**4. Conclusion**

The number of artifact handling techniques and algorithms are increasing drastically, however the artifact problem is still challenging for many applications. Particularly, the internal or physiologic artifacts are difficult to distinguish and remove. While simple measures such as artifact avoidance and artifact rejection can be utilized in some applications, most of the cases require special methods dedicated to handle artifacts in order to significantly reduce their harmful effects on signal of interest. Due to the varying nature of artifacts a generic method for all sorts of artifacts is still missing. However preprocessing pipelines provides some efficient approaches to this challenge. In future, the progress in machine learning and deep learning based approaches may yield more efficient, accurate and robust artifact removal options. Online artifact removal methods such as ASR must be developed to overcome various artifacts in daily life to be efficient for BCIs.
