New results using multi-array sensors and support vector machines for the detection and classification of organophosphate nerve agents

The threat of chemical and biological agents (CBAs) becoming the preferred weapon of mass destruction (WMD) for international terrorist organizations has produced a significant effort to develop tools that can detect CBAs and effectively combat biochemical warfare. CBAs can attack large populations while leaving infrastructures intact. Despite the availability of numerous sensing devices, intelligent hybrid sensors that can detect and degrade CBAs are virtually nonexistent. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphate nerve agents using parathion and dichlorvos as model stimulants compounds. SVMs were used for the design and evaluation of new and more accurate data extraction, preprocessing and classification. Experimental results using Structural Risk Minimization show a significant increase in classification accuracy when compared to the existing AromaScan baseline system. For the most difficult classification task, the Parathion vs Paraoxon pair, the following results were achieved (using the three SVM kernels), as described in this paper: (1) ROC Az indices from approximately 93% to greater than 99%, (2) partial Az values from ≈ 79% to 93%, (3) specificities from 76% to ≈ 84% at 100 and 98% sensitivity, and (4) PPVs from 73% to ≈ 84% at 100% and 98% sensitivities. These are excellent results, considering only one atom differentiates these nerve agents.