Ergonomics Design on Bottom Curve Shape of Shoe-Last Based on Experimental Contacting Pressure Data

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Ergonomcs Desgn on Bottom Curve Shape of Shoe-Last Based on Expermental Contactng Pressure Data 1 L Zaran, 2 Sh Ka *1Correspondng Author Wenzhou Vocatonal and Techncal College, lzr_101@sna.com 2 Wenzhou Vocatonal and Techncal College, sk.126@126.com Abstract Comfortable shoes desgn was depended on the bottom shape of shoes and ts relatve last. Mostly, the curve of bottom last plays mportant roles n shoes desgn research. To date, t was known that the morphology of shoe last bottom had a great nfluence to user s health and comfort. In ths paper, key characterstc parameters were used to control the 3-D dgtal model of the shoe last curves, and optmzed desgn was determned through analyzng the dynamc contactng pressure expermental data between the shoe and the foot, the reported comfort degree of the user s psychologcal evaluatons was also acqured subsequently. Fnally, the expermental results show the effectveness of the proposed method whle compared to the tradtonal methodologes. Comfort shoes desgn wll have potental benefts for human health. Keywords: Last Bottom, Curve Desgn, Ergonomcs, Contactng Pressure, Pedar Insole System 1. Introducton Shoe last s the drect model for shoe producton, the desgn level of shoes plays mportant role n foot comfortable feels. Research on shoes comfortable were manly developed n Italy, the Unted States, the Netherlands, South Korea, as well as Chna's Tawan and Hong Kong, and there have a lot of research were done by the department of ndustral engneerng of Korean Dongeu Unversty, department of ndustral management of Natonal Tawan Unversty of Scence and Technology, and Hong Kong Unversty of Scence and Technology. To date, research on mprovng the shoes comfort was manly dscussed n addng fller or changng the soles shape shoes, such as to change the heel concavty soles, arch support, the plantar crcumference by fllng materal, and the comprehensve utlzaton of the above methods [1]. Based on the above requrements, the comfortable soles are generally n lne wth the physologcal and morphologcal characterstcs of the complex curve of human foot [2]. Tradtonal desgn methods on the curve of last bottom bascally reled on the experence of the craftsmen, whch was low effcency and poor relablty; and n most cases, t only can be better n talored shoes for specfc customers, but for the bulk of the mass customer s producton, the sample s too large for users, and t s also more dffcult to fnd the best shape for shoe last. The soluton to ths problem must rely on modern expermental technques and data analyss technques. Fndng a shoe that fts properly can be a frustratng and tme consumng, t s known that the shape of the shoe s mportant, but lttle attenton s pad to ths feature of the shoes. Shoe manufactures make curved lasted shoes because they beleve that my curvng the foot nward t causes greater stablty to the foot. And prevous research shows that shoes wth the last that best matches the needs of each foot s best for the short term as well as the long term, whereas, curved lasts are best for those wth hgh arches who supnate. Ths paper ntroduced a parameters optmzaton method by testng the status of plantar pressure dstrbuton, and developed data analyss and curve modelng technology, furthermore, consdered the data acquston and analyss of shoes under sport-state, and gave comparng analyss method to contactng pressure data, and fnally, the last bottom curve of the shoe last optmzed desgn and manufacturng parameters were acqured. Internatonal Journal of Dgtal Content Technology and ts Applcatons(JDCTA) Volume7,Number7,Aprl 2013 do:10.4156/jdcta.vol7.ssue7.10 86

2. Influencng factors and the optmzaton of the desgn goals on sole comfort research Bottom ste of foot takes whole body s weght that t wll be more requrements of the mechancal propertes other than the vamp and upper of shoes, whch gves the largest contrbuton to the whole shoe s wearng comfort [3]. In ths paper, the wearng comfort analyss for the sole ste of foot was proposed and reasonable soles curve was desgned under unform dstrbuton to mantan a stable center of gravty n walkng and to avod foot hurtng whle by vacllatng leadng. Whle standng under normal statcally, plantar force can be smplfed to a three-pont support: the calcaneus, the frst metatarsal head and the ffth metatarsal head (Shown n Fgure 1). Calcaneus, after longtudnal arch and metatarsal composed arm, wth the metatarsal jont foot adducton, varus or outreach, and valgus wll be adaptable to walkng on uneven road. Calcaneal tubercle achlles wth tendon attachment, gastrocnemus, soleus muscle contracton wll also have a strong plantar flexon acton. Calcaneus contaned plantar wth sudden wthstand talar neck s also very sturdy wth the boat lgament attachment to support the metatarsal head and bears the weght. Fgure1. Bones Structure of Feet Fgure 2. Major Pressure Pont Maps of Plantar 87

