A systematic review on hybrid EEG/fNIRS in brain-computer interface

Z Liu, J Shore, M Wang, F Yuan, A Buss… - … Signal Processing and …, 2021 - Elsevier
As a relatively new field of neurology and computer science, brain computer interface (BCI)
has many established and burgeoning applications across scientific disciplines. Many …

[HTML][HTML] fNIRS-EEG BCIs for motor rehabilitation: a review

J Chen, Y **a, 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) …

[HTML][HTML] Functional near-infrared spectroscopy in non-invasive neuromodulation

C Huo, G Xu, H **e, T Chen, G Shao… - Neural Regeneration …, 2024 - journals.lww.com
Non-invasive cerebral neuromodulation technologies are essential for the reorganization of
cerebral neural networks, which have been widely applied in the field of central neurological …

Motor imagery brain–computer interface rehabilitation system enhances upper limb performance and improves brain activity in stroke patients: A clinical study

W Liao, J Li, X Zhang, C Li - Frontiers in Human Neuroscience, 2023 - frontiersin.org
This study compared the efficacy of Motor Imagery brain-computer interface (MI-BCI)
combined with physiotherapy and physiotherapy alone in ischemic stroke before and after …

Incorporating EEG and fNIRS patterns to evaluate cortical excitability and MI-BCI performance during motor training

Z Wang, L Yang, Y Zhou, L Chen, B Gu… - … on Neural Systems …, 2023 - ieeexplore.ieee.org
As electroencephalography (EEG) is nonlinear and nonstationary in nature, an imperative
challenge for brain-computer interfaces (BCIs) is to construct a robust classifier that can …

An fNIRS-based dynamic functional connectivity analysis method to signify functional neurodegeneration of Parkinson's disease

J Lu, X Zhang, Y Wang, Y Cheng, Z Shu… - … on Neural Systems …, 2023 - ieeexplore.ieee.org
Parkinson's disease (PD) is a prevalent brain disorder, and PD diagnosis is crucial for
treatment. Existing methods for PD diagnosis are mainly focused on behavior analysis, while …

fNIRS-based functional connectivity signifies recovery in patients with disorders of consciousness after DBS treatment

Z Shu, J Wu, H Li, J Liu, J Lu, J Lin, S Liang, J Wu… - Clinical …, 2023 - Elsevier
Objective While deep brain stimulation (DBS) has proved effective for certain patients with
disorders of consciousness (DOC), the working neural mechanism is not clear, the response …

Multimodal neural response and effect assessment during a BCI-based neurofeedback training after stroke

Z Wang, C Cao, L Chen, B Gu, S Liu, M Xu… - Frontiers in …, 2022 - frontiersin.org
Stroke caused by cerebral infarction or hemorrhage can lead to motor dysfunction. The
recovery of motor function is vital for patients with stroke in daily activities. Traditional …

[HTML][HTML] Optimizing SSVEP-based BCI system towards practical high-speed spelling

J Tang, M Xu, J Han, M Liu, T Dai, S Chen, D Ming - Sensors, 2020 - mdpi.com
The brain–computer interface (BCI) spellers based on steady-state visual evoked potentials
(SSVEPs) have recently been widely investigated for their high information transfer rates …

Incorporating EEG and EMG patterns to evaluate BCI-based long-term motor training

Z Wang, B He, Y Zhou, L Chen, B Gu… - … on Human-Machine …, 2022 - ieeexplore.ieee.org
Brain-computer interfaces (BCIs) provide users with a direct communication pathway
between the brain and the peripheral environment. BCI-controlled devices have the …