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Motor Activity

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The Combined Effects of Adaptive Control and Virtual Reality on Robot-Assisted Fine Hand Motion Rehabilitation in Chronic Stroke Patients: A Case Study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
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 for EEG decoding and visualization.

Human brain mapping
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...

Robot-Applied Resistance Augments the Effects of Body Weight-Supported Treadmill Training on Stepping and Synaptic Plasticity in a Rodent Model of Spinal Cord Injury.

Neurorehabilitation and neural repair
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 ...

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface.

BioMed research international
Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emergi...

Abstraction, Sensory-Motor Coordination, and the Reality Gap in Evolutionary Robotics.

Artificial life
One of the major challenges of evolutionary robotics is to transfer robot controllers evolved in simulation to robots in the real world. In this article, we investigate abstraction of the sensory inputs and motor actions as a tool to tackle this prob...

Feasibility of spirography features for objective assessment of motor function in Parkinson's disease.

Artificial intelligence in medicine
OBJECTIVE: Parkinson's disease (PD) is currently incurable, however proper treatment can ease the symptoms and significantly improve the quality of life of patients. Since PD is a chronic disease, its efficient monitoring and management is very impor...

Mantisbot is a robotic model of visually guided motion in the praying mantis.

Arthropod structure & development
Insects use highly distributed nervous systems to process exteroception from head sensors, compare that information with state-based goals, and direct posture or locomotion toward those goals. To study how descending commands from brain centers produ...

Automatic matching of surgeries to predict surgeons' next actions.

Artificial intelligence in medicine
OBJECTIVE: More than half a million surgeries are performed every day worldwide, which makes surgery one of the most important component of global health care. In this context, the objective of this paper is to introduce a new method for the predicti...

Evaluation Results of an Ontology-based Design Model of Virtual Environments for Upper Limb Motor Rehabilitation of Stroke Patients.

Methods of information in medicine
OBJECTIVES: 1) To enhance the content of an ontology for designing virtual environments (VEs) for upper limb motor rehabilitation of stroke patients according to the suggestions and comments of rehabilitation specialists and software developers, 2) t...

Decision making under uncertainty in a spiking neural network model of the basal ganglia.

Journal of integrative neuroscience
The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbi...