Cell capacitance estimation and detection

Stephen A Sladen, University of Rhode Island

Abstract

The aim of this thesis is to examine the behavior of the electrical properties such as the resistance and capacitance of the cell membrane. During specific biological processes, the electrical properties of the membrane can yield useful data which can be further exploited to study these phenomenons. Using simulations, an accurate model of the cell membrane was built based on a three-element analog electrical circuit. Presented in this thesis are several signal processing algorithms which are used to either estimate the parameter values of the model or detect the presence of a vesicle activity. ^ The estimation is achieved with least-squares estimation using three methods, one being a nonlinear estimation problem. The two non-iterative linear estimators involve invoking the linear model to fit the data set and the use of a matched filter followed by the use of cross-correlation. The nonlinear estimator is of the separable type, however associated is an extensive run time, undesirable in a real-time setting. The detection method uses a variety of low-pass filters and a trigonometric identity to detect a change in the phase of the filtered output, a very similar method seen in lock-in amplifiers. In both sets of algorithms, sufficient cycles from the sinusoidal excitations are ensured to produce results to within 99% of the true values. ^

Subject Area

Biomedical engineering|Electrical engineering

Recommended Citation

Stephen A Sladen, "Cell capacitance estimation and detection" (2016). Dissertations and Master's Theses (Campus Access). Paper AAI10142860.
http://digitalcommons.uri.edu/dissertations/AAI10142860

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