A mobile tele-radiology imaging system with JPEG2000 for an emergency care.

The aim of this study was to design a tele-radiology imaging system for rapid emergency care via mobile networks and to assess the diagnostic feasibility of the Joint Photographic Experts Group 2000 (JPEG2000) radiological imaging using portable devices. Rapid patient information and image exchange is helpful to make clinical decisions. We assessed the usefulness of the mobile tele-radiology system by measuring both a quantitative method, PNSR calculation, for image qualities, and its transmission time via mobile networks in different mobile networks, respectively; code division multiple access evolution-data optimized, wireless broadband, and high-speed downlink packet access; and the feasibility of the JPEG2000 computed tomography (CT) images by qualitatively assessing with the Alberta stroke program early CT score method with 12 CT image cases (seven normal and five abnormal cases). We found that the quality of the JPEG2000 radiological images was satisfied quantitatively and was judged as acceptable qualitatively at 5:1 and 10:1 compression levels for the mobile tele-radiology imaging system. The JPEG2000-format radiological images achieved a fast transmission while maintaining a diagnosis quality on a portable device via mobile networks. Unfortunately, a PDA device, having a limited screen resolution, posed difficulties in reviewing the JPEG2000 images regardless of the compression levels. An ultra mobile PC was preferable to study the medical image. The mobile tele-radiology imaging systems supporting JPEG2000 image transmission can be applied to actual emergency care services under mobile computing environments.ope

(A) study of emotional state detection algorithm using bio-signal

생체공학 협동과정/석사[한글]본 논문의 목적은 생체신호를 이용해 인간의 감정상태를 추정하는 것이다. 인간의 감정상태 추정을 위해 최적의 감정데이터 추출, 생체 파라미터 조합, 정확도와 계산 복잡도의 trade off등이 본 연구에서 다루고 있는 부분이다. 감정은 연속적이고 순간적으로 변화하기도하며 지속적인 감정상태를 나타내기도 한다. 연구의 목적은 순간적인 감정의 변화를 검출하는 것이고 인간의 감정을 다음과 같이 정의했다. 순간적인 감정상태를 측정하고 추정하기 위해 우선적으로 인간의 감정을 이원적인 두 가지 형태(쾌/불쾌)로 나누었다. 남성 19 여성 6명을 대상으로 감정유발실험을 진행 했으며 감정유발에 대한 자기설문평가(SAM)을 실시했다. Lang에 의해 고안된 SAM평가는 실험자에게 얻어진 데이터가 정말 감정이 유발된 데이터인지 아닌지에 대한 판단기준으로 작용했으며, 자극에 대한 반응정도에 대한 기준으로 작용되어 감성자극 실험에 유용한 설문지로 사용되었다. 인간의 감정상태를 정량적인 데이터로 나타내기 위해 3가지 생체신호 데이터를 측정 (ECG, GSR, SKT) 했다. 위 3가지 데이터는 비교적 측정하는 조건이 까다롭지 않았기 때문에 실험자가 측정 시 불편함을 거의 느끼지 못했다. 감정 유발되어 측정된 생체신호는 신호처리 과정과 패턴인식 과정을 거치게 된다. 우리는 순간적인 감정상태변화를 정확하게 검출하는데 목적이 있기 때문에 전처리 과정으로 생체신호 특징을 추출했고 여러 가지 다양한 패턴인식 알고리즘을 평가함으로써 감정추정에 높은 성능을 나타내는 알고리즘을 구성할 수 있었다.본 연구에서는 생체신호만을 이용해서 인간의 감정상태를 높은 정확도로 추정할 수 있었으며 사용된 각 파라미터는 손쉽게 측정 가능했고, 그 결과로서 간단한 생체신호의 측정만으로 인간의 감정상태를 정확히 추정함으로써 반응 형 유비쿼터스 서비스를 제공하는 핵심 기술로 활용 가능함을 말해주고 있다. [영문]The goal of this thesis is to develop the emotional state detection algorithm which responses according to user’s emotions. For this, we tried to distinguish emotions of human using biosignal parameters of ANS(Autonomous Nervous System). Why we especially focused on ANS is that ANS can not be adjusted by one's will and can reflect the changes in emotions. So we selected GSR, HRV and SKT as representative parameters which show the changes in ANS among many parameters of ANS. 25 subjects were participated for the Emotion-Experiment. We chose some video materials which can induce negative emotion or positive emotion from the supine subject and measured GSR, HRV and SKT while they are watching that materials. The data from those three parameters GSR, HRV and SKT were segmented and we analyzed and extracted the features of each segment. The results showed that there is a big difference between the positive and negative emotions. This paper shows that we can exactly distinguish two emotions using a few biological parameters.ope

