• Journal of the Korean Society of Costume
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• v.57 no.6 s.115
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• pp.1-16
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• 2007

The study aimed to develop the nightgown considering the construction and design features of the Shimui and the Cheolik. The analysis on the construction features of the Korean traditional costume and the physiological and motional attributes while sleeping resulted into the construction factors of the nightgown developed in the study. Consequently, the nightgown having these traditional Korean costume features were made for the evaluation. 4 different types of nightgowns were designed to be constructed. 20 professional clothing staff evaluated these 4 nightgowns developed and the existing nightgown used in the hotel industry. The results from the wearing test evaluation were: (1) to consider the stable closure of the gowns while wearing, the scores of the gowns developed were higher than the existing one. (2) the evaluations of the wearing comfort of the standing posture for the gowns developed and the existed were more or less similar but considering the lying down posture, the scores of the developed ones were significantly higher. (3) the gowns developed to have the wide-ham lines were considered more appropriate to the leg movement compared to the existing gown. The results from the fit and appearance test evaluation were: (1) throughout the all hight levels, the means of the gowns developed were higher than the existing gown's means in the most of the evaluation questions. (2) in the evaluation of the Korean traditional features, the gowns developed were more appropriate than the existing one. Consequently, the gowns developed were considered better to compare to the existing one in the context of postures, movements, comfort, appearance, fit, and design features.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.535-540
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• 2009

Recently, autonomous robots which can achieve the complex tasks have been required with the advance of robotics. Advanced robot vision for recognition is necessary for the realization of such robots. In this paper, we propose a method to recognize an object in the actual environment. We assume that a 3D-object model used in our proposal method is the voxel data. Its inside is full up and its surface has color information. We also define the word "recognition" as the estimation of a target object's condition. This condition means the posture and the position of a target object in the actual environment. The proposal method consists of three steps. In Step 1, we extract features from the 3D-object model. In Step 2, we estimate the position of the target object. At last, we estimate the posture of the target object in Step 3. And we experiment in the actual environment. We also confirm the performance of our proposal method from results.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.586-597
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• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• The Research Journal of the Costume Culture
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• v.3 no.1
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• pp.93-107
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• 1995

This study is concerned with the personal appearance of the Korean people implied in the Korean proverb. The results of this research was as follows: It appeared that the Korean people preferred the balanced features to the unusual ones in terms of personal appearance. It also revealed that cleanliness and neatness in clothing and in personal appearance were valued by the Korean people. Proper posture was emphasized by the Koreans. Generally, fair skin and small hands were favored by both sexes. Also the Korean people favored handsome, gentle, and decent features as well as dignified and noble character.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.63-72
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• 2014

In this paper, we propose a sign language recognition system using SVM and depth camera. Especially, we focus on the Korean sign language. For the sign language system, we suggest two methods, one in hand feature extraction stage and the other in recognition stage. Hand features are consisted of the number of fingers, finger length, radius of palm, and direction of the hand. To extract hand features, we use Distance Transform and make hand skeleton. This method is more accurate than a traditional method which uses contours. To recognize hand posture, we develop the decision tree with the hand features. For more accuracy, we use SVM to determine the threshold value in the decision tree. In the experimental results, we show that the suggested method is more accurate and faster when extracting hand features a recognizing hand postures.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.877-885
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• 2022

Vision-based activity recognition has been widely attempted at construction sites to estimate productivity and enhance workers' health and safety. Previous studies have focused on extracting an individual worker's postural information from sequential image frames for activity recognition. However, various trades of workers perform different tasks with similar postural patterns, which degrades the performance of activity recognition based on postural information. To this end, this research exploited a concept of human-object interaction, the interaction between a worker and their surrounding objects, considering the fact that trade workers interact with a specific object (e.g., working tools or construction materials) relevant to their trades. This research developed an approach to understand the context from sequential image frames based on four features: posture, object, spatial features, and temporal feature. Both posture and object features were used to analyze the interaction between the worker and the target object, and the other two features were used to detect movements from the entire region of image frames in both temporal and spatial domains. The developed approach used convolutional neural networks (CNN) for feature extractors and activity classifiers and long short-term memory (LSTM) was also used as an activity classifier. The developed approach provided an average accuracy of 85.96% for classifying 12 target construction tasks performed by two trades of workers, which was higher than two benchmark models. This experimental result indicated that integrating a concept of the human-object interaction offers great benefits in activity recognition when various trade workers coexist in a scene.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.147-156
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• 2024

