Brain and behavior computing /
edited by Mridu Sahu and G.R. Sinha.
- First edition.
- 1 online resource (xxvii, 400 pages) : color illustrations
Simulation tools for brain signal analysis -- Processing techniques and analysis of brain sensor data using electroencephalography (EEG) -- Application of machine learning techniques in electroencephalography signals -- Revolution of brain computer interface : an introduction -- Signal modelling using spatial filtering and matching wavelet feature extraction for classification of brain activity pattern -- Study and analysis of visual P300 speller on neurotypical subjects -- Effective brain-computer interface based on the adaptive-rate processing and classification of motor imagery tasks -- EEG based BCI systems for neurorehabilitation applications -- Scalp EEG classification using TQWT-entropy features for epileptic seizure detection -- An efficient single-trial classification approach for Devanagari script-based visual P300 speller using knowledge distillation and transfer learning -- Deep learning for brain image analysis -- Evolutionary optimization based two dimensional elliptical fir filters for skull stripping in brain imaging and disorder detection -- EEG based neurofeedback game for enhancing the focus level -- Detecting K-complexes in brain signals using WSST-2 detoks -- Directed functional brain networks : characterisation of information flow direction during cognitive function using non-linear granger causality -- Student behavior modeling and context acquisition : a ubiquitous learning framework.
"Brain and Behavior Computing provides an insight into the functions of the human brain. This book provides emphasis on brain and behavior computing with different modalities available such as signal and image processing, data science, statistics, distributed computing including fundamentals, model, algorithms, case studies, and research scope. It further illustrates brain signals sources and how the brain signal can process, manipulate and transform in different domains to extract information about the physiological condition of the brain. Emphasis is on real challenges in brain signal processing for variety of applications for analysis, classification, clustering and identification"--