• Korean Journal of Applied Biomechanics
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• v.33 no.1
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• pp.34-44
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• 2023

Objective: The purpose of this study was to examine the effects of increasing running speed on human stability by comparing the Lyapunov Exponent (LyE) and Coefficient of Variation (CV) methods, with the goal of identifying key variables and uncovering new insights. Method: Fourteen adult males (age: 24.7 ± 6.4 yrs, height: 176.9 ± 4.6 cm, weight: 74.7 ± 10.9 kg) participated in this study. Results: In the CV method, significant differences were observed in ankle (flexion-inversion/eversion; p < .05) and hip joint (internal-external rotation; p < .05) movements, while the center of mass (COM) variable in the coronal axis movements showed a significant difference at the p < .001 level. In the LyE method, statistical differences were observed at the p < .05 level in knee (flexion-extension), hip joint (internal-external rotation) movements, and COM across all three directions (sagittal, coronal, and transverse axis). Conclusion: Our results revealed that the stability of the human body is affected at faster running speeds. The movement of the COM and ankle joint were identified as the most critical factors influencing stability. This suggests that LyE, a nonlinear time series analysis, should be actively introduced to better understand human stabilization strategies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.103-108
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• 2016

In daily life, humans get stress very often. Stress is one of the important factors of healthy life and closely related to the quality of life. Too much stress is known to cause hormone imbalance of our body, and it is observed by the brain and bio signals. Based on this, the relationship between brain signal and stress is explored, and brain signal based stress index is proposed in our work. In this study, an EEG measurement device with 32 channels is adopted. However, only two channels (FP1, FP2) are used to this study considering the applicability of the proposed method in real enveironment, and to compare it with the commercial 2 channel EEG device. Frequency domain features are power of each frequency bands, subtraction, addition, or division by each frequency bands. Features in time domain are hurst exponent, correlation dimension, lyapunov exponent, etc. Total 6 subjects are participated in this experiment with English sentence reading task given. Among several candidate features, ${\frac{{\theta}\;power}{mid\;{\beta}\;power}}$ shows the best test performance (70.8%). For future work, we will confirm the results is consistent in low price EEG device.

• Knowledge Management Research
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• v.22 no.4
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• pp.119-133
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• 2021

As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.3
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• pp.55-62
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• 2000

This paper presents an analysis of the chaotic behavior in the discrete-time voltage mode chaotic generator fabricated using 0.8${\mu}{\textrm}{m}$ single poly CMOS technology. An approximated empirical equation is extracted from the measurement data of a nonlinear function block. Then the bifurcation diagram is simulated according to input variables and Lyapunov exponent λ which represent a dependence on an initial value is calculated. We show the interrelations among time waveforms, state transition, and power spectra for the state condition of chaotic circuit, such as equilibrium, periodic, and chaotic state. And results of experiments in the chaotic circuit with the $\pm$2.5V power supply and sampling clock frequency of 10KHz are shown and compared with the simulated results.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.45-53
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• 2000

This paper presents an analysis of the dynamical behavor in the chaotic neuron fabricated using 0.8${\mu}{\textrm}{m}$ single poly CMOS technology. An approximated empirical equation models for the sigmoid output function and chaos generative block of the chaotic neuron are extracted from the measurement data. Then the dynamical responses of the chaotic neuron such as biurcation diagram, frequency responses, Lyapunov exponent, and average firing rate are calculated with numerical analysis. In addition, we construct the chaotic neural networks which are composed of two chaotic neurons with four synapses and obtain bifurcation diagram according to synaptic weight variation. And results of experiments in the single chaotic neuron and chaotic neural networks by two neurons with the $\pm$2.5V power supply and sampling clock frequency of 10KHz are shown and compared with the simulated results.