Biohazards in Space Cabin
The project goals for the biopathogen/biohazard project were 100% accomplished. Goals included full spectral library
development, detection algorithm development, testing of the detection procedure using the hand-held sensor, and result
delivery. The four fungal biohazards of concern to space environments as identified from literature were, Penicillium
chrysogenum, Aspergillus flavus, Cladosporium cladosporioides, and Fusarium moniliforme.
In the course of the project,
pertinent research protocols were defined and hyperspectral images were acquired for the above mentioned list of space
pathogens. In addition, materials commonly used for spacecraft/space station construction were also acquired and imaged. These
materials are aluminum, Kevlar-Nomex, magnesium, Teflon, titanium, fiber glass, and Polyimide (Kapton) film. They were used as
backgrounds for the detection of the four biohazards.
All the images were preprocessed and calibrated based on the pre-defined
processing steps. Methods were developed for the extraction of individual spectral signatures from the calibrated hyperspectral
images. A spectral library including the biohazards and background space materials was built based on the acquired data.
Detection algorithms for the defined biopathogens were developed for the detection and identification of the biohazards against
the background materials.
Our results revealed the spectral bands capable of differentiating between all four fungal biohazards and all space background materials. The results are encouraging because they enable the development of a real-time sensor that uses only a few significant image bands for biopathogen/biohazard detection. Test images were also collected and examined using the hand-held sensor developed in the wound care project. Additionally, two patent applications were submitted based on the research results. Titles for the patents are “Video Tracking-Based Real-Time Hyperspectral Data Acquisition” (Pending 2005) and “Method and Apparatus for Non-Invasive Rapid Fungal Specie (Mold) Identification with Hyperspectral Imagery” (Pending 2006).
For more information about this or any other past research, contact us.