• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.3
• /
• pp.347-358
• /
• 2016

The paper presents a software architecture for a wearable device to measure vital signs with the real-time user's behavior recognition. Taking vital signs with a wearable device help user measuring health state related to their behavior because a wearable device is worn in daily life. Especially, when the user is running or sleeping, oxygen saturation and heart rate are used to diagnose a respiratory problems. However, in measuring vital signs, continuosly measuring like the conventional method is not reasonable because motion artifact could decrease the accuracy of vital signs. And in order to fix the distortion, a complex algorithm is not appropriate because of the limited resources of the wearable device. In this paper, we proposed the software architecture for wearable device using a simple filter and the acceleration sensor to recognize the user's behavior and measure accurate vital signs with the behavior state.

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.4
• /
• pp.93-102
• /
• 2019

As interest in wellness grows, There is a lot of research about monitoring individual health using wearable devices. Accordingly, a variety of methods have been studied to distinguish exercise from daily activities using wearable devices. Most of these existing studies are machine learning methods. However, there are problems with over-fitting on individual person's learning, data discontinuously recognition by independent segmenting and fake activity. This paper suggests a detection method for exercise activity based on the physiological response principle of heart rate up and down during exercise. This proposed method calculates activity intensity and heart rate from triaxial and photoplethysmography sensor to determine a heart rate recovery, then detects exercise by estimating activity intensity or detecting a heart rate rising state. Experimental results show that our proposed algorithm has 98.64% of averaged accuracy, 98.05% of averaged precision and 98.62% of averaged recall.

• Smart Media Journal
• /
• v.13 no.5
• /
• pp.19-25
• /
• 2024

The biggest type of behavior that prevents people with developmental disabilities from entering society is aggressive behavior. Aggressive behavior can pose a threat not only to the personal safety of the person with a developmental disability, but also to the physical safety of others. In this study, we propose a wearable system using a low-power processor. The proposed system uses an IMU (Inertial Measurement Unit) to analyze user behavior, and when attack behavior is not detected for a certain period of time through an LED array attached to the developed system, an interesting LED is displayed. By expressing patterns, we provide behavioral intervention through compensation to people with developmental disabilities. In order to implement a system that must be worn for a long time in a power-limited environment, we present a method to optimize performance and energy consumption across all stages, from data preprocessing to AI model application.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.11a
• /
• pp.264-268
• /
• 2005

This paper describes user context awareness system, which is one of the most essential technologies in various application services of ubiquitous computing. The proposed system used two-axial accelerometer, embedded in $SenseWear^{(R)}$ PRO2 Armband (BodyMedia). It was worn on the right upper arm of the experiment subjects. Using this data, PC-based fuzzy inference system was realized to distinguish human motion states, such as, tying, sitting, walking and running. The recognition rates of human motion states were 100 %, 98.64 %, 99.27 % and 100 % respectively for tying, sitting, walking and running.

• Journal of Fashion Business
• /
• v.5 no.1
• /
• pp.97-116
• /
• 2001

Character fashion was already turned up in Egyptian age and nowadays was worn to everybody as regardless of ages, level and sex of people. This paper reviewed character fashion and animation character based on USA and Japan that is outstanding more coming up today and compared and analyzed with our country's situation. Usually, character fashion would give imagnation of products and companies themselves for aesthetic sense and can show possessive feeling and personality. And that mean fashion used by character like pictures and signals(that include words figures and special signals) and these fashion using by animation character was come out in 1929. In spite of third producer, Korea, back from USA and Japan about character fashion, we faced many problems. In order to solve these problems, we must make our own pure character that do not need to pay royalty and must spread marketing strategy with character fashion of more various designs. Therefore we should concentrate for raising high quality works and avoid uneconomic investment and plagiarism and finally we must expand recognition concerning character fashion.

• International journal of advanced smart convergence
• /
• v.9 no.4
• /
• pp.132-138
• /
• 2020

Worldwide, the number of corona virus disease 2019 (COVID-19) confirmed cases is rapidly increasing. Although vaccines and treatments for COVID-19 are being developed, the disease is unlikely to disappear completely. By attaching a smart sensor to the respirator worn by medical staff, Internet of Things (IoT) technology and artificial intelligence (AI) technology can be used to automatically detect the medical staff's infection symptoms. In the case of medical staff showing symptoms of the disease, appropriate medical treatment can be provided to protect the staff from the greater risk. In this study, we design and develop a system that detects cough, a typical symptom of respiratory infectious diseases, by applying IoT technology and artificial technology to respiratory protection. Because the cough sound is distorted within the respirator, it is difficult to guarantee accuracy in the AI model learned from the general cough sound. Therefore, coughing and non-coughing sounds were recorded using a sensor attached to a respirator, and AI models were trained and performance evaluated with this data. Mel-spectrogram conversion method was used to efficiently classify sound data, and the developed cough recognition system had a sensitivity of 95.12% and a specificity of 100%, and an overall accuracy of 97.94%.

