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Deep Brain Stimulation

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Predicting Motor Responsiveness to Deep Brain Stimulation with Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Deep brain stimulation is a complex movement disorder intervention that requires highly invasive brain surgery. Clinicians struggle to predict how patients will respond to this treatment. To address this problem, we are working toward developing a cl...

Development and Application of Medicine-Engineering Integration in the Rehabilitation of Traumatic Brain Injury.

BioMed research international
The rapid progress of the combination of medicine and engineering provides better chances for the clinical treatment and healthcare engineering. Traumatic brain injury (TBI) and its related symptoms have become a major global health problem. At prese...

Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson's Disease.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: A downside of Deep Brain Stimulation (DBS) for Parkinson's Disease (PD) is that cognitive function may deteriorate postoperatively. Electroencephalography (EEG) was explored as biomarker of cognition using a Machine Learning (ML) pipeline.

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.

Acta neurochirurgica
BACKGROUND: Several surgical methods are used for deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD). This study aimed to compare clinical outcomes and electrode placement accuracy after robot-assisted (RAS) ver...

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Nature communications
Commonly used for Parkinson's disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here,...

PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes.

International journal of computer assisted radiology and surgery
PURPOSE: Deep Brain Stimulation (DBS) is a proven therapy for Parkinson's Disease (PD), frequently resulting in an enhancement of motor function. Nonetheless, several undesirable side effects can occur after DBS, which can worsen the quality of life ...

The Portiloop: A deep learning-based open science tool for closed-loop brain stimulation.

PloS one
Closed-loop brain stimulation refers to capturing neurophysiological measures such as electroencephalography (EEG), quickly identifying neural events of interest, and producing auditory, magnetic or electrical stimulation so as to interact with brain...

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

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Methodological approaches to deep brain stimulation (DBS) continue to evolve from awake frame-based to asleep frameless procedures with robotic assistance, primarily directed to optimize operative efficiency, lead accuracy, and patient co...

Robot-Assisted Deep Brain Stimulation: High Accuracy and Streamlined Workflow.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: A number of stereotactic platforms are available for performing deep brain stimulation (DBS) lead implantation. Robot-assisted stereotaxy has emerged more recently demonstrating comparable accuracy and shorter operating room times compare...

Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.

ACS chemical neuroscience
Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From measurements using fast scan cyclic voltammetry (FSCV), one of the main tools used to detect synapt...