This paper introduces the design of a turtle neck posture correction and prevention system for users of digital devices for a long time. The number of forward head posture patients in Korea increased by 13% from 2018 to 2021, and has not yet improved according to the latest statistics at the present time. Because of the nature of the disease, prevention is more important than treatment. Therefore, in this paper, we designed a system based on built-camera in most laptops to increase the accessiblility of the system, and utilize the features such as Pose Estimation, Face Landmarks Detection, Iris Tracking, and Depth Estimation of Google Mediapipe to prevent the need to produce artificial intelligence models and allow users to easily prevent forward head posture.

• Molecules and Cells
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• v.43 no.10
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• pp.880-888
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• 2020

Inherited peripheral neuropathy is a heterogeneous group of peripheral neurodegenerative disorders including Charcot-Marie-Tooth disease. Many peripheral neuropathies often accompany impaired axonal construction and function. To study the molecular and cellular basis of axon-defective peripheral neuropathy, we explore the possibility of using Caenorhabditis elegans, a powerful nematode model equipped with a variety of genetics and imaging tools. In search of potential candidates of C. elegans peripheral neuropathy models, we monitored the movement and the body posture patterns of 26 C. elegans strains with disruption of genes associated with various peripheral neuropathies and compiled a database of their phenotypes. Our assay showed that movement features of the worms with mutations in HSPB1, MFN2, DYNC1H1, and KIF1B human homologues are significantly different from the control strain, suggesting they are viable candidates for C. elegans peripheral neuropathy models.

• The Journal of Korean Physical Therapy
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• v.22 no.3
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• pp.45-48
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• 2010

Patients with the pusher syndrome show severe misperception of their own upright body orientation although visual vestibular processing is almost intact. They recognize their body as oriented upright when it is actually tilted nearly 20 degrees to the affected side. These patients resist any attempts to passively correct their tilted body posture towards an earth vertical upright orientation. They use the non-affected side arm and/or leg to actively push towards the affected side. Pusher syndrome patients have different prognoses and symptoms than general stroke patients without pusher syndrome. Pusher syndrome patients have a poor prognosis, so they need a long duration of treatment. Therefore, accurate diagnosis and proper treatment are important. In this study, we reviewed the symptoms, causes, evaluation, and treatment for pusher syndrome.

• Journal of Fashion Business
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• v.27 no.4
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• pp.125-140
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• 2023

This study aimed to develop a smart wearable device for assessing the risk angle associated with turtle neck syndrome in patients with Video Display Terminal (VDT) syndrome. Turtle neck syndrome, characterized by forward head posture resulting from upper cross syndrome, leads to thoracic kyphosis. In this research, a stretch sensor was used to monitor the progression of turtle neck syndrome, and the sensor data was analyzed using a Universal Testing Machine (UTM) and the Gauge Factor (GF) calculation method. The scapula and cervical spine angles were measured at five stages, with 15-degree increments from 0° to 60°. During the experimental process, the stretch sensor was attached to the thoracic spine in three different lengths: 30mm, 50mm, and 100mm. Among these, the attachment method yielding the most reliable data was determined by measuring with three techniques (General Trim Adhesive, PU film, and Heat Transfer Machine), and clothing using the heat transfer machine was selected. The experimental results confirmed that the most significant change in thoracic kyphosis occurred at approximately 30° of forward head posture. Prolonged deformity can lead to various issues, highlighting the need for textile sensor solutions. The developed wearable device aims to provide users with real-time feedback on their turtle neck posture and incorporate features that can help prevent or improve the condition.