Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review
Mamunur Rashid,Norizam Sulaiman,Anwar P. P. Abdul Majeed,Rabiu Muazu Musa,Ahmad Fakhri Ab. Nasir,Bifta Sama Bari,Sabira Khatun +6 more
TL;DR: 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.
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Abstract: Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements and breakthroughs that have been made in this particular field. Nonetheless, it is also worth mentioning that with these improvements, new challenges are constantly discovered. This article provides a comprehensive review of the state-of-the-art of a complete BCI system. First, a brief overview of electroencephalogram (EEG)-based BCI systems is given. Secondly, a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics. Finally, the challenges to the recent BCI systems are discussed, and possible solutions to mitigate the issues are recommended.
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A Survey on Neuromarketing using EEG Signals
Vaishali Khurana,Monika Gahalawat,Pradeep Kumar,Partha Pratim Roy,Debi Prosad Dogra,Erik Scheme,Mohammad Soleymani +6 more
TL;DR: A range of considerations for EEG-based neuromarketing strategies are surveyed, including the types of information that can be gathered, how marketing stimuli are presented to consumers, how such strategies may affect the consumer in terms of appeal and memory, machine learning techniques applied in the field, and the variety of challenges faced.
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A Structured and Methodological Review on Vision-Based Hand Gesture Recognition System
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TL;DR: This paper aims to uncover the limitations faced in image acquisition through the use of cameras, image segmentation and tracking, feature extraction, and gesture classification stages of vision-driven hand gesture recognition in various camera orientations.
Toward EEG-Based BCI Applications for Industry 4.0: Challenges and Possible Applications.
Khalida Douibi,Solène Le Bars,Alice Lemontey,Alice Lemontey,Lipsa Nag,Rodrigo Balp,Gabrièle Breda +6 more
TL;DR: In this article, the authors carried out a detailed literature review to investigate the main challenges and present criteria relevant to the future deployment of Brain-Computer Interface (BCI) applications for Industry 4.0.
Trends in EEG signal feature extraction applications
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TL;DR: In this article , the authors focus on electroencephalogram (EEG) signal analysis with an emphasis on common feature extraction techniques mentioned in the research literature, as well as a variety of applications that this can be applied to.
Brain–computer interface: trend, challenges, and threats
Baraka Jacob Maiseli,Abdi T. Abdalla,Libe Valentine Massawe,Mercy Mbise,Khadija Mkocha,Nassor Ally Nassor,Moses Ismail,James Michael,Samwel Kimambo +8 more
TL;DR: The analysis shows an exponential growth of BCI publications in China from 2019 onwards, exceeding those from the United States that started to decline during the same period.
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