• Title/Summary/Keyword: Physiological Signal

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The Vomeronasal Organ and Adjacent Glands Express Components of Signaling Cascades Found in Sensory Neurons in the Main Olfactory System

  • Lee, Sang Jin;Mammen, Alex;Kim, Esther J.;Kim, So Yeun;Park, Yun Ju;Park, Mira;Han, Hyung Soo;Bae, Yong-Chul;Ronnett, Gabriele V.;Moon, Cheil
    • Molecules and Cells
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    • v.26 no.5
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    • pp.503-513
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    • 2008
  • The vomeronasal organ (VNO) is a sensory organ that influences social and/or reproductive behavior and, in many cases, the survival of an organism. The VNO is believed to mediate responses to pheromones; however, many mechanisms of signal transduction in the VNO remain elusive. Here, we examined the expression of proteins involved in signal transduction that are found in the main olfactory system in the VNO. The localization of many signaling molecules in the VNO is quite different from those in the main olfactory system, suggesting differences in signal transduction mechanisms between these two chemosensory organs. Various signaling molecules are expressed in distinct areas of VNO sensory epithelium. Interestingly, we found the expressions of groups of these signaling molecules in glandular tissues adjacent to VNO, supporting the physiological significance of these glandular tissues. Our finding of high expression of signaling proteins in glandular tissues suggests that neurohumoral factors influence glandular tissues to modulate signaling cascades that in turn alter the responses of the VNO to hormonal status.

Estimation Method for Brain Activities are Influenced by Blood Pulsation Effect (Blood Pulsation의 효과가 뇌 활성화에 미치는 영향을 알아보는 방법)

  • Lee, W.H.;Ku, J.H.;Lee, H.R.;Han, K.W.;Park, J.S.;Kim, J.J.;Yoon, K.J.;Kim, I.Y.;Kim, S.I.
    • Journal of Biomedical Engineering Research
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    • v.28 no.3
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    • pp.338-343
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    • 2007
  • BOLD T2*-weighted MR images reflects cortical blood flow and oxygenation alterations. fMRI study relies on the detection of localized changes in BOLD signal intensity. Since fMRI measures the very small modulations in BOLD signal intensity that occur during changes in brain activity, it is also very sensitive to small signal intensity variations caused by physiologic noise during the scan. Due to the complexity of movement of various organs associated with heart beat, it is important to reduce cardiac related noise rather than other physiological noise which could be required with relatively simple method. Therefore, a number of methods have been developed for the estimation and reduction of cardiac noise in fMRI study. But, each method has limitation. In this study, we proposed a new estimation method for brain activities influenced by blood pulsation effect using regression analysis with blood pulsation signal and the correspond slice of fMRI. We could find out that the right anterior cingulate cortex and right olfactory cortex and left olfactory cortex were largely influenced by blood pulsation effect for new method. These observed areas are mostly on the structure of anterior cerebral artery in the brain. That is convinced with that our method would be valid and our new method is easier to apply in practice and reduce computational burden than the retrospective method.

Relationship Between Skin Impedance Signal, Reaction time, and Eye Blink Depending on Arousal Level (각성상태에 따른 피부임피던스 신호와 반응시간 및 눈 잡학임의 상관관계(E))

  • 고한우;김연호
    • Journal of Biomedical Engineering Research
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    • v.18 no.4
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    • pp.485-491
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    • 1997
  • This paper describes the relationship between skin impedance signal, behavioral signal, and subjective evaluation depending on arousal level. Nz and reaction time had similar trend with mKSS level, but eyeblink rate was different from these two parameters. eye-blink rate increased slowly from mKSS level 1 to 5, and had high increasing rate at mKSS 7. But it showed steep descent at mKSS level 9. Each subject showed different eye-blink rates, but changing rates of EBR was similar at eachm KSS level. Therefore it suggests that rising rate of EBR can be used arousal level criterion. From the result of reaction time test. human performance was decreased rapidly above the mKSS level 5, and false positive and false negative data was observed above the mKSS level 3. It is desirable to give a subject some stimuli such as sound or aroma to rise arousal level between mKSS level 3 and mKSS level 5.

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A Research for Removing ECG Noise and Transmitting 1-channel of 3-axis Accelerometer Signal in Wearable Sensor Node Based on WSN (무선센서네트워크 기반의 웨어러블 센서노드에서 3축 가속도 신호의 단채널 전송과 심전도 노이즈 제거에 대한 연구)

  • Lee, Seung-Chul;Chung, Wan-Young
    • Journal of Sensor Science and Technology
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    • v.20 no.2
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    • pp.137-144
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    • 2011
  • Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

Driver's Status Recognition Using Multiple Wearable Sensors (다중 웨어러블 센서를 활용한 운전자 상태 인식)

  • Shin, Euiseob;Kim, Myong-Guk;Lee, Changook;Kang, Hang-Bong
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.6
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    • pp.271-280
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    • 2017
  • In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.

The Design of Feature Selection Classifier based on Physiological Signal for Emotion Detection (감성판별을 위한 생체신호기반 특징선택 분류기 설계)

  • Lee, JeeEun;Yoo, Sun K.
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.11
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    • pp.206-216
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    • 2013
  • The emotion plays a critical role in human's daily life including learning, action, decision and communication. In this paper, emotion discrimination classifier is designed to reduce system complexity through reduced selection of dominant features from biosignals. The photoplethysmography(PPG), skin temperature, skin conductance, fontal and parietal electroencephalography(EEG) signals were measured during 4 types of movie watching associated with the induction of neutral, sad, fear joy emotions. The genetic algorithm with support vector machine(SVM) based fitness function was designed to determine dominant features among 24 parameters extracted from measured biosignals. It shows maximum classification accuracy of 96.4%, which is 17% higher than that of SVM alone. The minimum error features selected are the mean and NN50 of heart rate variability from PPG signal, the mean of PPG induced pulse transit time, the mean of skin resistance, and ${\delta}$ and ${\beta}$ frequency band powers of parietal EEG. The combination of parietal EEG, PPG, and skin resistance is recommendable in high accuracy instrumentation, while the combinational use of PPG and skin conductance(79% accuracy) is affordable in simplified instrumentation.

