Behavioural Neurology

Neural Engineering for Rehabilitation


Status
Published

Lead Editor

1Hong Kong Polytechnic University, Hong Kong

2Howard Hughes Medical Institute, Virginia, USA

3Northwestern University, Chicago, USA

4University of Nevada, Las Vegas, USA

5Delft University of Technology, Delft, Netherlands


Neural Engineering for Rehabilitation

Description

Neurorehabilitation has been identified as a grand challenge for the coming decades, mainly due to the fast growing population with neurological disorders (e.g., stroke, Alzheimer’s, and Parkinson’s, etc.). Efficient, quantitative, and automated rehabilitation services are in urgent need to release the increasing demands for long-term medical treatments and healthcare and to compensate the lack of manpower in rehabilitation professionals. Neural engineering is an active research area, where engineering technologies, such as robots, imaging, artificial intelligence, telecommunication, and sensors, have contributed to diagnosis, treatment, and long-term evaluation in rehabilitation processes. Advances in neural engineering techniques, from the fundamental research in laboratories to clinical trials, will definitely promote the automated and personalized rehabilitation in the future.

This special issue aims at compiling the latest researches and advances in neural engineering with an ultimate application in rehabilitation. We invite authors to submit original research and review articles that explore the related mechanisms and/or technologies.

Potential topics include but are not limited to the following:

  • Brain computer interfaces
  • Neural sensors
  • Neural prosthetics and robotics for rehabilitation
  • Neumuscular electrical stimulation
  • Neural signal processing in rehabilitation
  • Quantification of rehabilitation effectiveness
  • Neural imaging for rehabilitation
  • Neural tissue engineering

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 9240921
  • - Editorial

Advances in Neural Engineering for Rehabilitation

Xiaoling Hu | Ting Zhao | ... | Yuan Yang
  • Special Issue
  • - Volume 2017
  • - Article ID 3908135
  • - Review Article

Hand Rehabilitation Robotics on Poststroke Motor Recovery

Zan Yue | Xue Zhang | Jing Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 3435686
  • - Research Article

Gesture Decoding Using ECoG Signals from Human Sensorimotor Cortex: A Pilot Study

Yue Li | Shaomin Zhang | ... | Xiaoxiang Zheng
  • Special Issue
  • - Volume 2017
  • - Article ID 4820428
  • - Research Article

Characterizing Patients with Unilateral Vestibular Hypofunction Using Kinematic Variability and Local Dynamic Stability during Treadmill Walking

Peng Liu | Qiuhong Huang | ... | Yiqing Zheng
  • Special Issue
  • - Volume 2017
  • - Article ID 8349242
  • - Research Article

Effects of Robot-Assisted Training for the Unaffected Arm in Patients with Hemiparetic Cerebral Palsy: A Proof-of-Concept Pilot Study

Alessandro Picelli | Elisabetta La Marchina | ... | Nicola Smania
  • Special Issue
  • - Volume 2017
  • - Article ID 6261479
  • - Clinical Study

Cerebral Reorganization in Subacute Stroke Survivors after Virtual Reality-Based Training: A Preliminary Study

Xiang Xiao | Qiang Lin | ... | Le Li
  • Special Issue
  • - Volume 2017
  • - Article ID 6914216
  • - Research Article

An Exploratory Study of Intensive Neurofeedback Training for Schizophrenia

Wenya Nan | Feng Wan | ... | Agostinho Rosa
  • Special Issue
  • - Volume 2017
  • - Article ID 8041962
  • - Research Article

The Difference of Neural Networks between Bimanual Antiphase and In-Phase Upper Limb Movements: A Preliminary Functional Magnetic Resonance Imaging Study

Qiang Lin | Hai Li | ... | Le Li
  • Special Issue
  • - Volume 2017
  • - Article ID 3731802
  • - Review Article

Robotics in Lower-Limb Rehabilitation after Stroke

Xue Zhang | Zan Yue | Jing Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 2358386
  • - Research Article

The Effect of Dopaminergic Medication on Joint Kinematics during Haptic Movements in Individuals with Parkinson’s Disease

Kuan-yi Li | Pei-yi Chu | Kristen A. Pickett
Behavioural Neurology
 Journal metrics
Acceptance rate41%
Submission to final decision57 days
Acceptance to publication20 days
CiteScore2.900
Impact Factor2.093
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