EEG Artifact Removal Strategies for BCI Applications: A Survey
Publish place: majlesi Journal of Electrical Engineering، Vol: 18، Issue: 1
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
View: 97
This Paper With 11 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_MJEE-18-1_016
تاریخ نمایه سازی: 9 اردیبهشت 1403
Abstract:
This paper aims to provide a comprehensive examination of the Brain-Computer Interface and the more scientific discoveries that have resulted from it. The ultimate goal of this review is to provide extensive research in BCI systems while also focusing on artifact removal techniques or methods that have recently been used in BCI and important aspects of BCIs. In its pre-processing, artifact removal methodologies were critical. Furthermore, the review emphasizes the applicability, practical challenges, and outcomes associated with BCI advancements. This has the potential to accelerate future progress in this field. This critical evaluation examines the current state of BCI technology as well as recent advancements. It also identifies various BCI technology application areas. This detailed study shows that, while progress is being made, significant challenges remain for user advancement A comparison of EEG artifact removal methods in BCI was done, and their usefulness in real-world EEG-BCI applications was talked about. Some directions and suggestions for future research in this area were also made based on the results of the review and the existing artifact removal methods.
Authors
Pardhu Thottempudi
Department of Electronics & Communication Engg BVRIT HYDERABAD College of Engineering For Women Nizampet
Vijay Kumar
School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, India.
Nagesh Deevi
Department of Electronics and Communications Engineering, BVRIT HYDERABAD College of Engineering for Women, Hyderabad, India.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :