Student project: Improving Effectiveness in Selective Peripheral Nerve Stimulation

This project aims to explore methods to improve selective peripheral nerve stimulation utilizing available computational modeling tools and developing novel algorithms for closed-loop stimulation parameter optimization.

What you will do

The peripheral nervous system (PNS) consists of the nerves outside of the central nervous system (CNS) and connects the CNS to the organs, muscles, and skin. It is a bi-directional pathway between the CNS and internal organs and hence can have a powerful impact on the functionality of both. Currently, interest in peripheral nerve stimulation is growing as an alternative or a complement to pharmacological treatment, i.e., treatment with medication, for applications such as epilepsy, pain, depression, and chronic inflammatory diseases.

One of the major challenges for increasing the effectiveness of stimulation lies in achieving a closed-loop intervention such that stimulation paradigms are adapted based on direct sensing of stimulation effects. This can be achieved by recording neural activity or from reading out end organs themselves. This would ensure better spatial and functional selectivity of neuromodulation while minimizing unwanted side effects.

At imec, we have developed a neuromodulation framework capable of stimulating neural tissue in vivo and capturing direct neural response using an in-house peripheral nerve stimulation and sensing system. This system has been in use to explore novel stimulation paradigms in simple animal models such as earthworms, but also in large animal models such as pigs. Furthermore, we have enhanced existing computational model platforms to be able to explore complex stimulation methods and paradigms, utilizing precise anatomical information of peripheral nerves innervating different organs. This project aims to investigate the complex stimulation paradigms delivered over multi-contact electrodes, using the computational modelling simulations, and to translate those towards the in-vivo experimental setup. Exploration of closed-loop algorithms and their performance evaluation in-vivo towards more selective fibre activation is also envisioned.

Both, the simulation output and the in-vivo tests will evolve around the interpretation of the neural response in terms of action potentials (APs) and evoked compound action potentials (eCAPs). The implementation of control algorithms will be targeted towards adapting stimulation paradigms in near real-time to enable more advanced selective activation of nerve populations relevant for a specific health condition or state.

The student will be involved in both experimental and computational modelling activities to implement and test the methods and algorithms. The student is expected to implement specific control paradigms required for closing the loop and evaluate it in vivo on simple animal models (earthworms) and potentially in large animal models (pigs). The student will also deploy existing computational models to gain knowledge on the effects of specific stimulation paradigms and stimulating electrode configurations.

Student tasks will include:

• Literature review.
• Get acquainted with available computational models.
• Get acquainted with current in-vivo experimental setup.
• Perform computer simulations to optimize stimulation paradigms and to implement/test the closed-loop framework.
• Implement and test algorithms to enable closed-loop control paradigms.
• Design and perform experimental evaluations of several implemented strategies of improving stimulation selectivity.
• Report and documentation, depending on results, write a paper.
   

What we do for you

• You will be working on state-of-the-art technology and tools for stimulation of peripheral nerves that can be deployed to improve efficacy of neuromodulation treatments in the healthcare domain.
• You will be working in an inspiring high-tech environment, located within the Holst Centre in Eindhoven, and part of the larger IMEC organization, world-leader in R&D on nanotechnology and electronics.
• You will receive support from experienced researchers having diverse backgrounds relevant for the execution of the project.
• You will be a member of our multi-disciplinary team of researchers, engineers and innovators, and will be offered an opportunity to contribute to our ambitious aims in making real impact on actual healthcare needs. 

Who you are

• Excellent MSc student in Biomedical Engineering, Computer Science, or equivalent.
• You are entitled to do an internship in The Netherlands (have EU nationality and/or currently study at Dutch University).
• Available for 9 months or longer.
• Have good programming skills in python/Matlab.
• Have signal processing skills and experience, preferably processing of bio-signals.
• Experience with lab instrumentation (e.g., signal generators, oscilloscopes) is a plus.
• Experience in computational modelling (e.g., COMSOL, Neuron) is a plus.
• Eager to take ownership for your student project.
• Have a structured way of working.
• Have good command of spoken and written English.

Interested

Does this position sound like an interesting next step in your career at imec? Don’t hesitate to submit your application by clicking on ‘APPLY NOW’.
Should you have more questions about the job, you can contact jobs@imec.nl.