• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.47-53
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• 2010

An analysis of biosignal and performance data collected during driving has increasingly employed in research to explore a human-vehicle interface design for better safety and comfort. The present study developed a protocol and a system to effectively analyze biosignal and driving performance measurements in various driving conditions. Electrocardiogram (ECG), respiration rate (RR), and skin conductance level (SCL) were selected for biosignal analysis in the study. A data processing and analysis protocol was established based on a comprehensive review of related literature. Then, the established analysis protocol was implemented to a computerized system so that immense data of biosignal and driving performance can be analyzed with ease, efficiency, and effectiveness for an individual and/or a group of individuals of interest. The developed analysis system would be of use to examine the effects of driving conditions to cognitive workload and driving performance.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.119-138
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• 1999

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.12-18
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• 2004

본 글에서는 인체로부터 생체전기신호를 측정하고 처리 및 해석하는 기술을 소개한다. 일반적인 계측 시스템을 구성하는 필수적인 네 가지 요소는 측정대상, 센서부, 신호처리부, 그리고 출력부이다. 생체전기신호의 측정에서 측정대상은 인체를 포함하는 생명체이다. 경우에 따라서는 생명체로부터 떼어 낸 특정 부위가 측정대상이 될 수도 있으나 본 글에서는 살아 있는 인체를 측정대상으로 설정하기로 한다. 또한 인체로부터 방사되는 에너지를 측정하는 비접촉 방식은 다루지 않고, 측정 부위를 인체의 내부 또는 표면으로 제한한다. 즉, 센서를 측정 부위에 직접 부착하는 접촉형 인체-센서 인터페이스 방법을 사용하는 경우만을 다루기로 한다.(중략)

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.313-321
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• 2021

The global market for medical devices is huge, and it will continue showing remarkable growth in the future. However, due to the entry barrier to develop medical devices, many domestic companies have technical problems in entering the medical device industry. In this paper, we introduce an open platform that can help with research and development for companies in the healthcare industry. This open platform consists of a hardware part and a software part. A hardware part is combined into CPU, base and other modules that are easy to replace and assemble. A software part is based on application software for development developed by Bionet. We test the performance of the open medical device platform using a biosignal processing algorithm.

• Journal of Microbiology and Biotechnology
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• v.30 no.8
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• pp.1207-1213
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• 2020

Aflatoxin B1 (AFB1) is a mycotoxin produced by Aspergillus flavus (A. flavus). AFB1 is reported to have high thermal stability and is not decomposed by heat treatment during food processing. Therefore, in this study, knowing that AFB1 is metabolized by cytochrome P450 (CYP), our aim was to develop a method to detoxify A. flavus-contaminated maize, under normal temperature and pressure, using Escherichia coli expressing human CYP3A4. First, the metabolic activity of AFB1 by recombinant human CYP3A4 was evaluated. As a result, we confirmed that recombinant human CYP3A4 metabolizes 98% of AFB1. Next, we found that aflatoxin Q1, a metabolite of AFB1 was no longer mutagenic. Furthermore, we revealed that about 50% of the AFB1 metabolic activity can be maintained for 3 months when E. coli expressing human CYP3A4 is freeze-dried in the presence of trehalose. Finally, we found that 80% of AFB1 in A. flavus-contaminated maize was metabolized by E. coli expressing human CYP3A4 in the presence of surfactant triton X-405 at a final concentration of 10% (v/v). From these results, we conclude that AFB1 in A. flavus-contaminated maize can be detoxified under normal temperature and pressure by using E. coli expressing human CYP3A4.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.117-126
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• 2005

In this paper, it was suggested method to recognize the motion of a person(lying, sitting, walking, running) using fuzzy inference and wireless biologic signal processing system. These are to Perceive the motion of the person. Furthermore, the information of motion is indispensable parameter for Context Awareness (CA). In the present study, ADXL 202JE accelerometer sensor was used to measure for checking the continuance motion, biological quantify of motion, and motion pattern of a Person. The measured data was transmitted to CA server by Radio Frequency(RF). From the present result, we confirmed that it is difficult to decide the motion of walking and running with only the magnitude of the Longitudinal Accelerometer Average Value(LAAV) and moreover the covariance of LAAV in any block is very useful for CA of walking and running.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.1049-1050
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• 2015

e-health보드를 이용하여 측정한 생체신호를 실시간으로 블루투스통신을 통한 무선통신을 함으로서 PC와 연결한다. PC에서 송신된 데이터를 텍스트로 저장한 뒤 c#으로 체온, 심전도, 근전도, 피층 전기 반응, 호흡 5가지의 결과 값을 그래프로 보여준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1018-1019
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• 2023

목 아래로 전신마비가 되어 간병인 없이는 일상적인 생활이 불편한 와병 환자들을 위하여 뇌파(EEG) 및 목의 근전도(EMG)와 같은 생체신호 기반의 인터페이스를 제안하였다. 이를 이용하여 환자의 이상 상태를 보호자에게 알릴 수 있고 환자의 제한적인 움직임이나 집중하는 것만으로도 간단한 서비스 등을 직접 로봇에게 명령을 내릴 수 있도록 구현하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.463-467
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• 2000

In this paper, we have implemented the Web Server Patient Monitoring System using PPP. It is composed of two parts. The first part is the Analog board for acquiring ECG signals. The second part is the module for processing and transmitting the acquired signal. The second part is using PPP for dial-up networking, TCP/IP for Internet, HTTP for web browser and JAVA program for a Patient Monitoring Program in one chip. In home, it is not need to establish another network line because it uses a telephone line. And a user who want to monitor a patient's biosignal can monitor a patient without wholly open network because it is the network sewer. The Patient Monitoring Program runs on a web browser by downloaded JAVA codes when a user connect to this system. It can make the Home Patient Monitoring Program decrease cost. It can help to avoid the limitation of monitoring a patient.