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

Tutkimustuotos: Katsausartikkelivertaisarvioitu

8 Lataukset (Pure)

Abstrakti

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.

AlkuperäiskieliEnglanti
Artikkeli100151
JulkaisuArray
Vuosikerta14
DOI - pysyväislinkit
TilaJulkaistu - heinäk. 2022
OKM-julkaisutyyppiA2 Katsausartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Computer Science(all)

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