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Installation Instruction:

  1. Download and install MATLAB runtime (R2015a (8.5) 32/64).

  2. Download and Unzip physiOBS_vHM.rar

  3. Double click PhysiOBS.exe

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PhysiOBS is an observation analysis tool aiming to support researchers and practitioners in the demanding task of analyzing UX data sources at the post-study phase. It is available for download and has already been used in user testing studies conducted by researchers who are not related to the PhysiOBS team, e.g., in the evaluation of a software that aims to support journalists (Lindholm et al., 2018). In specific, they used PhysiOBS both to compare the stress level during different tasks and to validate the laboratory setting. Briefly, the proposed observation analysis tool supports:

  1. A concurrent view of all collected data sources in a single interface.

  2. Episodes Analysis of interaction which allows evaluators to move on specific periods instead of watching the entire session.

  3. Signal smoothing and normalization.

  4. Stress detection mechanism.

  5. Reporting mechanism of the results and 

  6. Saving/restoring a UX evaluation study in the form of a project.

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Lindholm, J., Backholm, K., & Högväg, J. (2018). What Eye Movements and Facial Expressions Tell Us about User-Friendliness: Testing a Tool for Communicators and Journalists. In Social Media Use In Crisis and Risk Communication

Related Publications:

  1. Liapis A., Katsanos C., Karousos N., Xenos M., Orphanoudakis T. (2020). User experience evaluation: a validation study of a tool-based approach for automatic stress detection using physiological signals. International Journal of Human-Computer Interaction Vol-TBD(Issue-TBD), pagesTBD. {IF-2019: 1.713}

  2. Liapis, A., Katsanos, C., Karousos, Sotiropoulos, D.G., N, Xenos, M., T, Orphanoudakis: UX Εvaluation Supported by Real-time Monitoring of Stress: a Tool-based Approach that Uses Heat-maps of Physiological Signals. Accepted for publication HCII2020

  3. Liapis, A., Katsanos, C., Sotiropoulos, D., Xenos, M., Karousos, N.: Recognizing emotions in human computer interaction: studying stress using skin conductance. In: Abascal, J., Barbosa, S., Fetter, M., Gross, T., Palanque, P., and Winckler, M. (eds.) Human-Computer Interaction – INTERACT 2015. pp. 255–262. Springer International Publishing (2015).

  4. Liapis, A., Karousos, N., Katsanos, C., Xenos, M.: Evaluating user’s emotional experience in HCI: the physiOBS approach. In: Kurosu, M. (ed.) Human-Computer Interaction. Advanced Interaction Modalities and Techniques. pp. 758–767. Springer International Publishing (2014).

  5. Liapis, A., Xenos, M.: The physiological measurements as a critical indicator in users’ experience evaluation. In: Proceedings of the 17th Panhellenic Conference on Informatics. pp. 258–263. ACM, New York, NY, USA (2013).

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