Mental state classification based on electroencephalogram (EEG) using multiclass support vector machine.

Journal: The Medical journal of Malaysia
Published Date:

Abstract

INTRODUCTION: Mental state refers to a person's state of mind from various perspectives, including consciousness, intention, and functionalism. Mental states closely related to everyday life include the concentrating state, neutral state, and relaxation state. Concentration is vital for cognitive tasks, while relaxation is crucial for comfort. However, individuals with mental disorders or neurological conditions often struggle to achieve these states, requiring effective detection and intervention. One method for detecting mental states is by using brainwave signals obtained through electroencephalogram (EEG). EEG has been widely used in neuroscience and clinical settings to objectively assess mental states by analyzing brainwave signals. Previous studies have demonstrated the potential of EEG-based mental state classification in stress detection, cognitive workload analysis, or depression detection.

Authors

  • S W Purnami
    Institut Teknologi Sepuluh Nopember, Department of Statistics, Surabaya, Indonesia. santi_wulan@its.ac.id.
  • S Karimah
    Institut Teknologi Sepuluh Nopember, Department of Statistics, Surabaya, Indonesia.
  • S Andari
    Institut Teknologi Sepuluh Nopember, Department of Statistics, Surabaya, Indonesia.
  • D P Wulandari
    Institut Teknologi Sepuluh Nopember, Department of Computer Enginering, Surabaya, Indonesia.
  • Y S Hadiwidodo
    Institut Teknologi Sepuluh Nopember, Department of Ocean Engineering, Surabaya, Indonesia.
  • W R Islamiyah
    Universitas Airlangga, Department of Neurology, Surabaya, Indonesia.
  • M M Maramis
    Universitas Airlangga, Department of Psychiatry, Surabaya, Indonesia.
  • J M Zain
    Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, Malaysia.