• 제목/요약/키워드: Artificial motion

검색결과 396건 처리시간 0.031초

인공 추간판 적용으로 인한 인접 운동 분절의 영향 (Effects on the Adjacent Motion Segments according to the Artificial Disc Insertion)

  • 김영은;윤상석
    • 한국정밀공학회지
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    • 제24권8호통권197호
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    • pp.122-129
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    • 2007
  • To evaluate the effect of artificial disc implantation and fusion on the biomechanics of adjacent motion segment, a nonlinear three-dimensional finite element model of whole lumbar spine (L1-S1) was developed. Biomechanical analysis was performed for two different types of artificial disc, ProDisc and SB $Charit{\acute{e}}$ III model, inserted at L4-L5 level and these results were also compared with fusion case. Angular motion of vertebral body, forces on the spinal ligaments and facet joint under sagittal plane loading with a compressive preload of 150 N at a nonlinear three-dimensional finite element model of Ll-S1 were compared. The implant did not significantly alter the kinematics of the motion segment adjacent to the instrumented level. However, $Charit{\acute{e}}$ III model tend to decrease its motion on the adjacent levels, especially in extension motion. Contrast to motion and ligament force changes, facet contact forces were increased in the adjacent levels as well as implanted level for constrained instantaneous center of rotation model, i.e. ProDisc model.

스포츠 현장에서 인공지능 활용 방안 (Utilization of Artificial Intelligence in the Sports Field)

  • Yang, Jeong Ok;Lee, Jook Sook
    • 한국운동역학회지
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    • 제32권3호
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    • pp.69-79
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    • 2022
  • Objective: The purpose of this study is to analyze trends related to sports and artificial intelligence (AI) to understand the trends and how they change according to time, and to establish methods to apply AI in sports. Both macro and micro perspectives related to sports utilization of AI were analyzed. Method: In this study, after analyzing and discussing various information related to the use of artificial intelligence in the sports through a search of academic journals, papers, books, and websites published recently at nationally and internationally, the application plan of artificial intelligence in the sports field was presented. Results: 1) Motion analysis technology using artificial intelligence is effective in sports where posture is important, and if it provides systematic feedback and training methods, it can help improve performance. 2) The introduction of a sports referee judgment system using artificial intelligence is expected to improve performance by restoring factual judgment and objective fairness in sports games. 3) Artificial intelligence will provide coaching staff and players with a variety of information to help improve performance through systematic coaching and improving feedback and enhanced training methods. 4) It is judged that artificial intelligence-related to sports ethics, sports ICT, sports marketing, sports prediction, etc. We think that based on the current AI research trends will have a positive impact on all sports-related areas, helping to revitalize sports. Conclusion: Motion analysis technology using artificial intelligence, sports referee judgment system, coaching using artificial intelligence, and artificial intelligence are judged to have a positive effect on all sports-related areas and help revitalize sports.

Application of neural networks and an adapted wavelet packet for generating artificial ground motion

  • Asadi, A.;Fadavi, M.;Bagheri, A.;Ghodrati Amiri, G.
    • Structural Engineering and Mechanics
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    • 제37권6호
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    • pp.575-592
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    • 2011
  • For seismic resistant design of critical structures, a dynamic analysis, either response spectrum or time history is frequently required. Owing to the lack of recorded data and the randomness of earthquake ground motion that may be experienced by structure in the future, usually it is difficult to obtain recorded data which fit the requirements (site type, epicenteral distance, etc.) well. Therefore, the artificial seismic records are widely used in seismic designs, verification of seismic capacity and seismic assessment of structures. The purpose of this paper is to develop a numerical method using Artificial Neural Network (ANN) and wavelet packet transform in best basis method which is presented for the decomposition of artificial earthquake records consistent with any arbitrarily specified target response spectra requirements. The ground motion has been modeled as a non-stationary process using wavelet packet. This study shows that the procedure using ANN-based models and wavelet packets in best-basis method are applicable to generate artificial earthquakes compatible with any response spectra. Several numerical examples are given to verify the developed model.

