AIMC Topic: Parkinson Disease

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Uncertainty Quantification of Oscillation Suppression During DBS in a Coupled Finite Element and Network Model.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Models of the cortico-basal ganglia network and volume conductor models of the brain can provide insight into the mechanisms of action of deep brain stimulation (DBS). In this study, the coupling of a network model, under parkinsonian conditions, to ...

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures.

Movement disorders : official journal of the Movement Disorder Society
For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qua...

Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity.

Frontiers in neural circuits
The brain enables animals to behaviorally adapt in order to survive in a complex and dynamic environment, but how reward-oriented behaviors are achieved and computed by its underlying neural circuitry is an open question. To address this concern, we ...

Basal Ganglia dysfunctions in movement disorders: What can be learned from computational simulations.

Movement disorders : official journal of the Movement Disorder Society
The basal ganglia are a complex neuronal system that is impaired in several movement disorders, including Parkinson's disease, Huntington's disease, and dystonia. Empirical studies have provided valuable insights into the brain dysfunctions underlyin...

Joint feature-sample selection and robust diagnosis of Parkinson's disease from MRI data.

NeuroImage
Parkinson's disease (PD) is an overwhelming neurodegenerative disorder caused by deterioration of a neurotransmitter, known as dopamine. Lack of this chemical messenger impairs several brain regions and yields various motor and non-motor symptoms. In...

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson's disease.

Journal of neuroscience methods
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson's disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data.

Test and Validation of a Smart Exercise Bike for Motor Rehabilitation in Individuals With Parkinson's Disease.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
To assess and validate the Smart Exercise Bike designed for Parkinson's Disease (PD) rehabilitation, 47 individuals with PD were randomly assigned to either the static or dynamic cycling group, and completed three sessions of exercise. Heart rate, ca...

A decision support system to improve medical diagnosis using a combination of k-medoids clustering based attribute weighting and SVM.

Journal of medical systems
The use of machine learning tools has become widespread in medical diagnosis. The main reason for this is the effective results obtained from classification and diagnosis systems developed to help medical professionals in the diagnosis phase of disea...

Symmetry Analysis of Gait between Left and Right Limb Using Cross-Fuzzy Entropy.

Computational and mathematical methods in medicine
The purpose of this paper is the investigation of gait symmetry problem by using cross-fuzzy entropy (C-FuzzyEn), which is a recently proposed cross entropy that has many merits as compared to the frequently used cross sample entropy (C-SampleEn). Fi...

A Q-backpropagated time delay neural network for diagnosing severity of gait disturbances in Parkinson's disease.

Journal of biomedical informatics
Parkinson's disease (PD) is a movement disorder that affects the patient's nervous system and health-care applications mostly uses wearable sensors to collect these data. Since these sensors generate time stamped data, analyzing gait disturbances in ...