[HTML][HTML] A review of electroencephalogram signal processing methods for brain-controlled robots
Z Huang, M Wang - Cognitive Robotics, 2021 - Elsevier
Brain-computer interface (BCI) based on electroencephalogram (EEG) signals can provide a
way for human to communicate with the outside world. This approach is independent of the …
way for human to communicate with the outside world. This approach is independent of the …
Task-dependent fractal patterns of information processing in working memory
We applied detrended fluctuation analysis, power spectral density, and eigenanalysis of
detrended cross-correlations to investigate fMRI data representing a diurnal variation of …
detrended cross-correlations to investigate fMRI data representing a diurnal variation of …
Toward asynchronous EEG-based BCI: Detecting imagined words segments in continuous EEG signals
T Hernández-Del-Toro, CA Reyes-García… - … Signal Processing and …, 2021 - Elsevier
Abstract An asynchronous Brain–Computer Interface (BCI) based on imagined speech is a
tool that allows to control an external device or to emit a message at the moment the user …
tool that allows to control an external device or to emit a message at the moment the user …
Detection of EEG K-complexes using fractal dimension of time frequency images technique coupled with undirected graph features
W Al-Salman, Y Li, P Wen - Frontiers in Neuroinformatics, 2019 - frontiersin.org
K-complexes identification is a challenging task in sleep research. The detection of k-
complexes in electroencephalogram (EEG) signals based on visual inspection is time …
complexes in electroencephalogram (EEG) signals based on visual inspection is time …
K-complexes detection in EEG signals using fractal and frequency features coupled with an ensemble classification model
ALS Wessam, Y Li, P Wen - Neuroscience, 2019 - Elsevier
K-complexes are important transient bio-signal waveforms in sleep stage 2. Detecting k-
complexes visually requires a highly qualified expert. In this study, an efficient method for …
complexes visually requires a highly qualified expert. In this study, an efficient method for …
Exoskeleton training modulates complexity in movement patterns and cortical activity in able-bodied volunteers
Robot-aided gait training (RAGT) plays a crucial role in providing high-dose and high-
intensity task-oriented physical therapy. The human-robot interaction during RAGT remains …
intensity task-oriented physical therapy. The human-robot interaction during RAGT remains …
EEG fractal analysis reflects brain impairment after stroke
M Rubega, E Formaggio, F Molteni, E Guanziroli… - Entropy, 2021 - mdpi.com
Stroke is the commonest cause of disability. Novel treatments require an improved
understanding of the underlying mechanisms of recovery. Fractal approaches have …
understanding of the underlying mechanisms of recovery. Fractal approaches have …
Detection of hypoglycemia using measures of EEG complexity in type 1 diabetes patients
Previous literature has demonstrated that hypoglycemic events in patients with type 1
diabetes (T1D) are associated with measurable scalp electroencephalography (EEG) …
diabetes (T1D) are associated with measurable scalp electroencephalography (EEG) …
An efficient approach for EEG sleep spindles detection based on fractal dimension coupled with time frequency image
Detection of the characteristics of the sleep stages, such as sleep spindles and K-complexes
in EEG signals, is a challenging task in sleep research as visually detecting them requires …
in EEG signals, is a challenging task in sleep research as visually detecting them requires …
Hypoglycemia-induced EEG complexity changes in Type 1 diabetes assessed by fractal analysis algorithm
In recent years, hypoglycemia-induced changes in the EEG signal of patients with Type 1
diabetes (T1D) have been quantified and studied mainly by linear approaches. So far …
diabetes (T1D) have been quantified and studied mainly by linear approaches. So far …