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다중노즐 3D프린터의 모니터링 시스템을 활용한 사용자 맞춤형 근골격계 재활기기 소재에 관한 연구
이선우(S. W. Lee),한현정(H. J. Han),최민석(M. S. Choi),이선곤(S. K. Lee),김주형(J. H. Kim),김용래(Y. R. Kim),권장우(J. W. Kwon) 한국재활복지공학회 2018 한국재활복지공학회 학술대회논문집 Vol.2018 No.4
In this paper we implement a remote monitoring system to create customized musculoskeletal rehabilitation devices, introduce the structures and properties of 3D printer filament materials which have the flexible tactile sensor entered into the rehabilitation equipment material with multiple nozzle 3D printers In addition, the material with the properties of the filament flexible tactile sensor proposed in this paper is a brittle and elastic material, and its length is adjusted by using a micro-stage within the elastic range limits, and the resistance value is measured and analyzed. As a result, the resistance increased up to 190%. As the experiment repeated, the conductive filament did not win the tension and was cut off, resulting in infinite divergence and disconnection of the electrode.
Depth Camera를 이용한 관절 가동 범위 측정에 대한 연구
안영샘(Y. S. Ahn),설현우(H. W. Seol),주성수(S. S. Joo),김원진(W. J. Kim),박은식(E. S. Park),권장우(J. W. Kwon) 한국재활복지공학회 2017 한국재활복지공학회 학술대회논문집 Vol.2017 No.4
In this paper, we investigated the range of joint motion using Kinect, a Depth Camera. Today, as patients interest in medical information grows, there is a need to show patients quantified data. In the current hospital, a physician uses a goniometer to measure the range of motion of a patient. However, due to limited workforce and the status of the patient within a limited period of time, there is a limit to efficiently inspect and treat patients. In order to provide efficient treatment, this paper proposes a measurement method of the range of motion of the limb using the Depth Camera. We used the program to measure more quickly than the conventional measurement method. The experimental result shows that the error is within 3% of the actual measurement method. In addition, using the Depth Camera, it is possible to store and manage the range of motion of the joints as quantified data.
재활 보조기기를 위한 FDM 3D프린팅 기반 PLA 출력물의 어닐링에 따른 최적화
김용래(Y. R. Kim),이선우(S. W. Lee),김주형(J. H. Kim),권장우(J. W. Kwon),이선곤(S. K. Lee) 한국재활복지공학회 2020 재활복지공학회논문지 Vol.14 No.1
3D프린터를 활용한 맞춤형 재활 기기를 제작하기 위해서 3D 프린팅으로 제작된 부품의 약한 기계적 강도와 내부 결함을 확인하기 어렵다는 점이 있다. 본 논문에서는 Poly Lactic Acid(PLA) 필라멘트를 이용하여 Fused Deposition Manufacturing(FDM) 3D프린터 출력 시 출력 온도와 출력속도, 적층 각도에 따른 기계적 강도에 미치는 영향을 인장실험을 통하여 알아보고 어닐링 방법을 통하여 기계적 강도 향상과 내부결함 판단법을 제안하고자 한다. 최적 출력 방법과 플라스틱 사출에서 주로 사용하는 어닐링 기법을 FDM 3D프린터에 적용하였고, 최적 어닐링 온도와 효과를 제안하였다. 이를 통해 맞춤형 재활 기기 제작 시 기계적 강도에 대한 이슈를 해결하고자 한다. 본 논문에서 제안하는 출력 조건은 온도 220℃ 출력 시 형상 오차가 적고 강도가 강했으며 어닐링 시 23%가 증가하였으며, 출력속도 10mm/s 시편의 강도가 가장 강했으며 어닐링 시 강도가 33% 증가하여 가장 효과가 크게 나타났다. 어닐링 온도로는 유리 전이온도 부근인 60℃에서는 모든 시편이 인장강도가 증가했으나, 결정화 온도근방인 105℃에서는 구조적 결함이 존재하는 출력물은 시편이 비틀림, 들뜸 현상에 의한 인장강도의 약화 현상이 발견되었다. 이러한 결과는 맞춤형 재활 기기 제작에서 높은 기계적 강도와 내부결함파악이 중요시 요구되는 부위에 제작되면 효과적으로 이용될 것이다. Major issues for manufacturing customized rehabilitation devices using 3D printers include weak mechanical strength and difficulty in identifying internal defects. In this paper the effect on the mechanical strength according to the printing temperature the printing speed, and the stacked angle of the FDM 3D printer was recognized through tensile experiment using PLA filament. In addition the optimal printing method and annealing technique which is used primarily in plastic injection, were applied to the FDM 3D printer, and the optimum annealing temperature and effect were recognized. This will solve the issue of mechanical strength in the manufacture of customized rehabilitation devices. The printing conditions proposed in this paper showed the greatest effect with low shape error and strong strength at 220℃ printing temperature, 23% increase in annealing, and 33% increase in annealing of 10mm/s specimen. The tensile strength of all specimens was increased at 60℃ near glass transition temperature, but at 105℃, crystallization temperature, the output with structural defects was twisted and the tensile strength was weakened by lifting phenomena. These results will be effectively used when high mechanical strength and internal defect fractures are made in the production of custom rehabilitation devices.
Pre-processing을 위한 CT MRI Registration에 대한 연구
안영샘(Y. S. Ahn),권장우(J. W. Kwon) 한국재활복지공학회 2018 한국재활복지공학회 학술대회논문집 Vol.2018 No.4
In this paper, there are more than 10 million people with cerebrovascular diseases worldwide, and this trend is steadily increasing. Especially in developed countries, patients with cerebrovascular disease are the leading cause of death rate, along with cancer and heart disease. Cerebrovascular disease requires ongoing management because the after-effect remains chronic, and the patient`s condition as well as condition on surface must be followed up with a radiological device. Since there is no way to see inside the skull with an X-ray, we need to check the patient`s condition using CT or MRI device. Even though the same Dicom file is the output, the resolution for each of the MRI and CT and the FOV is different, so it is necessary to manually adjust the size and to set it in order to compare at a glance. Therefore, even if doctors directly shoot with CT and MRI devices, there is a probability of making mistakes if they manually adjust the image, adjust to the image. Moreover, it would require a lot of work. To solve this problem, GAN (Generative Adversarial Networks) has been used to modulate MRI into CT through Deep Learning, which is one of the artificial intelligence technologies that has developed as the symbol of fourth industrial revolution era, giving the world a ripple effect. The same resolution and the same environment are assumed in this process. In order to create such DataSet, a pre-processing has to be done manually by a person, so that work can be performed. We conducted research to replace the uncertainly matched tasks by using the CT and MRI registration software with the existing CT and MRI images without conversion or by registering them after the output operation. Experimental results confirmed that the initial values of CT and MRI cannot be accurately registered for various reasons, and this software was proved necessary. In the future, this software can be applied to application image processing such as registration through Canny Edge Detection, Blur, Sift, and SURF image processing, mathematical algorithm, automatic image registration through machine learning and deep running. I will study further to make it more convenient.