Personalised tremor control by advanced clinical Deep Brain Stimulation.


CALL: 2018

DOMAIN: BM - Life Sciences, Biology and Medicine


LAST NAME: Baniasadi



HOST INSTITUTION: University of Luxembourg

KEYWORDS: Deep Brain Stimulation, Tremor, Control Theory, Machine learning, Open-loop vs Closed-loop Control, Movement Disorders

START: 2018-11-01

END: 2022-10-31


Submitted Abstract

Tremor is the most common symptom of movement disorders. One of the most effective ways to control tremor is Deep Brain Stimulation (DBS). Following the implantation of the DBS, electrodes are continuously stimulating specific parts of the brain at relatively high values to ensure long-term effectiveness of the procedure. However, this approach has several drawbacks. First, manual tuning of stimulation parameters may lead to poor performance, especially with newer electrodes containing multiple contact leads. The large number of parameters limits the search for optimal stimulation parameters. Second, many patients have tremor only under certain circumstances (e.g., voluntary movements or resting), meaning that continuous stimulation is completely unnecessary. Third, optimal stimulation parameters change. Throughout the day, stimulation parameters should adapt to patient needs, and in the long-term stimulation parameters need to compensate for the evolution of the disease. Since we cannot have physicians following patients 24 hours a day to continuously adjust stimulation parameters, this project proposes to develop algorithms to automatically make these adjustments. Furthermore, habituation to continuously ongoing DBS seems to reduce the overall effect of stimulation in the long run. Thus, the overall goal of the project is to eliminate tremor while minimising the energy supplied to the brain. The project aims to: 1) Design effective algorithms to initialise the stimulation parameters of multiple contacts leads. 2) Investigate new open-loop strategies for tremor suppression, with considerably lower energy supplied to the brain. 3) Develop a model-based controller to automatically regulate the stimulation parameters in real-time according to individuals’ dynamics. 4) Investigate commercial implementation of developed methods, and their associated trade-offs, between the different developed methods. This is an interdisciplinary project, connecting neurosurgeons with neurologists, engineers and mathematicians. It requires working closely with patients to develop personalised therapies that can potentially be commercially implemented. The developed method can be adapted to other treatments involving DBS, such as anorexia, depression and post-traumatic stress disorder.

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