Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states

AE Hramov, VA Maksimenko, AN Pisarchik - Physics Reports, 2021 - Elsevier
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

Feature extraction and classification methods for hybrid fNIRS-EEG brain-computer interfaces

KS Hong, MJ Khan, MJ Hong - Frontiers in human neuroscience, 2018 - frontiersin.org
In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …

A survey of human gait-based artificial intelligence applications

EJ Harris, IH Khoo, E Demircan - Frontiers in Robotics and AI, 2022 - frontiersin.org
We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …

Machine learning based liver disease diagnosis: A systematic review

RA Khan, Y Luo, FX Wu - Neurocomputing, 2022 - Elsevier
The computer-based approach is required for the non-invasive detection of chronic liver
diseases that are asymptomatic, progressive, and potentially fatal in nature. In this study, we …

Analyzing classification performance of fNIRS-BCI for gait rehabilitation using deep neural networks

H Hamid, N Naseer, H Nazeer, MJ Khan, RA Khan… - Sensors, 2022 - mdpi.com
This research presents a brain-computer interface (BCI) framework for brain signal
classification using deep learning (DL) and machine learning (ML) approaches on functional …

Enhanced accuracy for multiclass mental workload detection using long short-term memory for brain–computer interface

U Asgher, K Khalil, MJ Khan, R Ahmad, SI Butt… - Frontiers in …, 2020 - frontiersin.org
Cognitive workload is one of the widely invoked human factors in the areas of human–
machine interaction (HMI) and neuroergonomics. The precise assessment of cognitive and …

Analysis of human gait using hybrid EEG-fNIRS-based BCI system: a review

H Khan, N Naseer, A Yazidi, PK Eide… - Frontiers in Human …, 2021 - frontiersin.org
Human gait is a complex activity that requires high coordination between the central nervous
system, the limb, and the musculoskeletal system. More research is needed to understand …

fNIRS-EEG BCIs for motor rehabilitation: a review

J Chen, Y Xia, X Zhou, E Vidal Rosas, A Thomas… - Bioengineering, 2023 - mdpi.com
Motor impairment has a profound impact on a significant number of individuals, leading to a
substantial demand for rehabilitation services. Through brain–computer interfaces (BCIs) …

Interdisciplinary views of fNIRS: Current advancements, equity challenges, and an agenda for future needs of a diverse fNIRS research community

EJ Doherty, CA Spencer, J Burnison, M Čeko… - Frontiers in Integrative …, 2023 - frontiersin.org
Functional Near-Infrared Spectroscopy (fNIRS) is an innovative and promising
neuroimaging modality for studying brain activity in real-world environments. While fNIRS …

fNIRS evidence for distinguishing patients with major depression and healthy controls

J Chao, S Zheng, H Wu, D Wang… - … on Neural Systems …, 2021 - ieeexplore.ieee.org
In recent years, major depressive disorder (MDD) has been shown to negatively impact
physical recovery in a variety of patients. Functional near-infrared spectroscopy (fNIRS) is a …