• Korean Journal of Human Ecology
• /
• v.13 no.1
• /
• pp.153-158
• /
• 2004

With considerable development of comfortable and functional clothing in recent years, we need to evaluate the effects of garment pressure in daily wear on each parts of human body because the garment pressure is important to design the clothing. This study was designed to examine the effects of body postures on garment pressure on each parts of human body in the actual clothing conditions. All the data were collected from 50 volunteered subjects. The Garment pressure was measured in lune and December with 8 points CPMS clothing pressure system from scapular, upper am, elbow, under arm, front waist line, side waist line, abdomen, crista ilica, upper hip, middle hip, front thigh, back thigh, front knee and back knee. The postures of subjects were controlled with 3 positions such as standing (posture 1), sitting on the chair (posture 2), and sitting on the floor (posture 3) during measurement of clothing pressure. Clothing weights were more in men than in woman. It showed that clothing weights had no effects on the garment pressure. In this study, however, just the garment pressures on scapular and top of the hip increased significantly by clothing weight (p<. 05). Clothing horizontally pressed on scapular and top of hip but not on other parts. When subjects stood up, the garment pressure was the highest on the side waist. Especially, clothing pressure on the front waist point was lower than that of the left side waist. On the upper parts of the human body, the garment pressure of left side waist was the highest, and followed by front waist, crista ilica, and abdomen in order. When subjects were sitting on the chair, the garment pressure on the lower parts of the human body was the highest on the top of hip. When the subjects were sitting on the chair or on the floor, the surface area on their skin of hip and waist parts increased by postures. In addition, it showed that men felt more comfortable than women on higher clothing pressure level.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.44 no.1
• /
• pp.84-95
• /
• 2020

Wearing ease is a critical factor when designing special uniforms such as flight pilot's garment and should reflect occupational properties for better performance. This study measured skin surface on 31 areas in seven postures that refer to the pilot's occupational postures as well as made six prediction models including linear mixed model (LMM) for each body part to find the best fit model. Skin surface measured from 3D body scanned images of 11 male pilot participants. There were significantly positive and negative changes in various areas from standing posture (P1) to dynamic postures (P2-P7). Six models were designed in various compositions using stature and chest circumference as fixed effects and subject and posture as random effects. The best models were linear mixed models with one fixed effect (chest circumference or stature, varies with body parts) and two random effects (subject and posture). The results of this study provide reference data to set wearing ease for pilot's garment and suggests a new methodology in this research area, but verifying the effect of diverse independent variables is left for future studies.

• Journal of Internet Computing and Services
• /
• v.12 no.6
• /
• pp.83-94
• /
• 2011

Main researching issue in affective computing is to give a machine the ability to recognize the emotion of a person and to react it properly. Efforts in that direction have mainly focused on facial and oral cues to get emotions. Postures have been recently considered as well. This paper aims to discriminate emotions posture by identifying and measuring the saliency of posture features that play a role in affective expression. To do so, affective postures from human subjects are first collected using a motion capture system, then emotional features in posture are described with spatial ones. Through standard statistical techniques, we verified that there is a statistically significant correlation between the emotion intended by the acting subjects, and the emotion perceived by the observers. Discriminant Analysis are used to build affective posture predictive models and to measure the saliency of the proposed set of posture features in discriminating between 6 basic emotional states. The evaluation of proposed features and models are performed using a correlation between actor-observer's postures set. Quantitative experimental results show that proposed set of features discriminates well between emotions, and also that built predictive models perform well.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.3
• /
• pp.103-109
• /
• 2012

