Abstract action potential models for toxin recognition

action potential models for toxin recognition JAMES PETERSON* and TAUFIQUAR KHAN Department of Mathematical Sciences, Clemson University, Clemson, SC, USA (Received 14 December 2005) In this paper, we present a robust methodology using mathematical pattern recognition schemes to detect and classify events in action potentials for recognizing toxins in biological cells. We focus on event detection in action potential via abstraction of information content into a low dimensional feature vector within the constrained computational environment of a biosensor. We use generated families of action potentials from a classic Hodgkin–Huxley model to verify our methodology and build toxin recognition engines. We demonstrate that good recognition rates are achievable with our methodology.