Classification of epileptic EEG signals using PSO based artificial neural network and tunable-Q wavelet transform

ST George, MSP Subathra, NJ Sairamya… - Biocybernetics and …, 2020 - Elsevier
Epilepsy is a widely spread neurological disorder caused due to the abnormal excessive
neural activity which can be diagnosed by inspecting the electroencephalography (EEG) …

Emerging energy-efficient biosignal-dedicated circuit techniques: A tutorial brief

S Zhao, C Fang, J Yang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
High spatiotemporal resolution biosignal that is vital for biomedical applications results in an
information bottleneck that poses challenges for their transferring and processing. The …

Detection of ADHD from EEG signals using different entropy measures and ANN

R Catherine Joy, S Thomas George… - Clinical EEG and …, 2022 - journals.sagepub.com
Attention deficit hyperactivity disorder (ADHD) is a prevalent behavioral, cognitive,
neurodevelopmental pediatric disorder. Clinical evaluations, symptom surveys, and …

Detection of lung cancers from ct images using a deep CNN architecture in layers through ML

K Singh, Y Singh, D Barak, M Yadav - AI and IoT-Based …, 2023 - igi-global.com
Lung inflammation is caused by the development of cancer cells. As the frequency of cancer
rises, men and women are dying at a higher rate. With malignancy, cancerous cells multiply …

Extracting epileptic features in EEGs using a dual-tree complex wavelet transform coupled with a classification algorithm

W Al-Salman, Y Li, P Wen, FS Miften, AY Oudah… - Brain Research, 2022 - Elsevier
The detection of epileptic seizures from electroencephalogram (EEG) signals is traditionally
performed by clinical experts through visual inspection. It is a long process, is error prone …

A new approach for automatic detection of focal EEG signals using wavelet packet decomposition and quad binary pattern method

NJ Sairamya, MSP Subathra… - … Signal Processing and …, 2021 - Elsevier
A comprehensive feature representation for electroencephalogram (EEG) signal to achieve
effective epileptic focus localization using a one-dimensional quad binary pattern (QBP) is …

A machine learning-based method to identify bipolar disorder patients

J Mateo-Sotos, AM Torres, JL Santos… - Circuits, Systems, and …, 2022 - Springer
Bipolar disorder is a serious psychiatric disorder characterized by periodic episodes of
manic and depressive symptomatology. Due to the high percentage of people suffering from …

Multibit local neighborhood difference pattern optimization for seizure detection of west syndrome EEG signals

W Zhang, D Wu, J Cao, L Jiang… - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
West syndrome is a common age-related epileptic encephalopathy, which seriously
threatens children's intellectual development. The accurate detection of seizures in the …

Local Pattern Transformation-Based convolutional neural network for sleep stage scoring

H Zan, A Yildiz - Biomedical Signal Processing and Control, 2023 - Elsevier
Sleep stage scoring is essential for the diagnosis and treatment of sleep disorders.
However, manual sleep scoring is a tedious, time-consuming, and subjective task …

Automatic localization of seizure onset zone from high-frequency SEEG signals: A preliminary study

L **ao, C Li, Y Wang, J Chen, W Si… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Objective: Stereoelectroencephalogram (SEEG) has been widely adapted to detect the
electrical activity of patients with epilepsy. Due to the low-quality, large-amount, high …