• Proceedings of the ESK Conference
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• 1992.10a
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• pp.54-62
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• 1992

This work has been directed at studying and developing a prototype Computer Aided Design(CAD) tool to be used for planning tendon paths in hand reconstructive surgery. The application of CAD to rehabilitative surgery of the hand is a new field of endeavor. There are currently no existing systems designed to assist the orthopedic surgeon in planning these complex peocedures. Additionally, orthopedic surgeons are not trained in mechanics, kinematics, math modeling, or the use of computers. It was also our intent to study the mechanisms and the efficacy of the application of CAD techniques to this important aspect of hand surgery. The following advances are reported here: Interactive 3D tendon path definition tools., Software to calculate tendon excursion from an arbitrary tendon path crossing any number of joints., A model to interactively compute and display the foirces in muscle and tendon., A workstation environment to help surgeons evaluate the consequences of a simulated tendon transfer operation when a tendon is lengthened, rerouted, or reattached in a mew location., It also has been one of the primary concerns in this work that an interactive graphical surgical workstation must present a natural, user-friendly environment to the orthopedic durgeon user. The surgical workstation must ultimately aid the surgeon in helping his patient or in doing his work more efficiently or more reliably.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.687-688
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• 2023

Bone age assessment is a crucial task in pediatric radiology for assessing growth and development in children. In this paper, we explore the potential of Vision Transformer, a state-of-the-art deep learning model, for bone age assessment using X-ray images. We generate heatmap outputs using a pre-trained Vision Transformer model on a publicly available dataset of hand X-ray images and show that the model tends to focus on the overall hand and only the bone part of the image, indicating its potential for accurately identifying the regions of interest for bone age assessment without the need for pre-processing to remove background noise. We also suggest two methods for extracting the region of interest from the heatmap output. Our study suggests that Vision Transformer holds great potential for bone age assessment using X-ray images, as it can provide accurate and interpretable output that may assist radiologists in identifying potential abnormalities or areas of interest in the X-ray image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1071-1076
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• 2006

In this paper, we develop face and hand tracking for sign language recognition system. The system is divided into two stages; the initial and tracking stages. In initial stage, we use the skin feature to localize face and hands of signer. The ellipse model on CbCr space is constructed and used to detect skin color. After the skin regions have been segmented, face and hand blobs are defined by using size and facial feature with the assumption that the movement of face is less than that of hands in this signing scenario. In tracking stage, the motion estimation is applied only hand blobs, in which first and second derivative are used to compute the position of prediction of hands. We observed that there are errors in the value of tracking position between two consecutive frames in which velocity has changed abruptly. To improve the tracking performance, our proposed algorithm compensates the error of tracking position by using adaptive search area to re-compute the hand blobs. The experimental results indicate that our proposed method is able to decrease the prediction error up to 96.87% with negligible increase in computational complexity of up to 4%.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.64-70
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• 2014

In this paper, we propose a method that gives motion command to a mobile robot to recognize human being's hand gesture. Former way of the robot-controlling system with the movement of hand used several kinds of pre-arranged gesture, therefore the ordering motion was unnatural. Also it forced people to study the pre-arranged gesture, making it more inconvenient. To solve this problem, there are many researches going on trying to figure out another way to make the machine to recognize the movement of the hand. In this paper, we used third-dimensional camera to obtain the color and depth data, which can be used to search the human hand and recognize its movement based on it. We used HMM method to make the proposed system to perceive the movement, then the observed data transfers to the robot making it to move at the direction where we want it to be.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.639-645
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• 2012

In this paper, we propose a method that gives motion command to a mobile robot to recognize human being's hand gesture. Former way of the robot-controlling system with the movement of hand used several kinds of pre-arranged gesture, therefore the ordering motion was unnatural. Also it forced people to study the pre-arranged gesture, making it more inconvenient. To solve this problem, there are many researches going on trying to figure out another way to make the machine to recognize the movement of the hand. In this paper, we used third-dimensional camera to obtain the color and depth data, which can be used to search the human hand and recognize its movement based on it. We used HMM method to make the proposed system to perceive the movement, then the observed data transfers to the robot making it to move at the direction where we want it to be.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.57-64
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• 2014

