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<div><p>Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative technology with applications spanning robotics, virtual reality, medicine, and rehabilitation. However, existing BCI frameworks face several limitations, including a lack of stage...

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Bibliographic Details
Main Author:	Gursimran Singh (575288) (author)
Other Authors:	Aviral Chharia (22001788) (author), Rahul Upadhyay (2632240) (author), Vinay Kumar (178313) (author), Luca Longo (474781) (author)
Published:	2025
Subjects:	Medicine Cell Biology Neuroscience Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> electroencephalography wise flexibility essential steep learning curves place configurable flowchart machine learning models inclusive features leading elevated costs due applications spanning robotics minimal programming experience pynoetic also includes pynoetic &# 8217 modular python framework end gui coupled time bci development code bci design code development bci development minimal coding bci research design process pynoetic introduces present pynoetic virtual reality unique pick transformative technology thus accelerate strengths lie stimulus presentation seamless integration rich array proprietary software novel paradigms novel algorithms intricate aspects finally simulation feature extraction experimental research evaluation methods ensuring adaptability diverse needs data acquisition custom functionalities connectivity indices computer interfaces channel selection artifact removal analytical tools advanced users
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List of Abbreviations

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