IEEE Journal of Translational Engineering in Health and Medicine

Articles
Massage Therapy’s Effectiveness on the decoding EEG rhythms of Left/Right Motor Imagery and Motion Execution in Patients with Skeletal Muscle Pain
Objective: Most of effectiveness assessments of the widely-used Massage therapy were based on subjective routine clinical assessment tools, such as Visual Analogue Scale (VAS) score. However, few studies demonstrated the impact of massage on the Electroencephalograph (EEG) rhythm decoding of... 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
Estimating Fugl-Meyer Upper Extremity Motor Score From Functional-Connectivity Measures
Fugl-Meyer assessment is an accepted method of evaluating motor function for people with stroke. A challenge associated with this assessment is the availability of trained examiners to carry out the evaluation. Neurophysiological biomarkers show promise in addressing the above impediment.... Read more
Featured Articles
Associations Among Emotional State, Sleep Quality, and Resting-State EEG Spectra: A Longitudinal Study in Graduate Students
University students are routinely influenced by a variety of natural stressors and experience irregular sleep-wake cycles caused by the necessity to trade sleep for studying while dealing with academic assignments. Often these factors result in long-term issues with daytime sleepiness,... Read more
Featured Articles
Decoding Movement-Related Cortical Potentials Based on Subject-Dependent and Section-Wise Spectral Filtering
An important challenge in developing a movement-related cortical potential (MRCP)-based brain-machine interface (BMI) is an accurate decoding of the user intention for real-world environments. However, the performance remains insufficient for real-time decoding owing to the endogenous signal characteristics compared to... Read more
Featured Articles
Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex
Understanding how the human brain controls locomotion is a considerable neuroscience challenge that has required advancements in mobile neuroimaging methods. Mobile high-density electroencephalography (EEG) allows electrical brain activity to be measured non-invasively during gait, but these signals are prone to... Read more
Featured Articles
From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes
         There has been increased effort to understand the neurophysiological effects of concussion aimed to move diagnosis and identification beyond current subjective behavioral assessments that suffer from poor sensitivity. Recent evidence suggests that event-related potentials (ERPs) measured with electroencephalography (EEG) are... Read more
Featured Articles
Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters
   Data-driven spatial filtering algorithms optimize scores, such as the contrast between two conditions to extract oscillatory brain signal components. Most machine learning approaches for the filter estimation, however, disregard within-trial temporal dynamics and are extremely sensitive to changes in training... Read more
Featured Articles
Cortico-Muscular Coherence Modulated by High-Definition Transcranial Direct Current Stimulation in People With Chronic Stroke
    High-definition transcranial direct current stimulation (HD-tDCS) is a potential neuromodulation apparatus for stroke rehabilitation. However, its modulatory effects in stroke subjects is still not well understood. In this paper, the offline modulatory effects of HD-tDCS on the ipsilesional primary motor... Read more
Featured Articles
Graph Theory Analysis of Functional Connectivity in Major Depression Disorder with High-Density Resting State EEG data
        Existing studies have shown functional brain networks in patients with major depressive disorder (MDD) have abnormal network topology structure. But the methods to construct brain network still exist some issues to be solved. This study is to explore reliable and... Read more