Department of Computer Engineering, University of Engineering and Technology, Taxila, 47050, Pakistan.
Department of Computer Engineering, University of Engineering and Technology, Taxila, 47050, Pakistan.
Comput Biol Med. 2019 Apr;107:182-196. doi: 10.1016/j.compbiomed.2019.02.015. Epub 2019 Feb 25.
Stress is inevitably experienced by almost every person at some stage of their life. A reliable and accurate measurement of stress can give an estimate of an individual's stress burden. It is necessary to take essential steps to relieve the burden and regain control for better health. Listening to music is a way that can help in breaking the hold of stress. This study examines the effect of music tracks in English and Urdu language on human stress level using brain signals. Twenty-seven subjects including 14 males and 13 females having Urdu as their first language, with ages ranging from 20 to 35 years, voluntarily participated in the study. The electroencephalograph (EEG) signals of the participants are recorded, while listening to different music tracks by using a four-channel MUSE headband. Participants are asked to subjectively report their stress level using the state and trait anxiety questionnaire. The English music tracks used in this study are categorized into four genres i.e., rock, metal, electronic, and rap. The Urdu music tracks consist of five genres i.e., famous, patriotic, melodious, qawali, and ghazal. Five groups of features including absolute power, relative power, coherence, phase lag, and amplitude asymmetry are extracted from the preprocessed EEG signals of four channels and five bands, which are used by the classifier for stress classification. Four classifier algorithms namely sequential minimal optimization, stochastic decent gradient, logistic regression (LR), and multilayer perceptron are used to classify the subject's stress level into two and three classes. It is observed that LR performs well in identifying stress with the highest reported accuracy of 98.76% and 95.06% for two- and three-level classification respectively. For understanding gender, language, and genre related discriminations in stress, a t-test and one-way analysis of variance is used. It is evident from results that English music tracks have more influence on stress level reduction as compared to Urdu music tracks. Among the genres of both languages, a noticeable difference is not found. Moreover, significant difference is found in the scores reported by females as compared to males. This indicates that the stress behavior of females is more sensitive to music as compared to males.
压力几乎是每个人在生命的某个阶段都不可避免会经历的。对压力进行可靠和准确的测量，可以估算个体的压力负担。有必要采取必要的措施来减轻负担，重新获得控制，以促进更好的健康。听音乐是一种可以帮助打破压力束缚的方式。本研究使用脑信号来检验英语和乌尔都语音乐曲目对人类压力水平的影响。27 名受试者，包括 14 名男性和 13 名女性，母语为乌尔都语，年龄在 20 至 35 岁之间，自愿参加了这项研究。参与者的脑电图 (EEG) 信号是通过使用四通道 MUSE 头带记录的，同时听不同的音乐曲目。参与者被要求使用状态和特质焦虑问卷主观报告他们的压力水平。本研究中使用的英语音乐曲目分为摇滚、金属、电子和说唱四种类型。乌尔都语音乐曲目包括著名、爱国、悦耳、卡瓦利和格扎尔五种类型。从四个通道和五个频段的预处理 EEG 信号中提取了五个组的特征，包括绝对功率、相对功率、相干性、相位滞后和幅度不对称性，然后由分类器用于压力分类。使用了四种分类器算法，即序贯最小优化、随机梯度下降、逻辑回归 (LR) 和多层感知器，将受试者的压力水平分为两类和三类进行分类。结果表明，LR 在识别压力方面表现良好，两类和三类分类的准确率分别为 98.76%和 95.06%。为了了解性别、语言和类型相关的压力差异，使用 t 检验和单因素方差分析。结果表明，英语音乐曲目对降低压力水平的影响比乌尔都语音乐曲目更大。在两种语言的类型中，没有发现明显的差异。此外，女性报告的分数与男性相比有显著差异。这表明女性的压力行为对音乐比男性更敏感。
