Power Spectral Density Analysis of Electrodermal Activity for Sympathetic Function Assessment

Abstract

Time-domain features of electrodermal activity (EDA), the measurable changes in conductance at the skin surface, are typically used to assess overall activation of the sympathetic system. These time domain features, the skin conductance level (SCL) and the nonspecific skin conductance responses (NS.SCRs), are consistently elevated with sympathetic nervous arousal, but highly variable between subjects. A novel frequency-domain approach to quantify sympathetic function using the power spectral density (PSD) of EDA is proposed. This analysis was used to examine if some of the induced stimuli invoke the sympathetic nervous system's dynamics which can be discernible as a large spectral peak, conjectured to be present in the low frequency band. The resulting indices were compared to the power of low-frequency components of heart rate variability (HRVLF) time series, as well as to time-domain features of EDA. Twelve healthy subjects were subjected to orthostatic, physical and cognitive stress, to test these techniques. We found that the increase in the spectral powers of the EDA was largely confined to 0.045–0.15 Hz, which is in the prescribed band for HRVLF. These low frequency components are known to be, in part, influenced by the sympathetic nervous dynamics. However, we found an additional 5–10% of the spectral power in the frequency range of 0.15–0.25 Hz with all three stimuli. Thus, dynamics of the normalized sympathetic component of the EDA, termed EDASymp_n, are represented in the frequency band 0.045–0.25 Hz; only a small amount of spectral power is present in frequencies higher than 0.25 Hz. Our results showed that the time-domain indices (the SCL and NS.SCRs), and EDASymp_n, exhibited significant increases under orthostatic, physical, and cognitive stress. However, EDASymp_n was more responsive than the SCL and NS.SCRs to the cold pressor stimulus, while the latter two were more sensitive to the postural and Stroop tests. Additionally, EDASymp_n exhibited an acceptable degree of consistency and a lower coefficient of variation compared to the time-domain features. Therefore, PSD analysis of EDA is a promising technique for sympathetic function assessment.

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