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.

https://www.mdpi.com/1424-8220/11/1/1105/pdf

Advances in Electronic-Nose Technologies Developed for Biomedical Applications

This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

For centuries, our sense of smell has been used as a diagnostic tool in the practice of medicine, be it for recognising gas gangrene on the battle field or diabetic ketoacidosis in the emergency room. In recent decades, many scent detection studies have been performed with human, animal and electronic noses. The ability of humans to diagnose disease by smelling has only rarely been the subject of quantitative studies. Scent detection by animals, on the other hand, has been addressed in several diagnostic studies, which all suggest similar or even superior accuracy compared with standard diagnostic methods. Examples include, amongst many others, the use of dogs for the detection of lung cancer in breath samples, or rats for Mycobacterium tuberculosis detection in sputum. Studies using different types of electronic noses in conditions such as pulmonary disease and cancer have also shown promising results with high overall sensitivity and specificity. However, results of different types of noses are not easily generalisable and independent confirmation studies are generally lacking, which should be a focus for future research. In conclusion, scent detection by animals and electronic noses holds promise for the future and should receive higher priority in terms of research effort and funding.

Smelling the diagnosis: a review on the use of scent in diagnosing disease.

This paper presents a laboratory study of multi-class classification problem for multiple indoor air contaminants which belongs to a completely linear-inseparable case. Six kinds of indoor air contaminations (formaldehyde, benzene, toluene, carbon monoxide, ammonia and nitrogen dioxide) were recognized as indicators of air quality in this project. The effectiveness of the proposed HSVM model has been rigorously evaluated on the experimental E-nose data sets. In addition, we have also compared it with existing five methods including Euclidean distance to centroids (EDC), simplified fuzzy ARTMAP network (SFAM), multilayer perceptron neural network (MLP) based on back-propagation learning rule, individual FLDA and single SVM. Experimental results have demonstrated that the HSVM model outperforms other classifiers in general. Also, HSVM classifier preliminarily shows its superiority in solution to discrimination in various electronic nose applications.

Classification of multiple indoor air contaminants by an electronic nose and a hybrid support vector machine

Colorectal cancer (CRC) is a leading cause of cancer related death in Europe and the USA. There is no universally accepted effective non-invasive screening test for CRC. Guaiac based faecal occult blood (gFOB) testing has largely been superseded by Faecal Immunochemical testing (FIT), but sensitivity still remains poor. The uptake of population based FOBt testing in the UK is also low at around 50%. The detection of volatile organic compounds (VOCs) signature(s) for many cancer subtypes is receiving increasing interest using a variety of gas phase analytical instruments. One such example is FAIMS (Field Asymmetric Ion Mobility Spectrometer). FAIMS is able to identify Inflammatory Bowel disease (IBD) patients by analysing shifts in VOCs patterns in both urine and faeces. This study extends this concept to determine whether CRC patients can be identified through non-invasive analysis of urine, using FAIMS. 133 patients were recruited; 83 CRC patients and 50 healthy controls. Urine was collected at the time of CRC diagnosis and headspace analysis undertaken using a FAIMS instrument (Owlstone, Lonestar, UK). Data was processed using Fisher Discriminant Analysis (FDA) after feature extraction from the raw data. FAIMS analyses demonstrated that the VOC profiles of CRC patients were tightly clustered and could be distinguished from healthy controls. Sensitivity and specificity for CRC detection with FAIMS were 88% and 60% respectively. This study suggests that VOC signatures emanating from urine can be detected in patients with CRC using ion mobility spectroscopy technology (FAIMS) with potential as a novel screening tool.

/pdf/detection-of-colorectal-cancer-crc-by-urinary-volatile-52u6e1j62m.pdf

Detection of colorectal cancer (CRC) by urinary volatile organic compound analysis.

In this paper a study about the possibility of an early and non-invasive diagnosis of urinary tract cancers with an electronic nose is presented. Measurements of urine headspace were performed by means of an electronic nose based on eight quartz crystal microbalance (QCM) gas sensors coated with different metalloporphyrins. A total of 113 patients affected by various urological pathologies were involved in the experiment, 19 of them were measured twice, before and after the surgical treatment of the cancer. 18 healthy volunteers were used as a reference population. The e-nose data were processed by both principal component analysis (PCA) and discriminant analysis solved by partial least square (PLS-DA). The PLS-DA model related to the data of the healthy and the ills individuals, except the post-surgery samples, shows a complete discrimination between these two groups and a gradual differentiation between prostate and bladder cancer. The application of PCA to the whole data set, shows a migration of the post-surgery class towards the healthy group, suggesting that the headspace of urine samples of patients with the urinary tract cancer is different from that of healthy individuals. These preliminary results confirm a strict correlation between urine headspace and urological pathologies, enhancing the possibility to perform early diagnosis, considered of upmost importance along the medical diagnostic path.

C. Corsi

Papers

A preliminary study on the possibility to diagnose urinary tract cancers by an electronic nose

Ch4 infrared sensor system including a microheater and a thermopile