Master Thesis: A computational model of transcutaneous Spinal Cord Stimulation
Spinal Cord Stimulation (SCS) is an effective clinical treatment for neuropathic pain and has recently demonstrated to target a wide variety of neurological functions. However, the mechanisms of action between the applied electric fields and the underlying neural circuits remain largely enigmatic, limiting both the clinical efficacy as well as the pace of translational research of SCS. Computational modeling of SCS has recently emerged as a powerful tool for investigating both theoretical mechanisms and techniques to optimize the clinical application of the technology. Much of the field has focused on invasive SCS, which had a great impact on surgical targeting and stimulation parameter selection. However, recently transcutaneous SCS – a non-invasive, surface-electrode based neurostimulation therapy – received increasing attention as a cost-, time-, and risk-limited alternative to invasive SCS.
The successful student is asked to develop a patient-specific 3D Finite Element Method (FEM) model of the spinal cord and its surrounding and evaluate the effects of stimulation parameter selection on the electric field generated by transcutaneous SCS. The student is asked to couple the results of the FEM analysis with compartmental cable models of the axon, assess the outcomes of stimulation parameter selection of various neural substrates and optimise stimulation parameters accordingly.
|Project type||Master thesis|
|Period||Summer term 2022|
|Presence time||Virtual and/or at the Chair of Digital Health|
|Useful knowledge||Finite Element Method, Compartmental Cable Models, Programming, Neuroscience|
|Work distribution||50 % modeling and 50 % programming|
|Registration||E-mail to Dr. Andreas Rowald|
Literature recommendations are provided during the meetings. The candidate is further encouraged to research relevant publications on this topic.
Final presentation and final report/thesis