A Study of Combined Lossy Compression and Seizure Detection on Epileptic EEG Signals.

Electroencephalogram (EEG) has been widely used in diagnosing and detecting epileptic seizure. Large epileptic EEG databases have been built, the use of EEG compression is therefore becoming necessary. Epilepsy causes a change on EEG characteristics, especially on frequency, hence exploiting these features may improve the performance of EEG lossy compression techniques that are mostly working on frequency domain. In this paper, we propose a lossy compression method for epileptic EEG data, by exploiting the characteristics of EEG under epilepsy. Moreover, the recovered EEG signals processed by the proposed method are used by an EEG-based seizure detection system to evaluate the possibility of applying in real world as well as the impact of lossy compression on seizure detection. The results show that the proposed method gives a higher result, and applying the proposed method to EEG-based seizure detection system is feasible and has the advantage compared to using lossless ones.