Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
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 …
review the physical principles of BCIs, and underlying novel approaches for registration …
Feature extraction and classification methods for hybrid fNIRS-EEG brain-computer interfaces
In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …
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 …
focus on human gait studies and apply machine learning techniques. We identified six key …
Machine learning based liver disease diagnosis: A systematic review
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 …
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
This research presents a brain-computer interface (BCI) framework for brain signal
classification using deep learning (DL) and machine learning (ML) approaches on functional …
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
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 …
machine interaction (HMI) and neuroergonomics. The precise assessment of cognitive and …
Analysis of human gait using hybrid EEG-fNIRS-based BCI system: a review
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 …
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) …
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
Functional Near-Infrared Spectroscopy (fNIRS) is an innovative and promising
neuroimaging modality for studying brain activity in real-world environments. While fNIRS …
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 …
physical recovery in a variety of patients. Functional near-infrared spectroscopy (fNIRS) is a …