Focal cortical stroke often leads to persistent motor deficits, prompting the need for more effective interventions. The efficacy of rehabilitation can be increased by 'plasticity-stimulating' treatments that enhance experience-dependent modification...
We used a robotic exoskeleton to quantify specific patterns of abnormal upper limb motor behaviour in people who have had transient ischemic attack (TIA). A cohort of people with TIA was recruited within two weeks of symptom onset. All individuals co...
The development of coordinated reach-to-grasp movement has been well studied in infants and children. However, the role of motor cortex during this development is unclear because it is difficult to study in humans. We took the approach of using a bra...
BACKGROUND: The incidence of proximal humeral fractures increases with age. The functional recovery of the upper arm after such fractures is slow, and results are often disappointing. Treatment is associated with long immobilisation periods. Evidence...
Computational and mathematical methods in medicine
Nov 14, 2017
Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with...
Computational intelligence and neuroscience
Oct 19, 2017
Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. Th...
BACKGROUND: Classification of human behavior from brain signals has potential application in developing closed-loop deep brain stimulation (DBS) systems. This paper presents a human behavior classification using local field potential (LFP) signals re...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Sep 14, 2017
Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive training that is needed to trigger neuroplasticity following a stroke. However, the lack of fully adaptive assist-as-needed control of the ro...
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but...
Neurorehabilitation and neural repair
Jul 25, 2017
BACKGROUND: The application of resistive forces has been used during body weight-supported treadmill training (BWSTT) to improve walking function after spinal cord injury (SCI). Whether this form of training actually augments the effects of BWSTT is ...
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