Design and Implementation of an Emotion Recognition System using Physiological Signal (생체신호를 이용한 감정인지시스템의 설계 및 구현)

  • O, Ji-Soo;Kang, Jeong-Jin;Lim, Myung-Jae;Lee, Ki-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.1
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    • pp.57-62
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    • 2010
  • Recently in the mobile market, the communication technology which bases on the sense of sight, sound, and touch has been developed. However, human beings uses all five - vision, auditory, palatory, olfactory, and tactile - senses to communicate. Therefore, the current paper presents a technology which enables individuals to be aware of other people's emotions through a machinery device. This is achieved by the machine perceiving the tone of the voice, body temperature, pulse, and other biometric signals to recognize the emotion the dispatching individual is experiencing. Once the emotion is recognized, a scent is emitted to the receiving individual. A system which coordinates the emission of scent according to emotional changes is proposed.

Measurement of electro-physiological changes in the brain exposed to eletromagnetic wave radiation (전자파에 노출된 생체두부의 전기생리적 변화의 측정에 관한 연구)

  • 이준하;신현진;이상학;유동수;이무영;김성규
    • Progress in Medical Physics
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    • v.5 no.2
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    • pp.35-43
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    • 1994
  • Electromagnetic wave may induce effect and damage on the bio-body, either by electric fields of magnetic fields. We measure electrophysiological changs in rabbit's brain exposed to 2.45GHz micro wave(power density 40mW/cm$^2$) which distance 30cm from the source. In order to process the bio-electrical signal (EEG), used pre-amplifier module with self-made and Digtal analyzer computer system. Spectal analysis of the EEG showed variable power in the frequency range(1~30Hz) through each exposure time(10min, 20min, 30min) before and after. In effectively measured by the bio-electrical signal processing and can found threshold of minmal permissible exposure and lethal exposure.

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The Evaluation of Optimized Inversion-Recovery Fat-Suppression Techniques for T2-Weighted Abdominal MR Imaging : Preliminary report (복부의 T2강조 영상에서 지방소거기법의최적의 평가)

  • Lee, Da-Hee;Goo, Eun-Hoe
    • Korean Journal of Digital Imaging in Medicine
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    • v.14 no.1
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    • pp.31-35
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    • 2012
  • To test the real image quality of a spectral attenuated inversion-recovery (SPAIR) fat-suppression (FS) techniquein clinical abdominal MRI by comparison to turbo spin echo inversion-recovery (TSEIR) fat-suppression (FS) technique. 3.0T MRI studies of the abdomen were performed in 30 patients with liver lesions (hemangiomas n: 15; HCC n: 15). T2W sequences were acquired using SPAIR TSEIR. Measurements included retroperitoneal and mesenteric fat signal-to-noise (SNR) to evaluate FS; liver lesion contrast-to-noise (CNR) to evaluate bulk water signal recovery effects; and bowel wall delineation to evaluate susceptibility and physiological motion effects. SPAIR-TSEIR images produce significantly improved FS and liver lesion CNR. The mean SNR of the retroperitoneal and mesenteric fat for SPAIR were 20.5, 10.2 and TSEIR were 43.2, 24.1 (P<0.05). SPAIR-TSEIR images produced higher CNR for both hemangiomas CNR 164.88 vs 126.83 (P<0.05) and metastasis CNR 75.27 vs 53.19 (P<0.05). Bowel wall visualization was significantly improved using in both SPAIR-TSEIR (P< 0.05). The real image quality of SPAIR was better than over conventional TSEIR FS on clinical abdominal MRI scans.

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Effect of estradiol-$17{\beta}$ on proliferation in primary cultured chicken hepatocytes (초대 배양한 닭 간세포 증식에 대한 estradiol-$17{\beta}$의 효과)

  • Baek, Gyul;Kang, Ju-Won
    • Korean Journal of Veterinary Service
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    • v.31 no.4
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    • pp.457-463
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    • 2008
  • The sex steroid hormone estradiol-$17{\beta}(E_2)$ mediate their biological effects on development, differentiation and maintenance of reproductive tract and other target tissue through gene regulation by nuclear steroid receptors. Although the importance of $E_2$ in many physiological process has been reported, but little is known about the effects of $E_2$ on primary cultured chicken hepatocyte. therefore, in the present study, we have examined the effect of $E_2$ on cell proliferation and it's related signal cascades. $E_2$ increase $[^3H]$-thymidine incorporation in time-(${\leq}8hr$) and dose-($10^{-10}M$)dependent manner and treatment of $E_2$ increased the phosphorylation of p44/43 MAPKs(p44/42 mitogen-activated protein kinase) and JNK(c-Jun N-terminal kinase) in a time dependent manner. In addition, PD98059(p44/42 blocker, $10^{-5}M$), SP600125(JNK blocker, $10^{-6}M$) blocked the estrogen-induced increase in $[^3H]$-thymidine incorporation. In conclusion, $E_2$ stimulates the proliferation of primary cultured chicken hepatocytes and this action is mediated by p44/42 MAPKs and JNK signal transduction pathway.