[HTML][HTML] Concurrent fNIRS and EEG for brain function investigation: a systematic, methodology-focused review
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
[HTML][HTML] Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction
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 …
brain and the computer. Brain signals contain valuable information about the mental state …
[HTML][HTML] Optical imaging and spectroscopy for the study of the human brain: status report
This report is the second part of a comprehensive two-part series aimed at reviewing an
extensive and diverse toolkit of novel methods to explore brain health and function. While …
extensive and diverse toolkit of novel methods to explore brain health and function. While …
A survey of human gait-based artificial intelligence applications
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 …
Review on patient-cooperative control strategies for upper-limb rehabilitation exoskeletons
Technology-supported rehabilitation therapy for neurological patients has gained increasing
interest since the last decades. The literature agrees that the goal of robots should be to …
interest since the last decades. The literature agrees that the goal of robots should be to …
[HTML][HTML] fNIRS-EEG BCIs for motor rehabilitation: a review
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) …
[HTML][HTML] 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 …
Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: a review
With the emergence of an increasing number of functional near-infrared spectroscopy
(fNIRS) devices, the significant deterioration in measurement caused by motion artifacts has …
(fNIRS) devices, the significant deterioration in measurement caused by motion artifacts has …
Advanced electrode technologies for noninvasive brain–computer interfaces
Brain–computer interfaces (BCIs) have garnered significant attention in recent years due to
their potential applications in medical, assistive, and communication technologies. Building …
their potential applications in medical, assistive, and communication technologies. Building …
Driving drowsiness detection using spectral signatures of EEG-based neurophysiology
Introduction: Drowsy driving is a significant factor causing dire road crashes and casualties
around the world. Detecting it earlier and more effectively can significantly reduce the lethal …
around the world. Detecting it earlier and more effectively can significantly reduce the lethal …