Assesses disinfection efficacy in biosafety cabinets, indicating a reliable validation method for hygiene management.
Introduction Reliable surface disinfection of biosafety cabinets is essential to prevent contamination in pharmaceutical, clinical, and laboratory environments. However, manual cleaning using ethanol (ETH) and wiping is subject to operator variability, making objective verification of disinfection quality difficult. This paper proposes an integrated disinfection-validation system that combines thermal imaging, visual tracking, and pressure sensing to objectively assess the adequacy of ETH spraying and pressure-based wiping. Methods The proposed system integrated three sensing modalities: Red-green-blue (RGB) imaging, thermal sensing, and pressure detection. The RGB and thermal cameras (placed outside the biosafety cabinet) monitored the stainless steel (SUS) work surface, and the flexible pressure sensors (embedded in the wiping tool) detected the applied force. The system was biologically validated using Bacillus subtilis spores on SUS plates, using ETH spraying only, wiping only, and combined spraying and pressure-based wiping. Reproducibility was evaluated under different wiping speeds and operator techniques, using time-series and endpoint analyses. Results The system successfully visualized the sprayed, wiped, and untreated areas in real time. Only the combined treatment resulted in complete inhibition of bacterial growth, demonstrating the synergistic effect of chemical and mechanical actions in achieving effective disinfection. The classification accuracy and quantitative detection of the cleaned areas were consistent across the trials, confirming their reproducibility under variable wiping patterns. Conclusions This integrated sensing system provides a reliable and objective method for validating surface disinfection in biosafety cabinets. By enabling the real-time, recordable, and quantitative assessment of manual cleaning, it bridges the gap between procedural operations and verifiable decontamination, supporting standardized and data-driven hygiene management in biosafety and cell processing environments.
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Mizuno et al. (2026) studied this question.
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