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Selection of Relevant Features from Cognitive EEG Signals Using ReliefF and MRMR Algorithm

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Advancements of Medical Electronics

Part of the book series: Lecture Notes in Bioengineering ((LNBE))

Abstract

Cognition may be defined as a set of mental activities or processes which deals with knowledge, attention, memory and working memory, reasoning and computation, and judgement and evaluation. In this paper, we aim to study two distinctive cognitive processes dealing with evaluation of two similar stimuli and reasoning and computation of some mathematical problem. Here, we have used Wavelet Transforms and Distance Likelihood Ratio Test for feature extraction and classification respectively. We have also used two feature selection algorithm: ReliefF and Minimum Redundancy Maximum Relevance to select only the best relevant features for classification. The results show a 15 % improvement on accuracy when feature selection algorithms are used in the process. The results also suggests that the brain activation is dominant at the frontal, parietal and temporal region.

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Acknowledgments

The authors would like to thank Council of Scientific and Industrial Research, India for their financial assistance.

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Authors and Affiliations

  1. School of Bioscience and Engineering, Jadavpur University, Kolkata, India

    Ankita Mazumder, Poulami Ghosh, Anwesha Khasnobish, Saugat Bhattacharyya & D. N. Tibarewala

Authors
  1. Ankita Mazumder
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  2. Poulami Ghosh
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  3. Anwesha Khasnobish
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  4. Saugat Bhattacharyya
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  5. D. N. Tibarewala
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Corresponding author

Correspondence to Ankita Mazumder .

Editor information

Editors and Affiliations

  1. Information Technology, JIS College of Engineering, Kalyani, West Bengal, India

    Somsubhra Gupta

  2. Biomedical Engineering, JIS College of Engineering, Kalyani, West Bengal, India

    Sandip Bag

  3. Biomedical Engineering, JIS College of Engineering, Kalyani, West Bengal, India

    Karabi Ganguly

  4. Electronics & Communication Engineering, JIS College of Engineering, Kalyani, West Bengal, India

    Indranath Sarkar

  5. Electrical Engineering, JIS College of Engineering, Kalyani, West Bengal, India

    Papun Biswas

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Mazumder, A., Ghosh, P., Khasnobish, A., Bhattacharyya, S., Tibarewala, D.N. (2015). Selection of Relevant Features from Cognitive EEG Signals Using ReliefF and MRMR Algorithm. In: Gupta, S., Bag, S., Ganguly, K., Sarkar, I., Biswas, P. (eds) Advancements of Medical Electronics. Lecture Notes in Bioengineering. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2256-9_12

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  • DOI: https://doi.org/10.1007/978-81-322-2256-9_12

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2255-2

  • Online ISBN: 978-81-322-2256-9

  • eBook Packages: EngineeringEngineering (R0)

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