[HTML][HTML] Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction

K Barnova, M Mikolasova, RV Kahankova… - Computers in Biology …, 2023 - Elsevier
Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …

Locked-in syndrome revisited

L Schnetzer, M McCoy, J Bergmann… - Therapeutic …, 2023 - journals.sagepub.com
The locked-in syndrome (LiS) is characterized by quadriplegia with preserved vertical eye
and eyelid movements and retained cognitive abilities. Subcategorization, aetiologies and …

The neuromarketing concept in artificial neural networks: A case of forecasting and simulation from the advertising industry

RR Ahmed, D Streimikiene, ZA Channar, HA Soomro… - Sustainability, 2022 - mdpi.com
This research aims to examine a neural network (artificial intelligence) as an alternative
model to examine the neuromarketing phenomenon. Neuromarketing is comparatively new …

The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions

MA Taha, JA Morren - Muscle & Nerve, 2024 - Wiley Online Library
The rapid advancements in artificial intelligence (AI), including machine learning (ML), and
deep learning (DL) have ushered in a new era of technological breakthroughs in healthcare …

Review of closed-loop brain–machine interface systems from a control perspective

H Pan, H Song, Q Zhang, W Mi - IEEE Transactions on Human …, 2022 - ieeexplore.ieee.org
In recent years, brain–machine interface (BMI) technology has made great progress in
controlling external devices and restoring motor function for people with disabilities. To …

Eye Movement Signal Classification for Developing Human‐Computer Interface Using Electrooculogram

M Thilagaraj, B Dwarakanath… - Journal of …, 2021 - Wiley Online Library
Human‐computer interfaces (HCI) allow people to control electronic devices, such as
computers, mouses, wheelchairs, and keyboards, by bypassing the biochannel without …

Brain–computer interface for amyotrophic lateral sclerosis patients using deep learning network

J Ramakrishnan, D Mavaluru, RS Sakthivel… - Neural Computing and …, 2022 - Springer
Abstract Individuals with Motor Neuron Disease were unable to move from one place to
another because it gradually reduced all the voluntarily movement due to the degeneration …

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

F Pacini, P Dini, L Fanucci - Electronics, 2024 - mdpi.com
Driving a motorized wheelchair is not without risk and requires high cognitive effort to obtain
good environmental perception. Therefore, people with severe disabilities are at risk …

High performance computation of human computer interface for neurodegenerative individuals using eye movements and deep learning technique

J Ramakrishnan, R Doss, T Palaniswamy… - The Journal of …, 2022 - Springer
Disabilities due to neurodegenerative disease are rapidly increasing in number. The need
for rehabilitative devices to achieve a normal and comfortable life in the absence of …

[HTML][HTML] Cerebral palsy-affected individuals' brain-computer interface for wheelchair movement in an indoor environment using mental tasks

J Ramakrishnan - Egyptian Informatics Journal, 2024 - Elsevier
The technique of measuring brain signals or activities by placing electrodes on the scalp of
human beings is called Electroencephalogram (EEG). Brain-computer interface (BCI) is a …