• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5096-5110
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• 2015

The purpose of this study was to identify the effects of brain wave change through therapeutic recreation programs on depression, sleep disturbance and quality of life among elderly with dementia. The subjects of this quasi-experimental study consisted of two groups, one experimental group (N=14) and one control group (N=18), after excluding 8 participants from a total of 40 participants. The subjects of experimental group were randomly selected from the elderly (order than 65 years old) of senior care center in Daejoen and participated in 3-month therapeutic recreation program. On the other hand, the subjects of control group did not participated in any therapeutic recreation program. Each group's pre-post brain wave change, depression, sleep disturbance and quality of life were estimated. Through ANCOVA and Analysis of Structural Equation Modeling with SPSS window 17.0 and AMOS 7.0, this study found followings. Frist, the therapeutic recreation program group indicated significant improvement of brain waves, sleep disturbance and quality of Life. In addition, depression was significantly reduced in the therapeutic recreation program group. Second, significant causal relationships was found among brain waves, depression, sleep disturbance, and Quality of Life.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.513-514
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• 2016

Recently, many researches has performed on human brain wave actively. In order to analyze these brain waves using EEG(electroencephalography) sensors collect EEG data and EEG can be analyzed by using a frequency analysis of the EEG. In this paper, we performed EEG analysis that NeuroSky's mindwave mobile EEG sensor collects brain wave data and analyze the delta, theta, alpha, SMR, beta wave using a frequency analysis of collected EEG. Target of this study is analysis of what kind of relationship between concentration and brain wave in frequency domain. By these analysis, we can analyse not only the commonly known close relationship between concentration and beta wave but also analyse correlation of other frequency components. Furthermore our research result will be contribute to studies to be more advanced form of brain wave analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.57
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• pp.51-62
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• 2000

In this study, the psycho-physiological response of drivers was investigated in terms of EEG(Electroencephalogram), especially with the fractal dimensions computed by Chaotic algorithm. The Chaotic algorithm Is well Known to sensitively analyze the non-linear information such as brain waves. An automobile with a fully equipped data acquisition system was used to collect the data. Ten healthy subjects participated in the experiment. EEG data were collected while subjects were driving the car between Won-ju and Shin-gal J.C. on Young-Dong highway The results were presented in terms of 3-Dimensional attractor to confirm the chaotic nature of the EEG data. The correlation dimension and fractal dimension were calculated to evaluate the complexity of the brain activity as the driving duration changes. In particular, the fractal dimension indicated a difference between the driving condition and non-driving condition while other spectral variables showed inconsistent results. Based upon the fractal dimension, drivers processed the most information at the beginning of the highway driving and the amount of brain activity gradually decreased and stabilized. No particular decrease of brain activity was observed even after 100 km driving. Considering the sensitivity and consistency of the analysis by Chaotic algorithm, the fractal dimension can be a useful parameter to evaluate the psycho-physiological responses of human brain at various driving conditions.

• Horticultural Science & Technology
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• v.34 no.3
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• pp.472-487
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• 2016

This study aimed to determine the effects of floral fragrances on human brain waves and moods. A total of 44 subjects participated in this experiment. Group 1 consisted of 11 male and 14 female college students with a mean age of 24.5 years (${\pm}2.23$) and Group 2 consisted of 10 males and 9 females with a mean age of 54.3 years (${\pm}2.98$). Subjects were exposed to floral fragrances of Rosa hybrida, 'Hera' (hereafter referred to as "rose"), Cymbidium faberi (hereafter referred to as "orchid"), or odorless control flowers (hereafter referred to as "control"). Experiments took place in three rooms (rose, orchid, and control). Electroencephalographs (EEGs) were recorded during exposure to the odors and the data were processed using quantitative electroencephalographic (QEEG) techniques. The changing EEG patterns were analyzed by brain mapping and compressed spectral arrays, and the subjects' preferences (hedonic evaluations) were quantified with an A1 index. Increased activation of absolute alpha waves was verified on six of the eight EEG channels, with the right frontal and left occipital lobes exhibiting no changes and the left parietal region showing the greatest activation. According to the QEEG measurements in the electrode sites over the frontal, temporal, parietal, and occipital lobes, the strongest absolute alpha waves were induced in the parietal lobes, followed by the temporal lobes, with the other lobes showing no significant changes. On brain maps, the orchid fragrance induced greater absolute alpha and absolute mid-beta activities compared with the rose and control fragrances, and the rose fragrance induced high absolute mid-beta activation. To identify emotional responses to floral fragrances, the subjects were requested to fill in a questionnaire and the resulting odor-related emotional descriptors were analyzed using semantic differential and factor analysis. Principal component analysis identified "elegant" as the first principal component describing the floral fragrance, followed by "refreshing" and "aromatic." The subjects gave orchid higher scores for "elegant" and "refreshing," while finding rose more "aromatic." Differences in hedonic evaluation revealed by the A1 index appeared in the 65-115 sec range of scent exposure time. The subjects with ages of around 50 years showed olfactory preferences throughout the entire experimental time of 160 sec, most markedly in the later time segment (115-165 sec), showing an increasing preference with increasing exposure time. We conclude that rose fragrance can improve concentration by creating an aromatic environment conducive to a concentrated and calm state of mind, and orchid fragrance can make people feel pampered and relaxed by creating an elegant and refreshing environment.

