A Pervasive Approach to EEG-Based Depression Detection
A Pervasive Approach to EEG-Based Depression Detection
复制标题
基于脑电图的抑郁症检测的普遍方法
DOI：
10.1155/2018/5238028
复制
发表时间：
2018-01-01
期刊：
影响因子：
2.3
通讯作者：
Gutknecht, Jurg
中科院分区：
文献类型：
--
作者：
Cai, Hanshu;Han, Jiashuo;Gutknecht, Jurg
如今，抑郁症是世界范围内的主要健康问题和经济负担。然而，由于目前抑郁症诊断方法的局限性，一个普遍和客观的方法是必不可少的。在本研究中，一个心理生理数据库，包含213（92抑郁症患者和121名正常对照）的主题，构建。所有受试者在静息状态和声音刺激下的脑电图（EEG）信号，使用一个普及的前额叶三电极EEG系统在Fp 1，Fp 2，和Fpz电极站点收集。在使用结合卡尔曼推导公式、离散小波变换和自适应预测滤波器的有限脉冲响应滤波器进行去噪之后，总共提取了270个线性和非线性特征。然后，最小冗余最大相关特征选择技术降低了特征空间的维数。四种分类方法（支持向量机，K-最近邻，分类树和人工神经网络）区分抑郁症的参与者从正常对照组。使用10倍交叉验证来评估分类器的性能。结果表明，K-最近邻（KNN）的准确率最高，为79.27%。结果还表明，θ波的绝对功率可能是鉴别抑郁症的一个有效特征。本研究证明了三电极脑电普适采集系统用于抑郁症诊断的可行性。
Nowadays, depression is the world's major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 (92 depressed patients and 121 normal controls) subjects, was constructed. The electroencephalogram (EEG) signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal-lobe three-electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining the Kalman derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal-redundancy-maximal-relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods (Support Vector Machine, K-Nearest Neighbor, Classification Trees, and Artificial Neural Network) distinguished the depressed participants from normal controls. The classifiers' performances were evaluated using 10-fold cross-validation. The results showed that K-Nearest Neighbor (KNN) had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis.