• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.434-441
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• 2004

In this paper, an exoskeleton-type motion capturing system is designed and implemented. The device is designed to have 12 degree-of-freedom entirely to represent human arm motions. Forward and inverse kinematics of the device are analyzed to make sure of its singular positions. With the designed model parameters, simulation studies are conducted to verify that the designed motion capturing system is effective to represent human motions within the workspace. As a counterpart of the exoskeleton system, a mobile robot is built to follow human motion restrictively. Experimental studies of teleoperation from the exoskeleton device to control the mobile robot are carried out to show feasible application of wireless man-machine interface.

• Korean Journal of Applied Biomechanics
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• v.25 no.1
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• pp.123-130
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• 2015

Purpose : The purpose of this study was to investigate the reliability of 3D-inertia measurement unit (IMU) based shoes in gait analysis. This was done with respect to the results of the optical motion capturing system and to collect reference gait data of healthy subjects with this device. Methods : The Smart Balance$^{(R)}$ system of 3D-IMU based shoes and Osprey$^{(R)}$ motion capturing cameras were used to collect motion data simultaneously. Forty four healthy subjects consisting of individuals in 20s (N=20), 40s (N=13), and 60s (N=11) participated in this study voluntarily. They performed natural walking on a treadmill for one minute at 4 different target speeds (3, 4, 5, 6 km/h), respectively. Results : Cadence (ICC=.998), step length (ICC=.970), stance phase (ICC=.845), and double-support phase (ICC=.684) from 3D-IMU based shoes were in agreement with results of optical motion system. Gait data of healthy subjects according to different treadmill speeds and ages were matched to previous literature showing increased cadence and reduced step length for elderly subjects. Conclusion : Conclusively, 3D-IMU based shoes in gait analysis were a satisfactory alternative option in measuring linear gait parameters.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.25-32
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• 2007

In this paper, the abstract layer for motion capture system is designed and implemented to meet the various hardware and different capturing method. The abstract layer can offer the unified programming by providing device independent API(Application Programming Interface). The device drivers of the optical system and mechanical system are emulated to verify the designed abstract layer. The optical system employs the AOA Ole while the mechanical system uses BVH file. An application program is written to call the abstract layer functions to drive both optical and mechanical drivers and receive the frame data, simulated motion data, that are displayed sequentially on the computer screen by utilizing Direct3D.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.3
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• pp.10-17
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• 2009

In this paper, we explained the relation between evaluating display device and emotional image quality evaluation in human perceptual view. It is also suggested two emotional image quality evaluation method of display reflecting human visual function. One is the color space of CIECAM02 and the other is capturing moving image. It is necessary to standardize the evaluation methods of image quality based on emotional evaluation.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.33-38
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• 2007

In this paper, hardware implementation of interface and control between two robots, the master and the slave robot, are designed. The master robot is the motion capturing device that captures motions of the human operator who wears it. The slave robot is the corresponding humanoid robot arms. Captured motions from the master robot are transferred to the slave robot to follow after the master. All hardware designs such as PID controllers, communications between the master robot, encoder counters, and PWM generators are embedded on a single FPGA chip. Experimental studies are conducted to demonstrate the performance of the FPGA controller design.

• Journal of Magnetics
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• v.8 no.1
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• pp.70-73
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• 2003

We have developed a new tracking system of jaw movement. The system consists of two permanent NdFeB magnets and 32 elements of two-axial fluxgate sensor array, The two magnets are attached to head portion and front tooth. This system does not need any attachments of the head portion or mouth such as clutch or magnetic field sensor except magnets. The proposed system is applicable for five degree of freedom. Position accuracy within 2]m was achieved. We developed a 3D computer input device by using the above mentioned technique.

• Proceedings of the Korean Magnestics Society Conference
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• 2002.12a
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• pp.12-12
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• 2002

We present the new jaw tracking system that utilizes five degrees of freedom of head and lower jaw. The proposed method does not disturb the physiology because the system does not need to fix magnetic field sensors or clutch on the patient's body or mouth. The impact of this result goes beyond the conventional optical and magnetic tracking system of jaw movement [1][2]. Position accuracy within 1mm and reasonable cost is necessary for practical use of the jaw tracking system. (omitted)

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.181-190
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• 2021

Sports activities conducted by multiple people are difficult to proceed in a situation where a widespread epidemic such as COVID-19 is spreading, and this causes a lack of physical activity in modern people. This problem can be overcome by using online exercise contents, but it is difficult to check detailed postures such as during face-to-face exercise. In this study, we present a model that detects posture and tracks movement using IT system for better non-face-to-face exercise content management. The proposed motion tracking model defines a body model with reference to motion analysis methods widely used in physical education and defines posture and movement accordingly. Using the proposed model, it is possible to recognize and analyze movements used in exercise, know the number of specific movements in the exercise program, and detect whether or not the exercise program is performed. In order to verify the validity of the proposed model, we implemented motion tracking and exercise program tracking programs using Azure Kinect DK, a markerless motion capture device. If the proposed motion tracking model is improved and the performance of the motion capture system is improved, more detailed motion analysis is possible and the number of types of motions can be increased.

• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.21-27
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• 2002

This paper presents a mews event reenactment system (NERS), which generates virtual character animations in a quick and convenient manner. Thus, NERS can be used to produce computer graphics(CG) scenes of news events that are hard to photograph, such as fire, traffic accident, cases of murder, and so on. By using plenty of captured motion data and CG model data this system produces an appropriate animation of virtual characters straightforwardly without any motion capturing device and actors in the authoring stage. NERS is designed to be capable of making virtual characters move along user-defined paths, stitching motions smoothly and modifyingthe positions and of the articulations of a virtual character in a specific frame. Therefore a virtual character can be controlled precisely so as to interact with the virtual environments and other characters. NERS provides both an interactive and script-based (MEL: Maya Embedded Language) interface so that user can this system in a convenient way. This system has been implemented as a plug-in of commercial CG tool, Maya (Alias/wavefront), in order to make use of its advanced functions

• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.255-263
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• 2023

Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.