Parkinson's Disease

Artificial Neural Network-Based Prediction of Outcome in Parkinson's Disease Patients Using DaTscan SPECT Imaging Features.

PURPOSE: Quantitative analysis of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images can enhance diagnostic confidence and improve their potential as a biomarker to monitor the progression of Parkinson's disease (PD). In the present work, we aim to predict motor outcome from baseline DAT SPECT imaging radiomic features and clinical measures using machine learning ...

Neuroprotective effects of Suhexiang Wan on the in vitro and in vivo models of Parkinson's disease.

OBJECTIVE: To examine the role of KSOP1009 (a modified formulation of Suhexiang Wan essential oil) in an animal model of Parkinson's disease (PD) induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) injection.

Robotics and ophthalmology: Are we there yet?

Ophthalmology is a field that is now seeing the integration of robotics in its surgical procedures and interventions. Assistance facilitated by robots...

Improving Stability in Upper Limb Rehabilitation Using Variable Stiffness.

In a robotic rehabilitation setup, patient's safety and interaction stability are critical throughout the therapy. This paper addresses the stability ...

Deep Learning Techniques for Improving Digital Gait Segmentation.

Wearable technology for the automatic detection of gait events has recently gained growing interest, enabling advanced analyses that were previously l...

A 3D Deep Residual Convolutional Neural Network for Differential Diagnosis of Parkinsonian Syndromes on F-FDG PET Images.

Idiopathic Parkinsons disease and atypical parkinsonian syndromes have similar symptoms at early disease stages, which makes the early differential di...

Early Parkinson's Disease Detection via Touchscreen Typing Analysis using Convolutional Neural Networks.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder worldwide, causing both motor and non-motor symptoms. In the early stage...

Deep Learning based Gait Abnormality Detection using Wearable Sensor System.

Gait is an extraordinary complex function of human body that involves the activation of entire visceral nervous system, making human gait definite to ...

Automatic Classification and Monitoring of Denovo Parkinson's Disease by Learning Demographic and Clinical Features.

Parkinson's Disease (PD) is the second most prevalent progressive neurological disorder around the world with high incidence rates for seniors. Since ...

Wearable Sensors for Prodromal Motor Assessment of Parkinson's Disease using Supervised Learning.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. Idiopathic hyposmia (IH), a r...

Multiple-Instance Learning for In-The-Wild Parkinsonian Tremor Detection.

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests through slowly progressing symptoms, such as tremor, voice degradation and bra...

Assessment of human wrist rigidity and pain in post-traumatic patients.

The aim of this work is to present a novel robot-based method to assess the sources of a lack of functionality in patients with recent traumatic wrist...

Robot-based assessment of sitting and standing balance: preliminary results in Parkinson's disease.

Postural responses to unstable conditions or perturbations are important predictors of the risk of falling and can reveal balance deficits in people w...

Microelectrode Recordings Validate the Clinical Visualization of Subthalamic-Nucleus Based on 7T Magnetic Resonance Imaging and Machine Learning for Deep Brain Stimulation Surgery.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a proven and effective therapy for the management of the motor symptoms o...

Using two-dimensional convolutional neural networks for identifying GTP binding sites in Rab proteins.

Deep learning has been increasingly and widely used to solve numerous problems in various fields with state-of-the-art performance. It can also be app...

Fusion of WPT and MFCC feature extraction in Parkinson's disease diagnosis.

BACKGROUND: Parkinson's disease (PD) is a neurological disorder, progressive in nature. In order to provide customized patient care, diagnosis and mon...

Fuzzy Classification Methods Based Diagnosis of Parkinson's disease from Speech Test Cases.

BACKGROUND: Together with the Alzheimer's disease, Parkinson's disease is considered as one of the two serious known neurodegenerative diseases. Physi...

Three Dimensional Analysis of SPECT Images for Diagnosing Early Parkinson's Disease using Radial Basis Function Kernel - Extreme Learning Machine.

BACKGROUND: Parkinson's Disease (PD) is caused by the deficiency of dopamine, the neurotransmitter that has an effect on specific uptake region of the...

Effectiveness of robot-assisted gait training on motor impairments in people with Parkinson's disease: a systematic review and meta-analysis.

The aim of this systematic review and meta-analysis was to evaluate the effectiveness of robot-assisted gait training (RAGT) on motor impairments in p...

Zerobot®: A Remote-controlled Robot for Needle Insertion in CT-guided Interventional Radiology Developed at Okayama University.

Since 2012, we have been developing a remote-controlled robotic system (Zerobot®) for needle insertion during computed tomography (CT)-guided interven...