Automatic epilepsy detection from EEG introducing a new edge weight method in the complex network

S Supriya, S Siuly, Y Zhang - Electronics Letters, 2016 - Wiley Online Library
Automatic diagnosis of epilepsy using electroencephalogram (EEG) signals is a hot topic in
medical community as traditional diagnosis relies on tedious visual screening by highly …

Early diagnosis of glaucoma using multi-feature analysis and DBN based classification

F Ajesh, R Ravi, G Rajakumar - Journal of Ambient Intelligence and …, 2021 - Springer
In this new era, the advancement towards the diagnosis of disease in its early-stage has
improved. The medical field is not only equipped with the new generation devices but also …

Analysis of physiological signals using state space correlation entropy

RK Tripathy, S Deb, S Dandapat - Healthcare technology letters, 2017 - Wiley Online Library
In this letter, the authors propose a new entropy measure for analysis of time series. This
measure is termed as the state space correlation entropy (SSCE). The state space …

[HTML][HTML] Efficient software platform TFSAP 7.1 and Matlab package to compute Time–Frequency Distributions and related Time-Scale methods with extraction of signal …

B Boashash, S Ouelha - SoftwareX, 2018 - Elsevier
This article describes the source code used in the TFSAP toolbox (Boashash, 2016). It is
extended with additional functions to allow reproducible research as presented in Boashash …

Comparison of fuzzy output optimization with expectation maximization algorithm and its modification for epilepsy classification

SK Prabhakar, H Rajaguru - … of International Conference on Cognition and …, 2018 - Springer
Due to the sudden and hyper excessive electrical discharges occurring in a specific group of
cells in brain, a seizure is caused. The occurrence of the seizure can be in different regions …

Selection of optimum frequency bands for detection of epileptiform patterns

P Swami, M Bhatia, M Tripathi… - Healthcare …, 2019 - Wiley Online Library
The significant research effort in the domain of epilepsy has been directed toward the
development of an automated seizure detection system. In their usage of the …

A systematic mapping of feature extraction and feature selection methods of electroencephalogram signals for neurological diseases diagnostic assistance

WF de Almeida, CA de Moraes Lima… - IEEE Latin America …, 2021 - ieeexplore.ieee.org
Electroencephalogram (EEG) is a non-invasive tool used to monitor the electrical activities of
the brain. EEG signal analysis has several applications in the medical field. It is widely used …

Epileptic seizure detection employing cross-hyperbolic stockwell transform

NR Choudhury, SS Roy, A Pal… - … on Research in …, 2018 - ieeexplore.ieee.org
In the present work, cross Hyperbolic S-transform (XHST) is proposed as a novel feature
extraction technique from EEG signals for automated detection of epilepsy. XHST is …

A Space-Scale Estimation Method based on continuous wavelet transform for coastal wetland ecosystem services in Liaoning Province, China

B Sun, L Cui, W Li, X Kang, M Zhang - Ocean & Coastal Management, 2018 - Elsevier
Wetland ecosystem services are attracting increasing public attention. It is crucial that
management decisions for wetland ecosystem services quantify the economic value of the …

EM based non-linear regression and singular value decomposition for epilepsy classification

SK Prabhakar, H Rajaguru - 2017 6th ICT International Student …, 2017 - ieeexplore.ieee.org
One of the major disorders affecting the human brain is epilepsy and it impairs the daily lives
of the patients. Epilepsy is caused by sudden and random incidence of seizures. One of the …