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
Autonomous Robot for Removing Superficial Traumatic Blood
Objective: To remove blood from an incision and find the incision spot is a key task during surgery, or else over discharge of blood will endanger a patient’s life. However, the repetitive manual blood removal involves plenty of workload contributing... Read more
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Task-space Synergies for Reaching using Upper-limb Prostheses
Synergistic prostheses enable the coordinated movement of the human-prosthetic arm, as required by activities of daily living. This is achieved by coupling the motion of the prosthesis to the human command, such as the residual limb movement in motion-based interfaces... Read more
Articles
LoCoMo-Net: A Low-Complex Deep Learning Framework for sEMG Based Hand Movement Recognition for Prosthetic Control
Background: The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior. Therefore, in this paper we report a deep learning framework named ‘Low-Complex Movement recognition-Net’ (LoCoMo-Net)... Read more
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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
Articles, Published Articles
Cardiac-DeepIED: Automatic Pixel-level Deep Segmentation for Cardiac Bi-ventricle Using Improved End-to-End Encoder-Decoder Network
     Abstract Accurate segmentation of cardiac bi-ventricle (CBV) from magnetic resonance (MR) images has a great significance to analyze and evaluate the function of the cardiovascular system. However, the complex structure of CBV image makes fully automatic segmentation as a well-known challenge.... Read more
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Decoding Native Cortical Representations for Flexion and Extension at Upper Limb Joints Using Electrocorticography
       Brain–machine interface (BMI) researchers have traditionally focused on modeling endpoint reaching tasks to provide the control of neurally driven prosthetic arms. Most previous research has focused on achieving an endpoint control through a Cartesian-coordinate-centered approach. However, a joint-centered approach could... Read more
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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
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Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions
        Functional electrical stimulation (FES) is capable of activating muscles that are under-recruited in neurological diseases, such as stroke. Therefore, FES provides a promising technology for assisting upper-limb motor functions in rehabilitation following stroke. However, the full benefits of FES may... Read more