AI Medical Compendium Journal:
Journal of integrative neuroscience

Showing 21 to 26 of 26 articles

Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques.

Journal of integrative neuroscience
Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accu...

Statistical algorithms for emotion classification via functional connectivity.

Journal of integrative neuroscience
Pattern recognition algorithms decode emotional brain states by using functional connectivity measures which are extracted from EEG signals as input to the statistical classifiers. An open-access EEG dataset for emotional state analysis is used to cl...

Application of a brain-computer interface for person authentication using EEG responses to photo stimuli.

Journal of integrative neuroscience
In this paper, a personal authentication system that can effectively identify individuals by generating unique electroencephalogram signal features in response to self-face and non-self-face photos is presented. To achieve performance stability, a se...

Speech emotion recognition based on brain and mind emotional learning model.

Journal of integrative neuroscience
Speech emotion recognition is a challenging obstacle to enabling communication between humans and machines. The present study introduces a new model of speech emotion recognition based on the relationship between the human brain and mind. According t...

Relative wave energy-based adaptive neuro-fuzzy inference system for estimation of the depth of anaesthesia.

Journal of integrative neuroscience
The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent model...

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

Journal of integrative neuroscience
Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of f...