Reprint
EEG Signal Processing for Biomedical Applications
Edited by
February 2023
320 pages
- ISBN978-3-0365-6535-4 (Hardback)
- ISBN978-3-0365-6536-1 (PDF)
This book is a reprint of the Special Issue EEG Signal Processing for Biomedical Applications that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary
This reprint focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
EEG; transfer learning; review; decoding; classification; e-textile; head phantom; electroencephalography; conductive material; mental stress; EEG; data analysis; connectivity network; machine Learning; EEG; deep learning; vigilance decrement; sustained attention; mental fatigue; cross-participant; cross-task; task-generic; electroencephalogram; wavelet spectrum; ridge; segmentation; phase connectivity; epilepsy; traumatic brain injury; mental stress; electroencephalography; feature extraction; functional connectivity network; time-frequency features; machine learning; ALS; EEG; classifier; neural; connectivity; frequency-specific; BCI; acupuncture; EEG; dimensionality; neural subspace; latent variables; attractor; adaptive threshold; coherence; functional connectivity; multilayer network; otsu; EEG; functional connectivity; phase locking value; weighted phase lag index; complex Pearson correlation coefficients; transcranial magnetic stimulation; epilepsy; cerebral cortex stimulation; electromagnetic influence; neurostimulation; EEG; brain activity; virtual reality; neuropathic pain; spinal cord injury; fractal dimension; EEG; ERP; speech discrimination; classifier; EEG; epilepsy; seizure detection; machine learning; features; feature selection; motion artifact; electroencephalogram (EEG); functional near-infrared spectroscopy (fNIRS); wavelet packet decomposition (WPD); canonical correlation analysis (CCA); n/a