[PDF] Brain-Computer Interface: Advancement and Challenges | Semantic Scholar (2024)

An up-to-date assessment of the state-of-the-art in BCI technology is presented, providing valuable insight into where this field is heading in terms of progress and innovation.

The findings highlight the potential of BCIs in restoring motor function, improving the quality of life for individuals with various conditions, and enhancing human-technology interaction.

An in-depth examination of the advances and future possibilities of BCI technologies emphasizes the transformative influence of BCIs on human-computer interaction and their potential to alter healthcare, gaming, and other industries.

This chapter reviews the recent BCI related studies, followed by the most relevant applications, and presents the key issues and challenges which exist in regard to the BCI systems and also provides future directions.

This paper provides a first-of-its-kind comprehensive review of conventional signal processing and deep learning techniques for BCI MI signal analysis and presents the open research problems and future directions.

This study begins by introducing BCIs and proceed by explaining the principles of BCI-based neurorehabilitation, and goes through four specific types of NDs, including amyotrophic lateral sclerosis, Parkinson’s disease, Alzheimer's disease, and spinal muscular atrophy, to review some of the applications of BCIs in the neural rehabilitation of these diseases.

A BCI system based on Arduino circuit has been built based on the utilization of EEG signals to translate brainwave patterns into actionable commands to enhance communication capabilities for individuals afflicted with neurological disorders.

This work presents an exhaustive study on the feasibility of adopting BCI techniques for industrial applications, particularly Electroencephalography (EEG), and identifies the potential use cases of EEG-based BCI systems in industries in the current traction while accounting for their pros and cons.

The brain-computer interface and computer-brain interface technologies as components of BBI systems are reviewed, the development of BBI systems, applications of this technology, arising ethical issues and expectations for future use are reviewed.

A comprehensive examination of the Brain-Computer Interface and the more scientific discoveries that have resulted from it is provided, and significant challenges remain for user advancement.

...

...

This article provides a comprehensive review of the state-of-the-art of a complete BCI system and a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics.

The state-of-the-art of BCIs are reviewed, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface.

The current review evaluates EEG-based BCI paradigms regarding their advantages and disadvantages from a variety of perspectives, and various EEG decoding algorithms and classification methods are evaluated.

This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006, and asks what are the key signal processing components of a BCI and what signal processing algorithms have been used in BCIs.

A detailed survey of various applications of BCI using different feature extraction and classification techniques is done and all the current issues which hinder the efficiency ofBCI systems are compiled.

...

...