Stability Analysis of Multiscale Bubble Entropy and Power Metric based Seizure Detection Technique with MLA

Abstract

In this paper, we explore the use of multiscale bubble entropy and power metric for feature extraction procedure and extend it with MLA and stability analysis to design a reliable multichannel seizure detection technique. First, we represent the multichannel EEG signal in 2D matrix form and then apply AM FM model to exploit the decomposed form of EEG. Thereafter, we construct the complexity coefficient using multiscale bubble entropy analysis from decomposed EEG wave. Then, second feature set is formed by using simple and efficient power procedure to obtain absolute power index and relative power index. Using two machine learning approaches, classification performance of proposed approach is explored to correctly identify the epileptic seizures. To show the robustness of multiscale bubble entropy, the stability analysis is performed with normal EEG dataset. Experimental results demonstrate that our proposed technique can effectively detect the epileptic seizures and achieve a superior classification performance with the ANN classifier compared to KNN classifier. This method provides higher discriminating capability with greater stability, so that they could detect wider range of seizure and thus help advance the current diagnosis system.

KEYWORDS:

• ANN
• Bubble entropy
• EEG
• Epilepsy
• KNN
• Multiscale entropy

Additional information

Notes on contributors

Hemlata Pal

Hemlata Pal received the BE degree in electronics and communication from Medicaps University, Indore, India, in 2007, the ME degree from SGSITS Indore, India, in 2011. She is currently pursuing PhD from School of Electronics, Devi Ahilya University, Indore, India. Her current research interests include biomedical signal processing, medical image processing & compression of biomedical signals. Corresponding author. Email: [email protected]

Abhay Kumar

Abhay Kumar received MSc degree in electronics from IIT Delhi, India, MTech degree in optoelectronics and communication from IIT Delhi, India, in 1990 and the PhD degree from School of Electronics, Devi Ahilya University, Indore, India, in 2002. He is currently Head of Department of School of Electronics, Devi Ahilya University, Indore, India, His research interest includes digital signal processing, digital image processing and biomedical signal processing. Email: [email protected]