• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.1
• /
• pp.192-200
• /
• 2015

Several algorithms have been developed to classify arrhythmia which rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to classify the pattern by analyzing personalized ECG signal and extracting minimal feature. Thus, QRS pattern Analysis of personalized ECG Signal by Q, R, S peak variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and extract eight feature by amplitude and phase variability. Also, we classified nine pattern in realtime through peak and morphology variability. PVC, PAC, Normal, LBBB, RBBB, Paced beat arrhythmia is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 93.72% in QRS pattern detection classification.

• Journal of Korea Game Society
• /
• v.17 no.3
• /
• pp.21-32
• /
• 2017

Computer games must keep the user immersed for fun. According to the immersion theory, maintaining the user's immersive state requires a continuous balance of game skill level and game difficulty level This study proposes a game skill estimation method of 9th grade that can be applied to a casual action game that can assume a zero-sum game, and additionally proposed a difficulty guessing method. The proposed methods can be implemented quickly and easily because it is a method determining by conditional mathematical expressions. Experiments on the accuracy of the proposed methods for the customized Pac-Man game show that the accuracy of the skill level was 1.2 grade as the difference on the average and the accuracy of the game difficulty level was 1.81 grade the difference on the average. The results show that the proposed methods are accurate enough to be applied to casual action games satisfying the zero-sum condition.

• Journal of Korea Game Society
• /
• v.14 no.2
• /
• pp.45-54
• /
• 2014

With the spread of game platforms fueled by the development of smartphones, such classic games as and have been transplanted in smartphone and visual media. Which stirred an issue among gamers because classic games were the materials used. However, there is a lot of room for improvement because it developed from a different viewpoint from the experiences of gamers in many cases. Based on the judgment that the reasons why the experiences of gamers were not reproduced in visual media lay in intertextuality between games and visual media, this study analyzed "Pixels" as a case of good intertexts. The analysis results of intertextuality in the game show that it applied quotation, summary, mending, and satirical travesty to the elements only known to gamers in addition to a simple arrangement of representations and parody, thus succeeding in reproducing the experiences of gamers. It also took into account popular appeal with a fresh direction not familiar to non-gamers.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.9
• /
• pp.317-322
• /
• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.