Fgure 2 shows the locaton of schematc dagram relatve to a foot n the flat-heel state on three force pont (A, B, C), and D s the mappng pont at pedar, R s the second rght pont but s not a contactng pont, so, D and R s as reference, whch A-pont les on the ffth metatarsal jont head and located at the feet of the length of 63.5%; B pont les on the frst metatarsal jont head at the feet of the length of 66.5%; and C- pont les on the heel stress ponts and s located at 8% of the feet length. O s heel heart and located at 18% of the feet length. Accordng to the physologcal characterstcs of feet soles, the reasonable soles curve force dstrbuton should meet the followng three ndcators: 1) Force s manly concentrated n the foot of the three major around force pont that Fgure 2 shows a non-force pont need to be avoded to become the center of the force; 2) Force area should be as large as possble n order to reduce the peak plantar force; 3) The dstrbuton of state need to meet the user's psychologcal percepton of comfort. The frst two of the above three features ensure the physologcal comfort, and the thrd s the guarantee for psychologcal comfort [5]. Due to the vagueness of psychologcal comfort ndcators, desgn optmzaton process need to be sampled under a certan capacty for expermental testng, furthermore, to obtan accurate statstcal data. In addton, the three characterstcs had restrctve relatonshp Therefore, ths s a hdden target mult-objectve optmzaton problem, the fnal reasonable soluton would be an ntegrated optmzaton results. 3. Last bottom curve optmzaton desgn method For one par of shoes that was talored for a partcular user, the most reasonable plantar curve morphology s very complex, and also s relatve to the mappng between specfc user and plantar morphology[4]. However, due to ndvdual dfferences and many morphologcal detals on the demographc characterstcs soles orented for publc users are fltered. The performance of optmal curve morphology s relatvely smple and smooth, and therefore lmted seres of parameters can be used to carry out a complete descrpton, the last-bottom curve optmzaton desgn method can be expressed as to control of these morphologcal parameters optmzaton [5][6]. Followng the mechancs analyss and expermental testng, the qualty of the last bottom curve of the shoe last s manly reflected by three characterstc parameters, the last bottom heel- heart crown, the forefeet crown and the last bottom arc (the last bottom arc depends on the bottom of the heart concavty) determned the last bottom curve morphology [7] [8]. We proposed the characterstc modelng technques to establsh a drvng relatonshp between the last bottom and three characterstc parameters wth the last bottom curve morphology resulted n Fgure 3. Fgure 3 The relatonshp between characterstc parameters and last bottom morphology Fgure 3 shows how the three-dmensonal model of the shoe last feature modelng software s establshed by usng three parameter varables sketches role whch are defned by heart crown, forefeet convexty and concavty of the bottom heart; through the external program to change the value of the three varables, the three varables was derved to modfy the model of the shoe last to gve the correspondng morphology. The process for last bottom optmzed desgn was shown n Fgure 4. 88

Fgure 4 Optmzed process of last bottom The last bottom curves was generated by the optmzed process, and test samples were also produced, use the dstrbuton of the contactng pressure to calculate the value of the three evaluaton values, and then, based on three ndcators comprehensve analyss, followng the parameters of the modfed program, the satsfed outputs were acqured that s the end of the program. 4. Optmze desgn process of last bottom curves 4.1. Contactng Pressure test The testng equpment for contactng pressure was provded by NOVEL company- Pedar nsole pressure system, the Pedar system s a very accurate and relable plantar measurement system to acqure pressure dstrbuton, the nsole type of desgn s partcularly sutable and quck enough for montorng foot-load, through calculatng 3-dmensonal pressure dstrbuton of foot-bottom and analyzng the foot contactng area, puttng each nsole of the system on 99 sensors, so that each part of the pressure by a color change to show the real-tme wreless nput measurement data usng Bluetooth technology, t can be drectly measured to get plantar pressure dstrbuton n the dfferent states. Pedar nsoles contactng pressure system outputs pressure dstrbuton fnally (Shown n Fgure 5). Fgure 5 Pedar nsoles contactng pressure system We collected 50 testees datum; a comfort degree form was sgned. After testng process above, contactng pressure dstrbuton and psychologcal comfort datum, evaluaton on curve of last bottom 89

