Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in Individuals in Their 20s and 30s.

This study demonstrates how to generate a three-dimensional (3D) body model through a small number of images and derive body values similar to the actual values using generated 3D body data. In this study, a 3D body model that can be used for body type diagnosis was developed using two full-body pictures of the front and side taken with a mobile phone. For data training, 400 3D body datasets (male: 200, female: 200) provided by Size Korea were used, and four models, i.

Establish a machine learning based model for optimal casting conditions management of small and medium sized die casting manufacturers.

Die casting is a suitable process for producing complex and high precision parts, but it faces challenges in terms of quality degradation due to inevitable defects. The casting parameters play a significant role in quality, and in many cases, producers rely on their experience to manage these parameters. In order to address this, domestic small and medium sized die casting companies have established smart factories (MES) and collected data.

Machine learning-based obesity classification considering 3D body scanner measurements.

Obesity can cause various diseases and is a serious health concern. BMI, which is currently the popular measure for judging obesity, does not accurately classify obesity; it reflects the height and weight but ignores the characteristics of an individual's body type. In order to overcome the limitations of classifying obesity using BMI, we considered 3-dimensional (3D) measurements of the human body.

Development of an intrinsic health risk prediction model for camera-based monitoring of older adults living alone.

The number of older adults in Korea is increasing, along with the number of depressed older patients. The causes of depression in older adults include social isolation with negligible interaction with others, irregular nutritional habits, and self-negligence, i.e.

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values.

This study uses various body values (length, circumference, and volume) that can be derived from 3D data to determine variables and areas that substantially affect obesity and suggests guidelines for diagnosing obesity that are more elaborate than existing obesity indices. Body data for 170 participants (87 men and 73 women aged 20-30 years) are collected for the chest, abdomen, hips, and arms/legs. A 3D scanner, which can produce accurate body point results, and dual-energy X-ray (DEXA), which can accurately determine the fat percentage, are used to derive fat rates for each body part.

Artificial intelligence in positioning between mandibular third molar and inferior alveolar nerve on panoramic radiography.

Determining the exact positional relationship between mandibular third molar (M3) and inferior alveolar nerve (IAN) is important for surgical extractions. Panoramic radiography is the most common dental imaging test. The purposes of this study were to develop an artificial intelligence (AI) model to determine two positional relationships (true contact and bucco-lingual position) between M3 and IAN when they were overlapped in panoramic radiographs and compare its performance with that of oral and maxillofacial surgery (OMFS) specialists.

Development of a Wearable Camera and AI Algorithm for Medication Behavior Recognition.

As many as 40% to 50% of patients do not adhere to long-term medications for managing chronic conditions, such as diabetes or hypertension. Limited opportunity for medication monitoring is a major problem from the perspective of health professionals. The availability of prompt medication error reports can enable health professionals to provide immediate interventions for patients.

Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains.

In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessment method to verify scalability when implementing traceability systems based on key technologies for smart factories, such as Internet of Things (IoT) and BigData. To this end, based on existing research, we analyzed traceability requirements and an event schema for storing traceability data in MongoDB, a document-based Not Only SQL (NoSQL) database.

Environment and Its Influence on Health and Demographics in South Korea.

As the prevalence of overweight and obesity has been increasing in South Korea, it is critical to better understand possible associations between environmental surroundings and general health status. We characterize key health test readings and basic demographic information from 10,816 South Koreans, obtained from two Ubiquitous Healthcare (U-Healthcare) centers that have distinct surrounding neighborhood characteristics. One is located in a rural area in Busan, the other is located in an urban area in Daegu surrounded by a highly crowded residential and commercial business area.

Wearable Sensing of In-Ear Pressure for Heart Rate Monitoring with a Piezoelectric Sensor.

In this study, we developed a novel heart rate (HR) monitoring approach in which we measure the pressure variance of the surface of the ear canal. A scissor-shaped apparatus equipped with a piezoelectric film sensor and a hardware circuit module was designed for high wearability and to obtain stable measurement. In the proposed device, the film sensor converts in-ear pulse waves (EPW) into electrical current, and the circuit module enhances the EPW and suppresses noise.

U-Healthcare Center Service in Busan City, South Korea: An Empirical Analysis and the Results of 1 Year of Service.

Introduction: Studies have demonstrated that technological innovation is vital for prosperous economies, and greater technological innovation leads to improved public health indicators. The South Korean government has implemented policies to provide city services using information communication technologies, and ubiquitous healthcare (u-healthcare) wellness is one of these. This article presents the effects of using a u-healthcare center model that proves self-healthcare monitoring can work for the general population.

The Development and User Satisfaction Evaluation of Internet-Based N-Screen Healthcare Walking Content to Increase Continuous Usage Motivation.

Objective: The purpose of the current study is (1) to apply Internet-based N-Screen (this is used like the term "emultiscreen"; as the technology that provides services of shared content or application via N devices, it includes all screens such as personal computers [PCs], TV, and mobile devices) services to healthcare services by developing games for improving one's health and (2) to present ways to activate the use of health promotion contents in the future by investigating user satisfaction and whether there is any intention to accept the contents and/or use the services continuously.

Materials And Methods: In order to evaluate the customized health maintenance content provided by the healthcare walking system developed in the current study, 98 adult men and women residing in Seoul, Korea, were instructed to use 10 minutes' worth of the walking content. Perceived quality, level of trust in the results, effectiveness of the exercise, and overall satisfaction were measured in regard to the N-Screen-based walking content, including those for the cell phone, PC, and Internet protocol TV (IPTV).

How the awareness of u-healthcare service and health conditions affect healthy lifestyle: an empirical analysis based on a u-healthcare service experience.

Objective: The objectives of this study are (1) to establish a ubiquitous healthcare (u-healthcare) center for those who wish to use u-healthcare, allowing them to experience the service, and (2) to evaluate the users' awareness and expectations of the service based on their overall assessment.

Materials And Methods: To establish the u-healthcare center, a kiosk, devices for health checkup, a body-type examination system, and a physical fitness assessment system were installed. Also, a u-healthcare Web site was developed.

Development and evaluation of a mobile application for personal lifestyle check-up and improvement.

Objective: This study aimed (1) to help individuals analyze their own health status by checking their lifestyle, (2) to develop a user-friendly mobile application that offered prescriptions for lifestyle improvement, and (3) to examine whether the developed application had positive effects on users.

Materials And Methods: In order to develop a lifestyle analysis engine that would operate in an Android(®) (Google, Mountain View, CA)-based mobile application, survey data on health awareness behaviors of 25,124 participants from the 2009 Korean National Health and Nutrition Examination Survey (KNHANES) were analyzed. Additionally, in order for the users to be aware of their lifestyles and explore the effects of the developed mobile application on lifestyle management and improvement, an additional survey of the lifestyle awareness and levels of motivation for lifestyle improvement of 152 users was conducted.