Alpha and Beta brainwave characteristics to binaural beat treatment

Puzi, N. S. M.; Jailani, Rozita; Norhazman, Haryanti; Zaini, Norliza

doi:10.1109/cspa.2013.6530069

Cited by 22 publications

(19 citation statements)

References 14 publications

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“…Eventually, the results of the experiment are analyze and represent the similarly result from previous research for the subjects with have over-normal stress level who listening to the binaural beat which benefit especially Alpha band [20,21]. However, there are some different results from previous research for the subjects who listening to the relaxing music that shows the duration of exposure to the relaxing music should longer than 180 seconds for more clearly analysis [16].…”

Section: Discussionmentioning

confidence: 84%

“…Moreover, the binaural beat was selected to be the one of observed sound and can be reference the trend of result to another research that conclude the result of EEG frequency band especially Alpha band is ostensibly increased [20][21]. Equally important, the instrumental relaxing music or also known as new age music is a well-known music genre and widely used for unwind the audience's stress which is the similar goal of binaural beat [16].…”

Section: B Auditory Stimulusmentioning

confidence: 99%

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Effect of auditory stimulus in EEG signal using a Brain-Computer Interface

Naraballobh

Thanapatay

Chinrungrueng

et al. 2015

2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technolo

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The neuroscience research which related to the study of sounds that affected to the person and focused on create the system that observe the effects of binaural beat and instrumental relaxing music by analyzing the recorded Electroencephalogram (EEG) signal of the participants. In addition, the Brain-Computer Interface (BCI) is widely used for recording electrical brain wave signal readings and distinguishes the complexity of the EEG brain spectrum between the different EEG frequencies band including Delta, Theta, Alpha, Beta and Gamma. Moreover, there are 40 subjects was participated in this research. The statistic-based method Hypothesis Testing and Paired T-test were selected as a decision maker to analyze the EEG recorded from the participants using the Brain-Computer Interface to find the significant difference of each stimulus for every groups that separate by the stress level of participants which measured by using a Depression Anxiety and Stress Scales (DASS) questionnaire.

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Section: Discussionmentioning

confidence: 84%

Section: B Auditory Stimulusmentioning

confidence: 99%

Effect of auditory stimulus in EEG signal using a Brain-Computer Interface

Naraballobh

Thanapatay

Chinrungrueng

et al. 2015

2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technolo

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show abstract

“…Moreover, the experimental is represents differences from previous researches which especially focus only on Theta and Alpha band and analyzed by using only the percentage of subjects who gain or drop the EEG value of the particularly interested frequency band. Compare to another research, the difference of Low-Alpha of relaxing music for aged 51-70 and the difference of Theta of binaural beat for aged 31-50 are represent the one of interested factors, range of age is affected to the result of EEG value when providing the binaural beat and the relaxing music [16,20,21].…”

Section: Discussionmentioning

confidence: 90%

“…The binaural beat was selected to be in this paper because it can reference with the trend of result of the other research [20][21]. Then, the collection of the classical instrumental relaxing music or also known as new age music is randomly picked for consideration.…”

Section: B Auditory Stimulusmentioning

confidence: 99%

EEG-based analysis of auditory stimulus in a brain-computer interface

Naraballobh

Thanapatay

Chinrungrueng

et al. 2015

2015 6th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES)

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This research is related to Neuroscience research fields that study sounds which affect the state of mind of a person. The main focus of this research is to create a system that observes the effects of the auditory stimulus including binaural beats and relaxing music by analyzing the Electroencephalogram (EEG) readings of the participants. EEG is mostly used for recording electrical brain wave signal readings. In addition, the Brain-Computer Interface (BCI) is used to decipher the EEG brain spectrum readings and distinguish between the different EEG bands including Delta, Theta, Alpha, Beta and Gamma. There are 40 participants (20 males, 20 females) around the age group 31 -70 yrs. in this research. The EEG recorded from the participants using the Brain-Computer Interface (BCI) is analyzed using a statistic-based Paired T-test to find the significant difference of each stimulus with each group that separate by age of participants.

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“…The Emotiv EPOC has been used in numerous applications involving BCI, among them [7], [8], [9], [10], [11], and [12] stand out. This peripheral's potential distinguishes EEG signals by capturing them through 14 electrode sensors that allow the identification of different intentions from a user's thoughts.…”

Section: Introductionmentioning

confidence: 99%

Control of a Mobile Robot Through Brain Computer Interface

Moreno¹,

Alemán

2015

Inge cuc

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Abstract-This paper poses a control interface to command the movement of a mobile robot according to signals captured from the user's brain. These signals are acquired and interpreted by Emotiv EPOC device, a 14-electrode type sensor which captures electroencephalographic (EEG) signals with high resolution, which, in turn, are sent to a computer for processing. One brain-computer interface (BCI) was developed based on the Emotiv software and SDK in order to command the mobile robot from a distance. Functionality tests are performed with the sensor to discriminate shift intentions of a user group, as well as with a fuzzy controller to hold the direction in case of concentration loss. As conclusion, it was possible to obtain an efficient system for robot movements. Keywords-Brain Computer Interface -BCI, EmotivEpoc, Mobile Robot, Arduino, EEG.Resumen-En este artículo se presenta una interfaz de control que permite comandar el movimiento de un robot móvil en función de la captura de señales provenientes del cerebro del usuario. Dichas señales son adquiridas e interpretadas por medio del dispositivo Emotiv Epoc, el cual cuenta con 14 sensores tipo electrodo que captan señales electroencefalográficas (EEG) de alta resolución, que después son enviadas a un equipo de cómputo para ser procesadas. Se desarrolla una interfaz cerebro-computador (BCI) basada en el software y SDK del desarrollador del Emotiv mediante la cual se comanda de forma remota el robot móvil. Se realizan pruebas de funcionalidad con el sensor para discriminar una intención de desplazamiento por parte de un grupo de usuarios y un controlador difuso para sostener la dirección en casos de perdida de la concentración. Como conclusión, se logra obtener un sistema eficiente para la manipulación del robot.

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Alpha and Beta brainwave characteristics to binaural beat treatment

Cited by 22 publications

References 14 publications

Effect of auditory stimulus in EEG signal using a Brain-Computer Interface

Effect of auditory stimulus in EEG signal using a Brain-Computer Interface

EEG-based analysis of auditory stimulus in a brain-computer interface

Control of a Mobile Robot Through Brain Computer Interface

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