Dong Kyun Park

Home Health Gateway Based Healthcare Services Through U-Health Platform

The Ubiquitous Health, or u-Health, service is an IT health care service using the ubiquitous computing environment. U-Health provides customized medical services. As it is a service that has developed from the current hospital visiting medical system, the u-Health service provides a patient with healthcare anywhere and anytime. In this paper, we propose a home health gateway based healthcare services through the u-Health platform. Using home health gateway, u-Health can provide health monitoring, diet, and exercise services using the healthcare decision support module in the ubiquitous environment. This approach would offer specialized services using an external content provider of DB. In addition, a doctor can provide advice to patients using the monitoring service. The proposed u-Health platform provides effective services using home health gateway in ubiquitous environments to customers, which will improve the health of chronic patients.

Mobile healthcare application with EMR interoperability for diabetes patients

With digitalization of medical information and rapid distribution of smart devices, currently, healthcare service is actively planned and developed based on smart devices. By 2015, 500 million smartphone users are expected to use a mobile health application, especially for exercise, diet, and chronic disease management. Unlike other chronic diseases, diabetes can be managed by the patient. Therefore smart mobile device can be a universal tool for self-diabetes management because of its high penetration and functions. A mobile healthcare application for Android OS was developed to provide self-diabetes management. The application consists of Diabetes management, Weight management, Cardio-cerebrovascular risk evaluation, Stress and depression evaluation and Exercise management. The application synchronizes data with hospital’s EMR database to provide accurate data with minimized process of data input. This paper introduces detailed structure and functionalities of the application with EMR data synchronization aspect.

Evaluation of practical exercises using an intravenous simulator incorporating virtual reality and haptics device technologies

This study confirmed the educational effectiveness of practical exercises (PE) using intravenous (IV) simulators incorporating virtual reality (VR)/haptics (based on the sense of touch) device technologies. First-year nursing students (n=114) were randomly divided into three PE groups: Group A, utilizing a conventional arm model (IV arm); Group B, utilizing a VR/Haptics IV Simulator (IV sim); and Group C, utilizing both the IV arm and IV sim. Group C scored highest on procedures for conducting venipuncture. Group B was more successful in performing injections than Groups A and C. Group C required significantly less time than Group B to complete a venipuncture injection and was faster than Group A, although this difference was not significant. In conclusion, a new paradigm of PE is suggested using both IV sim and IV arm.

Trend of wireless u-Health

Wireless network based u-Health services enable peoples health care anytime, anywhere. Recently technology advance in the area of sensing, networking, processing is developed rapidly. This advance of information technology is raising the change of traditional healthcare system. By using wireless and mobile networks, patients could be monitored and managed outside hospitals and also examined with safety and efficiency in hospitals. Even though there are lots of services for u-Health including commercial services, to envision and make u-Health become more active in the future, safety and usefulness of u-Health in the perspective of medicine should be needed.

Differences among admitting departments in alerts and alert overrides for drug-drug interaction.

To determine differences in the incidence and risk factors of alerts for drug–drug interaction (DDI) and the rate of alert overrides by an admitting department.

Smart Information System for Gachon University Gil Hospital

Objectives In this research, the hospital information system of Gachon University Gil hospital is introduced and a future strategy for hospital information systems is proposed. Methods This research introduces the development conditions of hospital information system at Gachon University Gil hospital, information about the development of the enterprise resource planning (ERP), a medical service process improvement system, and the personal health record (PHR) system. Results The medical service process and work efficiency were improved through the medical service process improvement system, which is the most common hospital information system at Gachon University Gil hospital and which includes an emergency medical service system, an online evaluation system and a round support system. Conclusions Gachon University Gil hospital developed medical service improvement systems to increase work efficiency of medical team and optimized the systems to prove the availability of high-quality medical services for patients and their families. The PHR-based personalized health care solution is under development and will provide higher quality medical service for more patients in the future.

A multi-classifier based guideline sentence classification system.

