• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.295-295
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• 2006

• Journal of Oriental Neuropsychiatry
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• v.26 no.2
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• pp.89-102
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• 2015

Objectives: To examine the medical effectiveness of meditation programs ($\alpha$ version) by psychological types. Methods: MBTI, which was created by Katharine Cook Briggs and Isabel Briggs Myers, was used as the Psychological Type test and to investigate psychological temperament and functions and psychological preferences. Heart rate variability was used to test the effectiveness of meditation by investigating time domains (mean HR, SDNN, PSI) and frequence domain parameters (TP, LF, HF, LF or HF norm, Ln (TP or VLF or LF or HF). Results: 1. The autonomic nervous system became active, and both time domains and frequency domains showed positive responses to meditation in heart rate variability tests, without distinction of Psychological Types. 2. In Psychological Types using sensing over intuition for perception, there were positive responses as well as an increase of the parasympathetic nervous system's activeness to meditation for heart rate variability tests, depending on psychological temperaments and psychological functions. 3. In heart rate variability tests by preferences, there was no difference. Extroversion and Introversion types, Sensing over Intuition Types, Thinking over Feeling Types, Judging over Perception Types had an increase of activeness of the parasympathetic nervous system. Therefore, meditation has a positive physical and psychological relaxing effect. Conclusions: A complex meditation program has a positive effect on overall meditation. Especially in the MBTI test, sensing was superior to intuition when people recognized objects. The Sensing, Thinking and Judging type was more advantageous than Intuition, Feeling and Perception, respectively. In the future, a well-designed control study is needed, to develop a suitable meditation for each personality type.

• Proceedings of the KSRS Conference
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• v.2
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• pp.868-871
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• 2006

Mortality of domestic people from cardiovascular disease ranked second, which followed that of from cancer last year. Therefore, it is very important and urgent to enhance the reliability of medical examination and treatment for cardiovascular disease. Heart Rate Variability (HRV) is the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate and conditions of a human heart. In this paper, our aim is to extract a quantitative measure for HRV to enhance the reliability of medical examination for cardiovascular disease, and then develop a prediction method for extracting multi-parametric features by analyzing HRV from ECG. In this study, we propose a hybrid Bayesian classifier called FP-based Bayesian. The proposed classifier use frequent patterns for building Bayesian model. Since the volume of patterns produced can be large, we offer a rule cohesion measure that allows a strong push of pruning patterns in the pattern-generating process. We conduct an experiment for the FP-based Bayesian classifier, which utilizes multiple rules and pruning, and biased confidence (or cohesion measure) and dataset consisting of 670 participants distributed into two groups, namely normal and patients with coronary artery disease.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.113-120
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• 2010

This research is to evaluate the arousal level by using cardiovascular response. PPG was used in this study as one of the method of measuring it rather than ECG (Electrocardiography) for the purpose of solving ergonomic problem of sensing. The participants were in the age group of 20 (mean=24, standard deviation=1.25): five men and five women. Each experiment composed with four identical sets. First, a black screen was displayed for 30 second rest. Then, the prepared 6 pair images were randomly presented for 10 second stimulation and for 30 second non-stimulation. PPG was measured on the earlobes of experimenters at 200Hz sampling frequency. PPG amplitude, PPI(Pulse to Pulse Interval), and PRV(Pulse Rate Variability) were analyzed according to arousal level. T-test was performed to compare between the PPG variables of rest and relaxation, rest and arousal, and relaxation and arousal. Relative to the rest state, PPG amplitude decreased in relaxed state and increased in aroused state. Relative to the rest state, PPI decreased in both emotional states. However, more significant decline was observed in aroused state. PRV's LF and HF were used in the form of LF/HF to compare between the relaxed and the aroused state. Therefore, PPG signal showed significant differences between relaxed and aroused state. In conclusion, evaluation of human arousal level used in the PPG analysis demonstrated that PPG has better usability and comforter measurement than ECG and is clearly an alternative method of measuring arousal level.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.923-930
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• 2004

Wireless sensor networks is a core technology of ubiquitous computing which enables the network to aware the different kind of context by integrating exiting wired/wireless infranet with various sensor devices and connecting collected environmental data with applications. However it needs an energy-efficient approach in network layer to maintain the dynamic ad hoc network and to maximize the network lifetime by using energy constrained node. Cluster-based data aggregation and routing are energy-efficient solution judging from architecture of sensor networks and characteristics of data. In this paper. we propose a new distributed clustering algorithm in using distance from the sink. This algorithm shows that it can balance energy dissipation among nodes while minimizing the overhead. We verify that our clustering is more en-ergy-efficient and thus prolongs the network lifetime in comparing our proposed clustering to existing probabilistic clustering for sensor network via simulation.