Towards detecting programmers’ stress on the basis of keystroke dynamics
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 1621–1626 (2016)
Abstract. The article describes the idea of detecting stress among programmers on the basis of keystroke dynamics. An experiment with a group of students of artificial intelligence classes was performed. Two samples of keystroke data were recorded for each case, the first while programming without stress, the second under time pressure. A number of timing and frequency parameters were calculated for each sample. Then statistical analysis was performed to evaluate the significance of keystroke parameters changes. It turned out that some of the defined features might be indicators of being stressed.
- V. Sreecharan and M. Srinivasa Reddy, “A study on individual and interpersonal stress levels among software employees,” Int. Journal of Information Technology & Computer Sciences Perspectives, vol. 2(4), pp. 711-716, 2013.
- M. R. Wróbel, “Emotions in the software development process,” in Proc. 6th International Conference on Human System Interaction, Gdańsk, 2013, http://dx.doi.org/10.1109/HSI.2013.6577875.
- R. W. Picard, “Affective Computing”, MIT Press, Cambridge, 1997.
- A. Kołakowska, A. Landowska, M. Szwoch, W. Szwoch, M. R. Wróbel, “Emotion Recognition and its Application in Software Engineering”, in Proc. 6th International Conference on Human System Interaction, Gdańsk, 2013, http://dx.doi.org/10.1007/978-3-319-08491-6_5.
- S. V. Ioannou, A. T. Raouzaiou, V. A. Tzouvaras, T. P. Mailis, K. C. Karpouzis, S. D. Kollias, “Emotion recognition through facial expression analysis based on a neurofuzzy network,” Neural Networks, vol. 18(4), pp. 423-435, 2005, http://dx.doi.org/10.1145/1980022.1980177.
- M. Szwoch, P. Pieniążek, “Facial Emotion Recognition Using Depth Data,” in Proc. 8th Int. Conf. Human System Interaction, pp. 271-277, 2015, http://dx.doi.org/10.1109/HSI.2015.7170679.
- B. Schuller, M. Lang, G. Rigoll, “Multimodal emotion recognition in audiovisual communication”, in Proc. IEEE Int. Conference on Multimedia and Expo, ICME, Lausanne, 2002, http://dx.doi.org/10.1109/ICME.2002.1035889.
- A. J. Gill, R. M. French, D. Gergle, J. Oberlander, “Identifying Emotional Characteristics from Short Blog Texts,” in Proc. 30th Annual Conference of the Cognitive Science Society, 2008, pp. 2237-2242.
- W. Szwoch, “Using Physiological Signals for Emotion Recognition,” in Proc. 6th International Conference on Human System Interaction, Gdańsk, 2013, http://dx.doi.org/10.1109/HSI.2013.6577880.
- A. Kołakowska, “A review of emotion recognition methods based on keystroke dynamics and mouse movements,” in Proc. 6th International Conference on Human System Interaction, Gdańsk, 2013, http://dx.doi.org/10.1109/HSI.2013.6577879.
- L. M. Vizer, L. Zhou, A. Sears, “Automated stress detection using keystroke and linguistic features,” Int. Journal of Human-Computer Studies 67, pp. 870-886, 2009, http://dx.doi.org/10.1016/j.ijhcs.2009.07.005.
- C. Epp, M. Lippold, R. L. Mandryk, “Identifying emotional states using keystroke dynamics,” in Proc. Conf. on Human Factors in Computing Systems, Vancouver, pp 715-724, 2011, http://dx.doi.org/10.1145/1978942.1979046
- M. Rodrigues, P. Novais, F. Fdez-Riverola, “An approach to assess stress in e-learning students,” in Proc. 11th European Conf. e-Learning, pp. 461-467, 2012.
- A. Hernandez-Aguila, M. Garcia-Valdez, and A. Mancilla, “Affective States in Software Programming: Classification of individuals based on their Keystroke and Mouse Dynamics,” Research in Computing Science 87, 2014, pp. 27-34.
- J. Hernandez, P. Paredes, A. Roseway, M. Czerwinsky, “Under pressure: sensing stress of computer users,” in Proc. 14th Conf. Human Factors in Computing Systems, pp. 51-60, 2014, http://dx.doi.org/10.1145/2556288.2557165.
- A. Landowska, “Emotion monitor – concept, construction and lessons learned,” in Proc. Federated Conference on Computer Science and Information Systems, pp. 75-80, 2015, http://dx.doi.org/10.15439/2015F384.
- A. Landowska, “Emotion monitoring - verification of physiological characteristics measurement procedures,” Metrology and measurement systems, vol. 21(4), pp. 381-388, 2014, http://dx.doi.org/10.2478/mms-2014-0049.
- T. Mankiewicz, “Emotion recognition based on keystroke dynamics” (in Polish: “Rozpoznawanie emocji na podstawie dynamiki pisania na klawiaturze”), Master’s thesis, Gdańsk University of Technology, 2014.
- Centre for Studies on Human Stress, “How to measure stress in humans,” Fernand-Seguin Research Centre of Louis H. Lafontaine Hospital, Quebec, Canada, 2007.