Using EEG signal as a new type of biometric in user authentication systems has been emerging as an interesting research topic. However, one of the major challenges is that a huge amount of EEG data that needs to be processed, transmitted and stored. The use of EEG compression is therefore becoming necessary. In this paper, we investigate the feasibility of using lossy compression to EEG data in EEG-based user authentication systems. Our experiments performed on a large scale of three EEG datasets indicate that using EEG lossy compression is feasible compared to using lossless one. Moreover, a threshold for information lost has been discovered and the system accuracy is unchanged if the threshold is lower than or equal 11%.
Nguyen, B., Nguyen, D., Ma, W., & Tran, D. (2017). Investigating the possibility of applying EEG lossy compression to EEG-based user authentication. In Proceedings of the International Joint Conference on Neural Networks (Vol. 2017-May, pp. 79–85). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/IJCNN.2017.7965839