The purpose of this paper is to suggest the strategical lifting postures able to alleviate imbalanced EMG amplitude leading to an increase in low back muscle fatigue while lifting asymmetric load dynamically. Eleven male subjects are required to lift symmetrically an external load with 15.8kg and load center of gravity (LCG) deviated 10cm to the right from the floor to the waist height at the speed of about 25cm/sec. The EMG amplitudes on bilateral low back muscles (Longissimus, Iliocostalis, and Multifidus) are recorded during 2sec and analyzed. Independent variables are trunk postures (No bending vs. Bending to the LCG) and feet placements (Parallel vs. Right foot in front of the other vs. Right foot behind the other). Dependent variables are EMG amplitude average on six muscles and the EMG amplitude difference between right and left muscle group. Results indicate the phenomenon showing an amplitude increase in the left muscle group is equal to an decrease in the right one is observed in dynamic as well as static lifts, bending the trunk to the LCG increases amplitude discrepancy more than no trunk bending, and the amplitude discrepancy in one foot ipsilateral to LCG in front of the other foot is lowest among other foot postures. As bilateral EMG amplitude discrepancy increases total low back muscle fatigue, the strategical combination of no trunk bending and one foot close to LCG in front of the other is recommended for preventing elevated incidence of low back pain (LBP).

• The Research Journal of the Costume Culture
• /
• v.25 no.3
• /
• pp.301-314
• /
• 2017

This study focused on the movement adaptability of $19^{th}$ century classical opera stage costumes. Researchers focused on a basic $19^{th}$ century women's jacket. The study analyzed movement adaptability using ROM (range-of-motion) tests of the upper limb flexion and abduction postures. It developed two research garments to mimic basic $19^{th}$ century style jackets with or without gussets at the axilla. The ROM experiment identified the gusset size as 11cm in length. Experimental postures included upper limb flexion and abduction. The study measured subjective comfort at 8 postures. These postures included the flexion and abduction of the arms and torso. Subjects also evaluated the subjective comfort of the rotation posture of the torso. Researchers evaluated the similarities between research garments' silhouettes and the $19^{th}$ century women's jacket. The study used a 3D virtual fitting system to evaluate fit, and specialists further analyzed fit with photographs and 3D virtual graphics. The results are as follows. The silhouettes of both research garments were similar to the silhouettes of the $19^{th}$ century western women's jacket. The jacket with axilla gusset had a better fit than the basic style jacket. The basic style jacket without the axilla gusset showed limited movement adaptability at the shoulder joint and it caused discomfort at the axilla and elbow. The 3D virtual fit test was not a suitable method for analyzing silhouette similarity.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.6
• /
• pp.117-125
• /
• 2015

In the modern age, it is important for people to maintain a good sitting posture because they spend long hours sitting. Posture correction treatment requires a great deal of time and expenses with continuous observation by a specialist. Therefore, there is a need for a system with which users can judge and correct their postures on their own. In this study, we collected users' postures and judged whether they are normal or abnormal. To obtain a user's posture, we propose a four-joint motion capture system that uses inertial sensors. The system collects the subject's postures, and features are extracted from the collected data to build a database. The data in the DB are classified into normal and abnormal postures after posture learning using the K-means clustering algorithm. An experiment was performed to classify the posture from the joints' rotation angles and positions; the normal posture judgment reached a success rate of 99.79%. This result suggests that the features of the four joints can be used to judge and help correct a user's posture through application to a spinal disease prevention system in the future.

• Journal of the Korea Safety Management & Science
• /
• v.4 no.2
• /
• pp.11-22
• /
• 2002

In this study, an asymmetric lifting posture prediction model was developed, which was a three-dimensional model with 12 links and 23 degrees of freedom open kinematic chains. Although previous researchers have proposed biomechanical, psychophysical, or physiological measures as cost functions, for solving redundancy, they lack in accuracy in predicting actual lifting postures and most of them are confined to the two-dimensional model. To develop an asymmetric lifting posture prediction model, we used the resolved motion method for accurately simulating the lifting motion in a reasonable time. Furthermore, in solving the redundant problem of the human posture prediction, a moment weighted Joint Range Availability (JRA) was used as a cost function in order to consider dynamic lifting. However, it is known that the moment weighted JRA as a cost function predicted the lower extremity and L5/S1 joint motions better than the upper extremities, while the constant weighted JRA as a cost function predicted the latter better than the former. To compensate for this, we proposed a hybrid moment weighted JRA as a new cost function with moment weighted for only the lower extremity. In order to validate the proposed cost function, the predicted and real lifting postures for various lifting conditions were compared by using the root mean square(RMS) error. This hybrid JRA reduced RMS more than the previous cost functions. Therefore, it is concluded that the cost function of a hybrid moment weighted JRA can be used to predict three-dimensional lifting postures. To compare with the predicted trajectories and the real lifting movements, graphical validations were performed. The results also showed that the hybrid moment weighted cost function model was found to have generated the postures more similar to the real movements.

