Abstract
With the growing amount of data, it is necessary to create methods that facilitate its processing and that allow a more efficient knowledge extraction from them. The main objective of the project here discussed is to correlate the performance of a patient while playing a serious game with the data collected, at the same time, by an eye tracker and the emotions detected by the Face API of Microsoft Azure suite after processing the photos collected by a webcam. Using analysis algorithms and adequate data visualisations, it is intended to discover new relationships that connect the game results to biometric data and create new knowledge. Through the eye movement and facial expressions, collected while game playing, it is possible to show that children with memory deficit have a slower processing speed, fix more times, make more regressions, and they have more disposal to express an emotion of sadness or surprise.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Source: https://www.paulekman.com/universal-emotions/, accessed on 27/04/2021.
- 2.
Source: https://managementmania.com/en/six-basic-emotions, accessed on 20/01/2021.
- 3.
- 4.
Source: https://docs.microsoft.com/en-gb/azure/cognitive-services/face/concepts/face-detection, accessed on 27/04/2021.
- 5.
Link to visualise the images of the tests and horizontal eye movement: https://www.di.uminho.pt/~prh/BLOOM.
References
Jun Lee, S. Siau, K.: A review of data mining techniques. Ind. Manage. Data Syst. 101, 41–46 (2001)
McClean, S.: Data mining and knowledge discovery. Encyclopedia of Physical Science and Technology (Third Edition), pp. 229–246 (2003). http://www.sciencedirect.com/science/article/pii/B0122274105008450
Schuh, G., et al.: Data mining definitions and applications for the management of production complexity. In: 52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019, Procedia CIRP, vol. 81, pp. 874–879 (2019). http://www.sciencedirect.com/science/article/pii/S2212827119305220.
Gaggi, O., et al.: Serious games for early identification of developmental dyslexia. Comput. Entertain. 15 (2017). https://doi.org/10.1145/2629558
Singh, H. Human Eye Tracking and Related Issues: A Review. International Journal Of Scientific And Research Publications. 2 pp. 1-9 (2012,9)
Carter, B., Luke, S.: Best practices in eye tracking research. Int. J. Psychophysiol. 155, 49–62 (2020). http://www.sciencedirect.com/science/article/pii/S0167876020301458
Rayner, K.: The 35th Sir Frederick Bartlett lecture: Eye movements and attention in reading, scene perception, and visual search. Q. J. Exp. Psychol. 62, 1457–1506 (2009). https://doi.org/10.1080/17470210902816461
Stuart, S., et al.: Eye-tracker algorithms to detect saccades during static and dynamic tasks: A structured review. Physiol. Measure. 40, 02TR01 (2019). https://doi.org/10.1088%252F1361-6579%252Fab02ab
Cheng, D., Vertegaal, R.: An eye for an eye: A performance evaluation comparison of the LC technologies and Tobii eye trackers. In: Proceedings of ETRA-04, 61 (2004). https://doi.org/10.1145/968363.968378
Rayner, K.: Eye movement latencies for parafoveally presented words. Bull. Psychonomic Society. 11, 13–16 (1978). https://doi.org/10.3758/bf03336753
Abrams, R., Meyer, D., Kornblum, S.: Speed and accuracy of saccadic eye movements: Characteristics of impulse variability in the oculomotor system. J. Exp. Psychol. Human Percept. Perform. 15, 529–543 (1989). https://doi.org/10.1037/0096-1523.15.3.529
Lang, P.: The emotion probe: Studies of motivation and attention. Am. Psychol. 50, 372–385 (1995)
Gazzaniga, M., Heatherton, T., Veríssimo, V.: Ciência psicológica: mente, cérebro e comportamento. (Artmed,2005)
Gu, S., Wang, F., Patel, N., Bourgeois, J., Huang, J.: A model for basic emotions using observations of behavior in Drosophila. Front. Psychol. 10, 781 (2019). https://www.frontiersin.org/article/10.3389/fpsyg.2019.00781
Ekman, P.: An argument for basic emotions: Cognition and Emotion, 6, 169–200 (1992)
Jack, R., Garrod, O., Schyns, P.: Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over Time. Curr. Biol. 24, 187-192 (2014). https://www.sciencedirect.com/science/article/pii/S0960982213015194
Brunyé, T., Drew, T., Weaver, D., Elmore, J.: A review of eye tracking for understanding and improving diagnostic interpretation. Cogn. Res. Prin. Imp. 4 (2019). https://doi.org/10.1186/s41235-019-0159-2
Acknowledgments
This work has been supported by FCT- Fundação para a Ciência e Tecnologia within the Projects Scopes: UIDB/05757/2020 and UIDB/00319/2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
de Pinho, R., Pereira, M.J.V., Azevedo, A., Henriques, P.R. (2022). Relating Biometric Sensors with Serious Games Results. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-04826-5_10
Download citation
DOI: https://doi.org/10.1007/978-3-031-04826-5_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-04825-8
Online ISBN: 978-3-031-04826-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)