Use of artificial intelligence techniques to assist individuals with physical disabilities

S Pancholi, JP Wachs… - Annual Review of …, 2024 - annualreviews.org
Assistive technologies (AT) enable people with disabilities to perform activities of daily living
more independently, have greater access to community and healthcare services, and be …

An optimal channel selection for EEG-based depression detection via kernel-target alignment

J Shen, X Zhang, X Huang, M Wu, J Gao… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Depression is a mental disorder with emotional and cognitive dysfunction. The main clinical
characteristic of depression is significant and persistent low mood. As reported, depression …

Tumor malignancy detection using histopathology imaging

Y Kurmi, V Chaurasia, N Ganesh - Journal of medical imaging and …, 2019 - Elsevier
Image segmentation and classification in the biomedical imaging field has high worth in
cancer diagnosis and grading. The proposed method classifies the images based on a …

MuLHiTA: A novel multiclass classification framework with multibranch LSTM and hierarchical temporal attention for early detection of mental stress

L Xia, Y Feng, Z Guo, J Ding, Y Li, Y Li… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Mental stress is an increasingly common psychological issue leading to diseases such as
depression, addiction, and heart attack. In this study, an early detection framework based on …

[PDF][PDF] OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals

S Kumar, R Sharma, A Sharma - Peerj Computer Science, 2021 - peerj.com
A human–computer interaction (HCI) system can be used to detect different categories of the
brain wave signals that can be beneficial for neurorehabilitation, seizure detection and sleep …

A GAN guided parallel CNN and transformer network for EEG denoising

J Yin, A Liu, C Li, R Qian, X Chen - IEEE Journal of Biomedical …, 2023 - ieeexplore.ieee.org
Electroencephalography (EEG) signals are often contaminated with various physiological
artifacts, seriously affecting the quality of subsequent analysis. Therefore, removing artifacts …

A comparative study of regression analysis for modelling and prediction of bitcoin price

YK Saheed, RM Ayobami, T Orje-Ishegh - Blockchain Applications in the …, 2022 - Springer
The appraisal of Bitcoin's price-changing characteristics is extremely difficult because of the
nonlinear, nonstationary, effect of multiple uncontrollable factors, and volatile nature. The …

A usability study of low-cost wireless brain-computer interface for cursor control using online linear model

R Abiri, S Borhani, J Kilmarx… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Computer cursor control using electroencephalogram (EEG) signals is a common and well-
studied brain-computer interface (BCI). The emphasis of the literature has been primarily on …

[HTML][HTML] Electroencephalography measures to evaluate the user experience (UX) of chatbots systems: A systematic literature review

JR Leite Filho, TA Coleti, M Morandini - Computers in Human Behavior …, 2024 - Elsevier
Brain activity is a biological signal with unique characteristics that can determine important
patterns for recording and processing. The electroencephalogram (EEG) is the most used …

Separability of motor imagery directions using subject-specific discriminative EEG features

KP Thomas, N Robinson… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Electroencephalogram (EEG) based brain–computer interface (BCI) is an augmented
communication modality between the brain and computer that exclusively depends on …