순간중심 고정식 및 이동식 인공디스크 적용에 대한 유한요소 모델을 이용한 생체역학적 분석 (Biomechanical Analysis of the Implanted Constrained and Unconstrained ICR Types of Artificial Disc using FE Model)

  • 윤상석;정상기;김영은
    • 한국정밀공학회지
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    • 제23권4호
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    • pp.176-182
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    • 2006
  • Although several artificial disc designs have been developed for the treatment of discogenic low back pain, biomechanical changes with its implantation were rarely studied. To evaluate the effect of artificial disc implantation on the biomechanics of functional spinal unit, a nonlinear three-dimensional finite element model of L4-L5 was developed with 1-mm CT scan data. Biomechanical analysis was performed for two different types of artificial disc having constrained and unconstrained instant center of rotation(ICR), ProDisc and SB Charite III model. The implanted model predictions were compared with that of intact model. Angular motion of vertebral body, forces on the spinal ligaments and facet joint, and stress distribution of vertebral endplate for flexion-extension, lateral bending, and axial rotation with a compressive preload of 400N were compared. The implanted model showed increased flexion-extension range of motion compared to that of intact model. Under 6Nm moment, the range of motion were 140%, 170% and 200% of intact in SB Charite III model and 133%, 137%, and 138% in ProDisc model. The increased stress distribution on vertebral endplate for implanted cases could be able to explain the heterotopic ossification around vertebral body in clinical observation. As a result of this study, it is obvious that implanted segment with artificial disc suffers from increased motion and stress that can result in accelerated degenerated change of surrounding structure. Unconstrained ICR model showed increased in motion but less stress in the implanted segment than constrained model.

Prediction of Motion State of a Docking Small Planing Ship using Artificial Neural Network

  • Hoang Thien Vu;Thi Thanh Diep Nguyen;Hyeon Kyu Yoon
    • 한국항해항만학회지
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    • 제48권2호
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    • pp.116-124
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    • 2024
  • Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

움직임 기반 진단 및 치료 평가를 위한 인공폐결절 개발 (Development of Artificial Pulmonary Nodule for Evaluation of Motion on Diagnostic Imaging and Radiotherapy)

  • 우상근;박노운;박승우;유정우;한수철;이승준;김경민;강주현;지영훈;엄기동
    • 한국의학물리학회지:의학물리
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    • 제24권1호
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    • pp.76-83
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    • 2013
  • 진단 및 치료분야에서 호흡 움직임이 미치는 영향에 대한 연구는 외부 움직임을 관찰하여 실시되었으나, 이러한 외부 움직임은 내부 장기의 실제 움직임을 반영하지 못한다. 이에 본 연구에서는 개의 흉부 내 비침습적 이식이 가능한 인공 폐결절을 제작하여 동물실험에 대한 적용가능성을 확인하고 PET 영상 획득 및 방사선조사 시 움직임의 영향을 평가하고자하였다. 인공폐결절은 8 Fr 일회용 위장용 영양공급튜브를 개조하여 제작하였다. 제작된 결절모델은 마취된 개 4마리에 기관을 경유하여 기관지에 삽입한 뒤 방사선투시장치를 이용하여 위치를 확인하였다. PET 촬영용 인공폐결절은 내강에 $^{18}F$-FDG를 주입한 뒤 호흡운동 모사체에 장착하여 정지 상태, 10 rpm과 15 rpm의 종축 왕복운동간 PET 촬영을 실시하였다. 방사선조사용 인공폐결절은 유리선량계를 이식한 뒤 PET 촬영 시와 동일한 호흡운동 모사체에 장착하여 정지 상태, 10 rpm과 15 rpm의 종축 왕복운동간 1 Gy 선량을 조사하였다. 인공폐결절은 방사선투시장치 영상에서 실험동물의 후엽 근위부 세기관지에 이식되며 호흡에 따라 결절의 위치가 변화함을 확인하였다. PET 영상에서의 인공폐결절은 모사된 호흡 움직임에 따라 움직임에 의한 인공산물을 나타내었으며, 호흡동조게이트 시 SNR은 7.21로 기준영상의 SNR 10.15에 비해 감소하였으나 프로파일상 게이트영상의 영상계수는 정적영상에 비해 기준영상과 유사하여 PET 영상의 질을 개선함을 확인하였다. 방사선조사 실험간 인공폐결절 내 삽입된 유리선량계에 조사된 조사선량은 정지 상태와 10 rpm의 종축 왕복운동에서 0.91 Gy로 차이를 보이지 않았으나, 15 rpm의 종축 왕복운동에서 0.90 Gy로 오차범위 내 감소를 나타내었으며, 이온 전리함을 통한 조사선량 검출에서도 근소한 감소를 나타내었다. 본 실험에서 제작된 인공폐결절은 실험동물의 후엽 근위부 세기관지에 높은 재현성을 보이며 방사선투시 영상에서 폐의 내부 움직임을 반영하였다. PET 영상 내 움직임에 의한 인공산물이 관찰되며, 방사선 조사연구에서는 호흡운동이 미약한 영상 흐림을 일으킴을 확인하였다. 따라서 본 인공폐결절은 진단 및 치료분야에서 실험동물을 이용한 움직임 기반 진단 및 치료 평가에 유용한 도구로 사용될 것으로 기대된다.

