Neurology

Parkinson's Disease

Latest AI and machine learning research in parkinson's disease for healthcare professionals.

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Machine learning-based motor assessment of Parkinson's disease using postural sway, gait and lifestyle features on crowdsourced smartphone data.

OBJECTIVES: Remote assessment of gait in patients' homes has become a valuable tool for monitoring t...

An Underwater Robotic Manipulator with Soft Bladders and Compact Depth-Independent Actuation.

An underwater manipulator is essential for underwater robotic sampling and other service operations....

Discriminating progressive supranuclear palsy from Parkinson's disease using wearable technology and machine learning.

BACKGROUND: Progressive supranuclear palsy (PSP), a neurodegenerative conditions may be difficult to...

LFP-Net: A deep learning framework to recognize human behavioral activities using brain STN-LFP signals.

BACKGROUND: Recognition of human behavioral activities using local field potential (LFP) signals rec...

Untargeted Metabolomics for Metabolic Diagnostic Screening with Automated Data Interpretation Using a Knowledge-Based Algorithm.

Untargeted metabolomics may become a standard approach to address diagnostic requests, but, at prese...

A Super-Lightweight and Soft Manipulator Driven by Dielectric Elastomers.

Some applications are very sensitive to the weight of the robot, such as space manipulation or any u...

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavo...

Plasma and Serum Alpha-Synuclein as a Biomarker of Diagnosis in Patients With Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease, and α-synuclein plays...

Adaptive sparse learning using multi-template for neurodegenerative disease diagnosis.

Neurodegenerative diseases are excessively affecting millions of patients, especially elderly people...

Machine learning methods for optimal prediction of motor outcome in Parkinson's disease.

PURPOSE: It is vital to appropriately power clinical trials towards discovery of novel disease-modif...

Real-time machine learning classification of pallidal borders during deep brain stimulation surgery.

OBJECTIVE: Deep brain stimulation (DBS) of the internal segment of the globus pallidus (GPi) in pati...

Prevalence and Diagnosis of Neurological Disorders Using Different Deep Learning Techniques: A Meta-Analysis.

This paper dispenses an exhaustive review on deep learning techniques used in the prognosis of eight...

Compact Bone Surgery Robot With a High-Resolution and High-Rigidity Remote Center of Motion Mechanism.

OBJECTIVE: Two important and difficult tasks during a bone drilling procedure are guiding the orient...

Complexity Measures of Voice Recordings as a Discriminative Tool for Parkinson's Disease.

In this paper, we have investigated the differences in the voices of Parkinson's disease (PD) and ag...

Identification of distinct blood-based biomarkers in early stage of Parkinson's disease.

Parkinson's disease (PD) is a slowly progressive geriatric disease, which can be one of the leading ...

A Tunable-Q wavelet transform and quadruple symmetric pattern based EEG signal classification method.

Electroencephalography (EEG) signals have been widely used to diagnose brain diseases for instance e...

Comparison of Walking Protocols and Gait Assessment Systems for Machine Learning-Based Classification of Parkinson's Disease.

Early diagnosis of Parkinson's diseases (PD) is challenging; applying machine learning (ML) models t...

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