• 생물정신의학
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• 제16권2호
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• pp.69-75
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• 2009

Objectives : The detrended fluctuation analysis is one of the nonlinear methods for the investigation of biological time series. It quantifies the fractal scaling properties and is known to be useful in the evaluation of long-range correlations in time series. The heart rate variability(HRV) of obstructive sleep apnea syndrome (OSAS) patients during nighttime was analyzed by detrended fluctuation analysis to assess its relationship with the severity of the symptoms. Methods : Fifty nine untreated male OSAS patients with moderate to severe symptoms(mean age=45.4${\pm}$11.7 years, apnea-hypopnea index, AHI${\geq}$15) underwent nocturnal polysomnography. Moderate(AHI=15-30, N=22) and severe(AHI>30, N=37) OSAS patients were compared for the indices derived from detrended fluctuation analysis and frequency domain analysis of HRV. Results : In the detrended fluctuation analysis, the alpha values were 0.75${\pm}$0.11 and 0.82${\pm}$0.07 for the severe and the moderate OSAS groups respectively. The difference was significant(p<.01). The alpha value had negative correlation with AHI(r=-.425, p=.001). Negative correlation coefficients were also found in the relationships between the alpha values and very low frequency(VLF)(r=-.425, p=.001), low frequency(LF)(r=-.633, p= <.001) and the LF/HF ratio(r=-.305, p=.019) respectively. LF/HF ratio(p=.005) was higher in the severe OSAS group compared to that of the moderate OSAS group. Conclusion : In this study, the detrended fluctuation analysis showed the significant difference between the two OSAS groups classified according to their severity of symptoms. The scaling exponent showed the negative correlation with AHI and indicies of frequency domain analysis. This result suggests that detrended fluctuation analysis can be helpful to estimate the severity of OSAS.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.751-760
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• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.

• 수면정신생리
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• 제15권1호
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• pp.5-11
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• 2008

Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA ; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA ; 3) electrophysiological properties of narcolepsy could be characterized by the DFA ; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.

• 전기학회논문지
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• 제64권2호
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• pp.304-309
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• 2015

Applicable range of Photoplethysmography (PPG) becomes wider as a non-invasive physiological measurement technique. However, PPG waveform is easy to be distorted by ambient light or vascular variation from temperature changes. Especially, irregular variation of PPG waveform caused by ambient temperature not only severely distorts the PPG, but also leads miss interpretation in clinical applications. Therefore, the investigation of between temperature and PPG waveform is quite important in using PPG. The purpose of this research is to quantify the PPG waveform characteristic and to investigate the waveform variation following the temperature change on measuring site. To quantify the fluctuation of PPG waveform, we use two techniques; detrended fluctuation analysis (DFA) and AC/DC analysis of PPG. We record PPG under temperature stress, which applied by medical use heat pack ($40^{\circ}C$) and ice pack ($0^{\circ}C$). Ten participants were applied to the experiment, and the result was evaluated to approve the temperature effect with statistical method, Wilcoxon signed rank test. The result shows that the AC component (p<0.05) and perfusion index DFS scale exponent (p<0.01) of PPG have the significance to temperature stress except for a DC component of PPG.

• 생물정신의학
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• 제19권1호
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• pp.65-69
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• 2012

