• Safety and Health at Work
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• 제5권4호
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• pp.175-180
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• 2014

Wet-work can be defined as activities where workers have to immerse their hands in liquids for >2 hours per shift, or wear waterproof (occlusive) gloves for a corresponding amount of time, or wash their hands >20 times per shift. This review considers the recent literature on wet-work exposure, and examines wet-work as a main risk factor for developing irritant contact dermatitis of the hands. The aim of this paper is to provide a detailed description of wet-work exposure among specific occupational groups who extensively deal with water and other liquids in their occupations. Furthermore, it highlights the extent and importance of the subsequent adverse health effects caused by exposure to wet-work.

• 패션비즈니스
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• 제27권3호
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• pp.19-34
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• 2023

The purpose of this study was to analyze the three-dimensional hand-related dimensions of elderly women aged 70 to 84 years and to characterize them to develop safety gloves for dementia patients. The 3D data from the 8th Human Size Survey of the National Institute of Standards and Technology, Size Korea, were analyzed using the SPSS 26.0 program. The straight thumb length was longer in elderly women aged 70-74 than in those aged 80-84. To analyze the hand type of elderly women, four factors were categorized: hand and finger horizontal factor, hand vertical factor, finger digit V thickness factor, and finger length factor. Elderly women's hand types were categorized as 'long hands and thin fingers', 'thick hands with long fingers', and 'short hands and thick little fingers'. Elderly women aged 70-74 years and 80-84 years were analyzed as having the most 'long hands and thin fingers' type, while older women aged 75-79 years were analyzed as having the most 'thick hands and long fingers' type. It is known that the fingers get thicker and the size of hands increase as age advances, but by the age 80, there is a change in the size of hands again. In future research, it would be worth expanding to other age groups to explore differences between age groups and to develop safety gloves for real-world dementia patients based on the hand types analyzed.

• 대한인간공학회지
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• 제30권2호
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• pp.303-310
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• 2011

In this study, we employ CPM-GOMS analysis for explaining physical and cognitive processes and for quantitatively predicting when users are typing Korean text messages on mobile phones using both hands. First, we observe the behaviors of 10 subjects, when the subjects enter keypads with both hands. Then, basing upon MHP, we categorize the behaviors into perceptual, cognitive, motor operators, and then we analyze those operators. After that, we use the critical paths to model two task sentences. Also, we used Fitts' law method which was applied many times to predict text entering time on mobile phone to compare with the results of our CPM-GOMS model. We followed Lee's (2008) method that is well suited for text entry task using both hands and calculate total task time for each task sentences. For the sake of comparison between the actual data and the results predicted from our CPM-GOMS model, we empirically tested 10 subjects and concluded that there were no significant differences between the predicted values and the actual data. With the CPM-GOMS model, we can observe the human information processes composed on the physical and cognitive processes. Also we verified that the CPM-GOMS model can be well applied to predict the users' performance when they input text messages on mobile phones using both hands by comparing the predicted total task time with the real execution time.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.217-226
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• 2006

Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.138-141
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• 2002

In this paper, we developed a Master Hand which has 20 potentiometer for getting grasping data of human hands, a Slave Hand which has 20 DOF and five fingers with servo-motors, and a controller for the 7 DOF Arm with Multi-fingered hands. And, we programmed a 3D simulation S/W which controls a Robot System with Multi-fingered hands. A developed Robot System showed good performance in the grasping of an object with known position and shape.

• 전기전자학회논문지
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• 제17권1호
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• pp.44-50
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• 2013

본 논문에서는 로봇의 팔을 기본 센서로 사용하여 별도의 센서 없이 사람을 따라다니는 햅틱 기반 로봇을 제안한다. 로봇 팔의 관절 각각에는 움직임을 생성하기 위한 모터가 있으며, 로봇 팔에 힘을 가하여 움직이면 각 관절의 각도가 변하면서 모터에서 그 각도를 출력 신호로 내보낼 수 있다. 따라서 사람이 로봇의 팔을 잡고 당기거나 밀면 로봇에서는 그 움직임을 각도로 읽어들이는 촉감 인터페이스로 활용할 수 있다. 구현된 로봇은 사람이 팔로 로봇 팔을 잡아끄는 움직임을 측정하여 움직이며 사람이 손을 잡고 이끎으로서 사람을 따라다닐 수 있다.

