Hardware reconfigurable neural network based electronic nose system for early diagnosis of sterile body fluid infections

Abstract

In the midst of infectious diseases, detection of microorganisms in Sterile Body Fluids (SBF) has vital diagnostic and therapeutic implications. Sepsis and Urinary Tract Infections are such kinds which continue to be a major problem for neonates. The results of diagnostic studies of these diseases shall be informed without delay to the concerned physician for initiating accurate treatment. This research proposes a rapid (lt3 hours) and hand held diagnostic tool by employing Electronic nose system. Out of various microorganisms causing neonatal sepsis and Urinary Tract Infection (UTI), this research focuses on differentiating E.coli from other microorganisms. This research investigation also tries to identify the growth phase of E.coli as it cannot be identified by the conventional gold standard method. In order to carry out this study, cultured microbial samples were collected and the head space of each sample was analysed by Metal Oxide Semiconductor (MOS) sensor array. Four different pattern recognition procedures have been deployed; they are classified as linear: Principal Component Analysis (PCA) and three non linear : Multi Layer Perceptron (MLP), Principal Component Analysis hybrid (PCANN) and Support Vector Machine (SVM). In comparison with the results of previous work, it is found that in this work, the overall sensitivity 99.44% and the overall Specificity 100% are achieved comparatively in a shorter duration (lt3 hours). This study successfully demonstrated the feasibility of E-nose as a diagnostic tool for early diagnosis of sterile body fluid infections together with the possibility of recognising the growth phase. After investigation it has been realised that potential does exist for early diagnosis which may help save the neonates by providing them an appropriate antibiotic at the earliest. As the MOS sensory array can be fabricated as a chip, it is now assured that PARC (ANN) can also be put into the chip, thereby a prototype can be formed for devising hand held diagnostic tool.