• The Korean Journal of Physiology
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• v.30 no.1
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• pp.85-96
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• 1996

Adenosine and its analogues are known to possess analgesic effects and to be involved in the opiate-induced antinociception as well. This study was designed to investigate the effects of three adenosine agonists, 5'- (N-cyclopropyl) -carboxamidoadenosine(CPCA), 5'-N-ethylcarboxamidoadeno-sine (NECA) and $N^6-cyclohexyladenosine$ (CHA) on the signal transmission in the spinal cord and also to elucidate mechanisms of their actions in the anesthetized cat. All the tested adenosine agonists(i.v,) exerted inhibitory effects on the responsiveness of the wide dynamic range (WDR) cells, the inhibitory action of CHA, an adenosine $A_1$ receptor agonist, $(80{\mu}g/Kg)$ being most weak. The intravenous CPCA, an adenosine $A_2$ receptor agonist, $(20{\mu}g\;/Kg)$ and NECA, nonspecific adenosine receptor agonist, $(20{\mu}g\;/Kg)$ inhibited the responses of WDR cells to pinch and C fiber stimulation more strongly than those to brush and A fiber stimulation. CPCA (i.v.) also suppressed the responses of WDR cells to thermal stimulus. And all the CPCA-induced inhibitions were caffeine-reversible. When CPCA was directly applied onto the spinal cord or intravenously administered into the spinal cat, on average, about three quarters of the CPCA-induced inhibitory effect was abolished. On the other hand, in the animal with spinal lesions in the ipsilateral dorsolateral area, the CPCA-induced inhibition was comparable to that observed in the spinal cats. In conclusion, this study shows that adenosine agonists strongly suppress the responses of WDR cells to pinch, C fiber stimulation and thermal stimuli mainly through the supraspinal adenosine $A_2-receptors$.

• Korea Journal of Hospital Management
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• v.22 no.4
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• pp.1-15
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• 2017

This study was designed to analyze the effect of servicescape and human service quality on patients' internal response and their behavioral intention in dental care organizations. Self-administered survey questionnaires with structured instruments were developed, and a total of 226 responses were used for statistical analyses using SPSS Windows version 18.0 program and AMOS 18.0 program. Major findings of the study are as follows. First, among other servicescape components, air condition environment was found to have a positive effect on patients' cognitive and physiological responses, while signals and symbols had a positive effect on cognitive and emotional responses. Second, the competence, among other factors of the human service quality, had positive influence on cognitive and emotional responses, while customer understanding affected positively on emotional response. Third, none of the servicescape components showed a direct effect on patients' behavioral intention, but their influence was mediated by internal responses. However, customer understanding, among other human service quality factors, had a direct effect on patients' behavioral intention. Fourth, emotional response, among other internal response factors, proved to have positive influence on behavioral intention. Results from this study suggest that dental care service providers can increase their competitiveness and customer satisfaction by understanding and improving the most important areas of servicescape and human service quality.

• 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.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.3
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• pp.150-156
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• 2016

Extract of Broussometia kazinoki Rhizodermatis has been traditionally used for geopoong, diuresis, hwalhyeol. In the present study, the apoptotic effect of methanol extract of Broussometia kazinoki (MBK) were investigated. Cell viability of A549 cells was measured by MTT assay. Apoptosis-related protein and MAPK protein levels were measured by Western blot. Chromatin condensation of A549 cells was stained with DAPI. MBK inhibited cell proliferation of A549 cell. Based on DAPI staining, MBK-treated cells manifested nuclear shrinkage, condensation and fragmentation. Treatment of A549 cells with MBK resulted in activation of the caspase-3, -8, -9 and cleavage of poly ADP-ribose polymerase (PARP). In the upstream, MBK increased the expressions Bax and Bak, decreased the expression of Bcl-2, and augmented the Bax/Bcl-2 ratio. MBK-induced apoptosis was accompanied by sustained phosphorylation of JNK, p38 MAPK and apoptosis signal-regulating kinase (ASK)-1. These results suggest that MBK induced apoptosis in A549 cells through Bcl-2 family protein-mediated mitochondria/caspase-3 dependent pathway. In addition, MBK increased the activation of ASK-1, which are critical upsteam signals for JNK/p38 MAPK activation in A549 cancer cells.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.293-297
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• 2009

This paper describes a real-time reliable measurement and analysis system for ubiquitous healthcare based on IEEE802.15.4 standard. In order to obtain and monitor physiological body signals continuously, wearable pulse oximeter is designed in wrist that could used to measure oxygen saturation of a patient unobtrusively. The measured data was transferred to a central PC or server by using wireless sensor nodes via a wireless sensor network for storage and analysis purposes. LabVIEW server program was designed to monitor and process the measured photoplethysmogram(PPG) to accelerated plethysmogram(APG) by appling second order derivatives in server PC. These experimental results demonstrate that APG can precisely describe the features of an individual's PPG and be used as estimation of vascular elasticity for blood circulation.