Recently, many human-friendly communication methods have been studied for human-machine interface(HMI) without using any physical devices. One of them is the vision-based gesture recognition that this paper deals with. In this paper, we define some gestures for interaction with objects in a predefined virtual world, and propose an efficient method to recognize them. For preprocessing, we detect and track the both hands, and extract their silhouettes from the low-resolution hand images captured by a webcam. We modeled skin color by two Gaussian distributions in RGB color space and use blob-matching method to detect and track the hands. Applying the foodfill algorithm we extracted hand silhouettes and recognize the hand shapes of Thumb-Up, Palm and Cross by detecting and analyzing their modes. Then, with analyzing the context of hand movement, we recognized five predefined one-hand or both-hand gestures. Assuming that one main user shows up for accurate hand detection, the proposed gesture recognition method has been proved its efficiency and accuracy in many real-time demos.

• Journal of the Ergonomics Society of Korea
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• v.30 no.5
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• pp.597-603
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• 2011

Objective: The objective of this study was to compare one-hand and two-hands lifting activity in terms of biomechanical stress for the range of lifting heights from 10cm above floor level to knuckle height. Background: Even though two-hands lifting activity of manual materials handling tasks are prevalent at the industrial site, many manual materials handling tasks which require the worker to perform one-hand lifting are also very common at the industrial site and forestry and farming. Method: Eight male subjects were asked to perform lifting tasks using both a one-handed as well as a two-handed lifting technique. Trunk muscle electromyographic activity was recorded while the subjects performed the lifting tasks. This information was used as input to an EMG-assisted free-dynamic biomechanical model that predicted spinal loading in three dimensions. Results: It was shown that for the left-hand lifting tasks, the values of moment, lateral shear force, A-P shear force, and compressive force were increased by the average 43%, as the workload was increased twice from 7.5kg to 15.0kg. For the right-hand lifting task, these were increased by the average 34%. For the two-hands lifting tasks, these were increased by the average 25%. The lateral shear forces at L5/S1 of one-hand lifting tasks, notwithstanding the half of the workload of two-hands lifting tasks, were very high in the 300~317% of the one of two-hands lifting tasks. The moments at L5/S1 of one-hand lifting tasks were 126~166% of the one of two-hands lifting tasks. Conclusion: It is concluded that the effect of workload for one-hand lifting is greater than two-hands lifting. It can also be concluded that asymmetrical effect of one-hand lifting is much greater than workload effect. Application: The results of this study can be used to provide guidelines of recommended safe weights for tasks involved in one-hand lifting activity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.1-10
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• 2010

As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.457-468
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• 1997

The present paper deals with an economic order quan-tity model for items deteriorating at some constant rate with demand changing at a known and at a random point of time in the fixed pro-duction cycle.

• Journal of the Korean Applied Science and Technology
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• v.35 no.2
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• pp.532-539
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• 2018

This study is a descriptive study to analyze the hand washing practice of nurses working in clinic applying health belief model. This research involved 162 clinical nurse at G city. The data were collected from Sep 1, 2017 to Oct 31, 2017. The collected data were analyzed using an independent t-test, 1-way ANOVA, pearson's correlation coefficient and multiple regression analysis, where p-values of <0.05 were considered statistically significant by using SPSS 20.0. The overall practice of hand washing by general subjects were high 3.1 in all subjects, but there was no statistically significant difference. Health beliefs about hand washing practice according to general characteristics showed significant difference in perceived benefits (p<0.05), and there was a significant difference in perceived benefits and perceived barriers in age(p<0.05). In regard to the correlation among the subfactor of health beliefs, benefits had a statistically significant negative correlation to barriers and, positively correlated to cues to action. The results of this study suggest that continuing education of infection management in hospitals considering health beliefs about proper hand washing training will enhance hand washing practice.