基于k近邻的成人早期脑波信号浓度水平分类

Ahmad Azhari, Fathia Irbati Ammatulloh
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引用次数: 2

摘要

大脑控制着人类生活的中心。通过大脑,一切生活活动都可以完成。其中之一是认知活动。大脑的表现受精神状况、生活方式和年龄的影响。认知活动是对心理活动的观察,因此它包括涉及大脑记忆、信息处理和未来规划的心理症状。在这项研究中,浓度水平是在成人早期阶段(18-30岁)测量的,因为在这个阶段,大脑的思维更抽象,精神状况会影响它。本研究的目的是利用标准递进矩阵(SPM)测试类型的智商测试,观察成人早期阶段在认知活动形式的刺激下的集中水平。为了找出智商测试的结果需要很长时间,所以在本研究中,我们做了一个记录来获得脑电波,以便可以快速获得浓度水平的结果。脑电图数据采用脑电图(EEG)应用SPM试验作为刺激。每个应答者需要3次获取,总共10个应答者。本研究实现的方法是基于k-最近邻(kNN)算法的分类。在使用该方法之前,首先进行预处理,对信号进行减小和滤波(13-30 Hz)。首先对采集的数据进行结果提取,得到正确的特征,本研究中特征提取采用一阶统计特征,旨在从所获得的信号中找出典型信息。本研究的结果是将浓度水平分为高、中、低三类。最后,本研究结果显示准确率为70%。
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Classification of Concentration Levels in Adult-Early Phase using Brainwave Signals by Applying K-Nearest Neighbor
The brain controls the center of human life. Through the brain, all activities of living can be done. One of them is cognitive activity. Brain performance is influenced by mental conditions, lifestyle, and age. Cognitive activity is an observation of mental action, so it includes psychological symptoms that involve memory in the brain's memory, information processing, and future planning. In this study, the concentration level was measured at the age of the adult-early phase (18-30 years) because in this phase, the brain thinks more abstractly and mental conditions influence it. The purpose of this study was to see the level of concentration in the adult-early phase with a stimulus in the form of cognitive activity using IQ tests with the type of Standard Progressive Matrices (SPM) tests. To find out the IQ test results require a long time, so in this study, a recording was done to get brain waves so that the results of the concentration level can be obtained quickly.EEG data was taken using an Electroencephalogram (EEG) by applying the SPM test as a stimulus. The acquisition takes three times for each respondent, with a total of 10 respondents. The method implemented in this study is a classification with the k-Nearest Neighbor (kNN) algorithm. Before using this method, preprocessing is done first by reducing the signal and filtering the beta signal (13-30 Hz).The results of the data taken will be extracted first to get the right features, feature extraction in this study using first-order statistical characteristics that aim to find out the typical information from the signals obtained. The results of this study are the classification of concentration levels in the categories of high, medium, and low. Finally, the results of this study show an accuracy rate of 70%.
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