Preliminary Evaluation of Non-Conventional Conductive Materials for Electrodermal Activity Data Acquisition
; Santos, M.
Preliminary Evaluation of Non-Conventional Conductive Materials for Electrodermal Activity Data Acquisition, Proc Sociedade Portuguesa de Fisiologia International Conference of the Portuguese Physiology Society SPFis, Lisboa, Portugal, Vol. , pp. - , October, 2019.
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Introduction: Electrodermal activity (EDA) signal carries useful information about the sympathetic nervous system. Normally, it is recorded using non-polarizable Ag/AgCl electrodes, on the palm of the hand or the sole of the foot, which, in turn, can impose a hard constraint. More convenient locations and sensor setups are needed. A solution may pass by the use of e-textiles or 3D printed materials as electrodes since they can be integrated in a seamless manner and present advantageous proprieties useful for long- term recordings.
Methods: Conductive leather (GMLC), Lycra (MedTexP-130), and PLA (3D) materials were tested as electrodes, compared with dry Ag/AgCl electrodes from Thought Technology, considered as the gold standard. We used several know resistances, each at a time, ranging from 50kΩ to 3MΩ with tolerances of 1%, and connected them to a BITalino EDA sensor and acquisition board, via the electrodes. Each electrode had a 1 cm2 contact area, and exosomatic DC technique was the chosen method for EDA recording. A total of 10 measurements were taken with each resistance and each electrode material to and the Pearson correlation coefficients were computed in regard to the gold standard.
Results: The conductive lycra showed high correlation (r=0.999±0.000) as well as a very low resistivity of 4.27Ω.cm2. The 3D electrodes presented a resistivity of 3.3kΩ.cm2 and high correlation (r=0.950±0.005), although having an increased deviation under the 100kΩ mark. The conductive leather performed the worst, nonetheless, with good correlation (r=0.718±0.041) and resistivity of 3.5kΩ.cm2, while suffering as well of an increased deviation under 0.5MΩ.
Conclusions: Conductive lycra is the most promising material, opening the possibility to integrate EDA sensors in a more seamless fashion. Further studies should focus on testing the different electrode materials on live subjects to further validate our results and also study other possible locations to extract the EDA.