I. Introduction  
II. Emotion Models  
A. Discrete or Categorical Models  
B. Continuous or Multidimensional Models  
III. Databases  
IV. Data Annotation  
A. Discrete Annotation  
B. Continuous Annotation  
V. Data Preprocessing  
A. EEG Preprocessing  
B. ECG Preprocessing  
C. GSR Preprocessing  
D. 1D to 2D Conversion  
VI. Inter-Subject Data Variance  
A. Statistical Analysis  
B. Reasons of Inter-Subject Data Variance  
C. Reducing Inter-Subject Data Variance  
VII. Data Splitting  
A. Subject Independent Splitting  
B. Subject Dependent Splitting  
VIII. Multimodal Fusion  
IX. Future Challenges  
A. Data Acquisition  
B. Data Annotation  
C. Feature Extraction and Fusion  
D. Generalization of Models  
E. Modern Machine Learning Methods  
X. Conclusion