Abstract
The development of electronic-nose (e-nose) technologies for disease diagnostics was initiated in the biomedical field for detection of biotic (microbial) causes of human diseases during the mid-1980s. The use of e-nose devices for disease-diagnostic applications subsequently was extended to plant and animal hosts through the invention of new gas-sensing instrument types and disease-detection methods with sensor arrays developed and adapted for additional host types and chemical classes of volatile organic compounds (VOCs) closely associated with individual diseases. Considerable progress in animal disease detection using e-noses in combination with metabolomics has been accomplished in the field of veterinary medicine with new important discoveries of biomarker metabolites and aroma profiles for major infectious diseases of livestock, wildlife, and fish from both terrestrial and aquaculture pathology research. Progress in the discovery of new e-nose technologies developed for biomedical applications has exploded with new information and methods for diagnostic sampling and disease detection, identification of key chemical disease biomarkers, improvements in sensor designs, algorithms for discriminant analysis, and greater, more widespread testing of efficacy in clinical trials. This review summarizes progressive advancements in utilizing these specialized gas-sensing devices for numerous diagnostic applications involving noninvasive early detections of plant, animal, and human diseases.
Highlights
The development of electronic-nose (e-nose) technologies and devices for disease diagnostic applications has accelerated rapidly over the past decade
Electronic noses are electronic aroma detection (EAD) devices with the capability of high-throughput analysis of complex gaseous volatile organic compounds (VOCs) mixtures as composite metabolite profiles [21,22]. These instruments are innovative diagnostic tools with great potential for non-invasive earlier detection of numerous types of plant, animal and human diseases based on analysis of headspace VOC-metabolites derived from clinical samples
The need for simpler and portable e-nose devices to provide rapid, accurate diagnostic results and replace conventional cumbersome and time-consuming clinical and laboratory methods have resulted from the growing demand for improved healthcare instruments and procedures that are noninvasive and speed up point-of-care testing (POCT), allowing faster treatments for diseases, improved prognoses, shorter hospital stays, more rapid disease recovery and reduced healthcare costs [6,8]
Summary
The development of electronic-nose (e-nose) technologies and devices for disease diagnostic applications has accelerated rapidly over the past decade. Improvements in sensor technologies and arrays, machine-learning methods such as artificial neural networks (ANN), disease-specific reference libraries and databases, data-analysis software, and identification of disease biomarkers have contributed to advancements in e-nose diagnostic methods [1,2,3,4,5,6,7,8] These key advances have resulted in numerous new applications of e-nose technologies useful for the detection and identification of diseases with many different causes (biotic, abiotic, and genetic) which occur in various forms of living organisms including plants, animals, and humans [7,9,10].
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