# Breath Analysis: A Promising Tool for Disease Diagnosis--The Role of Sensors
###### Abstract
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Disease Type** & **Diseases** & **Ref.** \\ \hline
**Respiratory** & Asthma, COPD, obstructive sleep apnea syndrome, & [(19)] \\  & pulmonary arterial hypertension, cystic fibrosis & \\ \hline
**Malignant** & Lung, gastric, head and neck, breast, colon, prostate cancer & [(15)] \\ \hline
**Neurodegenerative** & [PERSON]’s disease, Parkinson’s diseases, multiple sclerosis & [(15)] \\ \hline
**Metabolic** & Diabetes, hyperglycemia & [(12; 2020)] \\ \hline
**Bacterial infections** & Upper respiratory tract infection, _Mycobacterium tuberculosis_, _Pseudomonas, Helicobacter pylori_ infection & [(32; 33)] \\ \hline
**Viral infections** & SARS-CoV-2 & [(24; 25; 26)] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Diseases investigated for diagnosis using breath analysis. Figure 1: Diagram summarizing the correlation of VOCs present in the exhaled breath, with oxidative stress and inflammatory conditions; metabolic breakdown of larger molecules leads to the formation of exhaled VOCs. Reprinted with permission from ref. (2019). Copyright © 2012 John Wiley & Sons Ltd.  
solid-phase microextraction (HS-SPME) [10, 31] (using silica fibers, coated with polymeric nanofilm, mainly Carboxen (CAR)/Polydimethylsiloxane (PDMS) [31]) and the needle trap device [31, 34] (sorbent polymer--CAR, PDMS, and/or divinylbenzene (DVB)--packed in a needle [31]). Apart from GC-MS, selected ion flow tube-mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), proton transfer reaction-mass spectrometry (PTR-MS) [17, 35], proton reaction transfer time-of-flight mass spectrometry (PRT-TOF-MS) [1], GC coupled with ion mobility spectrometry (GC-IMS), and flame ionization detector (GC-FID) [31] are also common techniques for breath analysis. However, spectrometry and spectroscopic methods exhibit important limitations [15], such as the use of bulky and expensive equipment by appropriately trained personnel, while the analysis is also time-consuming [15, 36], providing no real-time results [33]. In addition, pre-concentration methods, required before the analysis, could potentially lead to sample loss/contamination [34, 36]. Thus, despite the advantages of those analytical techniques, their use in clinical practice for point-of-care [37] or screening [33] is limited. During recent years, however, sensors and e-Noses, have exhibited the prospect of becoming strong diagnostic tools via breath analysis and are rising up to the existing clinical challenges [34, 35, 37]. Gas sensors comprise inexpensive and simple [12, 34, 37] easy-to-use devices that are small in size and thus portable [12, 34]. In addition, short response time and direct acquisition of results, as well as short sensor recovery time [12], render gas sensors attractive for point-of-care and personalized screening, diagnosis, and disease follow-up [34]. Exhaled gas-target analysis using sensors can be achieved by two different approaches (Figure 2). In the first case, a targeted approach is applied, using a selective mechanism [7, 14]. The target is recognized by a selective chemical sensor, designed to measure this single compound in a complex mixture, based on lock-key mechanism [7]. Such selective sensors have been developed for NO, NH\({}_{3}\), acetone, H\({}_{2}\)O\({}_{2}\)[6, 15], H\({}_{2}\)S, and CH\({}_{3}\)SH [15]. On the other hand, the detection of a unique gas-target pattern, rather than a single exhaled compound, is also possible. Semi-selective/ cross-reactive sensors are artificially intelligent nano-arrays [15] mimicking natural sensing systems [38, 39] and are also called \"electronic noses\" (e-Noses), \"artificial olfactory systems\" (gas analytes), or \"electronic tongues\" (liquid analytes). The array consists of distinctive sensors that respond to all/large part of the components of a complex mixture [38], at the same time, in a complementary way [39]. Due to their diversity each individual sensor of the array responds differently (yet not chemically selectively) to a given mixture.