Decoding Handwriting Trajectories from Intracortical Brain Signals for Brain‐to‐Text Communication
Sign Up to like & getrecommendations! Published in 2025 at "Advanced Science"
DOI: 10.1002/advs.202505492
Abstract: The potential to decode handwriting trajectories from brain signals has yet to be fully explored in clinical brain‐computer interfaces (BCIs). Here, intracortical neural signals are recorded from a paralyzed individual during attempted handwriting of complex… read more here.
Keywords: brain; handwriting trajectories; decoding handwriting; brain signals ... See more keywords
Nonparametric collective spectral density estimation with an application to clustering the brain signals.
Sign Up to like & getrecommendations! Published in 2018 at "Statistics in medicine"
DOI: 10.1002/sim.7972
Abstract: In this paper, we develop a method for the simultaneous estimation of spectral density functions (SDFs) for a collection of stationary time series that share some common features. Due to the similarities among the SDFs,… read more here.
Keywords: brain signals; estimation; basis; spectral density ... See more keywords
A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Medical Systems"
DOI: 10.1007/s10916-018-1020-8
Abstract: The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept… read more here.
Keywords: emotion; class includes; brain signals; brain ... See more keywords
Learning dynamics of electrophysiological brain signals during human fear conditioning
Sign Up to like & getrecommendations! Published in 2021 at "NeuroImage"
DOI: 10.1016/j.neuroimage.2020.117569
Abstract: Electrophysiological studies in rodents allow recording neural activity during threats with high temporal and spatial precision. Although fMRI has helped translate insights about the anatomy of underlying brain circuits to humans, the temporal dynamics of… read more here.
Keywords: fear conditioning; brain signals; electrophysiological brain; brain ... See more keywords
Wheelchair Free Hands Navigation Using Robust DWT_AR Features Extraction Method With Muscle Brain Signals
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2984538
Abstract: Researchers try to help disabled people by introducing some innovative applications to support and assess their life. The Brain-Computer Interface (BCI) application that covers both hardware and software models, is considered in this work. BCI… read more here.
Keywords: hands navigation; wheelchair free; method; brain signals ... See more keywords
mBGT: Encoding Brain Signals With Multimodal Brain Graph Transformer
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Consumer Electronics"
DOI: 10.1109/tce.2024.3425478
Abstract: Leveraging the multimodal brain signals collected from various electronic devices, such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) data, has been regarded as a promising technique for automated brain disease diagnosis. Existing studies on… read more here.
Keywords: brain; brain graph; brain signals; graph transformer ... See more keywords
Tensorpac: An open-source Python toolbox for tensor-based phase-amplitude coupling measurement in electrophysiological brain signals
Sign Up to like & getrecommendations! Published in 2020 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1008302
Abstract: Despite being the focus of a thriving field of research, the biological mechanisms that underlie information integration in the brain are not yet fully understood. A theory that has gained a lot of traction in… read more here.
Keywords: phase amplitude; tensorpac open; brain signals; electrophysiological brain ... See more keywords
EEG brain signals to detect the sleep health of a driver: An automated framework system based on deep learning
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Human Neuroscience"
DOI: 10.3389/fnhum.2022.915276
Abstract: Mental fatigue is complex disorganization that affects the human being's efficiency in work and daily activities (e.g., driving, exercising). Encephalography is routinely used to discern this fatigue. Several automatic procedures have deployed conventional approaches to… read more here.
Keywords: neural network; brain signals; eeg brain; convolutional neural ... See more keywords