• Korean Journal of Adult Nursing
• /
• v.25 no.6
• /
• pp.644-654
• /
• 2013

Purpose: The purpose of this study was to examine the effects of aroma foot reflexology massage on mood states specifically depression and brain waves of elderly women with osteoarthritis. Methods: The study was a nonequivalent control group non-synchronized design. The participants were 62 elderly women with osteoarthritis. The instruments were the Korean-Profile of Mood States-Brief for mood states and 8-channel EEG (Electroencephalogram) system for brain waves. Data were collected from March to May, 2012. Twenty-six participants were assigned to the treatment group and twenty-six to the comparison group. The data were analyzed using SPSS/WIN 17.0 version program, and included descriptive statistics, t-test, and ANCOVA. The intervention was conducted three times a week for two weeks. Results: There were significantly improvement in reported depression. s. Brain waves (EEG) increased significantly in F3, T3 of ${\alpha}$ wave and in F4, T3, and P4 of ${\beta}$ wave between the two groups. Conclusion: Aroma foot reflexology massage can be utilized as an effective intervention to decrease depression of mood states, increase of ${\alpha}$, and ${\beta}$ brain wave on woman elderly with osteoarthritis.

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

• Korean Journal of Child Studies
• /
• v.36 no.6
• /
• pp.85-100
• /
• 2015

This study divided elementary school 6th graders of into a higher academic achievement group (n=19) and a lower academic achievement group (n=19) in order to examine the tendency of left and right hemisphere preferences, characteristics and relationships of learning ability factors by means of EEG. For this purpose, brain waves in performing higher cognitive tasks for 5 min. were measured with a two-channel (Fp1, Fp2) EEG measurement system and hemisphere preference was measured by means of a questionnaire. Our results were as follows. First, hemisphere preference indicated that the higher group showed a left hemisphere tendency and the lower group indicated a right hemisphere tendency. Second, the first learning ability test found that the higher group performed its task rapidly with higher levels of concentration and cognitive strength and lower loading and the lower group conducted its task more slowly with lower levels of concentration and cognitive strength and higher loading. The second test showed that the higher group performed its task rapidly with lower levels of concentration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.951-953
• /
• 2015

Learning for thinking says the behavior of the organism changes as a result of practice or experience. It is very difficult to identify focusing ability objectively when students study. But, brain of the body is not so. EEG signal means continuously electric records of brain potential variation between two points on the scalp when brain activities take place. In types of EEG, there are delta(0~4Hz), theta(4~8Hz), alpha(8~13Hz), beta(13~30Hz) and gamma waves(30~50Hz). SMR waves and Mid-beta waves appear when focused for studying. Part for the most influence on concentrating reported that Mid-beta waves. In relation to brain activities, EEG has been actively researched for evaluating brain focus index system during learning and study. So, By using Biopac system for this study, measured brain wave was converted into FFT for extracting Mid-beta domain signals that are related to learning after giving focus invoked subjects to a small number of people. When concentrating, we measured the change in the power of the Mid-beta frequency domain and presented a correlation. Based on these results, we analyzed whether students are concentrated objectively on learning or not. and hope to offer more efficient learning method.

• The Journal of Korean Physical Therapy
• /
• v.35 no.1
• /
• pp.19-23
• /
• 2023

Purpose: The purpose of this study is to analyze the brain waves and develop various exercise programs to improve the physical and mental aspects of stroke patients when neurological physical therapy and sitting table tennis exercise are applied to stroke patients. Methods: In this study, an experiment was conducted on 15 patients diagnosed with stroke, and training was performed after changing the ping-pong table to a sitting position to apply ping-pong exercise to stroke patients. After training was conducted for 40 minutes twice a week for 4 weeks, brain waves were measured before and after. EEG was measured using Laxtha's DSI-24 equipment as a measurement tool, and data values were extracted through the Telescan program. Results: Most of the relative beta waves showed a significant difference before and after the intervention. As for the characteristics of beta waves, this result can be seen as being highly activated during exercise or other activities. Conclusion: Ping-pong exercise in a sitting position is a good intervention method for stroke patients, and it can help to use it as basic data in clinical practice by showing brain activity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.924-926
• /
• 2015

In this paper, we use the interface, which many countries concentrates research of Brain - Computer Interface with the device and MyndPlay based on the IoT intelligent Arduino. Finally we will make the Brain - Computer Connection environment, the purpose of Brain - Computer Interface. Recognizes the EEG of a person who wearing the equipment, analyze, classify, and we did a research to design an intelligent thing to suit user's condition. In addition, we use the XBee, and Bluetooth to communicate to other devices, such as smart phone. In conclusion, this paper check users current status via brain waves, and it allows to control the power and other objects by using the EEG(Electroencephalography).

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.237-242
• /
• 2020

Construction noise is among the most critical stressors that adversely affect the quality of life of the people residing near construction sites. Many countries strictly regulate construction noise based on sound pressure levels, as well as timeslots and type of construction equipment. However, individuals react differently to noise, and their tolerance to noise levels varies, which should be considered when regulating construction noise. Although studies have attempted to analyze individuals' stress responses to construction noise, the lack of quantitative methods to measure stress has limited our understanding of individuals' stress responses to noise. Therefore, the authors proposed a quantitative stress measurement framework with a wearable electroencephalogram (EEG) sensor to decipher human brain wave patterns caused by diverse construction stressors (e.g., worksite hazards). This present study extends this framework to investigate the feasibility of using the wearable EEG sensor to measure individuals' emotional stress responses to construction noise in a laboratory setting. EEG data were collected from three subjects exposed to different construction noises (e.g., tonal vs. impulsive noises, different sound pressure levels) recorded at real construction sites. Simultaneously, the subjects' perceived stress levels against these noises were measured. The results indicate that the wearable EEG sensor can help understand diverse individuals' stress responses to nearby construction noises. This research provides a more quantitative means for measuring the impact of the noise generated at a construction site on neighboring communities, which can help frame more reasonable construction noise regulations that consider various types of residents in urban areas.

• Journal of Korea Game Society
• /
• v.21 no.1
• /
• pp.91-98
• /
• 2021

In this paper, we propose the system that simultaneously controls objects in virtual reality and objects in real environments using brain waves. We propose a system that measures brain waves to grasp the user's concentration and quantifies them to raise or lower virtual and real objects. We implemented a web-based virtual reality system and an embedded system based on a raspberry pi for test of design. It was confirmed that the control of virtual and real objects is possible using BCI. The result was that it was possible to develop various contents using this.

• PNF and Movement
• /
• v.22 no.1
• /
• pp.139-149
• /
• 2024

Purpose: This study aimed to investigate the effects of gradually increasing treadmill inclination on the electroencephalogram (EEG) of stroke patients during gait training. Methods: Three stroke patients who were diagnosed with stroke within six months and capable of walking on a treadmill were selected as subjects. EEG electrodes were attached at Fp1, Fp2, F3, F4, C3, C4, P3, and P4 positions of the cerebral hemispheres using the International 10-20 system. The intervention involved walking for 2 minutes each at 0 degrees, 15 degrees, and 30 degrees inclination on the treadmill while focusing on a target point located in front during the treadmill gait training. The EEG (Smartingmobi, Serbia) generated when the treadmill gradient gradually increased was measured. In addition, relative alpha and relative beta waves were visualized through the Brain mapping program in the TeleScan program to assess the changes in each brain region for the activity of the EEG. Results: The relative alpha wave value decreased as treadmill inclination increased, while the relative beta wave value increased. Conclusion: Gradually increasing the inclination during treadmill gait training appears to be a crucial parameter for increasing the brain activity levels of stroke patients.

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