Signal Processing for Brain-Computer Interfaces

ISBN 10: 3725805202 / ISBN 13: 9783725805204

Published by MDPI AG, 2024

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - With the astounding ability to capture a wealth of brain signals, Brain-Computer Interfaces (BCIs) have the potential to revolutionize humans' quality of life by processing these brain signals for controlling external devices. Being an emerging and innovative field, BCIs offer numerous applications in various fields of life, including robotics, education, prosthetics, security and communication technologies. Processing neuro-physiological signals, a major component of BCIs, involves further procedures of (1) noise removal, (2) feature extraction and (3) classification. Pre-processed signals are subject to various noises, including power line noises, physiological noises, motion artifacts and interference noises. These noises can affect the efficiency of the entire BCI procedure. For this reason, noise removal algorithms are utilized for noise removal or reduction. Next, the process of feature extraction begins, in which algorithms are used to acquire relevant task-based features. This phase acquires data based on spectral, spatial and temporal domains. The last step for signal processing is classification, whereby the acquired and processed features are converted into viable commands, which ultimately control external devices. This reprint focuses particularly on these three signal-processing techniques.

Seller Inventory # 9783725805204

Bibliographic Details

• Title: Signal Processing for Brain-Computer Interfaces
• Publisher: MDPI AG
• Publication Date: 2024
• Language: English
• ISBN 10: 3725805202
• ISBN 13: 9783725805204
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 18D millimeters 250 millimeters width by 175 millimeters height by 18 millimeters depth
• Weight: 705 grams

About this title

Synopsis

With the astounding ability to capture a wealth of brain signals, Brain-Computer Interfaces (BCIs) have the potential to revolutionize humans' quality of life by processing these brain signals for controlling external devices. Being an emerging and innovative field, BCIs offer numerous applications in various fields of life, including robotics, education, prosthetics, security and communication technologies. Processing neuro-physiological signals, a major component of BCIs, involves further procedures of (1) noise removal, (2) feature extraction and (3) classification. Pre-processed signals are subject to various noises, including power line noises, physiological noises, motion artifacts and interference noises. These noises can affect the efficiency of the entire BCI procedure. For this reason, noise removal algorithms are utilized for noise removal or reduction. Next, the process of feature extraction begins, in which algorithms are used to acquire relevant task-based features. This phase acquires data based on spectral, spatial and temporal domains. The last step for signal processing is classification, whereby the acquired and processed features are converted into viable commands, which ultimately control external devices. This reprint focuses particularly on these three signal-processing techniques.