鞋具在人類生活起居上，佔有極為重要之地位，它提供人體足部最基本的保護與溫暖作用，同時更兼具引導時尚潮流之角色。隨著休閒運動風潮的興起與科技的進步，穿著舒適性與適足性之人因工程考量，逐漸成為鞋具設計的主要研發方向；而鞋墊在降低足底壓力，達成穿著的舒適度，鞋楦在與腳型圍度尺寸寬鬆適足性的配合上，為鞋具設計的重要指標。本研究基於此項概念，以足部鞋具穿著之舒適性與適足性為方向，藉由鞋墊足壓量測、足楦特徵圍度比對，達成鞋具設計評量的重要指標分析。研究上分為四階段：1.鞋墊足壓舒適度評價，方法上應用灰關聯與類神經網路分析，比對測試者穿著樣本鞋墊足壓分佈之差異，完成測試與評價，取得個人最適鞋墊，並獲取後續鞋楦設計所需預留之寬鬆舒感值11 mm、寬鬆範圍 4 mm。2.足楦圍度適足性評量，藉由逆向工程3D掃描與切層演算法取得測試者足部與鞋楦特徵圍度，再配合專家問卷，得到特徵圍度權重排序，完成建立鞋楦與足部配合之適足性評量模式。3.快速鞋具篩選系統建立，結合分析所得之鞋墊足壓寬鬆舒感值數據和足部鞋楦正確特徵圍度資料，應用模糊歸屬函數，建立一套最適鞋楦篩選系統。4.實例驗證，以10位志願者、20支鞋楦加入實際測試，驗證本系統之實用性，完成個人最適鞋墊與鞋楦分析之探討。本研究可作為個人鞋具設計舒適性與適足性之參考，廠商鞋具設計模組化之依據，亦可為醫療性鞋具客製化之建構，更可讓一般鞋具零售商，僅需憑藉消費者足部圍度資訊，快速取得最合適之鞋具，免除逐一試穿之時間耗費，增加其方便性。 Shoes have always occupied an extremely important position in human’s life. Not only do they provide the most basic protection and warmth of the human feet, but also play the role of fashion trend. Nowadays, with the rise of leisure sports and the advancement of technology, the comfort and suitability of footwear have gradually become the main research and development direction of footwear design. The Insole reduces the plantar pressure to achieve the comfort of wearing, and the shoe last with the loose fit of the foot shape is an important indicator for the design of the shoe. Based on the concept, this study takes the comfort and adequacy of the foot as the direction, and achieves an important analysis of the design of the shoe design by the Insole Plantar pressure measurement and the characteristic feature circumference comparison. The research is divided into four stages. First is the evaluation of the insole plantar pressure comfort. The method uses grey relational and neural network analysis to evaluate the difference while testing the plantar pressure distribution of the sample insole. It can obtain the most suitable personal insole, in which the relaxed comfort value that are reserved as 11 mm and the loose range 4 mm. Second is the fitness of shoe lasts girths. The reverse engineering 3D scanning and the triangle slicing are used to obtain the specific circumference of the tester's foot and shoe last. Then the feature girths are sorted by the expert questionnaires to complete the assessment of the suitability of the shoe last and the foot. Third is the establishment of rapid shoe screening system. It is to combine the obtained insole plantar pressure comfortable range value data and the correct feature circumference data of the shoe last with application of fuzzy membership function to establish a set of optimal footwear screening system. Fourth is the example verification. 10 volunteers and 20 shoe lasts join the actual test, which will verify the practicability of the system, complete the analysis and discussion of the most suitable insole and shoe last. This study can be used as the reference for future shoe design and acceleration modulization for manufacturers. It can also make contribution to the customized research and development of medical shoes. With the data, it provides convenience that general retailers can quickly get the most suitable shoes for customers who are not required to try on many others.