Objectives : Much is still unknown about the neurophysiological mechanisms or dynamics of the sleep onset process. Detrended fluctuation analysis (DFA) is a new tool for the analysis of electroencephalography (EEG) that may give us additional information about electrophysiological changes. The purpose of this study is to analyze long-range correlations of electroencephalographic signals by DFA and their changes in the sleep onset process. Methods : Thirty channel EEG was recorded in 61 healthy subjects (male:female=34:27, age=$27.2{\pm}3.0$ years). The scaling exponents, alpha, were calculated by DFA and compared between four kinds of 30s sleep-wakefulness states such as wakefulness, transition period, early sleep, and late sleep (stage 1). These four states were selected by the distribution of alpha and theta waves in O1 and O2 electrodes. Results : The scaling exponents, alpha, were significantly different in the four states during sleep onset periods, and also varied with the thirty leads. The interaction between the sleep states and the leads was significant. The means (${\pm}$ standard deviation) of alphas for the states were 0.94 (${\pm}0.12$), 0.98 (${\pm}0.12$), 1.10 (${\pm}0.10$), 1.07 (${\pm}0.07$) in the wakefulness, transitional period, early sleep and late sleep state respectively. The mean alpha of anterior fifteen leads was greater than that of posterior fifteen leads, and the two regions showed the different pattern of changes of the alpha during the sleep onset periods. Conclusions : The characteristic findings in the sleep onset period were the increasing pattern of scaling exponent of DFA, and the pattern was slightly but significantly different between fronto-temporal and parieto-occipital regions. It suggests that the long-range correlations of EEG have a tendency of increasing from wakefulness to early sleep, but anterior and posterior brain regions have different dynamical process. DFA, one of the nonlinear analytical methods for time series, may be a useful tool for the investigation of the sleep onset period.

• 한국산학기술학회논문지
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• 제11권7호
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• pp.2491-2496
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• 2010

EEG 신호에 내포된 상관특성을 알 수 있는 스케일 분석 기법인 DFA를 이용하여 수술 중 마취심도를 분석하고자하였다. 마취과 학회에서 제공하는 신체 분류 등급 1(건강한 환자), 2(경한 전신 질환, 기능 제한 없음) 등급의 환자를 대상으로 하였다. 정신병력이나 신경계 이상이 있는 환자는 제외하였다. 수술 중 마취 환자의 평균 연령은 $48.9{\pm}10.9$ 세이고, 평균체중은 $57.1{\pm}8.2$ kg, 평균 신장은 $158{\pm}6.6$cm 였다. 수술을 위한 마취 약제로는 Sevoflurane를 사용하였고, 수술단계는 수술전, 마취유도, 마취유도 직후, 수술중, 마취제 중지, 수술 후의 6단계로 나누어 분석하였다. DFA의 ��${\alpha}1$, ${\alpha}2$, ${\alpha}3$ 중 ${\alpha}1$, ${\alpha}3$는 수술전단계, 마취 유도 단계, 마취 유도 단계 직후, 마취제 중지 단계, 수술후 단계를 구별 할 수 있는 파라미터들로 수술 중 마취 심도를 평가 할 수 있는 파라미터로 이용될 수 있음을 확인 하였다.

• 한국한의학연구원논문집
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• 제14권1호
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• pp.85-89
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• 2008

This study is to investigate cardiotonic effect of acupuncture on heart rate variability(HRV) analyzed by a nonlinear way(DFA, Detrended Fluctuation Analysis). It was designed as a randomized, single-blind, waiting list-controlled, cross-over study. We assessed heart rate and R-R intervals in Circadian electrocardiography with a Holter monitoring device for twelve hospitalized participants. The compatible analytical program, Zymed, was used for generating the signals of R-R intervals from 24 hour-ECG. In DFA analysis, we produced DFA alpha 1, alpha 2 parameters according to the process of Cygwin module of Linux server. We tested if there was any difference between HRV parameters using SPSS, a statistical package. There was no difference between acupuncture and no treatment group in DFA alpha 2 parameter {95% Confidence Interval (-)0.058 - 0.037, P = .565}. Two group all showed large intra-individual variations. Consequently, acupuncture treatment did not modulate the complexity of HRV in a DFA analysis. This study can be a rationale for acupuncture's properties on cardiovascular and autonomic systems.

