IEEE Journal of Translational Engineering in Health and Medicine

Articles
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
Articles
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
Articles
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
Featured Articles
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
Featured Articles
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
Articles
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
Featured Articles
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
Featured Articles
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
Articles, Published Articles
Robust Sparse Representation and Multiclass Support Matrix Machines for the Classification of Motor Imagery EEG Signals
   Early Access Note: Early Access articles are new content made available in advance of the final electronic or print versions and result from IEEE’s Preprint or Rapid Post processes. Preprint articles are peer-reviewed but not fully edited. Rapid Post articles are... Read more