Effect of Movements on the Electrodermal Response after a Startle Event

Summary

Objectives: In this work the effect of quasi-stationary movements on the electrodermal activity (EDA) after a startle event has been investigated and evaluated. In previous EDA research there is a discrepancy between the use of controlled environment studies and daily life surveys. This paper aims to address this by expanding the knowledge about EDA in real life applications.

Methods: A minimally obtrusive body-worn measurement device was designed and produced that simultaneously records EDA and finger movements. During this study, five subjects walked at different speeds and listened to startling sound events. The EDA response to these startle events was analyzed for different walking speeds using crosscorrelograms and cumulative frequency plots.

Results: The measured response to the startle event is consistent with the signal characteristics described in the literature. The results show that the faster a person is walking the more the signal property of the phasic part of the EDA is approaching a uniform distribution. However, even at a walking speed of 6 km/h the effect of the startle event is statistically still visible in the EDA (p <0.05).

Conclusions: The presented work offers a good understanding of the EDA while walking at different speeds. Although the artefacts evoked by walking cannot be determined directly, information on the movement can be useful. Depending on the walking speed a measurement about the reliability of peak detection could be introduced.

Keywords

Galvanic skin response - startle reaction - artifacts

• References

• 1 Fuller GD. GSR History, & Physiology. San Francisco: Biofeedback Institute San Francisco; 1977
• 2 Boucsein W. Electrodermal activity. New York: Plenum Press; 1992
• 3 Ishchenko AN, Shev’ev PP. Automated complex for multiparameter analysis of the galvanic skin response signal. Biomedical Engineering 1989; 23 (03) 113-117.
• 4 Schmidt S, Walach H. Electrodermal activity (EDA) – State-of-the-art measurement and techniques for parapsychological purposes. The Journal of Parapsychology 2000; 64: 139-163.
• 5 Piacentini R. Emotions at Fingertips, Revealing Individual Features in Galvanic Skin Response signals [dissertation]. Università degli studi di Roma “‘La Sapienza”’; Rome: 2004
• 6 Dawson ME, Schell AM, Filion DL. In: Cacioppo JT, Tassinary LG. editors. The electrodermal system. Cambridge: Cambridge Press; 1990 pp 295-324.
• 7 Stress: Signs, Symptoms, Causes, and Effects (homepage on the Internet).. Santa Monica: Help-guide; ©2001-07 (updated 2007 Dec 13; cited 2008 Feb 12). Available from: http://www. helpguide.org/mental/stress_signs.htm.
• 8 Long-Term Stress May Shrink the Brain (home-page on the Internet). Atlanta, Georgia: Web MD Inc.. ©2005 – (updated 2005 May 20; cited 2008 Feb 12). Available from: http://www. webmd.com/balance/news/20050520/long-term-stress-may-shrink-brain.
• 9 Jacobs SC, Friedman R, Parker JD, Tofler GH, Jimenez AH, Muller JE. et al. Use of skin conductance changes during mental stress testing as an index of autonomic arousal in cardiovascular research. American Heart Journal 1994; 128 6 Pt 1 1170-1177.
• 10 Healey J, Picard RW. SmartCar: Detecting Driver Stress. In: ICPR; 2000. pp 4218-4221.
• 11 Jorgensen MM, Zachariae R. Repressive coping style and autonomic reactions to two experimental stressors in healthy men and women. Scandinavian Journal of Psychology 2006; 47 (02) 137-148.
• 12 Clements K, Turpin G. Life Event Exposure, Physiological Reactivity, and Psychological Strain. Journal of Behavioral Medicine 2000; 23 (01) 73-94.
• 13 Strauss M, Reynolds C, Hughes S, Park K, McDarby G, Picard RW. The HandWave Bluetooth Skin Conductance Sensor. In: Tao J, Tan T, Picard RW. editors. ACII. vol. 3784 of Lecture Notes in Computer Science. Springer; 2005. pp 699-706.
• 14 Dornbush S, Fisher K, McKay K, Prikhodko A, Segall Z. XPOD – A Human Activity and Emotion Aware Mobile Music Player. In: International Conference on Mobile Technology, Applications and Systems; 2005 pp 1-6.
• 15 Nasoz F, Alvarez K, Lisetti L, Finkelstein N. Emotion recognition from physiological signals using wireless sensors for presence technologies. Cogn Technol Work 2004; 6 (01) 4-14.
• 16 Westeyn T, Presti P, Starner T. ActionGSR: A Combination Galvanic Skin Response-Accelerometer for Physiological Measurements in Active Environments. In: ISWC. IEEE; 2006. pp 129-130.
• 17 Amft O, Lauffer M, Ossevoort S, Macaluso F, Lukowicz P, Tröster G. Design of the QBIC Wearable Computing Platform. In: ASAP ’04: Proceedings of the Application-Specific Systems, Architectures and Processors, 15th IEEE International Conference on (ASAP’04). Washington, DC, USA: IEEE Computer Society; 2004. pp 398-410.
• 18 Bächlin M, Roggen D, Tröster G. Context-aware platform for long-term life style management and medical signal analysis. In: 2nd SENSATION International Conference; 2007
• 19 Healey J, Picard RW. StartleCam: A Cybernetic Wearable Camera. In: ISWC; 1998. pp 42-49.
• 20 Gerstein GL, Kiang NYS. An Approach to the Quantitative Analysis of Electrophysiological Data from Single Neurons. Biophysical Journal 1960; 1 (01) 15-28.
• 21 von Mises R. Mathematical Theory of Probability and Statistics. New York and London: Mathematical Theory of Probability and Statistics New York: Academic Press; 1964