• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.2(A)
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• pp.133-134
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• 2010

• 대한정형도수물리치료학회지
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• 제2권1호
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• pp.9-19
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• 1996

지금까지의 내용을 요약하면 먼저, 인체의 각 관절 주위에는 관절의 움직임과 위치를 파악하는 감지기 역할을 하는 기계적 감수기가 있다. 이러한 감수기는 크게 네가지로 구분되어지는데 대개 I 형 감수기, II 형 감수기 등의 용어를 사용한다. 각각의 감수기의 특성(표 2.)을 알아보면, 루피니(Ruffini)감각기와 유사한 모양을 하고 있는 I 형 관절감수기는 주로 운동의 속도(speed)와 방향(direction)을 감지(detection)하며, 파시니안(Pacinian)감각기와 유사한 형태를 하고 있는 II 형 관절감수기는 매우 작은 움직임에 대한 감지를 하는데, 예를 들어 속도가 가속(acceleration)되는 것과 같은 움직임 등을 알아낸다. 이외에 골지건과 비슷한 모습을 하고 있는 II 형 관절감수기는 운동의 자세(position)와 방향에 대한 정보를 전달하게 된다. 관절의 자세 유지 혹은 안정성 즉, 정적(static) 운동에 주로 관여하는 I 형 관절감수기와, 역동적(dynamic)인 운동에 감지를 주로하는 II 형 관절감수기는 진동(oscillation)자극에 잘 촉진된다. 이러한 자극은 동통이 심하게 발생된 관절에 나타나는 근육의 과긴장(hypertonicity)과 동통을 경감시킬 수 있다. III 형 관절감수기는 억제(inhibitory)감수기라 할수 있는데, 골지건(Golgi tendon organ)의 기능과 매우 관련이 깊다. 이 감수기는 관절의 가동범위를 기계적인 자극으로 증가시키기 위해 관절의 가동 끝범위에서 강한 신장(strong stretch)이나 thrust 기술로 감수기를 촉진할 수 있다. 이러한 자극은 결국 근육에 이완을 얻게 할 수 있다. 위에서 언급한 관절 주위의 조직에 분포한 특별한 기계적 감지를 환자들의 임상 중상에 따라 선택적으로 자극하는 치료를 적용할 수 있다면, 현재 물리치료사들이 적용하고 있는 관절 가동운동을 좀 더 전문적인 수준으로 수행할 수 있을 것이다.

• 대한의용생체공학회:의공학회지
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• 제14권3호
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• pp.235-242
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• 1993

In the early stage of sacroilitis, it is'difficult to detect sacroiliac(Sl) abnormalities by conventional plain X-ray even though there are characteristic symptoms of ankylosing spondylitis. 3 dimensional volume rendering from the CT image was performed to make an early de tection of the structural changes of Sl joint. 2 cases who had clinical impression of ankylosing spondylitis without sacroilitis in plane X-ray and 1 case of typical ankylosing spondylitis as well as 1 case of normal control were studied. The Sl Joints were separated and each joint surface of sacrum and ilium was independently reconstructed by a special 3D manipulation program. All 2 patiant who complained of inflammatory lower back pain with no abnormal findings in the plain X-ray showed structural changes in 3 dimensionally reconstructed surface Image of the Sl joint compared to the normal control. Authors tried several parameters, such as fourler analysis of each surface and the mean and variance of Sl joint gap. We couldn't tell the statistical significance because of the limited number of cases. However, the parameters showed difference according to the progression of disease.

• International Journal of Korean Welding Society
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• 제2권2호
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• pp.51-56
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• 2002

The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement sensor and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal I-butt joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor was determined far the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 ㎜, and it was revealed that the system has excellent seam tracking ability for the I-butt joint of sheet metal.

• 대한간호학회지
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• 제35권1호
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• pp.5-15
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• 2005

Purpose: This study was conducted to develop a behavioral checklist to predict an autistic disorder and to identify the earliest detecting time. Method: One hundred and fifty eight children including normal, autistic, institutionalized normal, and retarded were assessed using critical interaction behavioral markers from literature review. Data was collected by semi-structured mother-child interaction by videotape recording and analyzed byfactor analysis, Cronbach a, Kappa, $x^2$, and Duncan. Result: Ten behavioral markers were sorted into 2 factors; joint-attention and synchronized behavior. Autistic children were impaired in pretend play, odeclarative pointing, proimperative pointing, gaze-monitoring, referential looking, showing, joint-attention, rhythmical vocal exchange, and synchronized laughing. The sychronized behavior was also a critical marker to predict the autistic disorder. However, it was difficult to differentiate autistic disorder from mental retardation. In addition, the appropriate detecting time was around 18 months after birth. Conclusion: This checklist should be behavior markers to predict autistic disorder and could be useful as educational material at children's clinics, parents class, and for caregivers in the health center. In addition, early detection should lead to treatment being started as soon after 18 months of age as possible.

• 대한임베디드공학회논문지
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• 제18권2호
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• 산업경영시스템학회지
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• 제46권3호
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• pp.268-274
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• 2023

Image mosaicking is one of the basic and important technologies in the field of application using images. The key of image mosaicking is to extract seamlines from a joint image. The method proposed in this paper for image mosaicking is as follows. The feature points of the images to be joined are extracted and the joining form between the two images is identified. A reference position for detection the seamlines were selected according to the joint form, and an image pyramid was created for efficient image processing. The outlines of the image including buildings and roads are extracted from the overlapping area with low resolution, and the seamlines are determined by considering the components of the outlines. Based on this, the seamlines in the high-resolution image was re-searched and finally the seamline for image mosaicking was determined. In addition, in order to minimize color distortion of the image with the determined seamline, a method of improving the quality of the mosaic image by fine correction of the mosaic area was applied. It was confirmed that the quality of the seamline extraction results applying the method proposed was reasonable.

• 로봇학회논문지
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• 제12권3호
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• pp.258-262
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• 2017

In this paper, we propose a new collision detection algorithm for human-robot collaboration. We use an IMU sensor located at the tip of the manipulator and the kinematic behavior of the manipulator to detect the unexpected collision between the robotic manipulator and environment. Unlike other method, the developed algorithm uses only the kinematic relationship between the manipulator joint and the end effector. Therefore, the collision estimation signal is not affected by the error of the dynamics model. The proposed collision detection algorithm detects the collision by comparing the estimated acceleration of the end effector derived from the position, velocity and acceleration trajectories of the robot joints with the actual acceleration measured by the sensor. In simulation, we compare the performance of our method with the conventional Residual Observer (ROB). Our method is less sensitive to the load variation because of the independency on the dynamic modeling of the manipulator.

• 한국통신학회논문지
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• 제33권4A호
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• pp.426-433
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• 2008

In this paper, we present a method to improve the performance of the four transmit antenna quasi-orthogonal space-time block code (STBC) in the coded system. For the four transmit antenna case, the quasi-orthogonal STBC consists of two symbol groups which are orthogonal to each other, but intra group symbols are not. In uncoded system with the matched filter detection, constellation rotation can improve the performance. However, in coded systems, its gain is absorbed by the coding gain especially for lower rate code. We propose an iterative decoding method to improve the performance of quasi-orthogonal codes in coded systems. With conventional quasi-orthogonal STBC detection, the joint ML detection can be improved by iterative processing between the demapper and the decoder. Simulation results shows that the performance improvement is about 2dB at 1% frame error rate.

• ETRI Journal
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• 제45권6호
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.