Game design to measure reflexes and attention based on biofeedback multi-sensor interaction

Sensors
Inigo de Loyola Ortiz-Vigon UriarteYolanda Garcia-Chimeno

Abstract

This paper presents a multi-sensor system for implementing biofeedback as a human-computer interaction technique in a game involving driving cars in risky situations. The sensors used are: Eye Tracker, Kinect, pulsometer, respirometer, electromiography (EMG) and galvanic skin resistance (GSR). An algorithm has been designed which gives rise to an interaction logic with the game according to the set of physiological constants obtained from the sensors. The results reflect a 72.333 response to the System Usability Scale (SUS), a significant difference of p = 0.026 in GSR values in terms of the difference between the start and end of the game, and an r = 0.659 and p = 0.008 correlation while playing with the Kinect between the breathing level and the energy and joy factor. All the sensors used had an impact on the end results, whereby none of them should be disregarded in future lines of research, even though it would be interesting to obtain separate breathing values from that of the cardio.

References

Apr 1, 1979·Headache·S Diamond
Mar 19, 2002·Journal of Psychosomatic Research·C Sanz-CarrilloM Montoro
Jun 15, 2004·Journal of Psychosomatic Research·Thomas RitzWalton T Roth
Jan 16, 2007·Applied Psychophysiology and Biofeedback·Afton L HassettPaul M Lehrer
Apr 6, 2011·Current Neurology and Neuroscience Reports·Yoko Nagai

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Citations

Jul 20, 2016·Sensors·Fabrizio LambertiJon Rokne
Sep 7, 2019·International Journal of Environmental Research and Public Health·Cristián Castillo-OleaClemente Zuñiga
Nov 3, 2020··Katelyn WileyMadison Klarkowski

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Software Mentioned

SPSS
Matlab
Kinect
Eye Tracker
COM
Eye
Zephyr BioHarness

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