Comparison of Electrodermal Activity from Multiple Body Locations Based on Standard EDA Indices’ Quality and Robustness against Motion Artifact

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 9; p. 3177
• Main Authors: Hossain, Md-Billal, Kong, Youngsun, Posada-Quintero, Hugo F., Chon, Ki H.
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 21.04.2022; MDPI
• Subjects: cognitive stress; Comparative analysis; Data Collection; Data entry; electrodermal activity; Electrodes; Exocrine glands; Foot; Galvanic Skin Response; Humans; Hydration; Male; Motion; Nervous system; Neurophysiology; SCR; Skin; statistical test; electrodermal activity; cognitive stress; SCR; statistical test
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22093177

The most traditional sites for electrodermal activity (EDA) data collection, palmar locations such as fingers or palms, are not usually recommended for ambulatory monitoring given that subjects have to use their hands regularly during their daily activities, and therefore, alternative sites are often sought for EDA data collection. In this study, we collected EDA signals (n = 23 subjects, 19 male) from four measurement sites (forehead, back of neck, finger, and inner edge of foot) during cognitive stress and induction of mild motion artifacts by walking and one-handed weightlifting. Furthermore, we computed several EDA indices from the EDA signals obtained from different sites and evaluated their efficiency to classify cognitive stress from the baseline state. We found a high within-subject correlation between the EDA signals obtained from the finger and the feet. Consistently high correlation was also found between the finger and the foot EDA in both the phasic and tonic components. Statistically significant differences were obtained between the baseline and cognitive stress stage only for the EDA indices computed from the finger and the foot EDA. Moreover, the receiver operating characteristic curve for cognitive stress detection showed a higher area-under-the-curve for the EDA indices computed from the finger and foot EDA. We also evaluated the robustness of the different body sites against motion artifacts and found that the foot EDA location was the best alternative to other sites.