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Self-tracking Reloaded: Applying Process Mining to Personalized Health Care from Labeled Sensor Data

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Transactions on Petri Nets and Other Models of Concurrency XI

Part of the book series: Lecture Notes in Computer Science ((TOPNOC,volume 9930))

Abstract

Currently, there is a trend to promote personalized health care in order to prevent diseases or to have a healthier life. Using current devices such as smart-phones and smart-watches, an individual can easily record detailed data from her daily life. Yet, this data has been mainly used for self-tracking in order to enable personalized health care. In this paper, we provide ideas on how process mining can be used as a fine-grained evolution of traditional self-tracking. We have applied the ideas of the paper on recorded data from a set of individuals, and present conclusions and challenges.

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Notes

  1. 1.

    http://sensor.informatik.uni-mannheim.de.

  2. 2.

    So far, we do not consider the sub-activities in the presented use cases.

  3. 3.

    http://sensor.informatik.uni-mannheim.de/#results.

  4. 4.

    Sequence mining techniques may in principle extract similar patterns. One difference is the inability for these techniques to present process view of the extracted patterns.

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Acknowledgments

This work as been partially supported by funds from the Ministry for Economy and Competitiveness (MINECO) of Spain and the European Union (FEDER funds) under grant COMMAS (ref. TIN2013-46181-C2-1-R).

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Authors and Affiliations

  1. University of Mannheim, Mannheim, Germany

    Timo Sztyler, Johanna Völker & Heiner Stuckenschmidt

  2. Universitat Politècnica de Catalunya, Barcelona, Spain

    Josep Carmona

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  1. Timo Sztyler
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  2. Josep Carmona
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  3. Johanna Völker
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  4. Heiner Stuckenschmidt
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Corresponding author

Correspondence to Timo Sztyler .

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Editors and Affiliations

  1. Newcastle University , Newcastle upon Tyne, United Kingdom

    Maciej Koutny

  2. FernUniversität in Hagen , Hagen, Germany

    Jörg Desel

  3. Leiden University , Leiden, The Netherlands

    Jetty Kleijn

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Sztyler, T., Carmona, J., Völker, J., Stuckenschmidt, H. (2016). Self-tracking Reloaded: Applying Process Mining to Personalized Health Care from Labeled Sensor Data. In: Koutny, M., Desel, J., Kleijn, J. (eds) Transactions on Petri Nets and Other Models of Concurrency XI. Lecture Notes in Computer Science(), vol 9930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53401-4_8

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  • DOI: https://doi.org/10.1007/978-3-662-53401-4_8

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  • Online ISBN: 978-3-662-53401-4

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