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논문 기본 정보

자료유형
학술저널
저자정보
A. Joshua Jafferson (SRM Institute of Science and Technology) Vijayakumar Ponnusamy (SRM Institute of Science and Technology) Jovana Jovic (Belgrade Metropolitan University) Miroslav Trajanovic (University of Nis)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.10 No.3
발행연도
2021.6
수록면
183 - 188 (6page)
DOI
10.5573/IEIESPC.2021.10.3.183

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초록· 키워드

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Paralyzed people have difficulty communicating with the world for their daily basic needs, and their caretakers have difficulty understanding their needs. The development and implementation of a handheld device-based brain-computer interface system with machine learning will solve the above problem. On the other hand, a simple handheld device cannot satisfy the computation of hunger ML algorithms and will have more latency. This paper overcomes the limitations of the above by processing the data in the cloud. The handheld device reads and preprocesses the electroencephalogram (EEG) data and forwards it to the IoT-based Cloud server. The cloud server applies the machine-learning algorithm and classifies it in the text, representing the word thought by the user. This text information result is sent back to the handheld device and intimates the caretaker to know the patient"s needs. The evaluation result of the proposed system for ten words to deal with the basic needs highlights the feasibility of implementing it in practice.

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Abstract
1. Introduction
2. Related Work
3. Materials and Methods
4. Performance Analysis and Result Discussion
5. Opportunities and Challenges
6. Conclusion
References

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