[ARTICLE] Neural Engineering for Rehabilitation – BioMed Research International – Full Text PDF

… In this special issue, we provide the eight research articles
showing recent advances in neural engineering for rehabilitation.
We hope that this special issue will further contribute
to promoting the development of neurorehabilitation and
fundamentally providing clinically feasible neurorehabilitative
methods. To this end, more clinical studies with real
patients are especially required to accurately evaluate the
clinical effect of new rehabilitative methods even though
experiments performed with healthy subjects generally show
similar clinical effects.
Han-Jeong Hwang
Do-Won Kim
Janne M. Hahne
Jongsang Son

 

Contents

Neural Engineering for Rehabilitation
Han-Jeong Hwang, Do-Won Kim, Janne M. Hahne, and Jongsang Son
Volume 2017, Article ID 9638098, 2 pages

EEG-Based Computer Aided Diagnosis of AutismSpectrum Disorder UsingWavelet, Entropy, and ANN
Ridha Djemal, Khalil AlSharabi, Sutrisno Ibrahim, and Abdullah Alsuwailem
Volume 2017, Article ID 9816591, 9 pages

Evaluation of a Compact Hybrid Brain-Computer Interface System
Jaeyoung Shin, Klaus-Robert Müller, Christoph H. Schmitz,
Do-Won Kim, and Han-Jeong Hwang
Volume 2017, Article ID 6820482, 11 pages

Patient-Centered Robot-Aided Passive Neurorehabilitation Exercise Based on Safety-Motion Decision-Making Mechanism
Lizheng Pan, Aiguo Song, Suolin Duan, and Zhuqing Yu
Volume 2017, Article ID 4185939, 11 pages

Vowel Imagery Decoding toward Silent Speech BCI Using Extreme Learning Machine with Electroencephalogram
Beomjun Min, Jongin Kim, Hyeong-jun Park, and Boreom Lee
Volume 2016, Article ID 2618265, 11 pages

Integrative Evaluation of Automated Massage Combined withThermotherapy: Physical, Physiological, and Psychological Viewpoints
Do-Won Kim, DaeWoon Lee, Joergen Schreiber, Chang-Hwan Im, and Hansung Kim
Volume 2016, Article ID 2826905, 8 pages

Effect of Anodal-tDCS on Event-Related Potentials: A Controlled Study
Ahmed Izzidien, Sriharasha Ramaraju, Mohammed Ali Roula, and PeterW. McCarthy
Volume 2016, Article ID 1584947, 8 pages

Analysis of the Influence of Complexity and Entropy of Odorant on Fractal Dynamics and Entropy of EEG Signal
Hamidreza Namazi, Amin Akrami, Sina Nazeri, and Vladimir V. Kulish
Volume 2016, Article ID 5469587, 5 pages

Data-Driven User Feedback: An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features
Chang-Hee Han, Jeong-Hwan Lim, Jun-Hak Lee, Kangsan Kim, and Chang-Hwan Im
Volume 2016, Article ID 3939815, 7 pages

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