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

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده ریاضی و علوم کامپیوتر، دانشگاه دامغان، دامغان، ایران.

10.22052/scj.2025.255557.1274

چکیده

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.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

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

نویسندگان [English]

  • Mojgan Katanforoush
  • Reza Pourgholi
School of Mathematics and Computer Science, Damghan University, Damghan, Iran.
چکیده [English]

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.

کلیدواژه‌ها [English]

  • Keywords: Brain-computer interface
  • electroencephalogram
  • preprocessing
  • classification
  • noise reduction