Transactions on
Neural Systems and Rehabilitation Engineering

TNSRE serves the community of biomedical engineers and clinical researchers who work at the intersection of neuroscience and physical medicine. We publish novel approaches and technologies for better understanding neural systems, human movement, and the relationships between them, with a focus on assistive devices that improve life for patients, for practicing clinicians, and for everyday use.
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Daniel P. Ferris, Ph.D.
Editor-in-chief
Editor-in-chief

Daniel P. Ferris is the Robert W. Adenbaum Professor of Engineering Innovation at the University of Florida J. Crayton Pruitt Family Department of Biomedical Engineering. He studies how to integrate machines and humans to improve human performance and mobility in health and disability. Specific research projects focus on robotic lower limb exoskeletons, bionic lower limb prostheses, and mobile brain imaging with high-density electroencephalography. Prof. Ferris completed his B.S. from the University of Central Florida, his M.S. from the University of Miami, and his Ph.D. from University of California, Berkeley. After earning his doctoral degree, he worked as a post-doctoral researcher in the UCLA Department of Neurology and the University of Washington Department of Electrical Engineering.​ Dr. Ferris spent 16 years at the University of Michigan until recently relocating to the University of Florida in June 2017.​

Daniel P. Ferris is the Robert W. Adenbaum Professor of Engineering Innovation at the University of Florida J. Crayton Pruitt Family Department of Biomedical Engineering. He studies how to integrate machines and humans to improve human performance and mobility in health and disability. Specific research projects focus on robotic lower limb exoskeletons, bionic lower limb prostheses, and mobile brain imaging with high-density electroencephalography. Prof. Ferris completed his B.S. from the University of Central Florida, his M.S. from the University of Miami, and his Ph.D. from University of California, Berkeley. After earning his doctoral degree, he worked as a post-doctoral researcher in the UCLA Department of Neurology and the University of Washington Department of Electrical Engineering.​ Dr. Ferris spent 16 years at the University of Michigan until recently relocating to the University of Florida in June 2017.​

Updates

Transactions on

Neural Systems and Rehabilitation Engineering

NOVEMBER 2020
VOLUME 28
NUMBER 11
ITNSB3
28
The IEEE Transactions on Neural Systems and Rehabilitation Engineering Volume 28 Issue 11 has been published.
Two-Dimensional Stockwell Transform and Deep Convolutional Neural Network for Multi-Class Diagnosis of Pathological Brain
Since brain lesion detection and classification is a vital diagnosis task, in this paper, the problem of brain magnetic resonance imaging (MRI) classification is investigated... Read more
12 Degrees of Freedom Muscle Force Driven Fibril-Reinforced Poroviscoelastic Finite Element Model of the Knee Joint
Accurate knowledge of the joint kinematics, kinetics, and soft tissue mechanical responses is essential in the evaluation of musculoskeletal (MS) disorders... Read more
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Plantar or Palmar Tactile Augmentation Improves Lateral Postural Balance with Significant Influence from Cognitive Load
Although it seems intuitive to address the issue of reduced plantar cutaneous feedback by augmenting it, many approaches have adopted compensatory sensory cues, such as tactile input from another part of the body, for multiple reasons including easiness and accessibility... Read more
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Adaptive Electrode Calibration Method based on Muscle Core Activation Regions and Its Application in Myoelectric Pattern Recognition
To reduce the bad effect of electrode shifts on myoelectric pattern recognition, this paper presents an adaptive electrode calibration method based on core activation regions of muscles... Read more
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Improving the Intelligibility of Speech for Simulated Electric and Acoustic Stimulation Using Fully Convolutional Neural Networks
Combined electric and acoustic stimulation (EAS) has demonstrated better speech recognition than conventional cochlear implant (CI) and yielded satisfactory performance under quiet conditions. However, when noise signals are involved, both the electric signal and the acoustic signal may be distorted, thereby resulting in poor recognition performance... Read more