• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.323-329
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• 2016

This paper describes an insole FFO(Functional Foot Orthosis) model for comfortable walking by considering weight distribution. There are many ways to make an insole FFO model such as using 3D computer graphics, or plaster manually. Thus, we proposed a standardized way to make an insole model, specifically called, robust and automatically personalized deformable insole model. Our proposed method showed 0.8cm average error compared between our proposed auto-deformable insole model and the other insole model manually deformed by experts. Therefore, our proposed method can be an efficient way to make a customized insole model with small error compared to the manually customized insole model.

• Journal of Biomedical Engineering Research
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• v.34 no.2
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• pp.80-90
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• 2013

Recently, functional insoles of wedge-type it is for the young to raise their height inserted between insole and heel cause foot pain and disease. Additionally, these have a problem with stability and excessively load-bearing during gait like high-heel shoes. In this study, we compared the changes in biomechanical characteristics of foot with different insole thickness then we will utilize for the development of the insole with the purpose of relieving the pain and disease. Subjects(male, n = 6) measured COP(center of pressure) and PCP(peak contact pressure) on the treadmill(140cm/s) using F-scan system and different insole thickness(0~50 mm) between sole and plantar surface during gait. Also, we computed changes of stresses at the foot using finite element model with various insole thickness during toe-off phase. COP moved anterior and medial direction and, PCP was increased at medial forefoot surface, $1^{st}$ and $2^{nd}$ metatarsophalangeal, ($9%{\uparrow}$) with thicker insoles and it was show sensitive increment as the insole thickness was increased from 40 mm to 50 mm. Change of the stress at the soft-tissue of plantar surface, $1^{st}$ metatarsal head represents rapid growth($36%{\uparrow}$). Also, lateral moments were increased over the 100% near the $1^{st}$ metatarsal as the insole thickness was increased from 0 mm to 30 mm. And it is show sensitive increment as the insole thickness changed 10 mm to 20 mm. As a result, it was expected that use of excessively thick insoles might cause unwanted foot pain at the forefoot region. Therefore, insole thickness under 30 mm was selected.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.12
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• pp.1065-1072
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• 2015

This paper is about the development of an insole sensor system that can determine the model of an exoskeleton robot for lower limb that is a multi-degree of freedom system. First, the study analyzed the kinematic model of an exoskeleton robot for the lower limb that changes according to the gait phase detection of a human. Based on the ground reaction force (GRF), which is generated when walking, to proceed with insole sensor development, the sensing type, location, and the number of sensors were selected. The center of pressure (COP) of the human foot was understood first, prior to the development of algorithm. Using the COP, an algorithm was developed that is capable of detecting the gait phase with small number of sensors. An experiment at 3 km/h speed was conducted on the developed sensor system to evaluate the developed insole sensor system and the gait phase detection algorithm.

• The Research Journal of the Costume Culture
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• v.25 no.3
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• pp.270-284
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• 2017

This study aimed to create 3D-printed insoles for flat-footed senior men using 3D systems. 3D systems are product-manufacturing systems that use 3-dimensional technologies like 3D scanning, 3D modeling, and 3D printing. This study used a 3D scanner (NexScan2), 3D CAD programs including Rapidform, AutoCAD, SolidWorks, Nauta+ compiling program, and a 3D printer. In order to create insoles for flat-footed senior men, we analyzed horizontal sections of 3D foot scans We selected 20 flat-footed and 20 normal-footed subjects. To make the 3D insole models, we sliced nine lines on the surface of the subjects' 3D foot scans, and plotted 144 points on the lines. We calculated the average of these 3D coordinates, then located this average within the 3D space of the AutoCAD program and created 3D sole models using the loft surface tools of the SolidWorks program. The sole models for flat feet differed from those of normal feet in the depth of the arch at the inner sideline and the big toe line. We placed the normal-footed sole model on a flat-footed sole model, and the combination of the two models resulted in the 3D insole for flat feet. We printed the 3D modeled insole using a 3D printer. The 3D printing material was an acrylic resin similar to rubber. This made the insole model flexible and wearable. This study utilized 3D systems to create 3D insoles for flat-footed seniors and this process can be applied to manufacture other items in the fashion industry as well.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.122-125
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• 2008

Even though many researchers studied the foot shape and dimension, those applications lacked. The purpose of this study was to develop insole pattern of elderly women according to footprint. Discrepancy in the classification criteria among of foot parameters complicates attempts for elderly women classification of foot sole. To develop a footprint-based classification technique for the classification of foot sole types by allowing simultaneous use of several parameters. Foot sole data from static standing footprints were recorded from 48 elderly women. The factors of footprint shape were determined. Cluster analysis was applied to obtain individual foot sole classifications. The classification model of foot insole is proposed for a classification of footprint in elderly women. An application of ANOVA, Duncan's analysis, frequency analysis, factor analysis, and cluster analysis have been made to footprint data. In order to make clear foot sole characteristics, the factors of footprint shape have been discussed. The results are as follows. The factors of footprint shape have been classified into four types: foot length, sole slope, outside sole slope, and foot width. The types of foot sole shape have been classified into four types: longed, shortened, outside sloped, and toes sloped.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.317-320
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• 2021

본 연구는 주기적인 알츠하이머 병의 중증도 모니터링을 위해 스마트 인솔을 통한 보행 특징 추출과 머신러닝 기반 중증도 분류의 성능에 대해 살펴보았다. 최근 고령화가 가속화되는 추세에 있어 치매 환자가 급증하고 있으며, 중증도가 심해질수록 필요한 치료 비용 및 노력이 급증하기 때문에 조기 진단이 최선의 치료 전략으로 보여진다. 환자 친화적이고 저비용의 관성 측정 장치가 내장된 스마트 인솔만을 사용하여 다양한 보행 실험 패러다임에서 환자의 보행 특징을 추출하고, 이를 알츠하이머 병의 중증도 진단을 위한 머신러닝 기반 분류기를 훈련시켜 성능을 평가한 결과, 숫자세기와 같이 뇌에 부하를 주는 하위 작업이 포함된 복합 보행을 측정한 데이터셋을 사용하여 훈련된 분류 모델이 일반 걷기 데이터셋을 사용한 모델보다 성능이 높게 나타나는 것이 관찰되었다. 본 연구는 안전하고 환경적 제약이 적은 방법을 사용하여 시기 적절한 진단뿐만 아니라 주기적인 중증도 모니터링 시스템의 일환으로 활용될 수 있을 것이다.