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Automated system for stress evaluation based on EEG signal: A prospective review
(Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
This paper reviews the issues related to the automated system for stress evaluation based on brain signal. It describes the current status of mental health especially in Malaysia. The anatomy of stress is briefly discussed ...
Moving vehicle noise classification using backpropagation algorithm
(Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)
The hearing impaired is afraid of walking along a street and living a life alone. Since it is difficult for hearing impaired to hear and judge sound information and they often encounter risky situations while they are in ...
Vowel recognition based on frequency ranges determined by bandwidth approach
(Institute of Eelectrical and Electronics Engineering (IEEE), 2009-07)
Automatic speech recognition (ASR) has made great strides with the development of digital signal processing hardware and software especially using English as the language of choice. In this paper, a new feature extraction ...
Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks
(Institute of Electrical and Electronics Engineering (IEEE), 2007-11-25)
Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients ...
Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network
(Inderscience Publisher, 2011)
This paper proposes a feature extraction method based on time-domain energy variation for the detection of vocal fold pathology. In this work, two different vocal fold problems (vocal fold paralysis and edema) are taken ...
Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders
(SpringerLink, 2008-06-25)
Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...
Supervised neural network classifier for voice pathology
(Kongu Engineering College, 2008-01-03)
The classification of normal and pathological voices using noninvasive acoustical analysis features helps speech specialist to perform accurate diagnoses of vocal and voice disease. Acoustic analysis is a non-invasive ...
Application of feedforward neural network for the classification of pathological voices
(Universiti Teknologi MARA (UiTM), 2007-03-09)
This paper present the application of feed forward neural network for the classification of pathological voices based on the on the acoustic analysis and EGG features. Acoustic analysis is a non-invasive technique based ...