Personalized Stress Management: Enabling Stress Monitoring with LifelogExplorer
| dc.contributor.author | Kocielnik, Rafal | |
| dc.contributor.author | Sidorova, Natalia | |
| dc.date.accessioned | 2018-01-08T09:17:45Z | |
| dc.date.available | 2018-01-08T09:17:45Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | Stress is one of the major triggers for many diseases. Improving stress balance is therefore an important prevention step. With advances in wearable sensors, it becomes possible to continuously monitor and analyse user’s behavior and arousal in an unobtrusive way. In this paper, we report on a case study in which users (21 teachers of a vocational school) were provided with wearable sensors and could view their arousal information put in the context of their life events during the period of four weeks using our software tool in an unsupervised setting. The goal was to evaluate user engagement and enabling of self-coaching abilities. Our results show that users actively explored their arousal data during the study. Further qualitative evaluation conducted with 15 of 21 users indicated that 12 of 15 users were able to learn about their stress patterns based on the information they obtained, but only 5 of them were able to come up with practical interventions for improving their stress balance on their own, while other users were of opinion that nothing can be done to reduce their stress, which suggests that self-coaching has some potential but there is need in further coaching support. | |
| dc.identifier.pissn | 1610-1987 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/11453 | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 29, No. 2 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Mental wellbeing | |
| dc.subject | Self-monitoring | |
| dc.subject | Stress | |
| dc.subject | Unobtrusive sensing | |
| dc.title | Personalized Stress Management: Enabling Stress Monitoring with LifelogExplorer | |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 122 | |
| gi.citation.startPage | 115 |