Characterizing longitudinal changes in impedance spectra of in-vivo peripheral nerve electrodes.

Near-infrared spectroscopy (NIRS) is emerging as a rapid, low-cost approach for point-of-care triage of hematomas resulting from traumatic brain injury. However, there remains a lack of standardized test methods for benchtop performance assessment of these devices and incomplete understanding of relevant light–tissue interactions. ntil array failure. We developed a method to classify the shapes of the magnitude and phase spectra, and correlated the classifications to circuit models and electrochemical processes at the interface likely responsible. We found categories of EIS characteristic of iridium oxide tip metallization, platinum tip metallization, tip metal degradation, encapsulation degradation, and wire breakage in the lead. We also fitted the impedance spectra as features to a fine-Gaussian support vector machine (SVM) algorithm for both IrOx and Pt tipped arrays, with a prediction accuracy for categories of 95% and 99%, respectively. Together, this suggests that these simple and computationally efficient algorithms are sufficient to explain the majority of variance across a wide range of EIS data describing Utah arrays. These categories were assessed over time, providing insights into the degradation and failure mechanisms for both the electrode–tissue interface and wire bundle. Methods developed in this study will allow for a better understanding of how EIS can characterize the physical changes to electrodes in vivo.