was delvered [9]. In order to obtan the basc prncple concluson, the statstcal characterstcs of mult-user stuaton wll not be consdered. 4.2. Indces Calculatng The optmzaton process s a bass for the calculaton of the evaluaton ndex values and contnues to modfy the argument cycle. Due to the last bottom curve s optmzaton needs, we need to make the knd of shoes and try and get the pressure dstrbuton, so the optmzaton process can only be n the form of a sem-automated [10]. A) Calculaton of the pressure concentrated ponts Calculatng the contactng pressure of concentrated pont whle the frst assumed of a poston between the foot and the sole of the user's fxed reman are not relatve, by comparng the measured resultant contactng pressure poston wth the values of user s foot sze and the calculaton of pressure dstrbuton dagram, t can be determned that the contactng pressure of the centralzed pont n a reasonable locaton based on the devaton of the poston, and the sze of the force were formng a concentrated contactng pressure of the quanttatve evaluaton of the locaton relatve to the pont ndcators. The process was shown n Fgure 6. Fgure 6 process of calculatng errors for contactng pressure pont The ntegrated poston error weghted ndcators calculaton was to get the man contactng pressure of the foot ponts of the actual pressure based on the sze rato of person, and determne the weght coeffcent of the poston errors of each pont, and then, calculate a comprehensve quanttatve ndcator. Integrated poston error weghted ndex formula was shown n formula (1) as below: C 1 n 1 w L (1), where s a contactng pressure pont of foot, w s a weght coeffcent, s the devaton of the pressure dstrbuton of the soles-locaton of the pont and concentraton pont of foot, L s foot length Weght coeffcent- w was calculated by formula (2) as below: w n P j1 P j (2), where n j1 P pressure pont. j s the sum of each contactng pressure ponts of feet, P s the value of contactng 90

As the contnuous dstrbuton of soles contactng pressure, we need to calculate t after a certan algorthm processng, so that the entre sole dstrbuted contactng pressure was taken nto an equvalent several contactng pont of concentrated pressure. was calculated by formula(3) as below: 1 n S S, j n j 1 (3), where S s the - th coordnates of the locaton, S, js concentrated pont locaton follow the j - th frame of contactng pressure dstrbuton, n s the number of samplng frames. In experments desgn, by usng a frequency of 8Hz, soles dynamc contactng pressure dstrbuton dagram was tested under the person s walkng crcumstance, and then, for each frame contactng pressure dstrbuton dagram, the extreme pont was calculated. These extreme ponts were correspondng to the feet force concentraton ponts. Fnally, the devaton value of all frames was calculated by the average force concentraton pont. B) Area calculatng for contactng pressure Foot pressure dstrbuton s measured by 99 sensors. Statstcal value of pressure s the number of sensors whose output value s greater than zero. Lkewse, the mean pressure can also be easly calculated. Because of walkng, speed and other factors, and to ensure the experment result, the calculaton of the force area was calculated by usng pressure dstrbuton samplng under statonary uprght posture. The force area ndcators expressed n a dmensonless rato value,.e. by the force area and foot outer contour surrounded by the rato of the area. C) Psychologcal percepton of comfort calculatng Comfort s a subjectve amount of psychologcal percepton; t s dffcult to be accurate measured, but the shoes qualty and user acceptance s of tremendous mpact. The psychologcal percepton comfort obtaned by actve evaluaton examnee was measured after 20 mnutes of walkng to the normal speed under 2.5 km / h. The comfort degree s gven an evaluaton value from 0 to 1. 4.3. Comprehensve analyss Values of the three ndcators above-mentoned are processed under dmensonless form, and the maxmum s 1, so the last bottom curve under the optmzaton ndex may be expressed as formula (4) as below: T wc c wss wkk (4), where C, S, K represent the contactng pressure of concentrated pont, force area and psychologcal comfort respectvely, wc, ws, wk are weghted coeffcents subjected to wc ws wk 1 and accordng to the shoe-makng experence and the mportance of the dfferent, they are assgned to 0.3, 0.2 and 0.5 respectvely that relatve to our prevous works on comfort degree research, all these weghted are fnshed by experts. 5 Optmzed Desgn process on curve of last bottom Ths experment llustrated the last bottom curve optmzaton process under 50mm-heght shoes. The optmzaton results of each round of drect output a rapd prototypng machne, to make the shoe last model, and accordng to the sample shoes, system contnued to the next round of optmzaton calculaton automatcally. In order to accelerate the optmzaton speed, ths project used the general nteractve genetc algorthm (IGA), the basc flow of the three parameters was gven by random mnor adjustments, and system generated 6 shoe-last under ndvdual populatons. Optmzaton ndcators- 91

