• Journal of International Academy of Physical Therapy Research
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• v.3 no.1
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• pp.364-369
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• 2012

The purpose of this study was to analyze lower limb muscle activity and 3D motion analysis according to change foot arch height during walking. We selected 9 young and healthy people who have been normal foot. And we selected 7 young and healthy people who have been flatfoot. So, people were divided into 2 groups and walked platform during 2 minutes twice for checked by 3D motion analysis. These data were characterized by EMG measurements of three muscles( tibialis anterior, medial and lateral gastrocnemius) while they were walking. The collected data were analyzed by Independent t test using the SPSS statistics program(Ver 12.0). In foot arch change, there were no significant difference in three muscles 3D motion analysis also found that there were no significant difference in joint angles. In this study was to analyze lower limb muscle activity and 3D motion analysis according to change foot arch, but there were no significant difference in 6 muscles neither joint angles.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.444-451
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• 2005

The analysis of human arm motion during steering maneuver is carried out for investigation of man-machine interface of driver and steering system Each arm is modeled as interconnection of upper arm, lower arm, and hand by rotational joints that can properly represents permissible joint motion, and both arms are connected to a steering wheel through spring and damper at the contact points. The joint motion law during steering motion is determined through the measurement of each arm movement, and subsequent inverse kinematic analysis. Combining the joint motion law and inverse dynamic analysis, joint stiffness of arm is estimated. Arm dynamic analysis model for steering maneuver is setup, and is validated through the comparison with experimentally measured data, which shows relatively good agreement. To demonstrate the usefulness of the arm model, it is applied to study the effect of steering column angle on the steering motion.

• Smart Media Journal
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• v.13 no.4
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• pp.16-22
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• 2024

Pitching is a major part of baseball, so much so that it can be said to be the beginning of baseball. Analysis of accurate pitching motions is very important in terms of performance improvement and injury prevention. When analyzing the correct pitching motion, the currently used motion capture method has several critical environmental drawbacks. In this paper, we propose analysis of pitching motion using the RGB-based Human Pose Estimation (HPE) model to replace motion capture, which has these shortcomings, and use motion capture data and HPE data to verify its reliability. The similarity of the two data was verified by comparing joint coordinates using the Dynamic Time Warping (DTW) algorithm.

• Journal of Sensor Science and Technology
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• v.5 no.4
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• pp.57-70
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• 1996

Motion can be estimated continuously from each sensor through the analysis of the instantaneous states of an object. This paper is aimed to introduce a method to estimate the general 3D motion of a planar object from the instantaneous states of an object using multi-sensor data fusion. The instantaneous states of an object is estimated using the linear feedback estimation algorithm. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown planar object. We present a fusion algorithm which combines averaging and deciding. With the assumption that the motion is smooth, the approach can handle the data sequences from multiple sensors with different sampling times. Simulation results show proposed algorithm is advantageous in terms of accuracy, speed, and versatility.

• Physical Therapy Korea
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• v.13 no.1
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• pp.54-60
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• 2006

This study aimed to compare movement patterns of shoulder joints between the right and left symmetry in stroke patients and control subjects. This study proposes use of the voluntary response index (VRI) calculated from quantitative analysis of surface electromyographic (sEMG) and motion data recorded during voluntary movement as a feeding task. The VRI is comprised of two numeric values, one derived from the total muscle activity recorded for the voluntary motor task (magnitude), and the other from the sEMG distribution across the recorded muscles with the similarity index (SI). Five stroke patients and five age-matched healthy controls were recruited. Feeding motion was performed using the provided spoon five times with rests taken on a chair in between tasks. EMG data were digitized and analyzed on the basis of the root mean square (RMS) envelope of activity. The average amplitude of responses was calculated. Responsiveness and clinically meaningful levels of discrimination between stroke patients and control for EMG magnitude and SI were determined. The similarity index of the results from two successive examinations of both sides apart for stroke patients and control subjects were .86 and .95 in motion analysis and .84 and .99 in electromyographic analysis. The SI of sEMG data and motion data was significantly correlated in stroke patients. The data suggest that SI is a sensitive program for comparing and analyzing the symmetry of muscle activity and motion in both sides. This analysis method has a clinical value in grading muscular activity and movement impairment after brain injury.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.52-54
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• 2021

In this paper we propose a method predict whether a video frame contains motion according to the invoking situation of the coding unit mode in HEVC. The motion prediction of video frames is conducive for use in video compression and video data extraction. In the existing technology, motion prediction is usually performed by high complexity computer vision technology. However, we proposed to analyze the motion frame based on HEVC coding unit mode which does not need to use the static background frame. And the prediction accuracy rate of motion frame analysis by our method has exceeded 80%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.969-975
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• 2002

Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.938-958
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• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1245-1248
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• 2004

This paper presents a new technique to analyze data on the coordinate x, y, z and apply these data to design the motion control to improve the efficiency of the engraving machine so that it can engrave accordingly in 3 dimensions. First, the tool path on the x-y plane is analyzed to be synchronized with the z-axis. The digital data is then sent to the motion control to guide the movement of the engrave point on the x-y plane. Tool path moves along the x-axis with zero degree and different values of the y-axis according to the coordinate of the digital data and the analysis along z-axis to determine the depth for engraving. The depth can be specified from the gray level with the 256 levels of resolution. The data obtained includes the distances on x-axis, y-axis, and z-axis, the acceleration of the engrave point's movement, and the speed of the engrave point's movement. These data is then transfered to the motion control to guide the movement of the engrave point along the z-axis associated with the x-y plane. The results indicate that engraving using this technique is fast and continuous. The specimen obtained looks perfect in 3D view.

• Fashion & Textile Research Journal
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• v.18 no.3
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• pp.338-350
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• 2016

The purpose of this study is to analyze joint angle for a range of swing motion derived through 3D motion analysis in order to design the ergonomic golf wear, use it for evaluation method of apparel fit to improve exercise functionality and provide the basic materials necessary for designing clothes. In order to do this, the subjects for this study were 3 men of age 20s. The data for a range of motion of golf swing were collected by using equipment for 3D motion analysis and then were used for analysis of joint angles and evaluation method of apparel fit. Range of motion was derived through 3D motion analysis of golf swing motion and joint angles for items of joint motion item and of X, Y, and Z-axis were calculated, respectively. In order to set the evaluation questions for evaluation of apparel fit, to find a range of motion at the maximal value and the minimal value of swing motion. As a result, during the swinging motion, neck extension, right shoulder extension, right/left elbow extension, right/left elbow supination did not appear. Items of joint motion showing the maximum at range of each swing motion were applied into 55 questions and consisted. The results of this study were meaningful as a basic study to apply 3D motion analysis to the fashion industry. It's expected to be used to design functional clothing.