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Effect of Model Complexity on Fiber Activation Estimates in a Wearable Neuromodulator for Migraine

Salkim, E; Shiraz, A; Demosthenous, A; (2017) Effect of Model Complexity on Fiber Activation Estimates in a Wearable Neuromodulator for Migraine. In: 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE Green open access

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Abstract

Migraine is a prevalent and highly disabling disorder. The pharmaceutical and invasive treatment methods have trouble-some side effects and associated risks, hence undesirable. Transcutaneous supraorbital neuromodulation has been shown to potentially suppress episodic migraine attacks yet results have low efficacy. This inconclusive response may be associated with neuroanatomical variations of patients which may be investigated using computational models. Model complexity is a limiting factor in implementing such techniques. This paper investigates the effect of model complexity on fiber activation estimates in transcutaneous frontal nerve stimulation. It is shown that the model can be simplified while minimally affecting the outcome.

Type: Proceedings paper
Title: Effect of Model Complexity on Fiber Activation Estimates in a Wearable Neuromodulator for Migraine
Event: 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 19-21 October 2017, Turin, Italy
Location: Turin, Italy
Dates: 19 October 2017 - 21 October 2017
ISBN-13: 9781509058037
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/BIOCAS.2017.8325080
Publisher version: https://doi.org/10.1109/BIOCAS.2017.8325080
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Computational models, frontal nerve, migraine, neuromodulation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10054719
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