Advances in Electronic-Nose Technologies Developed for Biomedical Applications

The research and development of new electronic-nose applications in the biomedical field has accelerated at a phenomenal rate over the past 25 years. Many innovative e-nose technologies have provided solutions and applications to a wide variety of complex biomedical and healthcare problems. The purposes of this review are to present a comprehensive analysis of past and recent biomedical research findings and developments of electronic-nose sensor technologies, and to identify current and future potential e-nose applications that will continue to advance the effectiveness and efficiency of biomedical treatments and healthcare services for many years. An abundance of electronic-nose applications has been developed for a variety of healthcare sectors including diagnostics, immunology, pathology, patient recovery, pharmacology, physical therapy, physiology, preventative medicine, remote healthcare, and wound and graft healing. Specific biomedical e-nose applications range from uses in biochemical testing, blood-compatibility evaluations, disease diagnoses, and drug delivery to monitoring of metabolic levels, organ dysfunctions, and patient conditions through telemedicine. This paper summarizes the major electronic-nose technologies developed for healthcare and biomedical applications since the late 1980s when electronic aroma detection technologies were first recognized to be potentially useful in providing effective solutions to problems in the healthcare industry

Artificial Odor Discrimination System using electronic nose and neural networks for the identification of urinary tract infection

Current clinical diagnostics are based on biochemical, immunological or microbiological methods. However, these methods are operator dependent, time consuming, expensive and require special skills, and are therefore not suitable for point-of-care testing. Recent developments in gas-sensing technology and pattern recognition methods make electronic nose technology an interesting alternative for medical point-of-care devices. An electronic nose has been used to detect Urinary Tract Infection from 45 suspected cases that were sent for analysis in a UK Public Health Registry. These samples were analysed by incubation in a volatile generation test tube system for 4-5h. Two issues are being addressed, including the implementation of an advanced neural network, based on a modified Expectation Maximisation scheme that incorporates a dynamic structure methodology and the concept of a fusion of multiple classifiers dedicated to specific feature parameters. This study has shown the potential for early detection of microbial ontaminants in urine samples using electronic nose technology

Applications and Advances in Electronic-Nose Technologies

Electronic-nose devices have received considerable attention in the field of sensor technology during the past twenty years, largely due to the discovery of numerous applications derived from research in diverse fields of applied sciences. Recent applications of electronic nose technologies have come through advances in sensor design, material improvements, software innovations and progress in microcircuitry design and systems integration. The invention of many new e-nose sensor types and arrays, based on different detection principles and mechanisms, is closely correlated with the expansion of new applications. Electronic noses have provided a plethora of benefits to a variety of commercial industries, including the agricultural, biomedical, cosmetics, environmental, food, manufacturing, military, pharmaceutical, regulatory, and various scientific research fields. Advances have improved product attributes, uniformity, and consistency as a result of increases in quality control capabilities afforded by electronic-nose monitoring of all phases of industrial manufacturing processes. This paper is a review of the major electronic-nose technologies, developed since this specialized field was born and became prominent in the mid 1980s, and a summarization of some of the more important and useful applications that have been of greatest benefit to man

Microbial and non-microbial volatile fingerprints : potential clinical applications of electronic nose for early diagnoses and detection of diseases

This is the first study to explore the potential applications of using qualitative volatile fingerprints (electronic nose) for early detection and diagnosis of diseases such as dermatophytosis, ventilator associated pneumonia and upper gastrointestinal cancer. The investigations included in vitro analysis of various dermatophyte species and strains, antifungal screening, bacterial cultures and associated clinical specimens and oesophageal cell lines. Mass spectrometric analyses were attempted to identify possible markers. The studies that involved e-nose comparisons indicated that the conducting polymer system was unable to differentiate between any of the treatments over the experimental period (120 hours). Metal oxide-based sensor arrays were better suited and differentiated between four dermatophyte species within 96 hours of growth using principal component analysis and cluster analysis (Euclidean distance and Ward’s linkage) based on their volatile profile patterns. Studies on the sensitivity of detection showed that for Trichophyton mentagrophytes and T. rubrum it was possible to differentiate between log3, log5 and log7 inoculum levels within 96 hours. The probabilistic neural network model had a high prediction accuracy of 88 to 96% depending on the number of sensors used. Temporal volatile production patterns studied at a species level for a Microsporum species, two Trichophyton species and at a strain level for the two Trichophyton species; showed possible discrimination between the species from controls after 120 hours. The predictive neural network model misclassified only one sample. Data analysis also indicated probable differentiation between the strains of T. rubrum while strains of T. mentagrophytes clustered together showing good similarity between them. Antifungal treatments with itraconazole on T. mentagrophytes and T. rubrum showed that the e-nose could differentiate between untreated fungal species from the treated fungal species at both temperatures (25 and 30°C). However, the different antifungal concentrations of 50% fungal inhibition and 2 ppm could not be separated from each other or the controls based on their volatiles. Headspace analysis of bacterial cultures in vitro indicated that the e-nose could differentiate between the microbial species and controls in 83% of samples (n=98) based on a four group model (gram-positive, gram-negative, fungi and no growth). Volatile fingerprint analysis of the bronchoalveolar lavage fluid accurately separated growth and no growth in 81% of samples (n=52); however only 63% classification accuracy was achieved with a four group model. 12/31 samples were classified as infected by the e-nose but had no microbiological growth, further analysis suggested that the traditional clinical pulmonary infection score (CPIS) system correlated with the e-nose prediction of infection in 68% of samples (n=31). No clear distinction was observed between various human cell lines (oesophageal and colorectal) based on volatile fingerprints within one to four hours of incubation, although they were clearly separate from the blank media. However, after 24 hours one of the cell lines could be clearly differentiated from the others and the controls. The different gastrointestinal pathologies (forming the clinical samples) did not show any specific pattern and thus could not be distinguished. Mass spectrometric analysis did not detect distinct markers within the fungal and cell line samples, but potential identifiers in the fungal species such as 3-Octanone, 1-Octen-3-ol and methoxybenzene including high concentration of ammonia, the latter mostly in T. mentagrophytes, followed by T. rubrum and Microsporum canis, were found. These detailed studies suggest that the approach of qualitative volatile fingerprinting shows promise for use in clinical settings, enabling rapid detection/diagnoses of diseases thus eventually reducing the time to treatment significantly.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Application and uses of electronic noses for clinical diagnosis on urine samples: A review

