Designing a brain-computer interface with the aim of classifying features and enhancing the signal-to-noise ratio

Articles in Press

Document Type : Original Article

Authors

1 School of Mathematics and Computer Science, Damghan University, Damghan, Iran.

2 Faculty of Mathematics and Computer Science, Damghan University, Damghan, Iran.

Abstract

Abstract: A brain-computer interface is a hardware and software communication system through which the user will be able to control computers and external devices using only their brain activities.Signal processing algorithm is the most important part of a brain-computer interface and includes the steps of data acquisition, preprocessing or signal amplification, feature extraction and classification.The aim of this research is to design the signal processing algorithm of a brain-computer interface and also to improve its performance using noise reduction methods.Considering the importance of feature extraction and classification steps, we must choose appropriate methods in these steps.
First, brain-computer system, signal processing algorithm and human nervous system and brain, electroencephalogram signal have been investigated. Then the pre-processing step and noise reduction techniques, the feature extraction step and the classification step and different classifiers with their applications and characteristics have been introduced. Finally, a new method based on channel selection using the placement of electrodes has been presented, which reduces noise and significantly increases the performance of the algorithm, and the use of this method increases the accuracy of the system.

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Main Subjects

Soft Computing Journal

Articles in Press, Accepted Manuscript
Available Online from 02 July 2025

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History

  • Receive Date: 01 October 2024
  • Revise Date: 01 June 2025
  • Accept Date: 12 June 2025

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