• Journal of Neurogastroenterology and Motility
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• v.24 no.4
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• pp.512-527
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• 2018

This review provides a comprehensive overview of brain imaging studies of the brain-gut interaction in functional gastrointestinal disorders (FGIDs). Functional neuroimaging studies during gut stimulation have shown enhanced brain responses in regions related to sensory processing of the homeostatic condition of the gut (homeostatic afferent) and responses to salience stimuli (salience network), as well as increased and decreased brain activity in the emotional response areas and reduced activation in areas associated with the top-down modulation of visceral afferent signals. Altered central regulation of the endocrine and autonomic nervous responses, the key mediators of the brain-gut axis, has been demonstrated. Studies using resting-state functional magnetic resonance imaging reported abnormal local and global connectivity in the areas related to pain processing and the default mode network (a physiological baseline of brain activity at rest associated with self-awareness and memory) in FGIDs. Structural imaging with brain morphometry and diffusion imaging demonstrated altered gray- and white-matter structures in areas that also showed changes in functional imaging studies, although this requires replication. Molecular imaging by magnetic resonance spectroscopy and positron emission tomography in FGIDs remains relatively sparse. Progress using analytical methods such as machine learning algorithms may shift neuroimaging studies from brain mapping to predicting clinical outcomes. Because several factors contribute to the pathophysiology of FGIDs and because its population is quite heterogeneous, a new model is needed in future studies to assess the importance of the factors and brain functions that are responsible for an optimal homeostatic state.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.465-468
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• 2014

In this paper, we describe a method capable of measuring biological signals including respiration, heart rate, blood pressure, and blood sugar, using UWB (Ultra Wide Band) pulses, while does not contact the human body. Physiological signal is a basic data for checking the health. Because life is longer and active area of human becomes very broad, the medical system and the physical human resources which are focused on existing hospital must be located close patient, In that way, they hope be to engage in healthy life by stepping a quick step and treatment. Thus, it must be fitted closely to the patient. It is necessary to monitor the health without inconvenience on an ongoing basis. How to utilize radio waves in this way have been studied for a long time. However, the characteristics of radio waves on the human body has not been accurately grasped and developed as such. Accordingly, it is a level that can not be applied clinically. So, it is not widely put to practical use. In this paper, We analyzed and described the impact and characteristics of UWB pulses to the human body is a problem existing.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.111-114
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• 2021

Phytochemicals in fruits, vegetables, cereals, and nuts, advertised as "antioxidants", combat undesirable effects of reactive oxygen species (ROS) in the body. These undesirable effects include cancer, cardiovascular diseases, and neurodegenerative disorders. Although ROS were initially considered to be primarily damaging agents, ROS have been discovered to play a role in signaling immune and other physiological responses in recent years. Several studies have demonstrated that ROS act as essential signaling molecules to promote metabolic health. Therefore, the overall advantage of the interference of ROS signals by antioxidants could be questionable. Future research is required to understand the implications of the application of phytochemicals in functional foods and supplements for health benefits on ROS levels in the body. This study describes the new roles of ROS and hormesis of various phytochemicals to provide a possible research guideline to food and nutrition scientists.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2304-2320
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• 2021

Intelligently detecting anomalies in health sensor data streams (e.g., Electrocardiogram, ECG) can improve the development of E-health industry. The physiological signals of patients are collected through sensors. Timely diagnosis and treatment save medical resources, promote physical health, and reduce complications. However, it is difficult to automatically classify the ECG data, as the features of ECGs are difficult to extract. And the volume of labeled ECG data is limited, which affects the classification performance. In this paper, we propose a Generative Adversarial Network (GAN)-based deep learning framework (called CAB) for heart arrhythmia classification. CAB focuses on improving the detection accuracy based on a small number of labeled samples. It is trained based on the class-imbalance ECG data. Augmenting ECG data by a GAN model eliminates the impact of data scarcity. After data augmentation, CAB classifies the ECG data by using a Bidirectional Long Short Term Memory Recurrent Neural Network (Bi-LSTM). Experiment results show a better performance of CAB compared with state-of-the-art methods. The overall classification accuracy of CAB is 99.71%. The F1-scores of classifying Normal beats (N), Supraventricular ectopic beats (S), Ventricular ectopic beats (V), Fusion beats (F) and Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively. Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.174-180
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• 2022

Emotion recognition is an essential component of complete interaction between human and machine. The issues related to emotion recognition are a result of the different types of emotions expressed in several forms such as visual, sound, and physiological signal. Recent advancements in the field show that combined modalities, such as visual, voice and electroencephalography signals, lead to better result compared to the use of single modalities separately. Previous studies have explored the use of multiple modalities for accurate predictions of emotion; however the number of studies regarding real-time implementation is limited because of the difficulty in simultaneously implementing multiple modalities of emotion recognition. In this study, we proposed an emotion recognition system for real-time emotion recognition implementation. Our model was built with a multithreading block that enables the implementation of each modality using separate threads for continuous synchronization. First, we separately achieved emotion recognition for each modality before enabling the use of the multithreaded system. To verify the correctness of the results, we compared the performance accuracy of unimodal and multimodal emotion recognitions in real-time. The experimental results showed real-time user emotion recognition of the proposed model. In addition, the effectiveness of the multimodalities for emotion recognition was observed. Our multimodal model was able to obtain an accuracy of 80.1% as compared to the unimodality, which obtained accuracies of 70.9, 54.3, and 63.1%.