• 패션비즈니스
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• 제26권5호
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• pp.62-75
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• 2022

The purpose of this study was to analyze the types of aesthetic characteristics and their expression methods in the goth style expressed with the sensibility of an illustrator, using the work of Toon Hertz as an example. As a research method for this purpose, previous studies and books were used to examine the components of fashion illustration, the concept and aesthetic characteristics of goth style, and the world of Toon Hertz's work. In the qualitative studies, Toon Hertz's works were collected and the characteristics of each component were analyzed. As a result of analyzing the aesthetic characteristics, Distortion appeared as the main element of the human body, and the human body was distorted through the method of combining the human body with animals, plants, and other objects. History was mainly expressed through fashion elements. Victorian clothing was predominant, the color was mainly black, and it was characterized by decorations, such as fancy laces, corsets, and shirrings. The screen layout and the object components appeared as the main components of mystery. Sensuality was a major component of the human body, and it emphasized decadent and sensual images of a woman sitting with both legs apart or placing her hands on her legs or chest. Fear was the main component of the human body, and strangeness and fear were created by omitting or removing parts of the body, such as women's arms, legs, hands, or eyes.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.159-162
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• 2007

The inverse kinematics problem in robotics is an essential work for grasping and manipulation tasks by robotic and humanoid hands. In this paper, an intelligent neural learning scheme for solving such inverse kinematics of humanoid fingers is presented. Specifically, a multi-layered neural network is utilized for effective inverse kinematics, where a dynamic neural learning algorithm is employed. Also, a bio-mimetic feature of general human fingers is incorporated to the learning scheme. The usefulness of the proposed approach is verified by simulations.

• 대한영양사협회학술지
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• 제15권3호
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• pp.220-231
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• 2009

The principal objective of this study was to evaluate elementary students' awareness of the importance of hand washing, as well as their hand-washing behavior. The data was collected by self-reported questionnaire from 697 students in elementary schools with serving food in a classroom in Busan. Their hand-washing frequency was high, at '3~4 times per day (37.0%)'. 51.0% of the respondents did not wash their hands that often because they were 'not accustomed' to washing their hands, and 35.9% of respondents regarded washing their hands as 'annoying'. The most frequently reported hand washing agent was 'soap and water (71.4%)'. Approximately 95~98% of the respondents always washed their hands after using the bathroom, 87.9% of them washed their hands before eating food, and 86.7% of them washed their hands upon returning home. However, 27.3%, 34.1% and 65.9% of the respondents did not wash their hands after handling money, after eating, and after coughing or sneezing, respectively. Significant factors related to increased hand-washing frequency were gender (p<0.001) and the period of attendance at kindergarten (p<0.05). The mean scores of importance and performance of hand washing were significantly higher for girls than for boys. The group with higher rate (over 4.5/5.0) for the importance of sanitary hand-washing behavior showed significantly higher scores in hand-washing behavior before serving food and before eating than those of the lower rated group (below 4.0/5.0). This study shows that sanitation education is required not only for food handlers but also for students in school foodservices.

• 제어로봇시스템학회논문지
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• 제7권4호
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• pp.309-318
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• 2001

In this paper, we describe methods that analyze a human gesture. A human interface(HI) system for analyzing gesture extracts the head and hand regions after taking image sequence of and operators continuous behavior using CCD cameras. As gestures are accomplished with operators head and hands motion, we extract the head and hand regions to analyze gestures and calculate geometrical information of extracted skin regions. The analysis of head motion is possible by obtaining the face direction. We assume that head is ellipsoid with 3D coordinates to locate the face features likes eyes, nose and mouth on its surface. If was know the center of feature points, the angle of the center in the ellipsoid is the direction of the face. The hand region obtained from preprocessing is able to include hands as well as arms. For extracting only the hand region from preprocessing, we should find the wrist line to divide the hand and arm regions. After distinguishing the hand region by the wrist line, we model the hand region as an ellipse for the analysis of hand data. Also, the finger part is represented as a long and narrow shape. We extract hand information such as size, position, and shape.