• Journal of the Korean Society for Precision Engineering
• /
• v.11 no.1
• /
• pp.138-149
• /
• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• Journal of the Ergonomics Society of Korea
• /
• v.34 no.5
• /
• pp.541-548
• /
• 2015

Objective: We introduce a hand gesture segmentation method using a wrist-worn wearable device which can recognize simple gestures of clenching and unclenching ones' fist. Background: There are many types of smart watches and fitness bands in the markets. And most of them already adopt a gesture interaction to provide ease of use. However, there are many cases in which the malfunction is difficult to distinguish between the user's gesture commands and user's daily life motion. It is needed to develop a simple and clear gesture segmentation method to improve the gesture interaction performance. Method: At first, we defined the gestures of making a fist (start of gesture command) and opening one's fist (end of gesture command) as segmentation gestures to distinguish a gesture. The gestures of clenching and unclenching one's fist are simple and intuitive. And we also designed a single gesture consisting of a set of making a fist, a command gesture, and opening one's fist in order. To detect segmentation gestures at the bottom of the wrist, we used a wrist strap on which an array of infrared sensors (emitters and receivers) were mounted. When a user takes gestures of making a fist and opening one's a fist, this changes the shape of the bottom of the wrist, and simultaneously changes the reflected amount of the infrared light detected by the receiver sensor. Results: An experiment was conducted in order to evaluate gesture segmentation performance. 12 participants took part in the experiment: 10 males, and 2 females with an average age of 38. The recognition rates of the segmentation gestures, clenching and unclenching one's fist, are 99.58% and 100%, respectively. Conclusion: Through the experiment, we have evaluated gesture segmentation performance and its usability. The experimental results show a potential for our suggested segmentation method in the future. Application: The results of this study can be used to develop guidelines to prevent injury in auto workers at mission assembly plants.

• Journal of the Korean Society of Costume
• /
• v.65 no.1
• /
• pp.118-135
• /
• 2015

In recent years, smart clothing had been developed in order to better detect and monitor physical movement of the patient, so that such activities such as location identification and biometric recognition could be done. However, most of the sensing devices of smart clothing were limited to smart sensing sports clothing and the designs did not consider the physical characteristics and the behavior of the wearer. Therefore, this study aimed to create an open protection system by developing a wearable sensing device for health monitoring and location information. For this purpose, this study developed eleven types of wearable sensing design that could be commercially sold and worn by people who needed their biological information to be constantly monitored. The study conducted four tests in order to develop three types of sensing devices for various sensing wears. The purpose of this study was to expand the user rang of smart sensing wears, and provide a foundation for the development of distinctive wearable sensing devices reflecting the user. Furthermore, contribute to the design for the person subject to protection.

• Journal of the Korean Society of Costume
• /
• v.60 no.2
• /
• pp.130-143
• /
• 2010

Hanbok industry is not based on a consumer-oriented market system, which is related to poor competitiveness in various areas, such as product planning, marketing, and flow of raw materials. The purpose of this paper is to design and conduct an empirical study on important aspects of consumers. experiences and perspectives about Hanbok, and thereby aims to provide much-needed guidance about ways to promote the Hanbok market. Out of 1065 questionnaires distributed, a total of 1039 was returned with responses and used for analyses. The respondent sample included consumers of various background characteristics in their residential areas, age, gender, education levels, and income levels. Cronbach's alpha and a factor analysis were employed for the reliability and the construct validation of the survey instrument. One-way ANOVA associated with post-hoc comparison tests was used to investigate differences across different demographic subgroups of consumers. The results show that consumers generally view Hanbok as one of the formal dresses, worn one or two times per year for traditional events or ceremonies. Consumers tend to show negative opinions about the pricing, and the inconvenience in cleaning and wearing Hanbok. However, consumers think very highly of the aesthetic values, the gracious styles, and the iconic identity of nationalism of Hanbok. This study suggests that Hanbok for modern consumers should be considered as clothing for a ritual, rather than clothing to reconstruct to be fitted to modern daily lives. Hanbok should be promoted as part of up-scaled and differentiated traditional cultures, as clothing that represents and enhances the traditional elegance and beauty unique to the Korean people.