Alim-Louis Benabid: stimulation and serendipity

  title={Alim-Louis Benabid: stimulation and serendipity},
  author={Ruth Williams},
  journal={The Lancet Neurology},
  • Ruth Williams
  • Published 1 December 2010
  • Medicine
  • The Lancet Neurology
Parametric evaluation of deep brain stimulation parameter configurations for Parkinson’s disease using a conformal wearable and wireless inertial sensor system and machine learning
These findings constitute an advance toward the pathway of attaining real-time closed loop automated parameter configuration tuning for treatment of Parkinson’s disease using deep brain stimulation.
Distinction of an Assortment of Deep Brain Stimulation Parameter Configurations for Treating Parkinson’s Disease Using Machine Learning with Quantification of Tremor Response through a Conformal Wearable and Wireless Inertial Sensor
A quantified response to an assortment of parameter configurations, such as the variation of amplitude, for the deep brain stimulation system is acquired through a conformal wearable and wireless inertial sensor system and consolidated using Python software automation to a feature set amenable for machine learning.
Preliminary Network Centric Therapy for Machine Learning Classification of Deep Brain Stimulation Status for the Treatment of Parkinson’s Disease with a Conformal Wearable and Wireless Inertial Sensor
The research achievement establishes a progressive pathway to the future objective of achieving deep brain stimulation capabilities that promote closed-loop acquisition of configuration parameters that are uniquely optimized to the individual through extrinsic means of a highly conformal wearable and wireless inertial sensor system and machine learning with access to Cloud computing resources.
Adaptive Filters to Remove Deep Brain Stimulation Artifacts from Local Field Potentials
This paper proposes a robust computational framework based on adaptive filtering strategy to automatically estimate the artifact induced by each individual DBS pulse, and to recover the neural response during the artifact, and confirmed using the LFP recorded from patients with PD at the level of Subthalamic Nucleus.
Deep Brain Stimulation for the Treatment of Movement Disorder Regarding Parkinson’s Disease and Essential Tremor with Device Characterization
These envisioned technology evolutions advocate the prominence of Network Centric Therapy for the treatment of neurodegenerative movement disorders, such as Parkinson’s disease and Essential tremor.
Wearable and Wireless Systems for Movement Disorder Evaluation and Deep Brain Stimulation Systems
The amalgamation of wearable and wireless systems with deep brain stimulation using machine learning as an augmented post-processing application implicate the evolutionary trends for the ability to achieve closed-loop optimization of parameter configurations with the development of Network Centric Therapy for a quantum leap in the treatment intervention for neurodegenerative movement disorders, such as Parkinson’s disease and Essential tremor.
In-vivo human head conductivity estimation by SEEG and EEG recorded in simultaneous with intracerebral electrical stimulation
The following work aims to determine the most robust optimization algorithm among common algorithms for optimizing the forward head model, and analyzes the sensitivity of the conductivity values given different conditions on stimulation position, measurement positions and number of compartments.
The 2016 AANS Presidential Address: Leading the way.
This AANS presidential address focuses on enduring values of the neurosurgical profession that transcend the current political climate and cites "de-professionalism" and commoditization of medicine as foremost among the threats that confront medicine and surgery today.
Deep Brain Stimulation for Parkinson's Disease: Historical and Neuroethical Aspects 35
The historical development of DBS techniques as applied to the therapy of Parkinson’s disease is explored, including their status as less destructive and partially reversible successors to surgical techniques employed in the pre-L-DOPA era.
Control Theory and Deep Brain Stimulation for Relief from Neurological Diseases
Attempts made by the authors to develop constructive models of the phenomenology of DBS, based on classical Control Theory tools such as the Nyquist Stability Criterion, the Describing Function, the Root Locus method, Liapunov's theorem of the First Approximation and the concept of the Equivalent Nonlinearity associated with injection of a "high frequency" wave into a nonlinear feedback loop to quench troublesome "low frequency" oscillations are presented.