• Journal of IKEEE
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• v.24 no.2
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• pp.654-660
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• 2020

Through the output of brain waves during muscle operation, this paper checks whether it is possible to find characteristic vectors of brain waves that are capable of dividing left and right movements by extracting brain waves in specific areas of muscle signal output that include the motion of the left and right muscles or the will of the user within EEG signals, where uncertainties exist considerably. A typical surface EMG and noninvasive brain wave extraction method does not exist to distinguish whether the signal is a motion through the degree of ionization by internal neurotransmitter and the magnitude of electrical conductivity. In the case of joint and motor control through normal robot control systems or electrical signals, signals that can be controlled by the transmission and feedback control of specific signals can be identified. However, the human body lacks evidence to find the exact protocols between the brain and the muscles. Therefore, in this paper, efficiency is verified by utilizing the results of application of CSP (Common Spatial Pattern) filter to verify that the left-hand and right-hand signals can be extracted through brainwave analysis when the subject's behavior is performed. In addition, we propose ways to obtain data through experimental design for verification, to verify the change in results with or without filter application, and to increase the accuracy of the classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.482-492
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• 2019

This study began with the assumption that the phonetics-centered interpretation of 100 Chinese characters would enhance thinking ability and comprehension. For this purpose, two experimental groups and a comparative group were recruited from the graduate students from June 3, 2017 to February 22, 2018. The experimental group participated in the phonetics-centered Chinese character lecture for 4 hours per week for 6 weeks for a total of 24 hours. QEEG were measured before and after the phonetics-centered Chinese character lecture. A total of 18 subjects ( nine subjects in the experimental group and nine comparative subjects) were included in the study, and the difference between before and after the QEEG of the experimental and comparative groups was analyzed, respectively. The conclusions drawn from this study are as follows. First, the Chinese character lecture changed brain waves. Second, the LORETA analysis before and after the lecture in the experimental group significantly decreased the delta wave in the brain region (Broadmann 40) associated with the meaning of language and phonology. This study result is meaningful because it shows the significant changes of EEG via the lecture.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.1916-1922
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• 2014

This study focuses on observing the brain function characteristics of maladaptive soldiers, through EEG analysis. The number of subjects was 1,119 including 59 maladaptive soldiers, 60 normal soldiers and 1,000 civil youths. The EEG measurements were performed from Sep. 2013 to Jan. 2014. As a result of the study, first, the soldier group's BRQ, ATQ, EQ, ASQ and BQ values were significantly higher than civil youth's, on the contrary to SRQ, ACQ, CQ which were higher in civil youth group. Second, compared to normal soldiers, the values of EQ and BQ were meaningfully low in maladaptive soldiers group, as well as the average values of each 8 quotient. In conclusion, military service can be assumed to have a positive effect on brain function of all soldiers due to regular life cycle, usual physical activities and balanced nutrition, but less effect on maladaptive soldiers who are exempted from those strict life.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.193-195
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• 2003

The analysis of EEG data is an important task in the domain of Brain Computer Interface (BCI). In general, this task is extremely difficult because EEG data is very noisy and contains many artifacts and consists of mixtures of several brain waves. The P300 component of the evoked potential is a relatively evident signal which has a large positive wave that occurs around 300 msec after a task-relevant stimulus. Thus automatic detection of P300 is useful in BCI. To this end, in this paper we employ a method of reference-based independent component analysis (ICA) which overcomes the ordering ambiguity in the conventional ICA. We show here. that ICA incorporating with prior knowledge is useful in the task of automatic P300 detection.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.25-31
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• 2023

The brain-machine interface(BMI) is a next-generation interface that controls the device by decoding brain waves(also called Electroencephalogram, EEG), EEG is a electrical signal of nerve cell generated when the BMI user thinks of a command. The brain-machine interface can be applied to various smart devices, but complex computational process is required to decode the brain wave signal. Therefore, it is difficult to implement a brain-machine interface in an embedded system implemented in the form of an edge device. In this study, we proposed a new type of brain-machine interface system using IoT technology that only measures EEG at the edge device and stores and analyzes EEG data in the cloud computing. This system successfully performed quantitative EEG analysis for the brain-machine interface, and the whole data transmission time also showed a capable level of real-time processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3833-3838
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• 2010

Brainwave can be the most effective means of detecting the state of the brain that changes moment by moment. Since brain has closed relations with hormones which are a foundation of metabolism, it needs to examine closely the mutual relationship between brainwave and hormone. We examined the possibility to find out such information about metabolism by comparing brainwave with cortisol hormone. The major variables are anti-stress quotient of brainwave and cortisol density which give stress information of the working women, to measure from March 3 to May 28, 2007. To find out the relationship between them, we performed such statistical analysis about the before and after of brainwave training as t-test, correlational analysis and regression analysis. We obtained following results: First, considerable changes of variables is shown by brain-wave training. Second, there exist a correlation between variables. Third, according to regression analysis, influence between variables is verified. Thus, we found that stress information of hormone analytical level can be obtined only through brainwave analysis.