeightsSynthetic weightsImportance rankingDesign decision model of elderly household medical productsU1 aesthetics (0.2414)U11 shape0.27000.06529U12 color0.31400.07596U13 material0.22400.054111U14 decoration0.19200.046312U2 functional (0.3103)U21 monitoring0.26400.08195U22 communication0.28600.08873U23 prompt0.24200.07517U24 remote control0.20800.064510U3 practicability (0.4483)U31 simplicity0.14800.06648U32 comfort0.31000.13982U33 durability0.19600.08794U34 safety0.34600.15511


## 3.1. Analysis of Design Elements

An elderly group is a special group, so the products aimed at the elderly group should also meet this particularity, that is, product design evaluation needs to meet the needs of the elderly group to the greatest extent [9]. Sociological research shows that the needs of the elderly group are divided into three dimensions, namely, the dimension of physiological needs, the dimension of social needs, and the dimension of cultural needs [10]. Objectively and physiologically, the three needs will show commonalities with the changes in the elderly group, which shows that each need can affect each other although they are located at different angles. Meyer pointed out that the process of aging should not be a biological process, but a process of change in which the subject participates in the realization of social behavior and social obligations [11]. The changing process of social aging will inevitably show differences in different environments. The social environment and objective environment can have a direct impact on the elderly group, and this impact is manifested in product design in the form of aesthetics, functionality, and practicality of the product.(1)
Aesthetics. The aesthetics of elderly household medical products is one of the important factors in their design. Therefore, the design needs to meet the psychological and physiological needs of the elderly. At present, the elderly household medical products on the market, such as blood pressure monitors and blood glucose meters, have problems such as cold shape, chaotic colors, and lack of humanization are ignoring the emotional needs of the elderly. We classify the design elements that are mainly considered for the appearance of elderly home medical products into four elements: shape, color, material, and decoration. The shape should be mainly streamlined, the color types should be simplified, and the aesthetics of the materials should take into account both visual and tactile sensations. The products of the elderly group, it is more inclined to use simple, warm, green, and environmentally friendly materials. The decoration is simple and easy to understand.(2)
Functionality. The functions of elderly products are mainly in the form of monitoring, communication, prompting, and remote control. The monitoring function is responsible for monitoring various data of the elderly group, the communication function is used to communicate with the elderly group and their families and the external environment, the prompt function is responsible for reminding the elderly group to fix their behavior, and the remote control function is for the elderly group with inconvenience and is used to help or replace the elderly mobile products.(3)
Practicality. The practical design is to measure the product value from the attributes of safety, comfort, reliability, and durability through accurate positioning of product functions. The measurement principle is based on the realization degree of product functionality. Medical products may not be of practical value due to their service life, usage environment, or operation methods. At the same time, the practicability of elderly products should also include the exclusion of idle functions of products. At present, the existing functions of elderly household products on the market are very different from the actual application for elderly groups. Most of the products have excess functions and auxiliary functions are idle, resulting in resource shortages and wasteful and meaningless output.


## 3.2. Establishment of Hierarchical Model for Elderly Home Medical Products

Based on AHP to construct the design decision model requirements, the model is divided into the target layer, criterion layer, and scheme layer. First, we set the target layer as the design evaluation of elderly home medical products. Secondly, according to the analysis of the design evaluation elements above, we set the first layer of the criterion layer as aesthetics U1, functional U2, and practical U3. Next, we extract the design categories for the design elements of the first layer of the criterion layer as the second layer of the criterion layer, including a total of 12 design categories, which are set as U11 modeling, U12 color, U13 material, U14 decoration, U21 monitoring function, U22 communication function, U23 prompt function, U24 remote control function, U31 simplicity, U32 comfort, U33 durability, and U34 safety. The AHP design decision model is shown in Figure2.Figure 2
Decision model for elderly home medical product design.


