Parkinson's Disease

Hybrid dilation and attention residual U-Net for medical image segmentation.

Medical image segmentation is a typical task in medical image processing and critical foundation in medical image analysis. U-Net is well-liked in medical image segmentation, but it doesn't fully explore useful features of the channel and capitalize on the contextual information. Therefore, we present an improved U-Net with residual connections, adding a plug-and-play, very portable channel attent...

Computational medication regimen for Parkinson's disease using reinforcement learning.

Our objective is to derive a sequential decision-making rule on the combination of medications to minimize motor symptoms using reinforcement learning (RL). Using an observational longitudinal cohort of Parkinson's disease patients, the Parkinson's Progression Markers Initiative database, we derived clinically relevant disease states and an optimal combination of medications for each of them by us...

Edge deep learning for neural implants: a case study of seizure detection and prediction.

Implanted devices providing real-time neural activity classification and control are increasingly used to treat neurological disorders, such as epilep...

Robotic colorectal surgery and ergonomics.

Improved ergonomics for the operating surgeon may be an advantage of robotic colorectal surgery. Perceived robotic ergonomic advantages in visualisati...

Getting into a "Flow" state: a systematic review of flow experience in neurological diseases.

BACKGROUND: Flow is a subjective psychological state that people report when they are fully involved in an activity to the point of forgetting time an...

Somatosensitive film soft crawling robots driven by artificial muscle for load carrying and multi-terrain locomotion.

Somatosensitive soft crawling robotics is highly desired for load carrying and multi-terrain locomotion. The motor-driven skeleton robots and pneumati...

Accessory pathway analysis using a multimodal deep learning model.

Cardiac accessory pathways (APs) in Wolff-Parkinson-White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there ar...

Effects of robot-assisted gait training on postural instability in Parkinson's disease: a systematic review.

INTRODUCTION: Postural instability is a cardinal feature of Parkinson's disease, together with rest tremor, rigidity and bradykinesia. It is a highly ...

A Review of Robotic and OCT-Aided Systems for Vitreoretinal Surgery.

The introduction of the intraocular vitrectomy instrument by Machemer et al. has led to remarkable advancements in vitreoretinal surgery enabling the ...

Ensemble deep model for continuous estimation of Unified Parkinson's Disease Rating Scale III.

BACKGROUND: Unified Parkinson Disease Rating Scale-part III (UPDRS III) is part of the standard clinical examination performed to track the severity o...

Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI.

Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of life for patients with various motor dysfunctions, such as ...

Automated assessment of the substantia nigra on susceptibility map-weighted imaging using deep convolutional neural networks for diagnosis of Idiopathic Parkinson's disease.

OBJECTIVES: Despite its use in determining nigrostriatal degeneration, the lack of a consistent interpretation of nigrosome 1 susceptibility map-weigh...

Interaction of Indirect and Hyperdirect Pathways on Synchrony and Tremor-Related Oscillation in the Basal Ganglia.

Low-frequency oscillatory activity (3-9 Hz) and increased synchrony in the basal ganglia (BG) are recognized to be crucial for Parkinsonian tremor. Ho...

Predicting Parkinson's disease trajectory using clinical and neuroimaging baseline measures.

INTRODUCTION: Predictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate pro...

State of the art in robotic rectal surgery: marginal gains worth the pain?

After their first introduction in the 1990s to overcome the limitations of conventional laparoscopic surgery, especially in confined spaces such as th...

Improved motor outcome prediction in Parkinson's disease applying deep learning to DaTscan SPECT images.

PURPOSE: Dopamine transporter (DAT) SPECT imaging is routinely used in the diagnosis of Parkinson's disease (PD). Our previous efforts demonstrated th...

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailments such as Parkinson's disease, Traumatic Brain ...

Comparison of clinical outcomes and accuracy of electrode placement between robot-assisted and conventional deep brain stimulation of the subthalamic nucleus: a single-center study.

BACKGROUND: Several surgical methods are used for deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD). This stud...

Investigating the relationship between the SNCA gene and cognitive abilities in idiopathic Parkinson's disease using machine learning.

Cognitive impairments are prevalent in Parkinson's disease (PD), but the underlying mechanisms of their development are unknown. In this study, we aim...

Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning.

Falling in Parkinsonian syndromes (PS) is associated with postural instability and consists a common cause of disability among PS patients. Current po...