An Empirical Muscle Intracellular Action Potential Model with Multiple Erlang probability Density Functions based on a Modified Newton Method. (January 2013)
- Record Type:
- Journal Article
- Title:
- An Empirical Muscle Intracellular Action Potential Model with Multiple Erlang probability Density Functions based on a Modified Newton Method. (January 2013)
- Main Title:
- An Empirical Muscle Intracellular Action Potential Model with Multiple Erlang probability Density Functions based on a Modified Newton Method
- Authors:
- Kim, Gyutae
Ferdjallah, Mohammed M.
McKenzie, Frederic D. - Abstract:
- The convolution of the transmembrane current of an excitable cell and a weighting function generates a single fiber action potential (SFAP) model by using the volume conductor theory. Here, we propose an empirical muscle IAP model with multiple Erlang probability density functions (PDFs) based on a modified Newton method. In addition, we generate SFAPs based on our IAP model and referent sources, and use the peak-to-peak ratios (PPRs) of SFAPs for model verification. Through this verification, we find that the relation between an IAP profile and the PPR of its SFAP is consistent with some previous studies, and our IAP model shows close profiles to the referent sources. Moreover, we simulate and discuss some possible ionic activities by using the Erlang PDFs in our IAP model, which might present the underlying activities of ions or their channels during an IAP.
- Is Part Of:
- Biomedical engineering and computational biology. Volume 5(2013)
- Journal:
- Biomedical engineering and computational biology
- Issue:
- Volume 5(2013)
- Issue Display:
- Volume 5, Issue 2013 (2013)
- Year:
- 2013
- Volume:
- 5
- Issue:
- 2013
- Issue Sort Value:
- 2013-0005-2013-0000
- Page Start:
- Page End:
- Publication Date:
- 2013-01
- Subjects:
- muscle intracellular action potential model -- single fiber action potential -- numerical optimization -- peak-to-peak ratio -- ionic activities in cell excitation
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610.2805 - Journal URLs:
- http://insights.sagepub.com/journal-biomedical-engineering-and-computational-biology-j170 ↗
http://www.uk.sagepub.com/home.nav ↗ - DOI:
- 10.4137/BECB.S11646 ↗
- Languages:
- English
- ISSNs:
- 1179-5972
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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