Evaluation and Analysis of physiological Data - Focus Area: Heart Rate Variability (HRV)

Subject:	Evaluation and Analysis of physiological Data - Focus Area: Heart Rate Variability (HRV)
Type:	Master Thesis
Supervisor:	Raphael Rissler
Add on:	Status: Open

Motivation

In today’s digital economy, Information Systems (IS) are a significant investment for companies and constitute an indispensable part of employees daily work [1]. Due to technological developments such as multi-media-rich user interfaces, IS are increasingly able to induce highly engaging, interactive, and holistic experiences [1]. One such experience called flow - defined as “the holistic sensation that people feel when they act with total involvement” [2, p. 36] - is considered to be of theoretical and practical significance as this phenomenon is expected to explain a considerable amount of well-being and performance at work [3–5].
However, despite increasing interest of IS scholars in flow [6], a central challenge is the limited knowledge about real-time measurement. Researchers typically rely on self-report scales which are administered post-task (e.g., [7, 8]). As flow occurs during task execution, post-task self-reported measures cannot assess parameters like the length or depth of flow during task execution, and are subject to reporting inaccuracies [9]. The recent rise of the NeuroIS field with the inclusion and development of psychophysiological measures therefore provides new possibilities for objective and continuous measurements of psychological constructs in the context of IS [10, 11]. On of these measurements is the heart rate variability (HRV).

Goal of the Thesis

The overall goal of this thesis project is the following:

Depict the state of the art in literature, how the hear rate variability (HRV) is linked to the Flow state
Extract the most appropriate algorithms / tools used by literature to calculate HRV and its specific features
Use this knowledge to analyse already existing data which we will provide to you and analyze them

Contact

Raphael Rissler: raphael.rissler@kit.edu

References

1. Agarwal, R., Karahanna, E.: Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. Manag. Inf. Syst. Q. 24, 665–694 (2000).
2. Csikszentmihalyi, M.: Beyond Boredom and Anxiety. Jossey-Bass, San Francisco, CA (1975).
3. Webster, J., Trevino, L.K., Ryan, L.: The dimensionality and correlates of flow in human-computer interactions. Comput. Human Behav. 9, 411–426 (1993).
4. Ghani, J.A., Supnick, R., Rooney, P.: The Experience of Flow in ComputerMediated and in Face-to-Face Groups. In: Proceedings of the 12th International Conference on Information Systems. pp. 229–237 (1991).
5. Mahnke, R., Benlian, A., Hess, T.: Flow experience in information systems research: Revisiting its conceptualization, conditions, and effects. In: Proceedings of the 35th International Conference on Information Systems. pp. 1–22 (2014).
6. Rissler, R., Nadj, M., Adam, M.T.P.: Flow in Information Systems research: Review, integrative theoretical framework, and future directions. In: International Conference on Wirtschaftsinformatik. pp. 1051–1065 (2017).
7. Jackson, S.A., Eklund, R.C.: Assessing flow in physical activity: The flow state scale-2 and dispositional flow scale-2. J. Sport Exerc. Psychol. 24, 133– 150 (2002).
8. Engeser, S., Rheinberg, F.: Flow, performance and moderators of challengeskill balance. Motiv. Emot. 32, 158–172 (2008).
9. Peifer, C.: Psychophysiological Correlates of Flow-Experience. In: Engeser, S. (ed.) Advances in Flow Research. pp. 139–164. Springer Science, New York, NY (2012).
10. Riedl, R., Léger, P.-M.: Fundamentals of NeuroIS Information Systems and the Brain. Springer Berlin Heidelberg (2016).
11. Riedl, R., Davis, F.D., Hevner, A.R.: Towards a NeuroIS Research Methodology: Intensifying the