Title: Evaluation of joint analysis of multiple interictal events for spike extraction and source imaging

Authors: Palani Thanaraj Krishnan; Parvathavarthini Balasubramanian; Chitra Krishnan

Addresses: Department of Electronics and Instrumentation Engineering, St. Joseph's College of Engineering, Anna University, Chennai 600119, India ' Department of Computer Science and Engineering, St. Joseph's College of Engineering, Anna University, Chennai 600119, India ' School of Electronics Engineering, VIT University, Chennai 600127, India

Abstract: Interictal spike extraction and epileptic source localisation is an important neuroimaging problem. Manual analysis of EEG interictal spikes is time-consuming and imposes an overwhelming workload for the physician. To overcome this problem, we investigate a joint analysis of EEG interictal events and automatic spike extraction for epileptic source localisation. In this work, Multivariate Empirical Mode Decomposition (MEMD) is applied to each event separately and the Intrinsic Mode Functions (IMFs) are extracted. The joint analysis combines IMFs of different interictal events to a common empirical mode domain. A power threshold step recovers the interictal spikes in the joint signal by filtering the background EEG activity and the noises. Experimental analysis of four epileptic patient data set shows that the filtered EEG signal indicates a significant improvement in the Signal to Noise Ratio (SNR) (p < 0.0047(t-test), min: 35.3283 dB and max: 52.2506 dB). The results of this paper show a good conformance (concordance rate, min:40% and max:80%) in localising the epileptogenic regions.

Keywords: EEG; source imaging; epilepsy; multivariate empirical mode decomposition; independent component analysis; standardised LORETA; power spectrum.

DOI: 10.1504/IJBET.2017.086553

International Journal of Biomedical Engineering and Technology, 2017 Vol.25 No.1, pp.77 - 102

Received: 18 Apr 2016
Accepted: 27 Jul 2016
Published online: 12 Sep 2017 *

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