The classification of electroencephalogram (EEG) signals is of significant importance in
brain–computer interface (BCI) systems. Aiming to achieve intelligent classification of EEG …

The Electroencephalography (EEG)-based precise emotion identification is one of the most
challenging tasks in pattern recognition. In this paper, an innovative EEG signal processing …

For brain computer interfaces (BCIs) research, the classification of motor imagery brain
signals is a major and challenging step. Based on the traditional sparse representation …

Smart technologies for women safety are gaining popularity over the last few decades.
Several nefarious approaches to women that outraged the entire nation awakened the …

Accurate as well as an efficient Spectrum Estimation (SE) is the fundamental requirement of
any practical wireless communication system for seamless connectivity. In this work an …

The purpose of the article is to check whether the method of estimating EEG signal energy,
treated as a feature, has an impact on the classification accuracy in BCI systems. The …

Heartbeat classification using parametric and time–frequency methods - Book chapter -
IOPscience This site uses cookies. By continuing to use this site you agree to our use of cookies …

Electroencephalography (EEG) gained popularity over similar modalities like Functional
Magnetic Resonance Imaging (fMRI) or Functional Near-Infrared Spectroscopy (fNRIS), for …

The purpose of the following study is to determine patterns generated by 6 movements:
Opening/Closing-Eye, Opening/Closing-Mouth, Concentration, Meditation, Eye Movement …

The analysis of Electromyography (EMG) signal is one of the effective determinants for the
valuable prosthetic devices. Now a day various techniques have been proposed by the …