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.
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.