부산대학교 도서관

Effective closed-loop neuromodulation relies on the acquisition of appropriate physiological control variables and the delivery of an appropriate stimulation signal. In particular, electroneurogram (ENG) data acquired from a set of electrodes applied at the surface of the nerve may be used as a potential control variable in this field. Improved electrode technologies and data processing methods are clearly needed in this context. In this work, we evaluated a new electrode technology based on multichannel organic electrodes (OE) and applied a signal processing chain in order to detect respiratory-related bursts from the phrenic nerve. Phrenic ENG (pENG) were acquired from nine Long Evans rats in situ preparations. For each preparation, a 16-channel OE was applied around the phrenic nerve’s surface and a suction electrode was applied to the cut end of the same nerve. The former electrode provided input multivariate pENG signals while the latter electrode provided the gold standard for data analysis. Correlations between OE signals and that from the gold standard were estimated. Signal to noise ratio (SNR) and ROC curves were built to quantify phrenic bursts detection performance. Correlation score showed the ability of the OE to record high-quality pENG. Our methods allowed good phrenic bursts detection. However, we failed to demonstrate a spatial selectivity from the multiple pENG recorded with our OE matrix. Altogether, our results suggest that highly flexible and biocompatible multi-channel electrode may represent an interesting alternative to metallic cuff electrodes to perform nerve bursts detection and/or closed-loop neuromodulation.