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 interesting conclusions and challenges.
CitationSztyler, T., Völker, J., Carmona, J., Meier, O., Stuckenschmidt, H. Discovery of personal processes from labeled sensor data: An application of process mining to personalized health care. A: International Workshop on Algorithms & Theories for the Analysis of Event Data. "Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data: Brussels, Belgium, June 22-23, 2015". Bruselas: CEUR-WS.org, 2015, p. 31-46.
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