IoT-enabled healthcare apps are providing significant value to society by offering cost-
effective patient monitoring solutions in IoT-enabled buildings. However, with a large …

The introduction of deep learning technology has greatly benefited the neuroscience field by
improving the electroencephalogram (EEG) signal analysis. These technologies have …

Objective. Brain–computer interface (BCI) is leveraged by artificial intelligence in EEG signal
decoding, which makes it possible to become a new means of human-machine interaction …

This paper presents an advanced approach for EEG artifact removal and motor imagery
classification using a combination of Four Class Iterative Filtering and Filter Bank Common …

Inter-subject or subject-independent emotion recognition has been a challenging task in
affective computing. This work is about an easy-to-implement emotion recognition model …

This study explores the history and current state of Brain-Computer Interfaces (BCIs),
focusing on non-invasive, EEG-based devices. BCIs have evolved from early studies in …

Abstract Music Entrainment Brain-Computer Interface (BCI) systems influence music as a
modulatory tool, synchronizing neural activities to the rhythm and structure of auditory …

Electroencephalography (EEG) is an invaluable tool in neuroscience, offering insights into
brain activity with high temporal resolution. Recent advancements in machine learning and …

In recent days, advancements in science, technology, and the social environment have
played a vital role in changing the social and emotional well-being of a person's life. These …

Humans commonly use speech to express their feelings. Recognizing emotions in speech is
a critical task where machine learning plays a crucial role. Speech Emotion Recognition …