AIMC Topic: Parkinson Disease

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An Intelligent Parkinson's Disease Diagnostic System Based on a Chaotic Bacterial Foraging Optimization Enhanced Fuzzy KNN Approach.

Computational and mathematical methods in medicine
Parkinson's disease (PD) is a common neurodegenerative disease, which has attracted more and more attention. Many artificial intelligence methods have been used for the diagnosis of PD. In this study, an enhanced fuzzy -nearest neighbor (FKNN) method...

String Grammar Unsupervised Possibilistic Fuzzy C-Medians for Gait Pattern Classification in Patients with Neurodegenerative Diseases.

Computational intelligence and neuroscience
Neurodegenerative diseases that affect serious gait abnormalities include Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington disease (HD). These diseases lead to gait rhythm distortion that can be determined by stride time ...

Pattern analysis of computer keystroke time series in healthy control and early-stage Parkinson's disease subjects using fuzzy recurrence and scalable recurrence network features.

Journal of neuroscience methods
BACKGROUND: Identifying patients with early stages of Parkinson's disease (PD) in a home environment is an important area of neurological disorder research, because it is of therapeutic and economic benefits to optimal intervention and management of ...

Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease.

Scientific reports
In this study, we apply a multidisciplinary approach to investigate falls in PD patients using clinical, demographic and neuroimaging data from two independent initiatives (University of Michigan and Tel Aviv Sourasky Medical Center). Using machine l...

Automated assessment of levodopa-induced dyskinesia: Evaluating the responsiveness of video-based features.

Parkinsonism & related disorders
INTRODUCTION: Technological solutions for quantifying Parkinson's disease (PD) symptoms may provide an objective means to track response to treatment, including side effects such as levodopa-induced dyskinesia. Vision-based systems are advantageous a...

Evaluation of an ontology-based system for computerized cognitive rehabilitation.

International journal of medical informatics
OBJECTIVES: This paper describes the results of a randomized clinical trial about the effectiveness of a computerized rehabilitation treatment on a sample of 31 patients affected by Parkinson disease.

Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is considered a degenerative disorder that affects the motor system, which may cause tremors, micrography, and the freezing of gait. Although PD is related to the lack of dopamine, the triggering pro...

Thalamocortical dysrhythmia detected by machine learning.

Nature communications
Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. It is characterized by a common oscillatory pattern in which resting-state alpha activity is replaced by cross-frequency coupling of low- and high-freq...

Rest tremor quantification based on fuzzy inference systems and wearable sensors.

International journal of medical informatics
BACKGROUND: Currently the most consistent, widely accepted and detailed instrument to rate Parkinson's disease (PD) is the Movement Disorder Society sponsored Unified Parkinson Disease Rating Scale (MDS-UPDRS). However, the motor examination is based...

Using echo state networks for classification: A case study in Parkinson's disease diagnosis.

Artificial intelligence in medicine
Despite having notable advantages over established machine learning methods for time series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet to be widely used for practical data mining applications. In this paper, w...