IEEE Transactions on Biomedical Engineering

Featured Articles
Sleep Monitoring Using Ear-Centered Setups: Investigating the Influence From Electrode Configurations
We combine ear-EEG sleep recordings with a state-of-the-art sleep scoring model, ‘seqsleepnet’, to investigate the upper limits of mobile sleep scoring. We manage to further improve on the state of the art in this field, and perform a detailed analysis of the influence of electrode positioning. From this, we find a general rule of thumb that as long a data set contain EOG information and electrode distance on the order of the width of the head, then good automatic sleep scoring is possible. We also find indications that the obtained automatic scoring may be more reliable than the manual scoring... Read more
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Stress Analysis Based on Simultaneous Heart Rate Variability and EEG Monitoring
Objective: Stress is a significant risk factor for various diseases such as hypertension, heart attack, stroke, and even sudden death. Stress can also lead to psychological and behavioral disorders. Heart rate variability (HRV) can reflect changes in stress levels while... Read more
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Feature Extraction and Identification of Alzheimer’s Disease based on Latent Factor of Multi-Channel EEG
Alzheimer’s disease is a neurodegenerative disease in old age, early diagnosis will help to delay the progression of the disease. Presently, the features of brain functional diseases can be obtained with EEG analysis, but the relationship between characteristics of EEG... Read more
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A Temporal-Spectral-based Squeeze-and-Excitation Feature Fusion Network for Motor Imagery EEG Decoding
Motor imagery (MI) electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with the outside world via external devices. Recent deep learning methods, which fail to fully explore both deep-temporal characterizations in... Read more
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Emotional Arousal and Valence Jointly Regulate the Auditory Response: A 40-Hz ASSR Study
Emotion is defined as a response to external stimuli and internal mental representations. It has been characterized as a multidimensional concept, primarily comprising two dimensions: valence and arousal. Existing studies have demonstrated that emotional experience exerts a powerful impact on... Read more
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VME-DWT: An Efficient Algorithm for Detection and Elimination of Eye Blink From Short Segments of Single EEG Channel
Objective: Recent advances in development of low-cost single-channel electroencephalography (EEG) headbands have opened new possibilities for applications in health monitoring and brain-computer interface (BCI) systems. These recorded EEG signals, however, are often contaminated by eye blink artifacts that can yield... Read more
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A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data
Background: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection have not been effectively harnessed due to sub-optimal classifier design... Read more
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Brain-Computer Interface-based Soft Robotic Glove Rehabilitation for Stroke
This paper presents the results of a study involving the use of a Brain-Computer Interface-based Soft Robotic Glove as a novel strategy in stroke rehabilitation. The technology uses the electroencephalogram signals from stroke patients to drive the assistive actions of the soft robotic glove to assist them in physically carrying out activities of daily living. The two-arm study showed prolonged improvements in FMA and ARAT scores although no significant intergroup differences were observed during the study. In addition, all of the patients in the BCI-SRG group also experienced a vivid kinesthetic illusion lasting beyond the active intervention period... Read more
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Dynamic reorganization of functional connectivity unmasks fatigue related performance declines in simulated driving
Although driving fatigue has long been recognized as one of the leading causes of fatal accidents worldwide, the underlying neural mechanisms remain largely unknown that impedes the developments of automatic detection techniques... Read more
Featured Articles
Small-World Propensity Reveals the Frequency Specificity of Resting State Networks
Functional connectivity (FC) is an important indicator of the brain’s state in different conditions, such as rest/task or health/pathology. Here we used high-density electroencephalography coupled to source reconstruction to assess frequency-specific changes of FC during resting state. Specifically, we computed... Read more