Cybersecurity in neural interfaces: Survey and future trends
With the joint advancement in areas such as pervasive neural data sensing, neural
computing, neuromodulation and artificial intelligence, neural interface has become a …
computing, neuromodulation and artificial intelligence, neural interface has become a …
Cross-Stimulus Transfer Method Using Common Impulse Response for Fast Calibration of SSVEP-Based BCIs
To achieve a high information transfer rate (ITR) in steady-state visual evoked potential
(SSVEP)-based brain-computer interfaces (BCIs), current decoding methods require …
(SSVEP)-based brain-computer interfaces (BCIs), current decoding methods require …
Brain Computer Interface (BCI) Machine Learning Process: A Review
SA Hanafi, HBA Rahman, DAA Pertiwi… - Journal of Electronics …, 2023 - shmpublisher.com
Abstract The abstraction of Brain Computer Interface (BCI) is a communication and control
system that translated human mind thoughts into real-world interaction without any use of …
system that translated human mind thoughts into real-world interaction without any use of …
Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition
Depression recognition based on physiological signals such as functional near-infrared
spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress …
spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress …
Longitudinal assessment of the effects of passive training on stroke rehabilitation using fNIRS technology
For patients with severe conditions such as stroke, passive exercise is commonly used in the
early stages of their rehabilitation training. This study aimed to assess the effect of passive …
early stages of their rehabilitation training. This study aimed to assess the effect of passive …
Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping
R Zhu, Q She, R Li, T Tan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Neurovascular coupling (NVC) provides important insights into the intricate activity of brain
functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have …
functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have …
Temporal-Spatial Conversion Based Sequential Convolutional LSTM Architecture for Detecting Drug Addiction
H Ma, J Yao, J Huang, W Zhang… - IEEE Signal Processing …, 2024 - ieeexplore.ieee.org
Drug addiction (DA) is a long-term and relapsing brain disorder with limited effective
treatments. Electroencephalography (EEG) is a highly promising tool for investigating DA …
treatments. Electroencephalography (EEG) is a highly promising tool for investigating DA …
A multimodal framework based on deep belief network for human locomotion intent prediction
J Li, J Zhang, K Li, J Cao, H Li - Biomedical Engineering Letters, 2024 - Springer
Accurate prediction of human locomotion intent benefits the seamless switching of lower
limb exoskeleton controllers in different terrains to assist humans in walking safely. In this …
limb exoskeleton controllers in different terrains to assist humans in walking safely. In this …
mBGT: Encoding Brain Signals With Multimodal Brain Graph Transformer
C Peng, T Guo, C Xie, X Bai, J Zhou… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Leveraging the multimodal brain signals collected from various electronic devices, such as
electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) data, has …
electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) data, has …
“Jumpingly” Perceive Time Series: Image Generation Approach to Modeling Functional Brain Activation
Y Yao, X Wu, KW Tong, M Zhang, Z Shi… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
This paper presents a novel Linear Mapping Field (LMF) to map time series into two-
dimensional images. The LMF extracts deeper features of fNIRS signals, which makes fNIRS …
dimensional images. The LMF extracts deeper features of fNIRS signals, which makes fNIRS …