Self-tracking reloaded : applying process mining to personalized health care from labeled sensor data

Sztyler, Timo ; Carmona, Josep ; Völker, Johanna ; Stuckenschmidt, Heiner

Additional URL:
Document Type: Book chapter
Year of publication: 2016
Book title: Transactions on Petri nets and other models of concurrency XI
The title of a journal, publication series: Lecture Notes in Computer Science
Volume: 9930
Page range: 160-180
Publisher: Koutny, Maciej
Place of publication: Berlin [u.a.]
Publishing house: Springer
ISBN: 978-3-662-53400-7 , 978-3-662-53401-4
ISSN: 0302-9743 , 1611-3349
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
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 {\em 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.

Dieser Eintrag ist Teil der Universitätsbibliographie.

Metadata export


+ Search Authors in

+ Page Views

Hits per month over past year

Detailed information

You have found an error? Please let us know about your desired correction here: E-Mail

Actions (login required)

Show item Show item