AIMC Topic: Motor Activity
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Evaluation Results of an Ontology-based Design Model of Virtual Environments for Upper Limb Motor Rehabilitation of Stroke Patients.
Methods of information in medicine
Feb 21, 2017
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
Dec 21, 2016
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...
EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.
Consciousness and cognition
Nov 14, 2016
fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ E...
Activity Recognition for Diabetic Patients Using a Smartphone.
Journal of medical systems
Oct 8, 2016
Diabetes is a disease that has to be managed through appropriate lifestyle. Technology can help with this, particularly when it is designed so that it does not impose an additional burden on the patient. This paper presents an approach that combines ...
Emergence of gamma motor activity in an artificial neural network model of the corticospinal system.
Journal of computational neuroscience
Sep 27, 2016
Muscle spindle discharge during active movement is a function of mechanical and neural parameters. Muscle length changes (and their derivatives) represent its primary mechanical, fusimotor drive its neural component. However, neither the action nor t...
Using Data From the Microsoft Kinect 2 to Quantify Upper Limb Behavior: A Feasibility Study.
IEEE journal of biomedical and health informatics
Sep 5, 2016
The objective of this study was to assess whether the novel application of a machine learning approach to data collected from the Microsoft Kinect 2 (MK2) could be used to classify differing levels of upper limb impairment. Twenty-four healthy subjec...
Evaluation of Strategies for Integrated Classification of Visual-Manual and Cognitive Distractions in Driving.
Human factors
May 10, 2016
BACKGROUND: Prior studies have demonstrated unique driver behavior outcomes when visual and cognitive distraction occurs simultaneously as compared to the occurrence of one form of distraction alone. This situation implies additional complexity for t...
A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning.
International journal of neural systems
Apr 28, 2016
Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shap...
Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.
International journal of neural systems
Apr 11, 2016
Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband optimization has been suggested to enhance classification a...
Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.
NeuroImage
Apr 11, 2016
Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the succes...
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