• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.6
• /
• pp.729-738
• /
• 2019

Recently, we aim to improve the quality of virtual reality contents based on quantitative analysis results of emotions through combination of emotional recognition field and virtual reality field. Emotions are analyzed based on the participant's vital signs. Much research has been done in terms of signal analysis, but the methodology for quantifying emotions has not been fully discussed. In this paper, we propose a normalization function design and expression method to quantify the emotion between various bio - signals. Use the Brute force algorithm to find the optimal parameters of the normalization function and improve the confidence score of the parameters found using the true and false scores defined in this paper. As a result, it is possible to automate the parameter determination of the bio-signal normalization function depending on the experience, and the emotion can be analyzed quantitatively based on this.

• Journal of Biomedical Engineering Research
• /
• v.21 no.5
• /
• pp.469-475
• /
• 2000

신경신호의 계측은 신경계의 연구에 필수적인 도구로 최근 반도체미세전극기술 등 수십, 수백개의 채널로부터 신경신호를 기록할 수 있는 방법들이 발달함에 따라 많은 수의 뉴런으로부터 신경 신호를 측정하여 컴퓨터로 그 신호를 처리할 수 있는 시스템의 필요성은 더욱 커지고 있다. 본 연구에서는 최대 16채널의 신경신호를 실시간에 측정하여 기록하고, 저장된 신호로부터 활동전위를 검출하며, 단일 뉴런들로부터의 신호를 분류하여 spike train의 형태로 저장한 뒤 여러 뉴런들간의 상관관계를 분석하기 위한 spike train 해석이 가능한 시스템을 개발하였다. 이 시스템은 보통사양의 PC이외에는 단지 신호획득보드만을 포함하여 다채널미세전극으로부터 뉴런의 신호를 측정, 증폭하여 호스트PC로 전송하고 저장하며 이로부터 활동전위를 검출하여 단일뉴런으로부터의 spike train으로 분류할 수 있다. 또한 저장된 spike train들로부터 신경회로망을 이루는 여러뉴런 들간의 관계를 분석하여 기능들이 시스템에 포함되어있다. 개발된 시스템을 사용하여 개구리 감각 신경의 신호를 실시간에 동시기록하여 활동전위을 검출하고 특징추출방법과 principal component analysis를 이용하여 분류한 뒤 spike train 해석을 수행하였다.

• Journal of the Korea Computer Industry Society
• /
• v.7 no.4
• /
• pp.437-446
• /
• 2006

Mobilecomputer offers more fundamental role than role assistance enemy of modern technology equipment and new Information <중략> These main weakness puts in structural relation between elements that compose system. Therefore, dynamics research that time urea of systematic adjustment has selected method code Tuesday nerve dynamics enemy who groping of approach that become analysis point is proper and do with recycling bioelectricity signal. Nature model of do living body signal digital analysis chapter as research result could be developed and scientific foundation groping could apply HSS (Hardware-software system) by rehalibitation purpose. Special quality that is done radish form Tuesday of bioelectricity signal formation furthermore studied, and by the result, fundamental process of bodysignal in do structure circuit form of analog - digital water supply height modelling do can.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.04a
• /
• pp.1051-1053
• /
• 2015

다양한 종류의 생체 신호들을 모니터링하는 연구들이 활발히 진행되면서 이제는 병원이나 전문기관뿐만 아니라 일상 생활 속 에서 사람들이 스마트폰을 이용하여 특별한 제약 없이 편리하게 측정 가능하다. 이러한 스마트폰의 특성을 살리고 그 중 카메라 PPG (Photo-plethysmography) 모듈을 통해 얻은 생체 신호 정보를 분석하여 사용자에게 분석된 정보를 보여줄 수 있다. 또한 얻은 생체 신호로 심박수를 구하고 얻어진 심박수 정보를 활용하여 이를 사용자에게 Hologram으로 보여주는 것을 목표로 한다.

• Journal of the Korean Society of Radiology
• /
• v.17 no.7
• /
• pp.1179-1187
• /
• 2023

Recent advancements in modern transportation have led to the active development of various biomedical signal and medical imaging technologies. Particularly, in the field of cognitive/neuroscience, the importance of electroencephalography (EEG) measurement and the development of accurate EEG measurement technology in moving vehicles represent a challenging area. This study aims to extensively investigate and analyze the trends in technology research utilizing EEG during driving. For this purpose, the Scopus database was used to explore EEG-related research conducted since the year 2000, resulting in the selection of about 40 papers. This paper sheds light on the current trends and future directions in signal processing technology, EEG measurement device development, and in-vehicle driver state monitoring technology. Additionally, a ultra compact 32-channel EEG measurement module was designed. By implementing it simply and measuring and analyzing EEG signals, in-vehicle EEG module's functionality was checked. This research anticipates that the technology for measuring and analyzing biometric signals during driving will contribute to driver care and health monitoring in the era of autonomous vehicles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.985-986
• /
• 2009

기존 연구에서 환자의 응급 상황이 발생했을 경우 병원에 도착하기 전 신속하고 정확한 체계적인 관리가 환자의 생명에 많은 영향을 미친다는 연구 결과가 보고되고 있다. 대부분의 어플리케이션에서는 많은 응급 상황에 대해 실시간 생체 신호들을 모니터링이 하기 위해 전송되는 생체 신호들은 많은 제한을 두고 있으므로 이런 생체 신호들을 무선 통신 기반에서 효율적인 설계가 요구되고 있다. 따라서 본 논문은 응급 상황의 이동 중에 환자의 생체 데이터와 환자의 영상을 실시간으로 전문가에게 전송하는 시스템을 설계함으로써 병원에 도착하기까지 숙련된 전문 의료 서비스 지원을 통해서 의사가 환자의 데이터를 분석 및 평가하고 치료 과정에서 환자의 처방을 즉각적으로 지시할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.41-43
• /
• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.11
• /
• pp.183-190
• /
• 2012

Conventional physical activity monitoring systems, which use accelerometers, global positioning system (GPS), heartbeats, or body temperature information, showed limited performances due to their own restrictions on measurement environment and measurable activity types. To overcome these limitations, we developed a portable exercise analysis system that can analyze aerobic exercises as well as isotonic exercises. For bioelectric signal acquisition during exercise, waist belt with two body contact electrodes was used. For exercise analysis, the measured signals were firstly divided into two signal groups with different frequency ranges which can represent respiration related signal and muscular motion related signal, respectively. After then, power values, differential of power values, and median frequency values were selected for feature values. Selected features were used as inputs of support vector machine (SVM) to classify the exercise types. For verification of statistical significance, ANOVA and multiple comparison test were performed. The experimental results showed 100% accuracy for classification of aerobic exercise and isotonic resistance exercise. Also, classification of aerobic exercise, isotonic resistance exercise, and hybrid types of exercise revealed 92.7% of accuracy.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.3
• /
• pp.9-15
• /
• 2011

U-healthcare system has an aim to provide reliable and fast medical services for patient regardless of time and space by transmitting to doctors a large quantity of vital signs collected from sensor networks. Existing u-healthcare systems can merely monitoring patients' health status. In this paper, we describe the implementation and validation of a prototype of a u-health monitoring system based on a wireless sensor network. This system is easy to derive physiologically meaningful results by analyzing rapidly vital signs. The monitoring system sends only the abnormal data of examinee to the service provider. This technique can reduces the wireless data packet overload between a monitoring part and service provider. The real-time bio-signal monitoring system makes possible to implement u-health services and improving efficiency of medical services.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.11a
• /
• pp.257-263
• /
• 2005

If baby disease not treats at early, case that cause problem in health hereafter much exists. Specially, because baby expresses own inexpedience by crying, parents or practitioner's is not apt to grasp. Therefore, In this paper, I wish to develop system for analyze if disease is in some region to analyze face and baby cry that organism signal appears intensive for baby disease diagnosis. In this paper, I wish to propose methodology that analyze organism signal that appear in face of whole baby organism signal analysis system. For this, I necessary region binary input baby face picture and to draw necessary five sensory organ and Myungdang region in baby disease diagnosis. Finally, the usefulness of this paper is verified by several experiments.