Estimating the Dead Space Volume Between a Headform and N95 Filtering Facepiece Respirator Using Microsoft Kinect

Area of Science:

• Biomedical Engineering
• Occupational Safety and Health
• Respiratory Protection Technology

Background:

• Dead space in N95 filtering facepiece respirators (FFRs) is a critical design parameter affecting performance and user experience.
• Accurate measurement of FFR dead space is essential for optimizing respirator fit and function.

Purpose of the Study:

• To present a novel method for estimating the dead space volume of N95 FFRs.
• To validate the proposed method through experimental measurements.
• To establish a correlation between simulation and experimental dead space volume data.

Main Methods:

• Utilized Microsoft Kinect Sensors for 3D scanning of headforms with and without FFRs.
• Employed geometric modeling software to define FFR dead space from scanned data.
• Calculated dead space volume using LS-DYNA simulation and validated with water displacement experiments.
• Investigated six different FFR models and five headform sizes (small, medium, large, long/narrow, short/wide).

Main Results:

• Simulation-derived dead space volumes ranged from 107.5 to 167.5 mL.
• Experimental measurements yielded dead space volumes between 98.4 and 165.7 mL.
• Linear regression analysis showed a strong correlation between simulation and experimental results, with R² = 0.85.

Conclusions:

• The novel 3D scanning and geometric modeling method provides a reliable estimation of N95 FFR dead space.
• The validated method offers a practical approach for respirator design and performance evaluation.
• Findings support the use of this technique for assessing dead space across various FFR and headform combinations.