Recently, electroencephalography (EEG) signals have shown great potential for emotion
recognition. Nevertheless, multichannel EEG recordings lead to redundant data …

This work proposes an emotion recognition technique by distinguishing appropriate
electroencephalogram (EEG) segments from acquired signal for target emotions. Generally …

Post-stroke depression (PSD) has negative impacts on the daily life of stroke survivors and
delays their neurological recovery. However, traditional post-stroke rehabilitation mainly …

Investigating gender differences based on emotional changes supports automatic
interpretation of human intentions and preferences. This allows emotion applications to …

Emotion detection is an important research issue in electroencephalogram (EEG). Signal
preprocessing and feature selection are parts of feature engineering, which determines the …

The feasibility and effectiveness of data fusion for the fault classification of bearing faults
have been very well iterated in the literature. However, all previous endeavors have been …

Early rehabilitation with the right intensity contributes to the physical recovery of stroke
survivors. In clinical practice, physicians determine whether the training intensity is suitable …

Abstract Mental Status Assessment (MSA) holds significant importance in psychiatry. In
recent years, several studies have leveraged Electroencephalogram (EEG) technology to …

This research paper proposes a novel robust high-performance power spectrum estimator,
and bispactral power density analyzer that has outstanding capabilities in estimating noisy …

Emotion affects human being's health to a great extent and it attracts lots of attention
recently. Objective measurements are necessary for identifying various emotion states. As a …