New Algorithm Improves Deep Brain Stimulation Programming Time
New research by Daria Anderson, a graduate student in the Butson lab, holds promise for improving the quality of life for patients with neurological disorders who have been treated with Deep Brain Stimulation (DBS). In DBS, electrodes are implanted in the brain to stimulate certain regions as a way to treat conditions such as Parkinson's disease.
These electrodes are becoming increasingly more complex and take longer to program to achieve a reduction in symptoms. Anderson developed an automated programming algorithm that can be used with current and new DBS technologies.
Anderson developed an automated programming algorithm to optimize DBS parameter selection for targeted neural activation. The optimization algorithm returns patient-specific contact configurations in near real-time, even for complex directional DBS leads.
Clinicians will be able to reduce the programming time using this algorithm, thus, saving treatment time and visits to the clinic for DBS patients.
This research was published in the Journal of Neural Engineering in January 2018. A link to the article, "Optimized programming algorithm for cylindrical and directional deep brain stimulation electrode" is available.