Integrating Wearable Data into Process Mining: Event, Case and Activity Enrichment

TL;DR

This paper investigates methods to incorporate wearable device data into process mining by enriching event logs with additional health-related information, aiming to improve analysis of personal productivity and well-being.

Contribution

It introduces three novel approaches for integrating wearable data into process mining, including attribute enrichment and new event creation, demonstrated with real-world smartwatch data.

Findings

Wearable data can be effectively linked to event logs.

Different integration approaches suit various analysis needs.

Challenges include technical and conceptual issues.

Abstract

In this short paper, we explore the enrichment of event logs with data from wearable devices. We discuss three approaches: (1) treating wearable data as event attributes, linking them directly to individual events, (2) treating wearable data as case attributes, using aggregated day-level scores, and (3) introducing new events derived from wearable data, such as sleep episodes or physical activities. To illustrate these approaches, we use real-world data from one person, matching health data from a smartwatch with events extracted from a digital calendar application. Finally, we discuss the technical and conceptual challenges involved in integrating wearable data into process mining for personal productivity and well-being.