• Title/Summary/Keyword: Bio-signals

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Estimation of Stress Status Using Bio-signals and Fuzzy Theory (생체신호와 퍼지이론을 이용한 스트레스 평가에 관한 연구)

  • Sin, Jae-U;Yun, Yeong-Ro;Park, Se-Jin
    • Journal of the Ergonomics Society of Korea
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    • v.18 no.1
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    • pp.121-131
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    • 1999
  • There have been many questionnaires, catecholeamins analysis and bio-signal analysis to analyze human stress condition through out the years, and especially researches in bio-signal analysis have been actively increasing. The purpose of our research is Quantitative analysis of stress with synthesis of bio-signals. The stress status was estimated using the bio-signals and fuzzy theory which combines these signals and physiological knowledge. Stress was estimated by a 'coin-stacking' experiment with two type-relax and stress status. To do the experiment EMG, respiration, periphery temperature, heart rate and skin conductances were used to evaluate human stress stages. The system was tested to 10 healthy persons and achieved a template of a stress progress and stress variations were classified to 4 steps by continuous or rising status of stress progress.

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Implementation of Implantable Bluetooth Bio-telemetry System for Transmitting Acoustic Signals in the Body with Wireless Recharging Function (무선 충전 가능한 블루투스 방식의 체내 음향신호 전송용 이식형 바이오 텔레메트리 시스템 구현)

  • Lee, Sang-June;Kim, Myoung Nam;Lee, Jyung Hyun;Lim, Hyung-Gyu;Cho, Jin-Ho
    • Journal of Korea Multimedia Society
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    • v.18 no.5
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    • pp.652-662
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    • 2015
  • It is necessary to develop small, implantable bio-telemetry systems which can measure and transmit patients' bio-signals from internal body to external receiver. When measuring bio-signals, like electrical bio-signals, acoustic bio-signal measurement has also a big clinical usefulness. But, sound signal has larger frequency bandwidth than any other bio-signals. When considering these issues, a wireless telemetry system which has rapid data transmission rate proportional to wide frequency bandwidth is necessary to be developed. The bluetooth module is used to overcome the data rate limitation caused by the large frequency bandwidth. In this paper, a novel multimedia bluetooth biotelemetry system was developed which consists of transmitter module located in the body and receiver device located outside of the body. The transmitter consists of microphone, bluetooth, and wireless charging device. And the receiver consists of bluetooth and codec system. The sound inside the skin is captured by microphone and sent to receiver by bluetooth while charging. The wireless charging system constantly supplies the electric power to the system. To verify the performance of the developed system, an in vitro experiment has been performed. The results show that the proposed biotelemetry system has ability to acquire the sound signals under the skin.

SQUID Systems for Magnetocardiographic Applications

  • Lee, Yong-Ho;Kim, Jin-Mok;Kwon, Hyuk-Chan;Yu, Kwon-Kyu;Kim, Ki-Woong;Park, Yong-Ki
    • Progress in Superconductivity and Cryogenics
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    • v.9 no.2
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    • pp.1-6
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    • 2007
  • As very sensitive magnetic field sensors, superconducting quantum interference devices (SQUIDs) are used to measure magnetic field signals from the human heart. By analyzing these cardiomagnetic signals, functional diagnoses of heart can be done. In order to measure weak biomagnetic signals, we need a multichannel SQUID array with sensor coverage large enough to cover the whole heart to enable the measurement in a single position setting. In this paper, we review the recent development of SQUID systems for measuring cardiomagnetic fields, with special emphasis on SQUID types.

Driving Performance Evaluation Using Bio-signals from the Prefrontal Lobe in the Driving Simulator

  • Kim, Young-Hyun;Kim, Yong-Chul
    • Journal of the Ergonomics Society of Korea
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    • v.31 no.2
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    • pp.319-325
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    • 2012
  • Objective: The aim of this study was to develop the assistive device for accelerator and brake pedals using bio-signals from the prefrontal lobe in the driving simulator and evaluate its performance. Background: There is lack of assistive devices for the driving in peoples with disabilities in Korea. However, if bio-signals and/or brain waves are used at driving a car, the people with serious physical limitations can improve their community mobility. Method: 15 subjects with driver's license participated in this study for experiment of driving performance evaluation in the simulator. Each subject drove the simulator the same course 10 times in three separated groups which use different interface controllers to accelerate and brake: (1) conventional pedal group, (2) joystick group and (3) bio-signal group(horizontal quick glance of the eyes and clench teeth). All experiments were recorded and the driving performances were evaluated by three inspectors. Results: Average score of bio-signal group for the driving in the simulator was increased 3% compared with the pedal group and was increased 9% compared with the joystick group(p<0.01). The subjects using bio-signals was decreased 44% in number of deduction compared with others because the device had the built-in modified cruise control. Conclusion: The assistive device for accelerator and brake pedals using bio-signals showed significantly better performance than using general pedal and a joystick interface(p<0.01). Application: This study can be used to design adaptive vehicle for driving in people with disabilities.

