• 제어로봇시스템학회논문지
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• 제17권8호
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• pp.747-752
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• 2011

HMMs (Hidden Markov Models) are widely used for biological signal, such as EEG (electroencephalogram) sequence, analysis because of their ability to incorporate sequential information in their structure. A recent trends of research are going after the biological interpretable HMMs, and we need to control the complexity of the HMM so that it has good generalization performance. So, an automatic means of optimizing the structure of HMMs would be highly desirable. In this paper, we described a procedure of classification of motor imagery EEG signals using HMM. The motor imagery related EEG signals recorded from subjects performing left, right hand and foots motor imagery. And the proposed a method that was focus on the validation of the HSA (Harmony Search Algorithm) based optimization for HMM. Harmony search algorithm is sufficiently adaptable to allow incorporation of other techniques. A HMM training strategy using HSA is proposed, and it is tested on finding optimized structure for the pattern recognition of EEG sequence. The proposed HSA-HMM can performs global searching without initial parameter setting, local optima, and solution divergence.

• 전자통신동향분석
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• 제38권6호
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• pp.62-74
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• 2023

In response to diverse external stimuli, sensory receptors generate spiking nerve signals. These generated signals are transmitted to the brain along the neural pathway to advance to the stage of recognition or perception, and then they reach the area of discrimination or judgment for remembering, assessing, and processing incoming information. We review research trends in neuromorphic sensory perception technology inspired by biological sensory perception functions. Among the various senses, we consider sensory nerve decoding technology based on sensory nerve pathways focusing on touch and smell, neuromorphic synapse elements that mimic biological neurons and synapses, and neuromorphic processors. Neuromorphic sensory devices, neuromorphic synapses, and artificial sensory memory devices that integrate storage components are being actively studied. However, various problems remain to be solved, such as learning methods to implement cognitive functions beyond simple detection. Considering applications such as virtual reality, medical welfare, neuroscience, and cranial nerve interfaces, neuromorphic sensory recognition technology is expected to be actively developed based on new technologies, including combinatorial neurocognitive cell technology.

• 한국멀티미디어학회논문지
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• 제18권5호
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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.

• BMB Reports
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• 제28권4호
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• pp.336-341
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• 1995

Using a mutant M13 phage derivative lacking a great part of the complementary strand synthesis origin, we identified six single-strand initiation (ssi) signals for DNA replication in pACYC184, pLG214, pGKV21, and pDPT270 plasmids, and named them $ssiA_{YC}$, $ssiA_{LG}$, $ssiB_{LG}$, $ssiA_{KV}$, $ssiA_{PT}$, and $ssiB_{PT}$, respectively. Two of them were from pDPT270, one from downstream the on of pACYC184, two from pLG214, one from upstream the plus origin of pGKV21. Introduction of these ssi signals into the deleted $ori_c$ site of a mutant filamentous M13 phage ($M13{\Delta}lac182$) resulted in the restoration of growth activity of this phage. These ssi signals were classified into a number of groups on the basis of sequence similarity. $ssiA_{YC}$ and $ssiA_{LG}$ show extensive sequence homology to the n'-site (primosome assembly sites) of ColE1, whereas $ssiB_{PT}$ is homologous to the n'-site of ${\Phi}X174$. $ssiA_{PT}$ belongs to G4-type ssi signals which require only dnaG primase and SSB protein for the priming of replication. In addition, possible biological roles of these ssi signals are discussed.

• 대한의용생체공학회:의공학회지
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• 제35권6호
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• pp.234-241
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• 2014

This study was designed to investigate the effects of stimulation intensity and inter-electrode distance on the parameters of the measured sensory nerve signal. 30 healthy subjects participated in this study. Sensory nerve signals were elicited by four different pulse amplitudes, i.e., 3, 6, 9, 12 mA, with the pulse width fixed at $500{\mu}s$. The sensory nerve signals elicited by the four different pulse amplitudes were measured by four different inter-electrode distances (20, 30, 40, and 50 mm). We extracted four parameters (pulse amplitude, pulse width, pulse area, and latency time from stimulation) from the sensory nerve signals. The measured pulse amplitude and pulse width were increased when the measuring inter-electrode distance was increased while the stimulating pulse amplitude was fixed. The measured pulse amplitude was saturated with the stimulating pulse amplitudes of over 6 mA while measuring inter-electrode distance. Under the same condition, measured pulse width was increased, and sensory nerve signal was initiated early. Sensory nerve signals, specially those of pulse amplitude, were distorted by a differential amplification method that commonly measures the human body signal. The experimental results indicate that the differential amplification method is required to be replaced when measuring nerve signals. Our observations suggested that the hyperpolarization of the action potential of the sensory nerve signal for preventing distortion could be used to clarify the correlation between the parameters of the sensory nerve signals and quantification of sensations.

