Hematocrit estimation using online sequential extreme learning machine
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DOI:
https://doi.org/10.15625/1813-9663/29/3/2750Keywords:
Hematocrit, neural network, extreme learning machine, online sequential training, glucose measurement.Abstract
Hematocrit (HCT) is the volume percentage of red blood cells in the whole blood. This is the most highly influencing factor in glucose measurement using handheld devices. In this paper, we present a new approach to estimate hematocrit from the transduced current curve which is produced by chemical reaction on electrochemical biosensors used in glucose measurement. Our method utilizes the single-hidden layer feedforward neural network trained by online sequential extreme learning machine. The experimental results are given to show high level of accuracy of the proposed method.Metrics
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Published
02-07-2013
How to Cite
[1]
H. T. Huynh and Q. D. Ho, “Hematocrit estimation using online sequential extreme learning machine”, JCC, vol. 29, no. 3, pp. 277–284, Jul. 2013.
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Section
Computer Science
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