• Korean Journal of Applied Biomechanics
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• v.24 no.2
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• pp.181-187
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• 2014

In this study, a real-time evaluation system for quantitative dynamic fitting during pedaling was developed. The system is consisted of LED markers, a digital camera connected to a computer and a marker detecting program. LED markers are attached to hip, knee, ankle joint and fifth metatarsal in the sagittal plane. Playstation3 eye which is selected as a main digital camera in this paper has many merits for using motion capture, such as high FPS (Frame per second) about 180FPS, $320{\times}240$ resolution, and low-cost with easy to use. The maker detecting program was made by using Labview2010 with Vision builder. The program was made up of three parts, image acquisition & processing, marker detection & joint angle calculation, and output section. The digital camera's image was acquired in 95FPS, and the program was set-up to measure the lower-joint angle in real-time, providing the user as a graph, and allowing to save it as a test file. The system was verified by pedalling at three saddle heights (knee angle: 25, 35, $45^{\circ}$) and three cadences (30, 60, 90 rpm) at each saddle heights by using Holmes method, a method of measuring lower limbs angle, to determine the saddle height. The result has shown low average error and strong correlation of the system, respectively, $1.18{\pm}0.44^{\circ}$, $0.99{\pm}0.01^{\circ}$. There was little error due to the changes in the saddle height but absolute error occurred by cadence. Considering the average error is approximately $1^{\circ}$, it is a suitable system for quantitative dynamic fitting evaluation. It is necessary to decrease error by using two digital camera with frontal and sagittal plane in future study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.61-69
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• 2010

This paper presents an efficient object selection algorithm by analyzing and detecting of human activity. Generally, when people point any something, they will put a face on the target direction. Therefore, the direction of the face and fingers and was ordered to be connected to a straight line. At first, in order to detect the moving objects from the input frames, we extract the interesting objects in real time using background subtraction. And the judgment of movement is determined by Principal Component Analysis and a designated time period. When user is motionless, we estimate the user's indication by estimation in relation to vector from the head to the hand. Through experiments using the multiple views, we confirm that the proposed algorithm can estimate the movement and indication of user more efficiently.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.380-392
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• 2013

A method to classify a golf swing motion into 7 sections using a Kinect sensor and a fuzzy system is proposed. The inputs to the fuzzy logic are the positions of golf club and its head, which are extracted from the information of golfer's joint position and color information obtained by a Kinect sensor. The proposed method consists of three modules: one for extracting the joint's information, another for detecting and tracking of a golf club, and the other for classifying golf swing motions. The first module extracts the hand's position among the joint information provided by a Kinect sensor. The second module detects the golf club as well as its head with the Hough line transform based on the hand's coordinate. Using a fuzzy logic as a classification engine reduces recognition errors and, consequently, improves the performance of robust classification. From the experiments of real-time video clips, the proposed method shows the reliability of classification by 85.2%.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.84-88
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• 2010

Recently, it is essential to have the system which can track down and identity the random object in the space in which security is a high priority. Due to the fact that we mentioned above, in this paper. We suggest the intelligent video surveillance system effective image-process-education in this paper. The experiment was conducted to check and track down the entering vehicle. And, Pan-Tilt-Zoom camera was used to obtain the enlarged image of the object while a vehicle was making stop in target area. As a result, the experiment has shown the data as following. When the object is in motion, success rate is 97.4%, while success rate is 91% when the object is motionless. By using the suggested system, effective image-process-education is should be achieved because the students who participate in the class can have simultaneous access to the system for real time image data and camera control.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.47-55
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• 2012

This paper describes the developed HILS and test equipment in order to test the performances of MMW(Millimeter-Wave) seeker which can detect and track a high speed of short-range ballistic missile and aircraft. This system is used to 141 horn antenna array, array switching, and gain and phase control algorithm to simulate various kind of targets and trajectory of high speed and maneuver moving target. In addition, it simulates not only velocity and range for these targets but also clutter and jamming environments. System configuration and implementation and the measurement results of major subsystems such as target motion simulator, simulation signal generator, high speed data aquisition unit, and central control unit are presented. These systems could verify the detection and tracking performance of MMW seeker through dynamic real-time test based on simulation flight scenario.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.345-354
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• 2014

