Ocular artifact elimination from electroencephalography signals: A systematic review
Electroencephalography (EEG) is the signal of intrigue that has immense application in the
clinical diagnosis of various neurological, psychiatric, psychological, psychophysiological …
clinical diagnosis of various neurological, psychiatric, psychological, psychophysiological …
Tunable-Q wavelet transform based multiscale entropy measure for automated classification of epileptic EEG signals
This paper analyzes the underlying complexity and non-linearity of electroencephalogram
(EEG) signals by computing a novel multi-scale entropy measure for the classification of …
(EEG) signals by computing a novel multi-scale entropy measure for the classification of …
Automated diagnosis of glaucoma using empirical wavelet transform and correntropy features extracted from fundus images
S Maheshwari, RB Pachori… - IEEE journal of …, 2016 - ieeexplore.ieee.org
Glaucoma is an ocular disorder caused due to increased fluid pressure in the optic nerve. It
damages the optic nerve and subsequently causes loss of vision. The available scanning …
damages the optic nerve and subsequently causes loss of vision. The available scanning …
Application of entropy measures on intrinsic mode functions for the automated identification of focal electroencephalogram signals
The brain is a complex structure made up of interconnected neurons, and its electrical
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
Epilepsy detection from EEG signals: a review
A Sharmila - Journal of medical engineering & technology, 2018 - Taylor & Francis
Over many decades, research is being attempted for the detection of epileptic seizure to
support for automatic diagnosis system to help clinicians from burdensome work. In this …
support for automatic diagnosis system to help clinicians from burdensome work. In this …
A novel approach for automated detection of focal EEG signals using empirical wavelet transform
A Bhattacharyya, M Sharma, RB Pachori… - Neural Computing and …, 2018 - Springer
The determination of epileptogenic area is a prime task in presurgical evaluation. The
seizure activity can be prevented by operating the affected areas by clinical surgery. In this …
seizure activity can be prevented by operating the affected areas by clinical surgery. In this …
Automated diagnosis of epilepsy using key-point-based local binary pattern of EEG signals
The electroencephalogram (EEG) signals are commonly used for diagnosis of epilepsy. In
this paper, we present a new methodology for EEG-based automated diagnosis of epilepsy …
this paper, we present a new methodology for EEG-based automated diagnosis of epilepsy …
Emotion recognition from EEG signals using empirical mode decomposition and second-order difference plot
N Salankar, P Mishra, L Garg - Biomedical Signal Processing and Control, 2021 - Elsevier
Emotion recognition from electroencephalography (EEG) signals is a very cost-effective
method to monitor the general well-being of an individual, an employee of an organization …
method to monitor the general well-being of an individual, an employee of an organization …
An integrated index for the identification of focal electroencephalogram signals using discrete wavelet transform and entropy measures
The dynamics of brain area influenced by focal epilepsy can be studied using focal and non-
focal electroencephalogram (EEG) signals. This paper presents a new method to detect …
focal electroencephalogram (EEG) signals. This paper presents a new method to detect …
Automated detection of focal EEG signals using features extracted from flexible analytic wavelet transform
Epilepsy is a neurological disease which is difficult to diagnose accurately. An authentic
detection of focal epilepsy will help the clinicians to provide proper treatment for the patients …
detection of focal epilepsy will help the clinicians to provide proper treatment for the patients …