Terahertz biophotonics as a tool for studies of dielectric and spectral properties of biological tissues and liquids

OA Smolyanskaya, NV Chernomyrdin… - Progress in Quantum …, 2018 - Elsevier
In this review, we describe dielectric properties of biological tissues and liquids in the
context of terahertz (THz) biophotonics. We discuss a model of the THz dielectric permittivity …

A biomedical perspective in terahertz nano-communications—A review

XX Yin, A Baghai-Wadji, Y Zhang - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Terahertz (THz)-band (0.1~ 10 THz) communications are celebrated to be a crucial enabling
technology for sixth generation (6G) wireless systems that fulfil the stringent requirements of …

A computerized method for automatic detection of schizophrenia using EEG signals

S Siuly, SK Khare, V Bajaj, H Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Diagnosis of schizophrenia (SZ) is traditionally performed through patient's interviews by a
skilled psychiatrist. This process is time-consuming, burdensome, subject to error and bias …

A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG

MNA Tawhid, S Siuly, H Wang, F Whittaker, K Wang… - Plos one, 2021 - journals.plos.org
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent
impairments in social interaction, speech and nonverbal communication, and restricted or …

A new framework for automatic detection of patients with mild cognitive impairment using resting-state EEG signals

S Siuly, ÖF Alçin, E Kabir, A Şengür… - … on Neural Systems …, 2020 - ieeexplore.ieee.org
Mild cognitive impairment (MCI) can be an indicator representing the early stage of
Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major …

Automatic and efficient framework for identifying multiple neurological disorders from EEG signals

MNA Tawhid, S Siuly, K Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The burden of neurological disorders is huge on global health and recognized as major
causes of death and disability worldwide. There are more than 600 neurological diseases …

Classification of alcoholic EEG signals using a deep learning method

L Farsi, S Siuly, E Kabir, H Wang - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Most of the traditional alcoholism detection methods are developed based on machine
learning based methods that cannot extract the deep concealed characteristics of …

Machine learning driven approach towards the quality assessment of fresh fruits using non-invasive sensing

A Ren, A Zahid, A Zoha, SA Shah… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
In agriculture science, accurate information of moisture content (MC) in fruits and vegetables
in an automated fashion can be vital for astute quality and grading evaluation. This demands …

A convolutional long short-term memory-based neural network for epilepsy detection from EEG

MNA Tawhid, S Siuly, T Li - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Epilepsy (EP) is a severe neurological disorder characterized by recurrent seizures, which
increases the risk of death three times more than normal. Currently, electroencephalography …

Sensing and non-destructive testing applications of terahertz spectroscopy and imaging systems: State-of-the-art and state-of-the-practice

W Nsengiyumva, S Zhong, L Zheng… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Terahertz (THz) technology has firmly established itself as an effective sensing and
nondestructive testing (NDT) technique for the detection of substances and physicochemical …