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Synchronous brain machine interface design using focused time delay networks
(Universiti Malaysia Perlis (UniMAP), 2012-02-27)
Focused time delay neural network based design for a
four-state Brain Machine Interface (BMI) to drive a wheelchair is
analyzed. Motor imagery signals recorded noninvasively using two
bipolar electrodes are used in the ...
Classification of EEG colour imagination tasks based BMI using energy and entropy features
(Universiti Malaysia Perlis (UniMAP), 2012-02-27)
Electroencephalogram (EEG) signals are the
electrophysiological measures of brain function and it is used to
develop a brain machine interface. Brain machine interface
(BMI) system is used to provide a communication and ...
Speaker accent recognition through statistical descriptors of Mel-bands spectral energy and neural network model
(IEEE Conference Publications, 2012-10)
Accent recognition is one of the most important topics in automatic speaker and speaker-independent speech recognition (SI-ASR) systems in recent years. The growth of voice-controlled technologies has becoming part of our ...
Brain machine interface for physically retarded people using colour visual tasks
(IEEE Conference Publications, 2010-05)
A Brain Machine Interface is a communication system which connects the human brain activity to an external device bypassing the peripheral nervous system and muscular system. It provides a communication channel for the ...
Image quality assessment using Elman neural network model
(Universiti Malaysia Perlis (UniMAP), 2012-02-27)
Measurement of visual quality is of fundamental
importance for numerous image and video processing
applications, where the goal of quality assessment algorithms is to
automatically assess the quality of images or videos ...
Classification of vehicle noise comfort level using feedforward neural network
(Universiti Malaysia Perlis (UniMAP), 2012-02-27)
Improved back propagation neural network for the diagnosis of pathological voices
(Association for Advancedment of Modelling and Simulation Techniques in Entreprises (A.M.S.E), 2008)
Most of vocal and voice diseases cause changes in the voice. ENT clinicians use acoustic voice analysis to characterize the pathological voices. Nowadays, voice diseases are increasing dramatically due to unhealthy social ...
BMI using spectral energy entropy for colour visual tasks
(Universiti Malaysia Perlis (UniMAP), 2010-10-16)
EEG signals are the electrophysiological measures
of brain function and it is used to develop a Brain
machine Interface. A Brain machine Interface (BMI)
system is used to provide a communication and
control technology ...
EEG based detection of conductive and sensorineural hearing loss using artificial neural networks
(Advanced Institute of Convergence IT, 2013-05)
In this paper, a simple method has been proposed to distinguish the normal and abnormal hearing subjects (conductive or sensorineural hearing loss) using acoustically stimulated EEG signals. Auditory Evoked Potential (AEP) ...
Discrimination of pathological voices using systole activated neural network
(Noise, Vibration and Comfort Research Group, 2007-11-27)
The discrimination of normal and pathological voices using noninvasive acoustical analysis features helps speech specialits to perform accurate diagnoses of vocal and voices disease. Acoustic analysis is a non-invasive ...