Statistical Measurement Validation with Application to Electronic Nose Technology

Mina Mirshahi, Vahid Partovi Nia, Luc Adjengue


An artificial olfaction called electronic nose (e-nose) relies on an array of gas sensors with the capability of mimicking the human sense of smell. Applying an appropriate pattern recognition on the sensor’s output returns odor concentration and odor classification. Odor concentration plays a key role in analyzing odors. Assuring the validity of measurements in each stage of sampling is a critical issue in sampling odors. An accurate prediction for odor concentration demands for careful monitoring of the gas sensor array measurements through time. The existing e-noses capture all odor changes in its environment with possibly varying range of error. Consequently, some measurements may distort the pattern recognition results. We explore e-nose data and provide a statistical algorithm to assess the data validity. Our online algorithm is computationally efficient and treats data as being sampled.


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Paper Citation

in Harvard Style

Mirshahi M., Nia V. and Adjengue L. (2016). Statistical Measurement Validation with Application to Electronic Nose Technology . In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 407-414. DOI: 10.5220/0005628204070414

in Bibtex Style

author={Mina Mirshahi and Vahid Partovi Nia and Luc Adjengue},
title={Statistical Measurement Validation with Application to Electronic Nose Technology},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},

in EndNote Style

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Statistical Measurement Validation with Application to Electronic Nose Technology
SN - 978-989-758-173-1
AU - Mirshahi M.
AU - Nia V.
AU - Adjengue L.
PY - 2016
SP - 407
EP - 414
DO - 10.5220/0005628204070414