Depression Detection Using Relative EEG Power Induced by Emotionally Positive Images and a Conformal Kernel Support Vector Machine
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Emotional Stimuli
2.3. Resting-State and Emotion-Induction EEG Data Collection
2.4. Apparatus, Settings, and EEG Preprocessing
2.5. Feature Extraction
2.6. Classification
2.6.1. LDA
2.6.2. QDA
2.6.3. SVM
2.6.4. CK-SVM
2.7. Performance Evaluation
2.7.1. LOPO-CV
2.7.2. Parameter Optimization
2.7.3. Feature Dimension Reduction
2.8. Statistical Analysis
3. Results
3.1. Statistical Analysis Results of Subjective Ratings of Valence and Arousal
3.2. LOPO-CV Classification Results Based on LDA Classifier and Top-N-F-Score-Ranked Features
3.3. Comparison of Top-N-F-Score-Ranked Features Across the Three Types of Relative Power During Resting State and Emotion-Induction State
3.4. Comparison of LOPO-CV Classification Performance Among Different Classifiers in the-Emotion Induction State
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Feature | State | Delta Band | Theta Band | ALPHA Band | Beta Band | Gamma Band | All Bands |
---|---|---|---|---|---|---|---|
RP-I | Resting | 65.45% (2) | 70.91% (7) | 63.64% (1) | 65.45% (44) | 61.82% (3) | 74.55% (7) |
EI | 72.73% (2) | 74.55% (2) | 72.73% (31) | 78.18% (45) | 74.55% (2) | 80.00% (6) | |
RP-II | Resting | 65.45% (53) | 70.91% (24) | 61.82% (3) | 63.64% (32) | 67.27% (3) | 70.91% (3) |
EI | 76.36% (13) | 76.36% (35) | 74.55% (4) | 70.91% (19) | 72.73% (2) | 76.36% (2) | |
RP-III | Resting | 65.45% (2) | 69.09% (5) | 63.64% (1) | 67.27% (39) | 65.45% (35) | 74.55% (7) |
EI | 78.18% (2) | 74.55% (2) | 65.45% (3) | 69.09% (2) | 70.91% (2) | 80.00% (7) |
Resting State | Emotion Induction | |||||
---|---|---|---|---|---|---|
Ranking | RP-I | RP-II | RP-III | RP-I | RP-II | RP-III |
1 | FP1-FP2(α) | T4-CP4(γ) | FP1-FP2(α) | FP1-FP2(δ) | FP1-FP2(α) | FP1-FP2(δ) |
2 | Fz-FCz(θ) | F8-C4(γ) | Fz-FCz(θ) | FP1-FP2(θ) | TP7-T6(β) | FP1-FP2(θ) |
3 | T4-CP4(γ) | FC3-CP3(θ) | FP1-FP2(θ) | TP7-T6(β) | TP7-T6(β) | |
4 | FT8-CP4(γ) | FT8-T4(δ) | C3-TP7(γ) | F4-CP3(θ) | ||
5 | FP1-FP2(θ) | CP3-CP4(γ) | C3-CP3(γ) | C3-CP3(γ) | ||
6 | FT8-T4(δ) | FT8-CP4(γ) | F4-CP3(θ) | F4-CP3(α) | ||
7 | F8-C4(γ) | FT8-T4(θ) | TP7-T6(γ) | |||
# electrodes | 9 | 6 | 9 | 7 | 4 | 7 |
Feature | LDA | QDA | SVM | CK-SVM |
---|---|---|---|---|
RP-I (6) | 80.00% | 65.45% | 81.82% | 81.82% |
RP-II (2) | 76.36% | 74.55% | 78.18% | 80.00% |
RP-III (7) | 80.00% | 70.91% | 80.00% | 83.64% |
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Wu, C.-T.; Dillon, D.G.; Hsu, H.-C.; Huang, S.; Barrick, E.; Liu, Y.-H. Depression Detection Using Relative EEG Power Induced by Emotionally Positive Images and a Conformal Kernel Support Vector Machine. Appl. Sci. 2018, 8, 1244. https://doi.org/10.3390/app8081244
Wu C-T, Dillon DG, Hsu H-C, Huang S, Barrick E, Liu Y-H. Depression Detection Using Relative EEG Power Induced by Emotionally Positive Images and a Conformal Kernel Support Vector Machine. Applied Sciences. 2018; 8(8):1244. https://doi.org/10.3390/app8081244
Chicago/Turabian StyleWu, Chien-Te, Daniel G. Dillon, Hao-Chun Hsu, Shiuan Huang, Elyssa Barrick, and Yi-Hung Liu. 2018. "Depression Detection Using Relative EEG Power Induced by Emotionally Positive Images and a Conformal Kernel Support Vector Machine" Applied Sciences 8, no. 8: 1244. https://doi.org/10.3390/app8081244