@inproceedings{fcaadcf533e34a52ab83fff8c2482466,
title = "Automatic depression discrimination on FNIRS by using general linear model and SVM",
abstract = "A method is proposed to distinguish patients with depression from healthy persons using data measured by Functional Near Infrared Spectroscopy (FNIRS) during a cognitive task. Firstly, General Linear Model (GLM) is used to extract features from 52-channel FNIRS data of patients with depression and normal healthy persons. Then a Support Vector Machine (SVM) classifier is designed for classification. The results of experiment show that the method can achieve a satisfactory classification with the accuracy 89.71% for total and 92.59% for patients. Also, the results suggest that FNIRS is a promising clinical technique in the diagnosis and therapy of depression.",
keywords = "Depression Discrimination, FNIRS, GLM, SVM",
author = "Hong Song and Weilong Du and Xin Yu and Wentian Dong and Wenxiang Quan and Weimin Dang and Huijun Zhang and Ju Tian and Tianhang Zhou",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014 ; Conference date: 14-10-2014 Through 16-10-2014",
year = "2014",
doi = "10.1109/BMEI.2014.7002785",
language = "English",
series = "Proceedings - 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "278--282",
booktitle = "Proceedings - 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014",
address = "United States",
}