웨어러블 센서를 활용한 경량 인공신경망 기반 손동작 인식기술 (A Light-weight ANN-based Hand Motion Recognition Using a Wearable Sensor)

  • 이형규
    • 대한임베디드공학회논문지
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    • 제17권4호
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    • pp.229-237
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    • 2022
  • Motion recognition is very useful for implementing an intuitive HMI (Human-Machine Interface). In particular, hands are the body parts that can move most precisely with relatively small portion of energy. Thus hand motion has been used as an efficient communication interface with other persons or machines. In this paper, we design and implement a light-weight ANN (Artificial Neural Network)-based hand motion recognition using a state-of-the-art flex sensor. The proposed design consists of data collection from a wearable flex sensor, preprocessing filters, and a light-weight NN (Neural Network) classifier. For verifying the performance and functionality of the proposed design, we implement it on a low-end embedded device. Finally, our experiments and prototype implementation demonstrate that the accuracy of the proposed hand motion recognition achieves up to 98.7%.

인공디스크에 대한 생체역학적 분석 (Biomechanical Analysis of the Artificial Discs)

  • 김영은;윤상석;정상기
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.907-910
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    • 2005
  • Although several artificial disc designs have been developed for the treatment of discogenic low back pain, biomechanical change with its implantation was rarely studied. To evaluate the effect of artificial disc implantation on the biomechanics of functional spinal unit, nonlinear three-dimensional finite element model of L4-L5 was developed with 1-mm CT scan data. Two models implanted with artificial discs, SB $Charit\acute{e}$ or Prodisc, via anterior approach were also developed. The implanted model predictions were compared with that of intact model. Angular motion of vertebral body, force on spinal ligaments and facet joint, and the stress distribution of vertebral endplate for flexion-extension, lateral bending, and axial rotation with a compressive preload of 400 N were compared. The implanted model showed increased flexion-extension range of motion and increased force in the vertically oriented ligaments, such as ligamentum flavum, supraspinous ligament and interspinous ligament. The increase of facet contact force on extension were greater in implanted models. The incresed stress distribution on vertebral endplate for implanted cases indicated that additinal bone growth around vertebral body and this is matched well with clinical observation. With axial rotation moment, relatively less axial rotation were observed in SB $Charit\acute{e}$ model than in ProDisc model.

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표면 근전도를 이용한 Artificial Neural Network 기반의 동작 분류 알고리즘 (Artificial Neural Network based Motion Classification Algorithm using Surface Electromyogram)

  • 정의철;김서준;송영록;이상민
    • 재활복지공학회논문지
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    • 제6권1호
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    • pp.67-73
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    • 2012
  • 본 논문에서는 표면 근전도 신호를 사용하여 손목 움직임의 동작을 분류하기 위해 인공 신경 회로망(ANN : Artificial Neural Network)기반의 동작 분류 알고리즘을 제안한다. 손목 움직임에 무리가 없는 20~30대 성인 26명을 대상으로 척측 수근 굴근과 척측 수근 신근에 부착한 2채널의 전극으로부터 표면 근전도 신호를 취득하고, 취득한 근전도로부터 손목의 굴곡, 신전, 내전, 외전, 휴식 다섯 동작을 인식한다. 빠른 처리 속도를 위해 획득한 신호로부터 시간 영역에서의 특징점을 추출하고 ANN을 이용한 동작 분류에 사용된다. 특징점으로 DAMV, DASDV, MAV, RMS를 사용하였으며, ANN 기반의 동작 분류의 인식율은 DAMV는 98.03%, DASDV는 97.97%, MAV는 96.95%, 그리고 RMS는 96.82%의 정확도를 나타낸다.

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Hybrid Model-Based Motion Recognition for Smartphone Users

  • Shin, Beomju;Kim, Chulki;Kim, Jae Hun;Lee, Seok;Kee, Changdon;Lee, Taikjin
    • ETRI Journal
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    • 제36권6호
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    • pp.1016-1022
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    • 2014
  • This paper presents a hybrid model solution for user motion recognition. The use of a single classifier in motion recognition models does not guarantee a high recognition rate. To enhance the motion recognition rate, a hybrid model consisting of decision trees and artificial neural networks is proposed. We define six user motions commonly performed in an indoor environment. To demonstrate the performance of the proposed model, we conduct a real field test with ten subjects (five males and five females). Experimental results show that the proposed model provides a more accurate recognition rate compared to that of other single classifiers.