A Study on Ubiquitous Psychological State Recognition Model Using Bio-Signals (생체정보를 이용한 유비쿼터스 심리상태 인식 모델 연구)

  • Chon, Ki-Hwan;Choi, Hyung-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.2B
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    • pp.232-243
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    • 2010
  • In this paper, various physiological signals of humans were measured and analyzed to inference their psychological state and biological information, and Bio-Signal Context aware system (BSC), which recognizes the current context of its users as well as the information of exterior environment and offers the service appropriate for them, was designed and implemented. The BSC extracts and analyzes the features from bio-signals, such as the measured electroencephalogram (EEG), electrocardiogram (ECG), and galvanic skin response (GSR), with its different sensors, has the input of the analyzed results, and discriminates four psychological states of rest, concentration, tension and melancholy. In addition to the results of the discriminated psychological states, the information of biological condition analyzed from the user's bio-signals, for example, heart rate variability (HRV), Galvanic skin response (GSR) and body temperature, and the information of external environment related to the user's are collected to offer the service fit for the user's present biological condition by inferring and recognizing the user's present situation.

Design of Computer Access Devices for Severly Motor-disability Using Bio-potentials (생체전위를 이용한 중증 운동장애자들을 위한 컴퓨터 접근제어장치 설계)

  • Jung, Sung-Jae;Kim, Myung-Dong;Park, Chan-Won;Kim, Il-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.11
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    • pp.502-510
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    • 2006
  • In this paper, we describe implementation of a computer access device for the severly motor-disability. Many people with severe motor disabilities need an augmentative communication technology. Those who are totally paralyzed, or 'locked-in' cannot use conventional augmentative technologies, all of which require some measure of muscle control. The forehead is often the last site to suffer degradation in cases of severe disability and degenerative disease. For example, In ALS(Amyotrophic Lateral Sclerosis) and MD(Muscular dystrophy) the ocular motorneurons and ocular muscles are usually spared permitting at least gross eye movements, but not precise eye pointing. We use brain and body forehead bio-potentials in a novel way to generate multiple signals for computer control inputs. A bio-amplifier within this device separates the forehead signal into three frequency channels. The lowest channel is responsive to bio-potentials resulting from an eye motion, and second channel is the band pass derived between 0.5 and 45Hz, falling within the accepted Electroencephalographic(EEG) range. A digital processing station subdivides this region into eleven components frequency bands using FFT algorithm. The third channel is defined as an Electromyographic(EMG) signal. It responds to contractions of facial muscles and is well suited to discrete on/off switch closures, keyboard commands. These signals are transmitted to a PC that analyzes in a time series and a frequency region and discriminates user's intentions. That software graphically displays user's bio-potential signals in the real time, therefore user can see their own bio-potentials and control their physiological signals little by little after some training sessions. As a result, we confirmed the performance and availability of the developed system with experimental user's bio-potentials.

Multi-modal Authentication Using Score Fusion of ECG and Fingerprints

  • Kwon, Young-Bin;Kim, Jason
    • Journal of information and communication convergence engineering
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    • v.18 no.2
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    • pp.132-146
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    • 2020
  • Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

Deep Learning based Emotion Classification using Multi Modal Bio-signals (다중 모달 생체신호를 이용한 딥러닝 기반 감정 분류)

  • Lee, JeeEun;Yoo, Sun Kook
    • Journal of Korea Multimedia Society
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    • v.23 no.2
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    • pp.146-154
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    • 2020
  • Negative emotion causes stress and lack of attention concentration. The classification of negative emotion is important to recognize risk factors. To classify emotion status, various methods such as questionnaires and interview are used and it could be changed by personal thinking. To solve the problem, we acquire multi modal bio-signals such as electrocardiogram (ECG), skin temperature (ST), galvanic skin response (GSR) and extract features. The neural network (NN), the deep neural network (DNN), and the deep belief network (DBN) is designed using the multi modal bio-signals to analyze emotion status. As a result, the DBN based on features extracted from ECG, ST and GSR shows the highest accuracy (93.8%). It is 5.7% higher than compared to the NN and 1.4% higher than compared to the DNN. It shows 12.2% higher accuracy than using only single bio-signal (GSR). The multi modal bio-signal acquisition and the deep learning classifier play an important role to classify emotion.

Development of Measurement System of Cutter Conditions for Combine Diagnosis (I) - Analysis of Vibration and Load Signals - (콤바인 예취부 고장진단을 위한 예취 칼날부의 진단 시스템 개발(I) - 진동 및 부하 신호 분석 -)

  • Choi, Chang-Hyun;Kim, Yong-Joo;Kim, Jong-Hyuck;Mun, Joung-Hwan
    • Journal of Biosystems Engineering
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    • v.32 no.3
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    • pp.190-196
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    • 2007
  • The purpose of this study is to develop a measurement system of cutter conditions for combine header diagnosis during rice harvesting. A load cell was installed at the locker-arm to measure load fluctuation and an acceleration senor was used to monitor vibration signal of cutter bar. The data were collected from a paddy field during harvesting. The tests were conducted with a normal cutter, a loosened cutter, a broken cutter, and a worn-out connecter pin at the field. The vibration signals converted by FFT (Fast Fourier Transformation), filtered, and normalized. The load data and peak values of vibration signals in four different frequency ranges were used to determine the cutting operation and the cutter conditions of combine. The multiple comparison tests showed that the load data and peak values of vibration signals were important to monitor the cutting operation and cutter conditions of combine header.

A Study on Algorithm of Emotion Analysis using EEG and HRV (뇌전도와 심박변이를 이용한 감성 분석 알고리즘에 대한 연구)

  • Chon, Ki-Hwan;Oh, Ju-Young;Park, Sun-Hee;Jeong, Yeon-Man;Yang, Dong-Il
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.10
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    • pp.105-112
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    • 2010
  • In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one's emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.