DocumentCode :
663167
Title :
Global sensitivity analysis of the probabilistic volume of tissue activated in a volume conductor model for deep brain stimulation
Author :
Schmidt, Christoph ; van Rienen, Ursula
Author_Institution :
Inst. of Gen. Electr. Eng., Univ. of Rostock, Rostock, Germany
fYear :
2013
fDate :
6-8 Nov. 2013
Firstpage :
1218
Lastpage :
1221
Abstract :
To date, various computational models exist to gain insight into the mechanisms of action of deep brain stimulation (DBS) as well as to predict the volume of tissue activated (VTA). The parameters of these models are subject to uncertainty, and knowledge about the sensitivity of the VTA on this uncertainty is scarce. The aim of this study was to perform a global sensitivity analysis of the probabilistic VTA on the uncertainty in the electrical properties of brain tissue as well as on the parameters of the electrode-tissue-interface, which is present under voltage controlled stimulation. Global sensitivity analysis was carried out using the polynomial chaos technique, which is based on polynomial expansions in random space. The results showed a major influence of the electrical conductivity of brain tissue, which suggests that the uncertainty of the tissue parameters is a crucial factor in the computational modeling of DBS.
Keywords :
bioelectric potentials; biological tissues; biomedical electrodes; brain; chaos; electrical conductivity; neurophysiology; patient treatment; physiological models; polynomials; probability; sensitivity analysis; DBS action mechanisms; DBS computational modeling; brain tissue; deep brain stimulation; electrical conductivity; electrode-tissue-interface parameters; global sensitivity analysis; polynomial chaos technique; polynomial expansions; probabilistic VTA; random space; voltage controlled stimulation; volume conductor model; volume of tissue activated; Brain modeling; Computational modeling; Probabilistic logic; Satellite broadcasting; Solid modeling; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location :
San Diego, CA
ISSN :
1948-3546
Type :
conf
DOI :
10.1109/NER.2013.6696159
Filename :
6696159
Link To Document :
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