A review of critical challenges in MI-BCI: From conventional to deep learning methods
Brain-computer interfaces (BCIs) have achieved significant success in controlling external
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …
Harnessing the power of artificial intelligence in otolaryngology and the communication sciences
Use of artificial intelligence (AI) is a burgeoning field in otolaryngology and the
communication sciences. A virtual symposium on the topic was convened from Duke …
communication sciences. A virtual symposium on the topic was convened from Duke …
Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease
Brain signal decoding promises significant advances in the development of clinical brain
computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for …
computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for …
Generating realistic neurophysiological time series with denoising diffusion probabilistic models
Denoising diffusion probabilistic models (DDPMs) have recently been shown to accurately
generate complicated data such as images, audio, or time series. Experimental and clinical …
generate complicated data such as images, audio, or time series. Experimental and clinical …
Scaling law in neural data: Non-invasive speech decoding with 175 hours of eeg data
Brain-computer interfaces (BCIs) hold great potential for aiding individuals with speech
impairments. Utilizing electroencephalography (EEG) to decode speech is particularly …
impairments. Utilizing electroencephalography (EEG) to decode speech is particularly …
A semi-supervised transferable LSTM with feature evaluation for fault diagnosis of rotating machinery
Z Tang, L Bo, X Liu, D Wei - Applied Intelligence, 2022 - Springer
Aiming at the issue of impracticality or costliness of collecting enough labeled signals under
all working conditions, the performance of a method usually suffers a significant loss when …
all working conditions, the performance of a method usually suffers a significant loss when …
Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models
J Berezutskaya, ZV Freudenburg… - Journal of Neural …, 2023 - iopscience.iop.org
Objective. Development of brain–computer interface (BCI) technology is key for enabling
communication in individuals who have lost the faculty of speech due to severe motor …
communication in individuals who have lost the faculty of speech due to severe motor …
Deep neural imputation: A framework for recovering incomplete brain recordings
Neuroscientists and neuroengineers have long relied on multielectrode neural recordings to
study the brain. However, in a typical experiment, many factors corrupt neural recordings …
study the brain. However, in a typical experiment, many factors corrupt neural recordings …
A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages
Advancements in decoding speech from brain activity have focused on decoding a single
language. Hence, the extent to which bilingual speech production relies on unique or …
language. Hence, the extent to which bilingual speech production relies on unique or …
[HTML][HTML] Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants
Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will
enable significant expansion in how numerous brain disorders are treated. Decoding …
enable significant expansion in how numerous brain disorders are treated. Decoding …