Jae-Keun Jang

A Study on the Effects of Chinese Qigong and Kundalini Yoga Meditations on the Heart Rate Variability of Skilled Students

Abstract: In this paper, we have investigated effects of two specific meditations (Chinese qigong meditation and Kun-dalini yoga meditation) on the heart rate variability (HRV), which is a well-known quantitative measure of autonomicbalance, of skilled students. To analyze the effects, the MIT/BIH physionet database was utilized. The databaseincludes RR intervals of eight skilled Chinese qigong meditators (5 women and 3 men; age range 26-35) and fourskilled Kundalini yoga meditators (2 women and 2 men; age range 20-52). RR intervals of each subject were measuredbefore and during the meditations. For HRV analysis, we have used typical four HRV parameters - the low frequencyto high frequency power ratio (LF/HF ratio), SD2/SD1 ratio, sample entropy, and fractal dimension. The LF/HF ratiowas calculated by the autoregressive spectrum and the SD2/SD1 ratio was derived from the Poincare plot. The sam-ple entropy was computed from the phase space plot and the fractal dimension was estimated by the Higuchi’s algo-rithm. In the experiments, the Wilcoxon signed rank test was employed because we used small datasets andcompared HRV parameters before and during the meditations. As a result, we have found increment of the LF/HFand SD2/SD1 ratios in both meditations; whereas the sample entropy is decreased during the meditations. In addition,the fractal dimension is increased during the Chinese qigong meditation; whereas it is decreased during the Kundaliniyoga meditation. The results show that the sympathetic nervous system is generally more activated in skilled Chi-nese qigong and Kundalini yoga meditators, but the activation of the parasympathetic nervous tone is suppressed.Key words: Heart rate variability, Chinese qigong meditation, Yoga meditation, Autonomic nervous system.

Mental health promotion system

Mental activity promotion system is presented that analyzes, quantifies, trains and prescribes based on analysis of logical, memorizing, concentrative, decisive, in conditions where time and space is involved, possibility of dementia, and on evaluation of lifestyle of subjects. Special consideration has been made to make the system motivational, persuasive, attractive and fun to use. The system has been successfully deployed in Bitgeoul Senior health town, Gwangju, South Korea.

The Effect of Age and Dual Task to Human Postural Control

The purpose of this study is to investigate the effect of aging and dual tasking to the postural control during quiet standing. It was hypothesized that the center of pressure (COP) dynamics would be differently affected by aging and characteristics of the task. Total 60 adults (35 young adults and 25 older adults) participated in this study. They conducted two different standing tasks (dual vs. Non- dual) twice in a random order. Variability, complexity, coupling and symmetric index from the left, right and overall COPs were mea- sured by various parameters in nonlinear, linear and frequency analyses methods. Results demonstrated that older adults had worse performance in postural control with decreased complexity in overall sway movement, and increased coupling between left and right limb COP movement, even though there was no significant difference in symmetric index. These tendencies are generally clearer in nonlinear measures at the dual task condition. Results implied that older adults had compensatory strategy in dual tasking which results in simple and combined postural movement patterns.

A morphological approach to pulse feature extraction from the digital volume pulse

The digital volume pulse (DVP) is a physiological signal obtained from the photoplethysmography. Since the photoplethysmography measures volumetric changes of blood occurred by heart contraction and properties of blood vessels, DVP contains several feature parameters that reflect cardiovascular events, such as arterial stiffness. In order to extract these parameters, a number of algorithms have been proposed and applied in various clinical settings. However, these algorithms mainly focus on the feature extraction based on the mathematical representation of the DVP. This approach may show high performance in regular pulse waveform, but there is a limit to apply these algorithms to the DVP that includes various pulse shapes. In order to cope with this problem, we have proposed a morphological algorithm based on the knowledge of human recognition way. From the result of the performance evaluation, we have achieved the low false positive rate of 7.41% and the low false negative rate of 1.91%. With such low error rate and increased applicability to various pulse waveforms, the proposed algorithm can be utilized as an effective solution for the DVP-based cardiovascular function assessment.