Título:
|
Self-tracking reloaded: Applying process mining to personalized health care from labeled sensor data
|
Autor/a:
|
Sztyler, Timo; Carmona Vargas, Josep; Völker, Johanna; Stuckenschmidt, Heiner
|
Otros autores:
|
Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals |
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. |
Abstract:
|
Peer Reviewed |
Materia(s):
|
-Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació -Data mining -Health care -Smartphones -Daily lives -Personalized healthcare -Process mining -Self-tracking -Sensor data -Mineria de dades |
Derechos:
|
|
Tipo de documento:
|
Artículo - Versión presentada Artículo |
Compartir:
|
|