Metal ion solutions identification using acoustic plate mode sensors and principal component analysis

Fabien J. Josse; Reiner Dahint; Sejal Shah; Egide V. Houndegla

doi:10.1117/12.370271

18 November 1999 Metal ion solutions identification using acoustic plate mode sensors and principal component analysis

Fabien J. Josse, Reiner Dahint, Sejal Shah, Egide V. Houndegla

Proceedings Volume 3857, Chemical Microsensors and Applications II; (1999) https://doi.org/10.1117/12.370271
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

The parameters used to rate acoustic wave-based chemical sensors are sensitivity and selectivity. While sensitivity can be improved by selecting the appropriate sensor device, selectivity still remains a major concern. This is primarily because the analytes under consideration often belong to the same group/class of chemicals. In such cases, the sensor output does not provide enough information to reliably identify, estimate and/or classify the analytes being investigated. As a result, data analysis techniques are used to extract selectivity from the sensor. An approach to analyze sensor signal data using statistical pattern recognition techniques such as principal component analysis and nearest neighbor algorithm is presented.

Citation Download Citation

Fabien J. Josse, Reiner Dahint, Sejal Shah, and Egide V. Houndegla "Metal ion solutions identification using acoustic plate mode sensors and principal component analysis", Proc. SPIE 3857, Chemical Microsensors and Applications II, (18 November 1999); https://doi.org/10.1117/12.370271

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