Abstract Action Potential Models for Toxin Recognition
2005 ◽
Vol 6
(4)
◽
pp. 199-234
◽
Keyword(s):
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.
2005 ◽
Vol 94
(6)
◽
pp. 4430-4440
◽
2007 ◽
Vol 98
(6)
◽
pp. 3666-3676
◽
1983 ◽
Vol 244
(3)
◽
pp. H341-H350
Keyword(s):
Keyword(s):
1999 ◽
Vol 81
(1)
◽
pp. 408-411
◽
1999 ◽
Vol 277
(2)
◽
pp. H826-H833
◽
2019 ◽
Vol 96
◽
pp. 15-26
◽
Keyword(s):
1988 ◽
Vol 254
(6)
◽
pp. H1157-H1166
◽
Keyword(s):
2015 ◽
Vol 39
(1)
◽
pp. 15-26
◽
2003 ◽
Vol 89
(2)
◽
pp. 657-664
◽