Montri Phothisonothai

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The objective of this study is to analyze the spontaneous electroencephalographic (EEG) data corresponding to body parts movement imagery tasks in terms of fractal properties. We proposed the six algorithms of fractal dimension (FD) estimators; box-counting algorithm, Higuchi algorithm, variance fractal algorithm, detrended fluctuation analysis, power(More)
In this paper, we propose a method to classify electroencephalogram (EEG) signal recorded from left- and right-hand movement imaginations. Three subjects (two males and one female) are volunteered to participate in the experiment. We use a technique of complexity measure based on fractal analysis to reveal feature patterns in the EEG signal. Effective(More)
The objective of this study is to classify spontaneous electroencephalogram (EEG) signal on the basis of fractal concepts. Four motor imagery tasks (left hand movement, right hand movement, feet movement, and tongue movement) were investigated for each EEG recording session. Ten subjects volunteered to participate in this study. As we known, fractal(More)
— The objective of this paper is to characterize the spontaneous electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine or a brain-computer interface (BCI). The processing technique used in this paper was the fractal analysis(More)
User authentication system to identify individual by using electroencephalograph (EEG) feature based on steady-state visual evoked potential (SSVEP) has been proposed. Recently, SSVEP has been used as a stimulator due to it plays an important role in the response to various visual stimuli, i.e., flickering rate (F), intensity (I), and duty cycle (D).(More)
This paper presents an automatic method to remove physiological artifacts from magnetoencephalogram (MEG) data based on independent component analysis (ICA). The proposed features including kurtosis (K), probability density (PD), central moment of frequency (CMoF), spectral entropy (SpecEn), and fractal dimension (FD) were used to identify the artifactual(More)
This paper proposes a classification method to determine maturity levels of durian by using fractal analysis. We used the automatic knocking machine to knock the durian in which the knocked-sound was analyzed in terms of fractal concepts, and the fractal dimension (FD) values to be presented as a feature. The fractal algorithm, namely, Higuchi's method was(More)
The extraction method based on time-frequency and fractal features was proposed to analyze intonations from Japanese speech signal. Two parameters were presented to reveal different feature patterns: Peak spectrum (F max) and Fractal dimension (FD) trajectories. The F max and FD were computed by using short-time Fourier transform (STFT) and Higuchi's(More)