Decision-level fusion method for diagnosis of major depressive disorder

Zhi Cao; Shixing Ye; Pingping Liu; Guanglan Wei; Feng Zhao

doi:10.1117/12.2687530

28 August 2023 Decision-level fusion method for diagnosis of major depressive disorder

Zhi Cao, Shixing Ye, Pingping Liu, Guanglan Wei, Feng Zhao

Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 1272409 (2023) https://doi.org/10.1117/12.2687530
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China

Abstract

The extraction of features from the electroencephalography (EEG) of patients with major depressive disorder (MDD) and the subsequent construction of classifiers using machine learning methods to fuse decision information from multiple classifiers at the decision level is an effective method to improve the final classification performance. However, the current multi-classifier fusion approach is plagued by the output error probability of the support vector machine (SVM) affecting the accuracy of the final decision. Thus, to counteract the influence of the error probability of the classifier outputs on the classification results, this study proposed a decision-level strategy based on SVM classification confidence. Specifically, multiple classifiers were trained and the confidence of the classifier classification outputs was constructed as confidence feature vectors to be input into the SVM for the final decision. Compared with a single classifier or the traditional multi-classifier fusion method, the proposed method exhibited a stronger ability to identify depression with an accuracy of 86.79%.

Citation Download Citation

Zhi Cao, Shixing Ye, Pingping Liu, Guanglan Wei, and Feng Zhao "Decision-level fusion method for diagnosis of major depressive disorder", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 1272409 (28 August 2023); https://doi.org/10.1117/12.2687530

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KEYWORDS

Electroencephalography

Feature extraction

Feature fusion

Brain

Education and training

Electrodes

Diseases and disorders

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