## 3.3. Index Weight Solution

For the research at the standard level, we adopted the form of an audience questionnaire survey. Among them, we distributed a total of 50 questionnaires, and the survey objects were mainly from the elderly, scientific researchers, and medical staff. Considering that it is difficult for the elderly to understand the form of the judgment matrix and there are too many evaluation scales, the scoring model is adopted here for the importance of the elements in the second criterion layer. This clearly demonstrates the importance of each element in the elderly population. The most important metric is set to 1, the next most important metric is set to 2, and so on. The results of the user questionnaire are shown in Table4.Table 4
Questionnaire survey results.
Indicator importance1234Modeling1514129Color241475Material8111615Decorate3111521Monitoring function1514912Communication function142196Prompt function1381613Remote control function871619Simplicity051431Comfort182192Durability472217Safety281750According to the statistical results of the questionnaire survey, we scored the highest importance score in the questionnaire as 4 points and the lowest importance score as 1 point, and the importance ratio decreased gradually. We perform a weighted average of the scoring results and calculated the data (the decimal point is rounded off) to obtain the weight values of the first criterion layer indicators. For example, the calculation method of modeling score is15∗4+14∗3+12∗2+9∗1, the score is 135, and the calculation method of the color score is 24∗4+14∗3+7∗2+5∗1, and the score is 157, the modeling/color ratio is 135/157, which is about 0.8599. The rest of the calculation is the same, and the research results are brought into the AHP model, and all results obtained have passed the consistency test. The judgment result matrix and calculation weight of each level are shown in Tables 5–8.Table 5
Judgment matrix and weight of elderly home medical product design.
GU1U2U3WeightConsistent resultsU11.00000.77780.53850.24140.0000U21.28571.00000.69230.3103U31.8571.4441.00000.4483Table 6
Judgment matrix and weight of aesthetic.
AU11U12U13U14Weight resultsConsistent resultsU111.00000.85991.20541.40620.27000.0000U121.16301.00001.40181.63540.3140U130.82960.71341.00001.16670.2240U140.71110.61150.85711.00000.1920Table 7
Judgment matrix and weight of functionality.
AU21U22U23U24Weight resultsConsistent resultsU211.00000.92311.09101.26920.26400.0000U221.08331.00001.18181.37500.2860U230.91670.84621.00001.16350.2420U240.78790.72730.85951.00000.2080Table 8
Judgment matrix and weight of practicality.
AU31U32U33U34Weight resultsConsistent resultsU311.00000.47740.75510.42770.14800.0000U322.09461.00001.58160.89600.3100U331.32430.63231.00000.56650.1960U342.33781.11611.76531.00000.3460By normalizing each weight value of the second criterion layer, the second-level judgment matrix and weight of the criterion layer can be obtained, as shown in Figure3 and the importance ranking of criteria layer is shown in Table 9.Figure 3
Weights of the second hierarchy.Table 9
Design element index comprehensive weight sorting.
Target layerPrimary indexSecondary indexWeightsSynthetic weightsImportance rankingDesign decision model of elderly household medical productsU1 aesthetics (0.2414)U11 shape0.27000.06529U12 color0.31400.07596U13 material0.22400.054111U14 decoration0.19200.046312U2 functional (0.3103)U21 monitoring0.26400.08195U22 communication0.28600.08873U23 prompt0.24200.07517U24 remote control0.20800.064510U3 practicability (0.4483)U31 simplicity0.14800.06648U32 comfort0.31000.13982U33 durability0.19600.08794U34 safety0.34600.15511


## 4. Case Analysis

### 4.1. Scheme Selection and Scoring

To verify the effectiveness of this method, we took the elderly household blood glucose meter as an example and selected 3 products from the market as the plans to be evaluated, as shown in Figure4. We selected five experts who have long been engaged in product design research to rate the cases. Combined with the design evaluation system of the middle-aged and elderly household medical products in Figure 2, the criterion layer was extracted and the Likert scale method [14]was used to score the three schemes in the interval of 0–10 points, and the average value was used to establish the original data scheme score, see Table 10.Figure 4
Blood glucose meter evaluation cases.Table 10
The program score of original data.
Evaluation indicatorsSchemeXscoreSchemeYscoreSchemeZscoreU117.618.128.32U126.878.567.15U137.136.567.31U146.127.277.32U219.139.079.22U226.125.856.01U239.439.569.52U245.015.235.51U317.528.648.83U327.097.066.91U336.517.688.33U348.738.819.05


### 4.2. Scheme Score Calculation

Combined with the weight value of the design indicators of the middle-aged and elderly household medical products in Figure3 and the scheme scores in Table 8, the comprehensive coefficient method is used to sum up the indicators. The variable wrepresents the weight ratio of each sublevel in the research results and represents the average value of the comprehensive evaluation of each sublevel. The total score of each scheme is obtained as follows:(2)X=ω1⋅V¯X1+ω2⋅V¯X2+⋯+ωn⋅V¯Xn=7.4190,Y=ω1⋅V¯Y1+ω2⋅V¯Y2+⋯+ωn⋅V¯Yn=7.7834,Z=ω1⋅V¯Z1+ω2⋅V¯Z2+⋯+ωn⋅V¯Zn=7.8601.From this, it can be concluded that the comprehensive score ranking of the three elderly home blood glucose meters is the optimal solutionZ ＞ Y ＞ X, that is, home blood glucose meter Z for the elderly is the best choice.


