A comparative study on feature extraction and classification of mind waves for brain computerinterface (BCI)

  • Authors

    • Manjula K
    • M B.Anandaraju
    2018-03-01
    https://doi.org/10.14419/ijet.v7i1.9.9749
  • Brain Computer Interface (BCI), Electroencephalogram (EEG), Feature Extraction, Feature Classification, Central Nervous System (CNS), Wavelet Transforms (WT).

  • Abstract

    Brain Computer Interfacing (BCI) is a methodology which imparts a path for communication from external world using brain signals through computer. BCI identifies the specific patterns in a person’s changing brain activity to initiate control which relates to the person’s intention. The BCI system paraphrases these signal patterns into meaningful control command. In evolving BCI system, numerous signal processing algorithms are proposed. Non-invasive Electroencephalogram (EEG) signals or mind waves are used to extract the distinguished features and further they are classified choosing an appropriate classifier. A study on different feature extraction & Classification algorithms is used in EEG-based BCI exploration and to identify their distinct properties. This paper proposes different methodologies of feature extraction and feature Classification. It also addresses the methods and technology adapted in every phase of the EEG signal processing.This comparative survey also helps in selecting suitable algorithm for the development and accomplishment of further classification of signals.

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  • How to Cite

    K, M., & B.Anandaraju, M. (2018). A comparative study on feature extraction and classification of mind waves for brain computerinterface (BCI). International Journal of Engineering & Technology, 7(1.9), 132-136. https://doi.org/10.14419/ijet.v7i1.9.9749

    Received date: 2018-02-26

    Accepted date: 2018-02-26

    Published date: 2018-03-01