RL-EGOFET cell biosensors: A novel approach for the detection of action potentials

Abstract

Electrolyte-gated organic field-effect transistors (EGOFETs) have been recently investigated as a flexible and low-cost solution for the recording of cellular activity. In particular, electrical pulses, called action potentials (APs), generated by neurons, cause a variation in the source-drain current of an EGOFET. In this paper we propose a method which allows detecting the generation of one or more APs when a given cell is stimulated through the injection of a current pulse. The proposed algorithm is based on three steps: denoising, event detection and event classification. The attention, in this paper, has been principally focused on the design of a suitable denoising algorithm which represents the first fundamental step in the development of an APs detection algorithm. Results reported in this paper show that the Empirical Mode Decomposition (EMD) represents a suitable solution which allows removing noise and, at the same time, keep low the number of eligible events.