Adaptive Single Micro-Particle Detection and Segmentation in Self-Mixing Interferometry Signals

This paper introduces a signal processing algorithm for micro-particle detection using the self-mixing interferometry (SMI) sensing scheme. Processing the laser output power modulation caused by the transit of single particles, the algorithm effectively segments the SMI signal associated with each particle. The algorithm was validated on the segmentation of different-size particles (2, 4, and 10 μm), and its performances are compared to the more established spectral amplitude detection method. The results highlight the SMI technique’s potential for micro-particle analysis and facilitate the adoption of new signal processing algorithms to improve signal feature extraction.