The electronic nose is able to provide useful information through the analysis of the volatile organic compounds in body fluids, such as exhaled breath, urine and blood. This paper focuses on the review of electronic nose studies and applications in the specific field of medical diagnostics based on the analysis of the gaseous headspace of human urine, in order to provide a broad overview of the state of the art and thus enhance future developments in this field. The research in this field is rather recent and still in progress, and there are several aspects that need to be investigated more into depth, not only to develop and improve specific electronic noses for different diseases, but also with the aim to discover and analyse the connections between specific diseases and the body fluids odour. Further research is needed to improve the results obtained up to now; the development of new sensors and data processing methods should lead to greater diagnostic accuracy thus making the electronic nose an effective tool for early detection of different kinds of diseases, ranging from infections to tumours or exposure to toxic agents

Ventilator associated pneumonia : analyses of volatile fingerprints for identification of causative microorganisms, assessment of anti-fungals and use of in vitro models for early clinical sample prediction

This study has involved the analysis of volatile fingerprints using a hybrid electronic nose (e-nose) to discriminate between and diagnose the microorganisms which cause ventilator–associated pneumonia (VAP), one of the most important infections in the hospital environment. This infection occurs in hospitalised patients with 48-72 hrs of mechanical ventilation. VAP diagnostics still remains a problem due to the lack of a precise diagnostic tool. The current tests are mostly based on quantitative cultures of samples from the lower lung airways with clinical findings, which do not often result in accurate diagnoses of the disease. Cont/d.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Ventilator associated pneumonia : analyses of volatile fingerprints for identification of causative microorganisms, assessment of anti-fungals and use of in vitro models for early clinical sample prediction

This study has involved the analysis of volatile fingerprints using a hybrid electronic nose (e-nose) to discriminate between and diagnose the microorganisms which cause ventilator–associated pneumonia (VAP), one of the most important infections in the hospital environment. This infection occurs in hospitalised patients with 48-72 hrs of mechanical ventilation. VAP diagnostics still remains a problem due to the lack of a precise diagnostic tool. The current tests are mostly based on quantitative cultures of samples from the lower lung airways with clinical findings, which do not often result in accurate diagnoses of the disease. Cont/d.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Supporting wound infection diagnosis: advancements and challenges with electronic noses

Wound infections are a major problem worldwide, both for the healthcare system and for patients affected. Currently available diagnostic methods to determine the responsible germs are time-consuming and costly. Wound infections are mostly caused by various bacteria, which in turn produce volatile organic compounds. From clinical experience, we know that depending on the bacteria involved, a specific odor impression can be expected. For this reason, we hypothesized that electronic noses, i.e., non-invasive electronic sensors for the detection of volatile organic compounds, are applicable for diagnostic purposes. By providing a comprehensive overview of the state-of-research, we tested our hypothesis. In particular, we addressed three overarching questions: 1) which sensor technologies are suitable for the diagnosis of wound infections and why? 2) how must the (biological) sample be prepared and presented to the measurement system? 3) which machine learning methods and algorithms have already proven successful for the classification of microorganisms? The corresponding articles have critically been reviewed and are discussed particularly in the context of their potential for clinical diagnostics. In summary, it can already be stated today that the use of electronic noses for the detection of bacteria in wound infections is a very interesting, fast and non-invasive method. However, reliable clinical studies are still missing and further research is necessary

Development of medical point-of-care applications for renal medicine and tuberculosis based on electronic nose technology

Introduction: Current clinical diagnostics are based on biochemical, immunological or microbiological methods. However, these methods are operator dependent, time consuming, expensive and require special skills, and are therefore not suitable for point-of-care testing. Recent developments in gas-sensing technology and pattern recognition methods make electronic nose technology an interesting alternative for medical point-of-care devices. Methods: We applied a gas sensor array based on 14 conducting polymers to monitor haemodialysis in vitro and to detect pulmonary tuberculosis in both culture and sputum. Results and discussion: The electronic nose is able to distinguish between control blood and “uraemic” blood. Furthermore, the gas sensor array is not only capable of discriminating pre- from post-dialysis blood (97% accuracy) but also can follow the volatile shift occurring during a single haemodialysis session. The electronic nose can be used for both dialysate side and blood-side monitoring of haemodialysis. The pattern observed for post- and pre-dialysis blood might reflect the health status of the patients and can therefore be related to the long-term outcome. Furthermore, the gas sensor array was also able to discriminate between Mycobacterium spp. and other lung pathogens such as Pseudomonas aeruginosa. More importantly the gas sensor array was capable of resolving different Mycobacterium spp. such as Mycobacterium tuberculosis, M. scrofulaceum, and M. avium in both liquid culture and spiked sputum samples. The detection limit for M. tuberculosis in both sputum and liquid culture is 1 x 104 mycobacteria ml-1 and therefore partially fulfils the requirement set by the WHO. The gas sensor array was able to detect culture proven TB with a sensitivity of 89% and a specificity of 91%. Conclusions: In conclusion, this study has shown the ability of an electronic nose as a point-of-care device in these areas.EThOS - Electronic Theses Online ServiceGBUnited Kingdo