Stress detection and reduction using EEG signals

M. S. Kalas, B. Momin
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引用次数: 37

Abstract

According to world health organization, stress is a significant problem of our times and affects both physical as well as the mental health of people. There are various traditional stress detection methods are available. Research in area of stress detection has developed many techniques for monitoring the human brain that can be used to study the human behavior. However, there are researches on stress detection methods and not on stress reduction methods in terms of technology. This research proposes a novel method that detects the stress using EEG signals and reduces the stress by introducing the interventions into the system. This research uses the k-means clustering method to measure the perceived stress which divide the subjects into different categories and estimate the stress level. The proposed method is useful in developing products for human stress reduction. The success of implementation and development of this research will expected to help in reducing time consumed and human power in determining best solution for stress management.
利用脑电图信号进行应力检测和减小
根据世界卫生组织的说法,压力是我们这个时代的一个重大问题,影响着人们的身体和精神健康。传统的应力检测方法多种多样。在压力检测领域的研究已经发展出许多监测人脑的技术,这些技术可以用来研究人类的行为。然而,在技术上,对应力检测方法的研究较多,而对应力减小方法的研究较少。本研究提出了一种利用脑电图信号检测压力的新方法,并通过在系统中引入干预措施来减少压力。本研究采用k-均值聚类法测量被试的感知压力,将被试划分为不同的类别并估计压力水平。该方法可用于开发人体减压产品。这项研究的成功实施和发展将有助于减少在确定压力管理最佳解决方案方面所消耗的时间和人力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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