Properties and Perspectives of Digital Holographic Microscopy for Bioaerosol Detection

Bioaerosols are an important component of air quality and their detection has emerged as a central concern. Current bio-detection tools do not meet the need to be fast, autonomous and ready for use in the field. Artificial intelligence-powered digital holographic microscopy (DHM) offers a possible solution for real-time, cost-effective and field-deployable bioaerosol analysis. This study investigates the characteristics of DHM using a simulation-based approach to define the theoretical limit of detection for submicron objects under different experimental conditions. Spherical particles with different diameters were simulated according to Mie scattering theory, optimising their size and refractive index to be comparable to bacteria. Statistical analysis was used to analyse particles' holograms, both individually and across a range of concentrations. The evidence from this study indicates that air rather than water medium allows more reliable identification of smaller particles. In addition, basic statistical indices enable the differentiation between particles and the background, as well as discrimination among particles based on their diameter, even with higher particle concentrations. Overall, this study suggests that DHM allows for detection and distinction of airborne micro- and even nano-particles. The theoretical detection limit with a lensless setup is around 500 nm, while with a lens-based setup it can reach at least 30 nm under ideal conditions.