In this paper, we propose a real-time algorithm for estimating the relative position and velocity of a person with respect to a robot using a Kinect sensor and an extended Kalman filter (EKF). Additionally, we propose an algorithm for controlling the robot in the proximity of a person in a variety of modes. The algorithm detects the head and shoulder regions of the person using a histogram of oriented gradients (HOG) and a support vector machine (SVM). The EKF algorithm estimates the relative positions and velocities of the person with respect to the robot using data acquired by a Kinect sensor. We tested the various modes of proximity movement for a human in indoor situations. The accuracy of the algorithm was verified using a motion capture system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.63-70
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• 2023

In this paper, we propose a Mixed Reality based rehabilitation exercise solution with the goal of mitigating one of the most common chronic conditions among the elderly, musculoskeletal disorders. In modern society, as the number of elderly increases, more people engage in office work and engage in more sedentary activities. Due to repetitive work in the office, muscle strength decreases and this causes many difficulties in daily life. In this study, we developed a mixed reality based exercise platform to solve these chronic musculoskeletal diseases. VR is not appropriate for elderly because of dizziness. In addition, we developed a wearable sensor based on IMU and attached it to important parts of the upper body to motion tracking. We developed a algorithm synchronize to raw data from wearable sensor with in a vr avatar. Ederly can check in real time whether rehabilitation exercises are being performed accurately through the avatar.

• The Journal of Korean Society for Radiation Therapy
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• v.17 no.2
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• pp.125-131
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• 2005

Purpose : For stereotactic radiosurgery (SRS) of a tumor in the region whose movement due to respiration is significant, like Lung lower lobe, the gated therapy, which delivers radiation dose to the selected respiratory phases when tumor motion is small, was performed using the Respiratory gating system and its clinical effectiveness was evaluated. Materials and Methods : For two SRS patients with a tumor in Lung lower lobe, a marker block (infrared reflector) was attached on the abdomen. While patient' respiratory cycle was monitored with Real-time Position Management (RPM, Varian, USA), 4D CT was performed (10 phases per a cycle). Phases in which tumor motion did not change rapidly were decided as treatment phases. The treatment volume was contoured on the CT images for selected treatment phases using maximum intensity projection (MIP) method. In order to verify setup reproducibility and positional variation, 4D CT was repeated. Results : Gross tumor volume (GTV) showed maximum movement in superior-inferior direction. For patient #1, motion of GTV was reduced to 2.6 mm in treatment phases ($30{\sim}60%$), while that was 9.4 mm in full phases ($0{\sim}90%$) and for patient #2, it was reduced to 2.3 mm in treatment phases ($30{\sim}70%$), while it was 11.7 mm in full phases ($0{\sim}90%$). When comparing two sets of CT images, setup errors in all the directions were within 3 mm. Conclusion : Since tumor motion was reduced less than 5 mm, the Respiratory gating system for SRS of Lung lower lobe is useful.

• Progress in Medical Physics
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• v.20 no.3
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• pp.132-138
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• 2009

Studies on target motion in 4-dimensional radiotherapy are being world-widely conducted to enhance treatment record and protection of normal organs. Prediction of tumor motion might be very useful and/or essential for especially free-breathing system during radiation delivery such as respiratory gating system and tumor tracking system. Neural network is powerful to express a time series with nonlinearity because its prediction algorithm is not governed by statistic formula but finds a rule of data expression. This study intended to assess applicability of neural network method to predict tumor motion in 4-dimensional radiotherapy. Scaled Conjugate Gradient algorithm was employed as a learning algorithm. Considering reparation data for 10 patients, prediction by the neural network algorithms was compared with the measurement by the real-time position management (RPM) system. The results showed that the neural network algorithm has the excellent accuracy of maximum absolute error smaller than 3 mm, except for the cases in which the maximum amplitude of respiration is over the range of respiration used in the learning process of neural network. It indicates the insufficient learning of the neural network for extrapolation. The problem could be solved by acquiring a full range of respiration before learning procedure. Further works are programmed to verify a feasibility of practical application for 4-dimensional treatment system, including prediction performance according to various system latency and irregular patterns of respiration.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.717-722
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• 2001

This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.