1 INTRODUCTION  
1.1 An overview of brain-computer interface (BCI)  
1.2 Our Contributions  

2 ADVANCES IN SENSING TECHNOLOGIES  
2.1 An overview of EEG sensors/devices  
2.2 Commercialised EEG devices  

3 SIGNAL ENHANCEMENT AND ONLINE PROCESSING  
3.1 Artefact handling  
3.2 EEG Online Processing  

4 MACHINE LEARNING AND FUZZY MODELS IN BCI APPLICATIONS  
4.1 An overview of machine learning  
4.2 Transfer learning  
4.3 Interpretable Fuzzy Models  

5 DEEP LEARNING ALGORITHMS WITH BCI APPLICATIONS  
5.1 Convolutional Neural Networks (CNN)  
5.2 Generative Adversarial Networks (GAN)  
5.3 Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)  
5.4 Deep Transfer Learning (DTL)  
5.5 Adversarial Attacks to Deep Learning Models in BCI  

6 BCI-BASED HEALTHCARE SYSTEMS  

7 DISCUSSION AND CONCLUSION