Parkinson's Disease

Decoding pre-movement neural activity from thalamic LFPs for adaptive neurostimulation in tremor patients

Understanding the neural mechanisms underlying movement initiation is crucial for advancing movement-driven adaptive deep brain stimulation therapies for tremor disorders. We investigated the feasibility of decoding pre-movement periods of upper limb movements by machine learning using thalamic local field potentials (LFPs) and scalp electroencephalography (EEG) signals. Data were analysed from 11...

Effect of robot-assisted gait training on motor dysfunction in Parkinson's patients:A systematic review and meta-analysis.

BACKGROUND: Robot-assisted gait training (RAGT) has been reported to treat motor dysfunction in patients with Parkinson's disease (PD) in the last few years. However, the benefits of RAGT for treating motor dysfunction in PD are still unclear.

[The efficacy analysis of neurosurgical robot-assisted DBS in the treatment of elderly Parkinson's disease].

To investigate the surgical efficacy of neurosurgery robot deep brain stimulation(DBS) in the treatment of elderly Parkinson's disease(PD). The clin...

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

Objective and quantitative monitoring of movement impairments is crucial for detecting progression in neurological conditions such as Parkinson's dise...

A Completely Portable and Concealable, Lightweight Assistive Exosuit for Upper Limbs.

Exosuits are a relatively new trend in wearable robotics to answer the flaws of their exoskeleton counterparts, but they remain impractical as the lac...

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

IMPORTANCE: Until now, other than complex neurologic tests, there have been no readily accessible and reliable indicators of neurologic dysfunction am...

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

BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagn...

Current Status of Robotic Gastrointestinal Surgery.

Development of surgical support robots began in the 1980s as a navigation and auxiliary device for endoscopic surgery. For remote surgery on the battl...

Review on the Artificial Intelligence-based Nanorobotics Targeted Drug Delivery System for Brain-specific Targeting.

Contemporary medical research increasingly focuses on the blood-brain barrier (BBB) to maintain homeostasis in healthy individuals and provide solutio...

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

The collection of Parkinson's Disease (PD) time-series data usually results in imbalanced and incomplete datasets due to the geometric distribution of...

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

Parkinson is the second most common neurodegenerative disease, mainly related to progressive locomotor alterations caused by dopamine deficiency. The ...

End-to-end Deep Learning of Polysomnograms for Classification of REM Sleep Behavior Disorder.

Rapid eye movement (REM) sleep behavior disorder (RBD) is parasomnia and a prodromal manifestation of Parkinson's disease. The current diagnostic meth...

Towards a Closed-loop Neuro-Robotic Approach to DBS Electrode Implantation based on Real-Time Wrist Rigidity Evaluation.

The iHandU system is a wearable device that quantitatively evaluates changes in wrist rigidity during Deep Brain Stimulation (DBS) surgery, allowing c...

Frameless Robot-Assisted vs Frame-Based Awake Deep Brain Stimulation Surgery: An Evaluation of Technique and New Challenges.

BACKGROUND: Methodological approaches to deep brain stimulation (DBS) continue to evolve from awake frame-based to asleep frameless procedures with ro...

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

Parkinson's disease (PD) is a neurodegenerative disorder. Hence, there is a tremendous demand for adapting vocal features to determine PD in an earlie...

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

BACKGROUND: Gait impairments are common disabling symptoms of Parkinson's disease (PD). Among the approaches for gait rehabilitation, interest in robo...

Self-normalized Classification of Parkinson's Disease DaTscan Images.

Classifying SPECT images requires a preprocessing step which normalizes the images using a normalization region. The choice of the normalization regio...

Predicting the Progression of Parkinson's Disease MDS-UPDRS-III Motor Severity Score from Gait Data using Deep Learning.

Parkinson's disease (PD) is a common neurodegenerative disease presenting with both motor and non-motor symptoms. Among PD motor symptoms, gait impair...

Robot-induced hallucinations in Parkinson's disease depend on altered sensorimotor processing in fronto-temporal network.

Hallucinations in Parkinson's disease (PD) are disturbing and frequent non-motor symptoms and constitute a major risk factor for psychosis and dementi...

Effect of robot-assisted gait training on gait automaticity in Parkinson disease: A prospective, open-label, single-arm, pilot study.

Gait automaticity is reduced in patients with Parkinson disease (PD) due to impaired habitual control. The aim of this study was to investigate the ef...