### 4.3. Evaluation Results Inspection

After obtaining the comprehensive ranking of the 3 elderly household blood glucose meters, the ranking results need to be verified. The verification method mainly relies on the monthly sales, related comments, and comprehensive scores of the three elderly household blood glucose meters on the T-mall platform [15–29]. The final data are summarised in Table 11. It has been verified that the ranking results in Table 11 are consistent with the evaluation results obtained by introducing AHP, which proves that the method has certain feasibility.Table 11
Data collection of three products in T-mall, namely, product image, monthly sales, related comment, and overall rating.
NameProduct imageMonthly salesRelated commentOverall ratingSanuo blood glucose meter190848914.8Johnson & Johnson blood glucose meter159398104.9Roche blood glucose meter1780169704.9


## 4.1. Scheme Selection and Scoring

To verify the effectiveness of this method, we took the elderly household blood glucose meter as an example and selected 3 products from the market as the plans to be evaluated, as shown in Figure4. We selected five experts who have long been engaged in product design research to rate the cases. Combined with the design evaluation system of the middle-aged and elderly household medical products in Figure 2, the criterion layer was extracted and the Likert scale method [14]was used to score the three schemes in the interval of 0–10 points, and the average value was used to establish the original data scheme score, see Table 10.Figure 4
Blood glucose meter evaluation cases.Table 10
The program score of original data.
Evaluation indicatorsSchemeXscoreSchemeYscoreSchemeZscoreU117.618.128.32U126.878.567.15U137.136.567.31U146.127.277.32U219.139.079.22U226.125.856.01U239.439.569.52U245.015.235.51U317.528.648.83U327.097.066.91U336.517.688.33U348.738.819.05


## 4.2. Scheme Score Calculation

Combined with the weight value of the design indicators of the middle-aged and elderly household medical products in Figure3 and the scheme scores in Table 8, the comprehensive coefficient method is used to sum up the indicators. The variable wrepresents the weight ratio of each sublevel in the research results and represents the average value of the comprehensive evaluation of each sublevel. The total score of each scheme is obtained as follows:(2)X=ω1⋅V¯X1+ω2⋅V¯X2+⋯+ωn⋅V¯Xn=7.4190,Y=ω1⋅V¯Y1+ω2⋅V¯Y2+⋯+ωn⋅V¯Yn=7.7834,Z=ω1⋅V¯Z1+ω2⋅V¯Z2+⋯+ωn⋅V¯Zn=7.8601.From this, it can be concluded that the comprehensive score ranking of the three elderly home blood glucose meters is the optimal solutionZ ＞ Y ＞ X, that is, home blood glucose meter Z for the elderly is the best choice.


## 4.3. Evaluation Results Inspection

After obtaining the comprehensive ranking of the 3 elderly household blood glucose meters, the ranking results need to be verified. The verification method mainly relies on the monthly sales, related comments, and comprehensive scores of the three elderly household blood glucose meters on the T-mall platform [15–29]. The final data are summarised in Table 11. It has been verified that the ranking results in Table 11 are consistent with the evaluation results obtained by introducing AHP, which proves that the method has certain feasibility.Table 11
Data collection of three products in T-mall, namely, product image, monthly sales, related comment, and overall rating.
NameProduct imageMonthly salesRelated commentOverall ratingSanuo blood glucose meter190848914.8Johnson & Johnson blood glucose meter159398104.9Roche blood glucose meter1780169704.9


## 5. Conclusion

The purpose of this study is to improve the quality and science of household medical product design by improving the evaluation method of household medical product design. Compared with other methods of household medical product design evaluation, this paper introduces the analytic hierarchy process (AHP) to evaluate and analyze the overall design elements of household medical products and obtains the order of importance of each design element, which provides a quantitative decision basis for the elderly household medical products and related products. The introduction of the analytic hierarchy process (AHP) can transform complex and fuzzy design evaluation into quantitative solution, thus gradually improving the design evaluation method of household medical products, giving designers a more rigorous reference and making the design results more reasonable. In this paper, the research results show that the weight of safety is 0.1551, the highest importance, followed by the weight of comfort is 0.1389, the importance is second only to product modeling, and design should be taken as a key reference element of design. Due to the limitations of this research, this research method needs to be gradually improved in future research. Firstly, the design elements can be more rationally classified by employing expert interviews and the addition of literature to optimize the hierarchical analysis model and make it more scientific. Secondly, in the questionnaire research, the questionnaire can be optimized and upgraded, as the subject of this study is the elderly, the understanding and perception of the elderly should be taken into account when designing the questionnaire. Finally, in terms of validating the research results, mathematical models such as the fuzzy evaluation method can be incorporated to validate the results so that they are more reasonable and when applying this research method to the evaluation of the same type of product design, it needs to be optimized and improved according to the different target users and usage scenarios.[12].



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*Source: 4036030-2022-08-05.xml*