AIMC Topic: Parkinson Disease

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A Deep Learning Approach for Grading of Motor Impairment Severity in Parkinson's Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Objective and quantitative monitoring of movement impairments is crucial for detecting progression in neurological conditions such as Parkinson's disease (PD). This study examined the ability of deep learning approaches to grade motor impairment seve...

Neurologic Dysfunction Assessment in Parkinson Disease Based on Fundus Photographs Using Deep Learning.

JAMA ophthalmology
IMPORTANCE: Until now, other than complex neurologic tests, there have been no readily accessible and reliable indicators of neurologic dysfunction among patients with Parkinson disease (PD). This study was conducted to determine the role of fundus p...

Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening.

Journal of Parkinson's disease
BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagnosis of IPD. Cardiac autonomic dysfunction begins in the early stages of IPD, and an electrocardiogr...

Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI.

GigaScience
BACKGROUND: DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing.

A Riemannian Deep Learning Representation to Describe Gait Parkinsonian Locomotor Patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Parkinson is the second most common neurodegenerative disease, mainly related to progressive locomotor alterations caused by dopamine deficiency. The gait kinematic is a principal disease biomarker that associates patterns like the step length, flexe...

Dyskinesia Estimation of Imbalanced Data Using a Deep-Learning Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The collection of Parkinson's Disease (PD) time-series data usually results in imbalanced and incomplete datasets due to the geometric distribution of PD complications' sever-ity scores. Consequently, when training deep convolutional models on these ...

Optimized Deep Learning for the Classification of Parkinson's Disease Based on Voice Features.

Critical reviews in biomedical engineering
Parkinson's disease (PD) is a neurodegenerative disorder. Hence, there is a tremendous demand for adapting vocal features to determine PD in an earlier stage. This paper devises a technique to diagnose PD using voice signals. Initially, the voice sig...

Robot-assisted gait training in patients with Parkinson's disease: Implications for clinical practice. A systematic review.

NeuroRehabilitation
BACKGROUND: Gait impairments are common disabling symptoms of Parkinson's disease (PD). Among the approaches for gait rehabilitation, interest in robotic devices has grown in recent years. However, the effectiveness compared to other interventions, t...