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Yunyoung Nam,Jung Wook Park IEEE 2013 IEEE Journal of Biomedical and Health Informatics Vol.17 No.2
<P>This paper presents a child activity recognition approach using a single 3-axis accelerometer and a barometric pressure sensor worn on a waist of the body to prevent child accidents such as unintentional injuries at home. Labeled accelerometer data are collected from children of both sexes up to the age of 16 to 29 months. To recognize daily activities, mean, standard deviation, and slope of time-domain features are calculated over sliding windows. In addition, the FFT analysis is adopted to extract frequency-domain features of the aggregated data, and then energy and correlation of acceleration data are calculated. Child activities are classified into 11 daily activities which are wiggling, rolling, standing still, standing up, sitting down, walking, toddling, crawling, climbing up, climbing down, and stopping. The overall accuracy of activity recognition was 98.43% using only a single- wearable triaxial accelerometer sensor and a barometric pressure sensor with a support vector machine.</P>
Nam Yunyoung,Kim Jung-Yeon,Choi Hyung Oh,Keonsoo Lee 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.2
Atrial fi brillation (AF) is the type of arrhythmia that raises possibility of severe health problems such as heart failure and stroke and it is known that a major risk factor of AF includes overweight and obesity. Based on this association between such health-related indicators, we propose a smart scale that is capable of measuring weight and electrocardiography (ECG) simultaneously. The scale was developed using Arduino Uno, a Wheatstone bridge load cell, and ECG sensors. The ECG signals were processed to compute heart rate (in other words, RR interval). The smart scale was evaluated with four healthy volunteers in terms of reliability showing high agreement with a commercial device for ECG monitoring. In addition, it implements Atrial Fibrillation (AF) detection using machine-learning classifi ers including a k-Nearest Neighbor (kNN) method, a Decision Tree (DT), and a Neural Network (NN) on relatively short recordings of ECG obtained while using the scale. The root mean square of the successive diff erences between heart beats (RMSSD) and the Shannon entropy of the RR interval (ECG features) were extracted from ECG signals for AF detection. Performance of AF detection was tested with patients who were treated at a Cardiology Center after balancing data by applying over- and under-sampling techniques such as Synthetic Minority Over-sampling Technique (SMOTE) and the Tomek Link (T-Link) algorithm. After addressing the data imbalance, the AF detection performance of each classifi er (kNN, DT, and NNs) was 98.9%, 97.8%, and 98.9% respectively. This work has successfully demonstrated weight and cardio activity monitoring features while using a scale that may help keep the records of sensitive health related indexes on a daily basis.
Nam, Yunyoung,Kim, Yeesock The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
This paper proposes an exercise recommendation system for treating obesity that provides systematic recommendations for exercise and diet. Five body indices are considered as indicators for recommend exercise and diet. The system also informs users of prohibited foods using health data including blood pressure, blood sugar, and total cholesterol. To maximize the utility of the system, it displays recommendations for both indoor and outdoor activities. The system is equipped with multimode sensors, including a three-axis accelerometer, a laser, a pressure sensor, and a wrist-mounted sensor. To demonstrate the effectiveness of the system, field tests are carried out with three participants over 20 days, which show that the proposed system is effective in treating obesity.
Individualized Exercise and Diet Recommendations
Yunyoung Nam,Yeesock Kim 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
This paper proposes an exercise recommendation system for treating obesity that provides systematic recommendations for exercise and diet. Five body indices are considered as indicators for recommend exercise and diet. The system also informs users of prohibited foods using health data including blood pressure, blood sugar, and total cholesterol. To maximize the utility of the system, it displays recommendations for both indoor and outdoor activities. The system is equipped with multimode sensors, including a three-axis accelerometer, a laser, a pressure sensor, and a wrist-mounted sensor. To demonstrate the effectiveness of the system, field tests are carried out with three participants over 20 days, which show that the proposed system is effective in treating obesity.
남윤영(Yunyoung Nam),황인준(Eenjun Hwang) 한국정보과학회 2001 한국정보과학회 학술발표논문집 Vol.28 No.2Ⅰ
최근 들어 기업이나 관공서, 기관 등에서 상호간에 정보를 서로 교환하거나 사용자에게 게시할 때, 대부분 웹을 통해 브라우저에서 볼 수 있도록 HTML(HyperText Markup Language)형태로 제작하게 된다. 그러나 HTML로 제작된 웹 페이지는 구조적인 정보나 다양한 정보를 표시할 수 없다는 문제점이 있으며, 빠르게 변하는 정보인 경우 상세한 정보 표현 면에서 취약하다는 단점이 있다. XML(eXtensible Markup Language)은 이러한 문제점을 해결할 수 있는 마크업(markup) 언어로써 차세대 데이터 교환의 표준으로 채택하고 있다. 한편, XML이 HTML보다 더 나은 구조와 기능을 제공하고 있으나 XML 자체만으로는 XML이 가지는 여러 가지 장점들을 충분히 활용하기 어렵게 때문에 스크립트 언어의 사용이나 애플리케이션의 제작이 필수적이다. 본 논문에서는 효율적인 정보의 교환과 공유를 위해 XForm과 XML Query를 사용하여 정보를 데이터베이스에 저장하고 XML 형태로 추출, 교환할 수 있으며, 서버(server)와 클라이언트(client) 사이에서의 정보 교류뿐만 아니라 유사한 컨텐츠를 제공하는 여러 서버들간의 정보 공유를 지원하는 정보 처리 시스템을 제안한다.
이질적인 분산 환경에서의 MPEG 비디오의 파싱을 위한 스케쥴링 알고리즘
남윤영(Yunyoung Nam),황인준(Eenjun Hwang) 한국정보과학회 2004 정보과학회논문지 : 시스템 및 이론 Vol.31 No.11·12
디지털 비디오의 사용이 보편화되면서 비디오에 대한 효율적인 브라우징이나 검색의 요구가 증가하게 되었다. 이러한 연산을 지원하기 위해서는 효과적인 비디오 인덱싱이 결합되어야 한다. 비디오 인덱싱에서 가장 기초적인 단계의 하나는 비디오를 샷과 장면으로 파싱하는 것이다. 일반적으로, 비디오 파싱은 복잡한 연산을 필요로 하기 때문에, 기존의 단일 컴퓨터 환경에서는 많은 시간이 소요된다. 기존의 연구는 일정한 시간 동안에 각 슬레이브들에게 작업을 할당하는 라운드 로빈 방식을 사용하였다. 그러나 이러한 방식은 이질적인 환경에서는 적용하는데 어려움이 있다. 본 논문에서는 이질적인 분산 컴퓨팅 환경에서 사용가능한 병렬 파싱 알고리즘인 사이즈 적응적인 라운드 로빈과 동적으로 사이즈 적응적인 라운드 로빈 방식을 제안하였다. 성능을 비교하기 위해 몇 가지 실험을 하였으며, 그 결과를 분석하였다. As the use of digital videos is getting popular, there is an increasing demand for efficient browsing and retrieval of video. To support such operations, effective video indexing should be incorporated. One of the most fundamental steps in video indexing is to parse video stream into shots and scenes. Generally, it takes long time to parse a video due to the huge amount of computation in a traditional single computing environment. Previous studies had widely used Round Robin scheduling which basically allocates tasks to each slave for a time interval of one quantum. This scheduling is difficult to adapt in a heterogeneous environment. In this paper, we propose two different parallel parsing algorithms which are Size-Adaptive Round Robin and Dynamic Size-Adaptive Round Robin for the heterogeneous distributed computing environments. In order to show their performance, we perform several experiments and show some of the results.