• Journal of Biosystems Engineering
• /
• v.34 no.2
• /
• pp.120-126
• /
• 2009

The purpose of this study was to develop a visibility evaluation system for cabin type combine. Human's field of view was classified into five levels (perceptive, effective, stable gaze, induced, and auxiliary) depending on rotation of human's head and eye. Divider, reaper lever, gearshift, dashboard, and conveying part were considered as major viewpoints of combine. Visibilities of combine was evaluated quantitatively using the viewpoints and the human's field of view levels. The visibility evaluation system for cabin type combine was consisted of a laser pointer, stepping motors to control the direction of view, gyro sensors to measure horizontal and vertical angle, and I/O interface to acquire the signals. Tests were conducted with different postures ('sitting straight', 'sitting with $15^{\circ}$ tilt', 'standing straight', and 'standing with $15^{\circ}$ tilt'). The LSD (least significant difference) multiple comparison tests showed that the visibilities of viewpoints were different significantly as the operator's postures were changed. The results showed that the posture at standing with $15^{\circ}$ tilt provided the best visibility for operators. The divider of the combine was invisible due to blocking with the cabin frame at many postures. The reaper lever showed good visibilities at the postures of sitting or standing with $15^{\circ}$ tilt. The gearshift, the dashboard, and the conveying part had reasonable visibilities at the posture of sitting with $15^{\circ}$ tilt. However, most viewpoints of the combine were out of the stable gaze field of view level. Modifications of the combine design will be required to enhance the visibility during harvesting operation for farmers' safety and convenience.

• Journal of the Korean Society of Safety
• /
• v.26 no.5
• /
• pp.81-88
• /
• 2011

The goal of this study was to determine whether food industry workers are exposed to musculoskeletal loads due to the work time, frequency, awkward postures and inappropriate workspace design. Three catering workers were evaluated based on job analysis and posture analysis. The results showed that the four most time-consuming tasks were arranging(17%), cooking(16%), handling before cooking(15%) and cutting(15%), and the four most frequent tasks were arranging(21%), cooking(18%), handling after cooking(16%) and handling before cooking(13%). The most common posture was a standing posture(73%) with neutral back(73%), and bent head(50%), left lower arm(71%), right lower arm(78%) and right hand(60%). The comparative analysis of subtasks for the risk levels of musculoskeletal disorders was conducted using the work time, frequency and cumulative time of the postures. The 'displaying' and 'handling after cooking' showed higher risk levels than other subtasks. In addition, the height and length of the tables were evaluated to be inadequate for the workers. It can be concluded that the working environments for catering workers of restaurants should be improved due to the high cumulative time of awkward postures of upper extremities.

• Journal of the Society of Disaster Information
• /
• v.19 no.4
• /
• pp.897-907
• /
• 2023

Purpose: In this study, We aim to estimate a untrained person's three postures using a 2D CNN model which is trained with minimal FFT data collected by a 24GHz FMCW radar. Method: In an indoor space, we collected FFT data for three distinct postures (standing, sitting, and lying) from three different individuals. To apply this data to a 2D CNN model, we first converted the collected data into 2D images. These images were then trained using the 2D CNN model to recognize the distinct features of each posture. Following the training, we evaluated the model's accuracy in differentiating the posture features across various individuals. Result: According to the experimental results, the average accuracy of the proposed scheme for the three postures was shown to be a 89.99% and it outperforms the conventional 1D CNN and the SVM schemes. Conclusion: In this study, we aim to estimate any person's three postures using a 2D CNN model and a 24GHz FMCW radar for disastrous situations in indoor. it is shown that the different posture of any persons can be accurately estimated even though his or her data is not used for training the AI model.