Disruption of parkinsonian brain oscillations
By: Cédric Join , Jakub Orłowski , Antoine Chaillet and more
Potential Business Impact:
Helps Parkinson's patients by adjusting brain signals.
Deep brain stimulation (DBS) is an advanced surgical treatment for the symptoms of Parkinson's disease (PD), involving electrical stimulation of neurons within the basal ganglia region of the brain. DBS is traditionally delivered in an open-loop manner using fixed stimulation parameters, which may lead to suboptimal results. In an effort to overcome these limitations, closed loop DBS, using pathological subthalamic beta (13--30 Hz) activity as a feedback signal, offers the potential to adapt DBS automatically in response to changes in patient symptoms and side effects. However, clinically implemented closed-loop techniques have been limited to date to simple control algorithms, due to the inherent uncertainties in the dynamics involved. Model-free control, which has already seen successful applications in the field of bioengineering, offers a way to avoid this limitation and provides an alternative method to apply modern control approach to selective suppression of pathological oscillations.
Similar Papers
Deep Learning Model Predictive Control for Deep Brain Stimulation in Parkinson's Disease
Optimization and Control
Helps Parkinson's patients by fine-tuning brain jolts.
Neurophysiologically Realistic Environment for Comparing Adaptive Deep Brain Stimulation Algorithms in Parkinson Disease
Neurons and Cognition
Helps Parkinson's treatment by testing brain gadget ideas.
A Real Data-Driven, Robust Survival Analysis on Patients who Underwent Deep Brain Stimulation for Parkinson's Disease by Utilizing Parametric, Non-Parametric, and Semi-Parametric Approaches
Applications
Helps doctors predict Parkinson's survival for men and women.