Through spike sorting, information about the neurons’ activity is acquired via extracellular recordings of action potentials. In this work, a simple and fast approach based on the standard deviation of a channel’s recording for the detection of the neurons’ signals (spikes) is presented and evaluated. Furthermore, an analysis concerning data filtering is done. The results indicate that the performance of the detection approach strongly depends on the spike density. With lower densities, filtering and higher thresholds return adequate results. At higher densities, different parameters make nearly no differences.