Combining EEG signal processing with supervised methods for Alzheimer's patients classification
Abstract Background Alzheimer's Disease (AD) is a neurodegenaritive disorder
characterized by a progressive dementia, for which actually no cure is known. An early …
characterized by a progressive dementia, for which actually no cure is known. An early …
Neurofeedback tunes scale-free dynamics in spontaneous brain activity
Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the
regularity of their fluctuations: low values representing more random (decorrelated) while …
regularity of their fluctuations: low values representing more random (decorrelated) while …
A novel wavelet selection method for seismic signal intelligent processing
Wavelet transform is a widespread and effective method in seismic waveform analysis and
processing. Choosing a suitable wavelet has also aroused many scholars' research interest …
processing. Choosing a suitable wavelet has also aroused many scholars' research interest …
Electroencephalogram analysis with extreme learning machine as a supporting tool for classifying acute ischemic stroke severity
Stroke is one of the highest causes of death in adults and disability in Indonesia, even in the
world. Therefore, it is necessary to diagnose stroke in the early stage and give accurate …
world. Therefore, it is necessary to diagnose stroke in the early stage and give accurate …
Alcoholism classification based on eeg data using independent component analysis (ica), wavelet de-noising and probabilistic neural network (pnn)
NT Rachman, H Tjandrasa… - … International seminar on …, 2016 - ieeexplore.ieee.org
Alcoholism is a clinical symptom characterized by a tendency to drink more alcohol than
planned or commonly called alcoholics. Alcoholics will suffer the damage in some parts of …
planned or commonly called alcoholics. Alcoholics will suffer the damage in some parts of …
[HTML][HTML] Wavelet Decomposition and Feedforward Neural Network for Classification of Acute Ischemic Stroke based on Electroencephalography
Wavelet Decomposition and Feedforward Neural Network for Classification of Acute Ischemic
Stroke based on Electroencephalography title Title Author Issue Keywords Current Issue : Vol …
Stroke based on Electroencephalography title Title Author Issue Keywords Current Issue : Vol …
Brainwave classification without the help of limb movement and any stimulus for character-writing application
Abstract Recently, Brain-Computer Interfaces (BCIs) have been extensively popular for
employing Electroencephalography (EEG) signals to control devices with different …
employing Electroencephalography (EEG) signals to control devices with different …
Classification of EEG Signal using Independent Component Analysis and Discrete Wavelet Transform based on Linear Discriminant Analysis
Abstract Autism Spectrum Disorder (ASD) is a neurodevelopment syndrome decreasing
sufferers' social interaction, communication skills, and emotional expression. Autism …
sufferers' social interaction, communication skills, and emotional expression. Autism …
Overt mental stimuli of brain signal for person identification
MW Rahman, M Gavrilova - 2016 International Conference on …, 2016 - ieeexplore.ieee.org
Cybersecurity is an important and challenging issue faced by governments, financial
institutions and ordinary citizens alike. Secure identification is needed for accessing …
institutions and ordinary citizens alike. Secure identification is needed for accessing …
Emerging EEG and kinect face fusion for biometrie identification
MW Rahman, ML Gavrilova - 2017 IEEE Symposium Series on …, 2017 - ieeexplore.ieee.org
Multimodal biometrie systems attract attention as security systems due to their ability to
eliminate the limitations of unimodal systems, such as noisy data, intra-elass variability, inter …
eliminate the limitations of unimodal systems, such as noisy data, intra-elass variability, inter …