Depression recognition using machine learning methods with different feature generation strategies

作者：

Highlights：

• Novel method for depression recognition of Electroencephalography is proposed.

• Propose an ensemble model which consists of deep forest and SVM.

• Add spatial information of EEG caps by image conversion method

• Perform EEG signals processing and analysis on multiple frequency bands.

摘要

•Novel method for depression recognition of Electroencephalography is proposed.•Propose an ensemble model which consists of deep forest and SVM.•Add spatial information of EEG caps by image conversion method•Perform EEG signals processing and analysis on multiple frequency bands.

论文关键词：Depression,EEG,Ensemble model,Deep learning

论文评审过程：Received 10 January 2019, Revised 11 July 2019, Accepted 16 July 2019, Available online 17 July 2019, Version of Record 13 August 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.07.004