Using a Wireless Measure of Electrodermal Activity: Comparisons to Traditional Wired Equipment

Background: Electrodermal activity (EDA) has long been utilized as a physiological measure of arousal, stress, and anxiety. Traditional wired measures of EDA require a laboratory setting, electrodes attached to a polygraph by wires, and a stationary subject. New wireless EDA equipment can record in the real world without the obtrusiveness of traditional equipment. However, despite these advantages, the validity of such equipment has not been widely examined in pediatric or special needs populations.

Objectives: The purpose of this study was to compare the EDA data obtained from wireless equipment (Q-Sensor) to data from traditional, gold-standard equipment (BIOPAC). Our hypotheses were: (1) wired and wireless EDA measures would be moderately-to-highly correlated, and (2) wireless skin conductance level would be significantly lower than the wired signal due to electrode type and placement.

Methods: Participants were 37 children 6-12 years old (n=19 typical, n=17 autism spectrum disorder, ASD). EDA data using wired and wireless equipment were recorded from children in their home environment during a passive attention-sustaining task. Wired electrodes were place on distal phalanx of the second and third fingers of the non-dominant hand; wireless equipment was fit into a strap worn around the wrist, with electrodes touching the anterior surface of the wrist. A low-pass filter was applied to data from both wired and wireless sources to filter out noise and reduce artifacts. Correlation analyses to compare the average skin conductance level (SCL) and non-specific skin conductance response frequency (NS-SCR) across subjects were undertaken. Additionally, in order to measure the overall signal similarity (OSS) we computed a point-by-point Pearson’s correlation coefficient between the wired and wireless signals from each subject.

Results: No significant correlation was found in SCL between wired and wireless equipment in either group (typical r=.03; ASD r=.29; p’s≥.26). Additionally, the wireless SCL was significantly lower than wired results in both groups (p’s<.001). Due to the extremely low SCL of the wireless signal, no NS-SCRs of ≥.05µS were obtained. Therefore, analyses were required to identify an appropriate smaller amplitude threshold of NS-SCRs for subsequent Q-Sensor evaluation. Starting with .05μS we decreased the amplitude threshold, testing 17 potential amplitudes until the highest correlation was found between wired and wireless NS-SCR frequency (threshold = .002μS, r=0.57). Comparing the NS-SCR frequency using the smaller amplitude threshold for wireless signals to the traditional .05µS amplitude for wired signals, large correlations of NS-SCRs between wired and wireless equipment were found in children with ASD (r=.71, p<.01) and all children combined (r=.57, p<.01), but not in the typical-only group (r=.11). Weak but significant OSS measures were found between the wired and wireless EDA waveforms in the ASD group (median correlation value r=0.28 with 100% of participants p<.05) and TD group (r=0.23, with 89% of participants p<0.05).

Conclusions: Preliminary support exists for the use of the new, wireless Q-Sensor when investigating NS-SCR frequency and OSS in children with ASD. However, further research is required in clinical and non-clinical populations to examine the ideal electrode type and placement for wireless EDA collection in ambulatory settings.