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Development of EEG data acquisition device by using single board computer
(Inderscience Enterprises Ltd., 2013)
Electroencephalogram (EEG) plays a vital role in several medical diagnosis (brain tumour detection, Alzheimer disease, epilepsy, etc.), engineering applications (emotion detection, drowsiness detection, stress assessment, ...
Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
(IEEE Conference Publications, 2013-09)
Emotion recognition using physiological signals is one of the key research areas in Human Computer Interaction (HCI). In this work, we identify the six basic emotional states (Happiness, sadness, fear, surprise, disgust ...
Classification of emotional States from electrocardiogram signals: a non-linear approach based on hurst
(BioMed Central, 2013-05)
Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) ...
FCM clustering of emotional stress using ECG features
(IEEE Conference Publications, 2013-04)
Emotional stress refers to the inducement of stress due to the consequence of a continuous experience of negative emotions (sad, anger, fear and disgust). This work aims to investigate the effect of negative emotions in ...
Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
(IEEE Conference Publications, 2013-04)
Driver drowsiness is one of the major causes for several road accidents over the world. In this study, Electroencephalogram (EEG) signals were acquired using 14 electrodes from 50 subjects. All the electrodes are placed ...
Subtractive fuzzy classifier based driver distraction levels classification using EEG
(Society of Physical Therapy Science, 2013)
[Purpose] In earlier studies of driver distraction, researchers classified distraction into two levels (not distracted, and distracted). This study classified four levels of distraction (neutral, low, medium, high). [Subjects ...
Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
(Society of Physical Therapy Science, 2013-06)
[Purpose] Intelligent emotion assessment systems have been highly successful in a variety of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to assess five different human emotions ...
Wavelet packet transform based driver distraction level classification using EEG
(Mathematical Problems in Engineering, 2013)
We classify the driver distraction level (neutral, low, medium, and high) based on different wavelets and classifiers using wireless electroencephalogram (EEG) signals. 50 subjects were used for data collection using 14 ...