Using the Taguchi method to optimize the inspection equipment for human chorionic gonadotropin detection

Chia Hsien Yeh, Zi Qi Zhao, Yu Cheng Lin, Pi Lan Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study successfully fabricated the optical inspection system for detecting the commercial human chorionic gonadotropin (hCG) strips (cut-off value of the hCG commercial product is 25 mIU/mL) and developed the detection model from qualitative to quantitative analysis. In order to achieve the better linearity and decrease the standard deviation (increase the signal to noise ratio, S/N), the Taguchi method was used to find the optimal parameters in the optical inspection system. The hCG strip was based on the lateral flow immunoassay, and the color of the test and control line was caused by the colloid-gold. Because of the sandwich model, the color of the colloid-gold in the test line was darkened by increased the hCG concentration. In the results, the S/N was increased from 43.48 to 53.38 dB, and the hCG concentration detection was from 6.25 to 50 mIU/mL (the standard deviation less than 10%). The optical inspection system had the optimal parameters to decrease the detection limit and increase the linearity by using the Taguchi method and could apply to detect various commercial products (e.g. KET, Troponin I, FABP, etc.).

Original languageEnglish
Title of host publicationIEEE SENSORS 2014, Proceedings
EditorsFrancisco J. Arregui
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1125-1127
Number of pages3
EditionDecember
ISBN (Electronic)9781479901616
DOIs
Publication statusPublished - 2014 Dec 12
Event13th IEEE SENSORS Conference, SENSORS 2014 - Valencia, Spain
Duration: 2014 Nov 22014 Nov 5

Publication series

NameProceedings of IEEE Sensors
NumberDecember
Volume2014-December
ISSN (Print)1930-0395
ISSN (Electronic)2168-9229

Other

Other13th IEEE SENSORS Conference, SENSORS 2014
Country/TerritorySpain
CityValencia
Period14-11-0214-11-05

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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