Bedload transport is an important process in fluvial hydraulics as determines fluvial morphology. Classical approaches describing bedload transport processes were focused on the macroscopic aspects of the granular-fluid flows, with no consideration of the mechanics of sediment motion at grain-scale. Better predictions of bedload fluxes can be achieved through fundamental research on grain mechanics for which detailed measurements of bedload fluxes at grain-scale are instrumental. Several bedload measurement methods adopted in controlled laboratory environments can be found in the literature. To overcome some drawbacks associated with such techniques, a novel impact-based prototype particle counter is proposed in the present paper. This device works by detecting the impacts of sediment particles on a sensitive surface. Digital signal processing and pattern recognition techniques are employed to detect impacts and count them. The advantages, like monitoring bedload for long periods, small data footprint, no need for optical access, real-time analysis, adaptability to different channel widths, and the limitations of the impact surface technique are discussed. The performances of the particle counter prototype have been tested comparing the results obtained with real reference data collected with high-speed video recordings. For a sampling time of 90 s a good overall agreement in what concerns the bedload time series was observed. The average solid discharge and the lateral distribution of bedload showed a slight disagreement between the two methods, mainly due to false particle impacts detected by the particle counter prototype and included in the analysis. It was also found that both the systems were able to capture the expected temporal stochastic variation of bedload and both leaded to similar autocorrelation functions and energy spectra.