Applied Software Development with Python and Machine Learning Involving Wearable and Wireless Systems for Movement Disorder Treatment Through Deep Brain Stimulation

10.1142/12249 ◽  
2021 ◽  
Author(s):  
Robert LeMoyne ◽  
Timothy Mastroianni
Keyword(s):  
Machine Learning ◽  
Deep Brain Stimulation ◽  
Software Development ◽  
Movement Disorder ◽  
Brain Stimulation ◽  
Wireless Systems ◽  
Applied Software ◽  
Disorder Treatment ◽  
Deep Brain

scholarly journals Predicting optimal deep brain stimulation parameters for Parkinson’s disease using functional MRI and machine learning

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alexandre Boutet ◽  
Radhika Madhavan ◽  
Gavin J. B. Elias ◽  
Suresh E. Joel ◽  
Robert Gramer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
A Priori ◽  
Brain Response ◽  
Brain Responses ◽  
Clinical Benefits ◽  
Deep Brain

AbstractCommonly 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, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Deep Brain Stimulation in an Additional Patient With ADCY5-Related Movement Disorder

2016 ◽  
Vol 32 (4) ◽  
pp. 438-439 ◽  
Author(s):  
Inge A. Meijer ◽  
Joan Miravite ◽  
Brian H. Kopell ◽  
Naomi Lubarr
Keyword(s):  
Deep Brain Stimulation ◽  
Movement Disorder ◽  
Brain Stimulation ◽  
Additional Patient ◽  
Deep Brain

Dystonia

2017 ◽  
Author(s):  
Jeri Yvonne Williams ◽  
David G Standaert
Keyword(s):  
Clinical Practice ◽  
Deep Brain Stimulation ◽  
Movement Disorder ◽  
Brain Stimulation ◽  
Age Of Onset ◽  
Anticholinergic Drugs ◽  
Body Parts ◽  
Botulinum Toxins ◽  
Deep Brain

Dystonia is a movement disorder characterized by sustained or intermittent muscle contractions. Classification of dystonia is based on age of onset, distribution of body parts affected, and underlying etiology. A large number of different genetic forms of dystonia have been discovered in recent years. Although these syndromes are important to recognize, the majority of dystonias encountered in clinical practice are of unknown cause. Therapy of dystonia includes medications, particularly anticholinergic drugs, use of botulinum toxins, and deep brain stimulation.

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