• 감성과학
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• 제20권2호
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• pp.161-170
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• 2017

감정은 학습능력, 행동, 판단력 등 삶의 많은 부분에 영향을 끼치므로 인간의 본질을 이해하는 데 중요한 역할을 한다. 그러나 감정은 개인이 느끼는 강도가 다르며, 시각 영상 자극을 통해 감정을 유도하는 경우 감정이 지속적으로 유지되지 않는다. 이러한 문제점을 극복하기 위하여 총 4가지 감정자극(행복, 슬픔, 공포, 보통) 시 생체신호(뇌전도, 맥파, 피부전도도, 피부 온도)를 획득하고, 이로부터 특징을 추출하여 분류기의 입력으로 사용하였다. 감정 패턴을 확률적으로 해석하여 다른 공간으로 매핑시켜주는 역할을 하는 Restricted Boltzmann Machine (RBM)과 Multilayer Neural Network (MNN)의 은닉층 노드를 이용하여 비선형적인 성질의 감정을 구별하는 Deep Belief Network (DBN) 감정 패턴 분류기를 설계하였다. 그 결과, DBN의 정확도(약 94%)는 오류 역전파 알고리즘의 정확도(약 40%)보다 높은 정확도를 가지며 감정 패턴 분류기로서 우수성을 가짐을 확인하였다. 이는 향후 인지과학 및 HCI 분야 등에서 활용 가능할 것으로 사료된다.

• Molecules and Cells
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• 제41권10호
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• pp.923-932
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• 2018

Ethylene regulates numerous aspects of plant growth and development. Multiple external and internal factors coordinate ethylene production in plant tissues. Transcriptional and post-translational regulations of ACC synthases (ACSs), which are key enzymes mediating a rate-limiting step in ethylene biosynthesis have been well characterized. However, the regulation and physiological roles of ACC oxidases (ACOs) that catalyze the final step of ethylene biosynthesis are largely unknown in Arabidopsis. Here, we show that Arabidopsis ACO1 exhibits a tissue-specific expression pattern that is regulated by multiple signals, and plays roles in the lateral root development in Arabidopsis. Histochemical analysis of the ACO1 promoter indicated that ACO1 expression was largely modulated by light and plant hormones in a tissue-specific manner. We demonstrated that point mutations in two E-box motifs on the ACO1 promoter reduce the light-regulated expression patterns of ACO1. The aco1-1 mutant showed reduced ethylene production in root tips compared to wild-type. In addition, aco1-1 displayed altered lateral root formation. Our results suggest that Arabidopsis ACO1 integrates various signals into the ethylene biosynthesis that is required for ACO1's intrinsic roles in root physiology.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 춘계학술대회
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• pp.49-52
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• 1994

We have developed a biological signal measurement, archiving, and communication system (SiMACS). The front end of the system is the intelligent data processing unit (IDPU) which includes ECG, EEG, EMG, blood pressure, respiration, temperature measurement modules, module control and data acquisition unit, real-time display and signal processing unit. IDPUS are connected to central data base unit through LAN(Ethernet). Workstations which receive signals from central DB and provide various signal analysis tools are also connected to the network. The developed PC-based SiMACS is described.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.395-397
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• 1997

We have applied the neural network method for the neural networkmethod for the automatic scoring of the sleep stage. 17 features are extracted from the recorded EEG, EOG and EMG signals. These features are inputed to tile multilayer perceptron model. Neural network was trained with error-back propagation method. Results are compared with manual scoring of the experts, and show the possibility of application of automatic method in sleep stage scoring.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.430-433
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• 1997

We present the preliminary algorithms for automatic sleep scoring. According to the Rechtschaffen & Kales[3]'s critera, we developed six events detectors and eight parameters which contain the background information of signals, such as EEG, EMG, EOG. With the calculated parameters, we scored each epoch by IF-THEN rules, ANFIS for REM preiods, and finally Neural Network for unobvious epochs. The typical point of this algorithm is that the epoch which had good data sets were calculated in the first stage, and unobvious epochs were postponed until the final stage. After staging the good epochs, we classified unobvious epochs by the dominant stage of previous and posterior epochs.