A comparison of online methods for change point detection in ion-mobility spectrometry data
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 bee...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | Array |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590005622000182 |
| _version_ | 1818209376715931648 |
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| author | Anton Kondratev Katri Salminen Jussi Rantala Timo Salpavaara Jarmo Verho Veikko Surakka Jukka Lekkala Antti Vehkaoja Philipp Müller |
| author_facet | Anton Kondratev Katri Salminen Jussi Rantala Timo Salpavaara Jarmo Verho Veikko Surakka Jukka Lekkala Antti Vehkaoja Philipp Müller |
| author_sort | Anton Kondratev |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T04:59:44Z |
| format | Article |
| id | doaj.art-5c45c81b21274fd1bb11c8886afea74f |
| institution | Directory Open Access Journal |
| issn | 2590-0056 |
| language | English |
| last_indexed | 2024-12-12T04:59:44Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Array |
| spelling | doaj.art-5c45c81b21274fd1bb11c8886afea74f2022-12-22T00:37:16ZengElsevierArray2590-00562022-07-0114100151A comparison of online methods for change point detection in ion-mobility spectrometry dataAnton Kondratev0Katri Salminen1Jussi Rantala2Timo Salpavaara3Jarmo Verho4Veikko Surakka5Jukka Lekkala6Antti Vehkaoja7Philipp Müller8Tampere University, Korkeakoulunkatu 7, Tampere, 33720, Finland; Corresponding author.Tampere University of Applied Sciences, Kuntokatu 3, Tampere, 33520, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandTampere University, Korkeakoulunkatu 7, Tampere, 33720, FinlandWhen 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.http://www.sciencedirect.com/science/article/pii/S2590005622000182AlgorithmsChange detectionIon mobility spectrometry |
| spellingShingle | Anton Kondratev Katri Salminen Jussi Rantala Timo Salpavaara Jarmo Verho Veikko Surakka Jukka Lekkala Antti Vehkaoja Philipp Müller A comparison of online methods for change point detection in ion-mobility spectrometry data Array Algorithms Change detection Ion mobility spectrometry |
| title | A comparison of online methods for change point detection in ion-mobility spectrometry data |
| title_full | A comparison of online methods for change point detection in ion-mobility spectrometry data |
| title_fullStr | A comparison of online methods for change point detection in ion-mobility spectrometry data |
| title_full_unstemmed | A comparison of online methods for change point detection in ion-mobility spectrometry data |
| title_short | A comparison of online methods for change point detection in ion-mobility spectrometry data |
| title_sort | comparison of online methods for change point detection in ion mobility spectrometry data |
| topic | Algorithms Change detection Ion mobility spectrometry |
| url | http://www.sciencedirect.com/science/article/pii/S2590005622000182 |
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