Brainwaves feature classification by applying K-Means clustering using single-sensor EEG

Abstract

The use of brainwave signal is a step in the introduction of the individual identity using biometric technology based on characteristics of the body. Brainwave signal has unique characteristics and different on each individual because the brainwave cannot be read or copied by people so it is not possible to have a similarity of one person with another person. To be able to process the identification of individual characteristics, which obtained from the signal brainwave, required a pattern of brain activity that is prominent and constant. Cognitive activity testing using a single-sensor EEG (Electroencephalogram) divided into two categories, called the activity of cognitive involving the ability of the right brain (creativity, imagination, holistic thinking, intuition, arts, rhythms, nonverbal, feelings, visualization, tune of songs, daydreaming) and the left brain (logic, analysis, sequences, linear, mathematics, language, facts, think in words, word of songs, computation) give a different cluster based on two times the test on mathematical activities (no cluster slices of experiment 1 and experiment 2). The result showed that cognitive activity based on math activity can provide a signal characteristic that can be used as the basis for a brain-computer interface applications development by utilizing EEG single-sensor.

Principal component analysis implementation for brainwave signal reduction based on cognitive activity

“…Our research extends previous experimental work [5]. Data acquisition process is obtained using Neurosky Mindset using a EEG sensor (so-called electrode), placed in FP1 (frontal lobe) position based on the 10-20 system.…”

“…Cognitive activity of the brain is based on several studies related to psychological perceptions [3]- [5][11] [18]. This cognitive activity aims to gain a specific response from the brain's cognitive activity (so-called cognitive task).…”

“…The use of cognitive tasks is aimed at triggering the specific response of the human brain arising from the cognitive aspect. This development is also referred as cognitive biometrics [5].…”

“…The use of brain waves has several advantages over other biometric authentication systems such as fingerprint and iris scan. Brainwave signals have characteristics and characteristics typical of the individual so it is impossible to have similarities, imitated or read by others [5].…”

Identification of Toddlers’ Nutritional Status using Data Mining Approach

“…K-means clustering algorithm is also widely implemented in medical science field such as applying k-means clustering to analyze identification of individual characteristics using brainwave signal [17], to identify new candidate drug compounds that have relation with lung cancer drugs [18], to make recommendation of antiarrhythmic drugs [19], and extraction cancer signatures [20]. The other studies are clustering medical data to find direction and effectiveness of the research work [21], enhance cancer subtype prediction [22], color-converted segmentation algorithm for magnetic resonance imaging (MRI) brain images [23] and EEG analysis to detect drowsy driving [24].…”