A comparison of online methods for change point detection in ion-mobility spectrometry data

Anton Kondratev, Katri Salminen, Jussi Rantala, Timo Salpavaara, Jarmo Verho, Veikko Surakka, Jukka Lekkala, Antti Vehkaoja, Philipp Müller

Research output: Contribution to journalReview ArticleScientificpeer-review

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Abstract

When on-site classification of volatile organic compounds (VOCs) is required, a portable ion mobility spectrometer (IMS) is a suitable choice. However, the IMS readings often show transient phases before they stabilize. Even so the importance of transient phase and features extracted from it has been highlighted in the literature, it has not, to our knowledge, been used for IMS-based classification so far. This paper analyzes whether change point detection algorithms with low computational complexity can separate transient and stable phases in IMS readings. The algorithms were tested on IMS data from different types of mushrooms. All algorithms successfully detected switches from transient to stable phase. The most accurate results were provided by the previously proposed multivariate max-CUSUM algorithm and the matrix form CUSUM algorithm, which is developed in this paper.

Original languageEnglish
Article number100151
JournalArray
Volume14
DOIs
Publication statusPublished - Jul 2022
Publication typeA2 Review article in a scientific journal

Keywords

  • Algorithms
  • Change detection
  • Ion mobility spectrometry

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Computer Science(all)

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