Deep learning approaches for neural decoding across architectures and recording modalities
JA Livezey, JI Glaser - Briefings in bioinformatics, 2021 - academic.oup.com
Decoding behavior, perception or cognitive state directly from neural signals is critical for
brain–computer interface research and an important tool for systems neuroscience. In the …
brain–computer interface research and an important tool for systems neuroscience. In the …
[HTML][HTML] 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 …
machine interaction (HMI) and neuroergonomics. The precise assessment of cognitive and …
Deep recurrent–convolutional neural network for classification of simultaneous EEG–fNIRS signals
H Ghonchi, M Fateh, V Abolghasemi… - IET Signal …, 2020 - Wiley Online Library
Brain–computer interface (BCI) is a powerful system for communicating between the brain
and outside world. Traditional BCI systems work based on electroencephalogram (EEG) …
and outside world. Traditional BCI systems work based on electroencephalogram (EEG) …
[HTML][HTML] Deep learning-based multilevel classification of Alzheimer's disease using non-invasive functional near-infrared spectroscopy
TKK Ho, M Kim, Y Jeon, BC Kim, JG Kim… - Frontiers in aging …, 2022 - frontiersin.org
The timely diagnosis of Alzheimer's disease (AD) and its prodromal stages is critically
important for the patients, who manifest different neurodegenerative severity and …
important for the patients, who manifest different neurodegenerative severity and …
CGAN-rIRN: a data-augmented deep learning approach to accurate classification of mental tasks for a fNIRS-based brain-computer interface
Y Zhang, D Liu, T Li, P Zhang, Z Li… - Biomedical optics express, 2023 - opg.optica.org
Functional near-infrared spectroscopy (fNIRS) is increasingly used to investigate different
mental tasks for brain-computer interface (BCI) control due to its excellent environmental …
mental tasks for brain-computer interface (BCI) control due to its excellent environmental …
[HTML][HTML] Combining robust level extraction and unsupervised adaptive classification for high-accuracy fNIRS-BCI: An evidence on single-trial differentiation between …
Y Zhang, D Liu, P Zhang, T Li, Z Li, F Gao - Frontiers in neuroscience, 2022 - frontiersin.org
Functional near-infrared spectroscopy (fNIRS) is a safe and non-invasive optical imaging
technique that is being increasingly used in brain-computer interfaces (BCIs) to recognize …
technique that is being increasingly used in brain-computer interfaces (BCIs) to recognize …
Classification algorithm for fNIRS-based brain signals using convolutional neural network with spatiotemporal feature extraction mechanism
Y Qin, B Li, W Wang, X Shi, C Peng, Y Lu - Neuroscience, 2024 - Elsevier
Abstract Brain Computer Interface (BCI) is a highly promising human–computer interaction
method that can utilize brain signals to control external devices. BCI based on functional …
method that can utilize brain signals to control external devices. BCI based on functional …
[HTML][HTML] Deep neural network to differentiate internet gaming disorder from healthy controls during stop-signal task: a multichannel near-infrared spectroscopy study
Q Wang, Y Li, H Su, N Zhong, Q Xu… - Biomedical Engineering …, 2023 - degruyter.com
Abstract Internet Gaming Disorder (IGD), as one of worldwide mental health issues, leads to
negative effects on physical and mental health and has attracted public attention. Most …
negative effects on physical and mental health and has attracted public attention. Most …
[HTML][HTML] Novel fNIRS study on homogeneous symmetric feature-based transfer learning for brain–computer interface
K Khalil, U Asgher, Y Ayaz - Scientific reports, 2022 - nature.com
The brain–computer interface (BCI) provides an alternate means of communication between
the brain and external devices by recognizing the brain activities and translating them into …
the brain and external devices by recognizing the brain activities and translating them into …
Multi-class classification of motor execution tasks using fNIRS
F Shamsi, L Najafizadeh - 2019 IEEE Signal Processing in …, 2019 - ieeexplore.ieee.org
This paper investigates the problem of classification of multi-class movement execution
tasks from signals obtained via functional near infrared spectroscopy (fNIRS). fNIRS data is …
tasks from signals obtained via functional near infrared spectroscopy (fNIRS). fNIRS data is …