Objectives An efficient clinical process guideline (CPG) modeling service was designed that uses an enhanced intelligent search protocol. The need for a search system arises from the requirement for CPG models to be able to adapt to dynamic patient contexts, allowing them to be updated based on new evidence that arises from medical guidelines and papers. Methods A sentence category classifier combined with the AdaBoost.M1 algorithm was used to evaluate the contribution of the CPG to the quality of the search mechanism. Three annotators each tagged 340 sentences hand-chosen from the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7) clinical guideline. The three annotators then carried out cross-validations of the tagged corpus. A transformation function is also used that extracts a predefined set of structural feature vectors determined by analyzing the sentential instance in terms of the underlying syntactic structures and phrase-level co-occurrences that lie beneath the surface of the lexical generation event. Results The additional sub-filtering using a combination of multi-classifiers was found to be more effective than a single conventional Term Frequency-Inverse Document Frequency (TF-IDF)-based search system in pinpointing the page containing or adjacent to the guideline information. Conclusions We found that transformation has the advantage of exploiting the structural and underlying features which go unseen by the bag-of-words (BOW) model. We also realized that integrating a sentential classifier with a TF-IDF-based search engine enhances the search process by maximizing the probability of the automatically presented relevant information required in the context generated by the guideline authoring environment.

Association with Self-Perception for Obesity and Mental Health among Korean Adolescent

：Obesity has been linked to various psychological problems as well as medical complications, especially among adolescents. Previous studies have suggested an association between body weight and depression or self-esteem ; however, there has been little evidence on self-perception of weight and mental health. The aim of this study was to examine the associa-tion of perceptional weight status with mental health in Korean adolescents.

Personalized Urination Activity Recognition Based on a Recurrent Neural Network Using Smart Band

Purpose Though it is very important obtaining exact data about patients’ voiding patterns for managing voiding dysfunction, actual practice is very difficult and cumbersome. In this study, data about urination time and interval measured by smart band device on patients’ wrist were collected and analyzed to resolve the clinical arguments about the efficacy of voiding diary. By developing a smart band based algorithm for recognition of complex and serial pattern of motion, this study aimed to explore the feasibility of measurement the urination time and intervals for voiding dysfunction management. Methods We designed a device capable of recognizing urination time and intervals based on specific postures of the patient and consistent changes in posture. These motion data were obtained by a smart band worn on the wrist. An algorithm that recognizes the repetitive and common 3-step behavior for urination (forward movement, urination, backward movement) was devised based on the movement and tilt angle data collected from a 3-axis accelerometer. The sequence of body movements during voiding has consistent temporal characteristics, so we used a recurrent neural network and long short-term memory based framework to analyze the sequential data and to recognize urination time. Real-time data were acquired from the smart band, and for data corresponding to a certain duration, the value of the signals was calculated and then compared with the set analysis model to calculate the time of urination. A comparative study was conducted between real voiding and device-detected voiding to assess the performance of the proposed recognition technology. Results The accuracy of the algorithm was calculated based on clinical guidelines established by urologists. The accuracy of this detecting device was high (up to 94.2%), proving the robustness of the proposed algorithm. Conclusions This urination behavior recognition technology showed high accuracy and could be applied in clinical settings to characterize patients’ voiding patterns. As wearable devices are developed and generalized, algorithms detecting consistent sequential body movement patterns reflecting specific physiologic behavior might be a new methodology for studying human physiologic behavior.

Development of Personalized Urination Recognition Technology Using Smart Bands

Purpose This study collected and analyzed activity data sensed through smart bands worn by patients in order to resolve the clinical issues posed by using voiding charts. By developing a smart band-based algorithm for recognizing urination activity in patients, this study aimed to explore the feasibility of urination monitoring systems. Methods This study aimed to develop an algorithm that recognizes urination based on a patient’s posture and changes in posture. Motion data was obtained from a smart band on the arm. An algorithm that recognizes the 3 stages of urination (forward movement, urination, backward movement) was developed based on data collected from a 3-axis accelerometer and from tilt angle data. Real-time data were acquired from the smart band, and for data corresponding to a certain duration, the absolute value of the signals was calculated and then compared with the set threshold value to determine the occurrence of vibration signals. In feature extraction, the most essential information describing each pattern was identified after analyzing the characteristics of the data. The results of the feature extraction process were sorted using a classifier to detect urination. Results An experiment was carried out to assess the performance of the recognition technology proposed in this study. The final accuracy of the algorithm was calculated based on clinical guidelines for urologists. The experiment showed a high average accuracy of 90.4%, proving the robustness of the proposed algorithm. Conclusions The proposed urination recognition technology draws on acceleration data and tilt angle data collected via a smart band; these data were then analyzed using a classifier after comparative analyses with standardized feature patterns.