T has been tested and calculated as ftness value, and then select the parameters of the T value s greater crossover to generate the next batch program [11][12]. Curve based on nteractve genetc algorthm to optmze the desgn process was shown n Fgure 7. Start Determne sze of the foot Determne the parameters Last morphylogy Sample producton Genetc operator for parameters reconstructon Contactng pressure testng Evaluaton on ndces N Crteral Y Outputs Fgure 7 Interactve Genetc Algorthm based optmzed desgn of curve After 5-round optmzng, 3 models were selected and shown n Fgure 8. (a) (b) (c) Fgure 8 Parameters Optmzed Shoe-last Model Optmzed parameters for 3 models were shown n Table 1. Table 1. Optmzed parameters for 3 models C S K T a 0.881 0.659 0.93 0.8611 b c 0.892 0.647 0.94 0.867 0.896 0.655 0.94 0.870 92

6. Concluson and future works In ths paper, optmzaton method of shoe-last bottom curve desgn based on the evaluaton of the contactng pressure expermental data was ntroduced, the case study shows the effectveness of the proposed method, and t s also a pragmatc and relable desgn methods n shoe-last degn. Expermental results also proved that the actual effect of the method was satsfactory. But due to the relatvely small number of test samples, the data contans some certan errors; to obtan more accurate results, the number of samples must be ncreased, but ths wll also brng the cost ncreasng of expermental. How to effectvely mprove the optmzaton process, makng as lttle loop to get the optmal soluton s the next step works. 7. Reference [1] Ameersng Luxmon, Yan Luxmon, Shoe-last desgn nnovaton for better shoe fttng, Computers n Industry, Elsever, vol. 60, no. 8, pp. 621-628, 2009 [2] E. Dmas, D. Brassouls, 3D geometrc modellng based on NURBS: a revew, Advances n Engneerng Software, Elsever, vol. 30, no.9-11, pp.741-751, 1999 [3] Chung-Shng Wang, An analyss and evaluaton of ftness for shoe lasts and human feet, Computers n Industry, Elsever, vol. 61, no. 6, pp. 532-540, 2010 [4] Sung-Hwan Km, K-Hoon Shn, Wanjn Chung, A method for modfyng a surface model wth non-unformly scattered dsplacement constrants for shoe sole desgn, Advances n Engneerng Software, Elsever, vol. 39, no. 9, pp. 713-724, 2008 [5] Ishhara S, Ishhara K, Nagamach M, Matsubara Y. An analyss of Kanse structure on shoes usng self-organzng neural networks, Internatonal Journal of Industral Ergonomcs, Elsever, vol. 19, no. 2, pp. 93-104, 1997 [6] Fu Jng, Ajay Joneja, Ka Tang, Modelng wrnkles on smooth surfaces for footwear desgn, Computer-Aded Desgn, Elsever, vol. 37, no. 8, pp. 815-823, 2005 [7] Axel Hllmann, Deter Rosenbaum, Wnfred Wnkelmann, Plantar and dorsal feet loadng measurements n patents after rotaton plasty, Clncal Bomechancs, Elsever, vol. 15, pp. 359-364, 2000 [8] Pu W. Kong, Hendrk De Heer. Wearng the F-Scan moble n-shoe pressure measurement system alters gat characterstcs durng runnng. Gat & Posture, Elsever, vol. 29, pp. 143-145, 2009 [9] Vtor Tessutt, Francs Trombn-Souza, Ana Paula Rbero, Ana Luza Nunes, Isabel de Camargo Neves Sacco, In-shoe plantar pressure dstrbuton durng runnng on natural grass and asphalt n recreatonal runners, Journal of Scence and Medcne n Sport, Elsever, vol. 13, no. 1, pp. 151-155, 2010 [10] Sh Ka, Research on Mechancal Model of Vrtual Human-shoes System based on Fuzzy Assocaton Rule Mnng, n proceedngs of 2009 Internatonal Conference on Networkng and Dgtal Socety (ICNDS 2009), IEEE, pp. 296-299, 2009 [11] Gang L, Jngfa Lu, Zhaoxa Lu,,Yu Zheng, Genetc Algorthm wth Pull Moves for Foldng 2D Model Protens, Internatonal Journal of Dgtal Content Technology and ts Applcatons, AICIT, vol. 6, no. 21, pp. 412-418, 2012 [12] Ca Guoqang, Ja Lmn, Yang Janwe, Lu Habo, Improved Wavelet Neural Network Based on Hybrd Genetc Algorthm Applcatonn on Fault Dagnoss of Ralway Rollng Bearng, Internatonal Journal of Dgtal Content Technology and ts Applcatons, AICIT, vol. 4, no. 2, pp. 135-141, 2010 93