정신-생리학적 해석 기반 생체신호처리기법을 이용한 정서상태의 정량적 분석

Interdisciplinary Program on Biomedical Engineering Dept. of Electrical and Electronic Engineering/박사The objective of this thesis is to investigate human emotion and cognitive states based on the psycho-physiological understanding using various biosignals. Three experiments were performed by participant with independent experimental environment and protocols. These results and expected effects were summarized as follows.(1) The study of human emotion was shown the difference for the responses of event related potential (ERP) from participants (n=19, 30 age) through two kinds of protocols (picture: number set with emotional faces: cognitive responses depending on emotion distractor, video clips: sadness/amusement emotion stimuli: cognitive responses with emotion mood as interference).The first experiment has statistically approached the ERPs (n75, p100, n200, and p300) by correspondence with emotional faces from EEG signal. The ERPs were relatively more influenced by negative emotional faces such as annoy, disgust, and sadness. The second experiment demonstrate that negative emotion (sadness) could has an affected on the cognitive abilities (ERP, behavioral response) as interference, and these response has a trend depending on both gender and disposition. (2) The developed method, genetic algorithm based optimized extreme learning machine, demonstrate that this algorithm has resulted in the high accuracy (87.9%), the selection of dominated EEG features, and optimized algorithm structure for classifying the mental states.(3) Sleep study was investigated compromising factors between the accuracy for estimating the sleep stage and the convenience for measuring signal. EEG is recommended for applications that require high accuracy (85%), whereas for applications that prioritize ease of measurement rather than accuracy, use of the autonomic nervous system related signal combination is recommended (80%).From the three independent experiments, I expect these results have a positive spreading effect. (1) These results have shown the possibility of quantitative analysis for estimating human affective states from biological features and advanced algorithms. These results and methods are available in psychology, medicine, ergonomics, and forensic science. (2) The developed algorithm with attention (cognition) could be applicable to education and medicine (e.g. ADHD). Finally, (3) we could indirectly estimate human emotional states by analysis of sleep stage. Thus, proposed analytic method (accurate and convenience for sleep stage estimation) could be understood to emotion and cognition of human easily.restrictio

금속성 나노와이어의 전계방출과 퍼짐 수송

Thesis(doctoral)--서울대학교 대학원 :물리학부,2005.Docto

An analysis of correlation between EEG signal and HRV during attentional status with children under 15 years

This paper illustrates the inter-relationship between the theta/alpha ratio of the EEG signal and multiple HRV related parameters associated with the cardiovascular system response during event-related stimuli. Both EEG and PPG signals were simultaneously recorded in 21 healthy subjects. All subjects had their attention focused on the CNT program for nine minutes. Time-frequency analysis was applied to the EEG and PPG signals. The theta/alpha ratio was extracted from the EEG results, and the HRV features, including beat interval(1), SDNN(2), RMSSD(3), NN50(4), LF(5), HF(6), and LF/HF(7), were extracted from the PPG. Through multiple linear regression, the relationship (R2) between the multiple combined features and the theta/alpha rhythm was identified. As a result, the combinations of R2(R2=0.253; seven dimensions) and the theta/alpha ratio indicated a higher inter-relationship value than those of other combinations. The combinations of features that were greater than three dimensions, based on {SDNN(2), HF(6)}, generally showed higher R2 value. We demonstrate that the high dimensional combinations had a higher correlation than did the low dimensional combinationsope

HRV Analysis for Aged Using Visual Stimulus Protocol

The ratio of aged class has been increasing gradually not only in Korea, but also in the world since several years ago. As a result, many unexpected social problems started to now. The burden charged to this society is to solve those problems; how to take care of that aged people, how to offer jobs to them, etc. It means that the study about the aged class should be done soon. Due to that need, this thesis is wrote out. The aim of this thesis is to detect the emotion of aged people and establish a certain algorithm for detecting it. In the whole process of experiment and analysis, I used HRV(Heart Rate Variability) data since the heart is a representative which is controlled by the ANS(autonomic nervous system), and the ANS reflects the changes in emotion. After stimulating the aged people with the authorized pictures which induce different emotions each. 1 measured HRV of those aged. The HRV data is then analyzed in the two domain area, time and frequency. 1 guessed that the result would show some certain differences according to the pictures and it was shown from the experiment. Seeing the result, HRV was changed by what the aged felt looking at the pictures. Then it also means that visual stimulation influence on the has of the aged people.ope

Wearable ECG Monitoring System Using Conductive Fabrics and Active Electrodes

The aim of this paper is to develop nonintrusive type ECG monitoring system based on active electrode with conductive fabric. Our developed electrode can measure ECG signal without the electrolyte gel or the adhesives causing skin trouble. For the stable measurement of ECG signal, the buffer amplifier with high input impedance and the noise bypassing shield with conductive fabric were developed. This system involves real-time ECG signal monitoring, and wireless communication using the Zigbee protocol. We show experimental results for developing wearable ECG monitoring system and demonstrate how it can be applied to the design of nonintrusive electrode with conductive fabricope

Genetic fuzzy classifier for sleep stage identification

Soft-computing techniques are commonly used to detect medical phenomena and help with clinical diagnoses and treatment. In this work, we propose a design for a computerized sleep scoring method, which is based on a fuzzy classifier and a genetic algorithm (GA). We design the fuzzy classifier based on the GA using a single electroencephalogram (EEG) signal that detects differences in spectral features. Polysomnography was performed on four healthy young adults (males with a mean age of 27.5 years). The sleep classifier was designed using a sleep record and tested on the sleep records of the subjects. Our results show that the genetic fuzzy classifier (GFC) agreed with visual sleep staging approximately 84.6% of the time in detection of wakefulness (WA), shallow sleep (SS), deep sleep (DS), and rapid eye movement (REM) stagesope