• 천문학회보
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• 제41권1호
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• pp.81.2-81.2
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• 2016

Many signals in the nature have power-law behaviors, namely they are "scale-free". The method of detrended fluctuation analysis (DFA), as one of the popular methods (e.g., Rescaled range analysis and Spectral analysis) for determining scale-free nature of time series, has a very important advantage that the DFA can be applied to both stationary and non-stationary signals. The analysis of time series using the DFA has been broadly used in physiology, finance, hydrology, meteorology, geology, and so on. We performed the DFA of 16 Spaceweather HMI Active Region Patch (SHARP) parameters for 38 HMI Active Region Patches (HARPs) obtained by Solar Dynamics Observatory (SDO) from May 2010 to June 2014. The main results from this study are as follows. (1) The most of the time series data are non-stationary. (2) The DFA scaling exponents of "mean vertical current density" for 38 HARPs have a negative correlation coefficient (-0.41) with flare index. (3) The DFA scaling exponents of parameters such as "Sum of the absolute value of net currents per polarity", "Absolute value of the net current helicity", and "Mean photospheric excess magnetic energy density" for the most active HARPs having more than 10 major flares, have positive correlation coefficients (0.64, 0.59, and 0.53, respectively) with the ratio of "the number of CMEs associated with major flares" to "the number of major flares". Physical interpretations on our results will be discussed.

• 수면정신생리
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• 제14권1호
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• pp.42-48
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• 2007

목 적：뇌파의 비선형적 특성을 연구하는 방법으로 탈경향 변동분석이 사용되고 있다. 본 연구에서는 정상인 수면 뇌파에 탈경향변동분석을 적용하여 수면뇌파의 비선형적 특성, 채널 별 차이, 수면단계별 차이를 규명하고자 하였다. 방 법：정상인 12명($23.8{\pm}2.5$세, 남：여=7：5)를 대상으로 야간수면다원검사를 시행하였다. 수면다원검사를 통해 얻어진 뇌파를 채널 별, 수면단계별로 나누어 탈경향변동분석 시행 후 여기서 얻어진 축척지수(scaling exponent)를 선형혼합모형 분석을 통해 비교하였다. 결 과：정상인 수면다원검사에서 얻어진 뇌파의 축척지수는 1 내외의 값을 보여 장기-시간적연관성, 자기유사성을 보였다. C3 채널의 축적지수가 O1채널의 축적지수보다 높은 값을 보였다. 수면단계가 진행함에 따라 축적지수는 증가하였으며, 1단계 수면과 렘수면은 축적지수는 통계적 차이를 보이지 않았다. 결 론：정상인 수면 뇌파는 탈경향변동분석에서 무축척요동(scale-free fluctuation), 장기-시간적 관련성(long-range temporal correlation), 자기유사성(self-similarity) 및 스스로 짜여진 고비성(self-organized criticality) 등의 비선형적 특성을 보였다. 탈경향변동분석에서 얻어진 축적지수는 뇌파 채널 별, 수면단계별 차이를 보여 수면 뇌파를 연구하는 중요한 도구로 사용될 수 있다.

• 한국방사선학회논문지
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• 제7권1호
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• pp.25-30
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• 2013

본 논문은 1998년부터 2011년까지 강릉 지역의 지방 방사능 측정소에서 측정된 공간 감마선량률의 통계 적인 성질을 조사하였다. Autocorrelation Function Analysis(ACF), Rescaled Range Analysis(R/S Analysis), Detrended Fluctuation Analysis(DFA)의 방법들이 사용되었으며, 이 중 DFA는 non-stationary한 시계열의 장거리 상관성을 보여주는 좋은 방법으로 알려져 있다. 우리는 이 연구를 통해 다음의 사실을 알았다. 첫 번째, 공간 감마선량률은 두 가지 다른 경향을 갖는 크로스 오버가 나타난다. 이것은 연중 공간 감마선량률은 강한 장기 기억 특성이 나타나는데 비해 연간으로 넘어가면 상관성이 사라지는 것을 의미한다. 두 번째, 각 분석 방법들의 지수들이 있는데 이 지수들 사이의 관계식이 맞음을 확인 하였다.