IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Affective computing is one of the key technologies to achieve advanced brain-machine interfacing. It is increasingly concerning research orientation in the field of artificial intelligence. Emotion recognition is closely related to affective computin...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
The brain-computer interface (BCI) connects the brain and the external world through an information transmission channel by interpreting the physiological information of the brain during thinking activities. The effective classification of electroenc...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Classification of electroencephalogram (EEG) signal data plays a vital role in epilepsy detection. Recently sparse representation-based classification (SRC) methods have achieved the good performance in EEG signal automatic detection, by which the EE...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
In this study, an online transfer TSK fuzzy classifier O-T-TSK-FC is proposed for recognizing epilepsy signals. Compared with most of the existing transfer learning models, O-T-TSK-FC enjoys its merits from the following three aspects: 1) Since diffe...
. To identify a new electrophysiological feature characterising the epileptic seizures, which is commonly observed in different types of epilepsy.. We recorded the intracranial electroencephalogram (iEEG) of 21 patients (12 women and 9 men) with mult...
The use of imagined speech with electroencephalographic (EEG) signals is a promising field of brain-computer interfaces (BCI) that seeks communication between areas of the cerebral cortex related to language and devices or machines. However, the comp...
Electroencephalogram (EEG) signals portray hidden neuronal interactions in the brain and indicate brain dynamics. These signals are dynamic, complex, chaotic and nonlinear, the nature of which is represented with features - fractal dimensions, entrop...
Electrocardiogram (ECG) signals represent the electrical activity of the human hearts and consist of several waveforms (P, QRS, and T). The duration and shape of each waveform and the distances between different peaks are used to diagnose heart disea...
IEEE transactions on bio-medical engineering
Sep 20, 2021
OBJECTIVE: This article shows the interest in deep learning techniques to detect motor imagery (MI) from raw electroencephalographic (EEG) signals when a functional electrical stimulation is added or not. Impacts of electrode montages and bandwidth a...
Exposure to mental stress for long period leads to serious accidents and health problems. To avoid negative consequences on health and safety, it is very important to detect mental stress at its early stages, i.e., when it is still limited to acute o...
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