Measurement of blood-borne volatile organic compounds (VOCs) occurring in human exhaled breath as a result of metabolic changes or pathological disorders is a promising tool for noninvasive medical diagnosis, such as exhaled acetone measurements in terms of diabetes monitoring. The conventional methods for exhaled breath analysis are based on spectrometry techniques, however, the development of gas sensors has made them more and more attractive from a medical point of view. This review focuses on the latest achievements in gas sensors for exhaled acetone detection. Several different methods and techniques are presented and discussed as well.

In this work, the latest achievements in the field of copper oxide thin film gas sensors are presented and discussed. Several methods and deposition techniques are shown with their advantages and disadvantages for commercial applications. Recently, CuO thin film gas sensors have been studied to detect various compounds, such as: nitrogen oxides, carbon oxides, hydrogen sulfide, ammonia, as well as several volatile organic compounds in many different applications, e.g., agriculture. The CuO thin film gas sensors exhibited high 3-S parameters (sensitivity, selectivity, and stability). Furthermore, the possibility to function at room temperature with long-term stability was proven as well, which makes this material very attractive in gas-sensing applications, including exhaled breath analysis.

In this work, a broad overview in the field of strontium titanate (ST, SrTiO₃)-, barium titanate (BT, BaTiO₃)- and barium strontium titanate (BST, BaSrTiO₃)-based gas sensors is presented and discussed. The above-mentioned materials are characterized by a perovskite structure with long-term stability and therefore are very promising materials for commercial gas-sensing applications. Within the last 20 years, the number of papers where ST, BT and BST materials were tested as gas-sensitive materials has ten times increased and therefore an actual review about them in this field has been expected by readers, who are researchers involved in gas-sensing applications and novel materials investigations, as well as industry research and development center members, who are constantly searching for gas-sensing materials exhibiting high 3S parameters (sensitivity, selectivity and stability) that can be adapted for commercial realizations. Finally, the NO₂-sensing characteristics of the BST-based gas sensors deposited by the authors with the utilization of magnetron sputtering technology are presented.

Background: Exhaled acetone analysis has long been recognized as a supplementary tool for diagnosis and monitoring diabetes, especially type 1 diabetes. It is essential, therefore to determine the relationship between exhaled acetone concentration and glucose in blood. Usually, a direct linear correlation between this both compounds has been expected. However, in some cases we can observe a reverse correlation. When blood glucose was increasing, breath acetone declined. Methods: The breath analysis as a supplementary tool for diagnosing and monitoring diabetes makes sense only in case of utilization of portable analyzers. This need has created a market for gas sensors. However, commercially available acetone gas sensors are developed for measuring samples at several tens part per million. The exhaled acetone concentration was measured using commercial acetone gas sensor (TGS 822, 823 Figaro, Arlington Heights, IL, USA Inc) with micropreconcentrator in low temperature cofired ceramics. The reference analyzer–mass spectrometry (HPR-20 QIC, Hiden Analytical, Warrington, UK) was used. Results: Twenty-two healthy volunteers with no history of any respiratory disease participated in the research, as did 31 patients diagnosed with type 1 diabetes. Respectively, 3 healthy volunteer and 5 type 1 diabetes mellitus subjects with reverse trend were selected. The linear fitting coefficient various from 0.1139 to 0.9573. Therefore, it is necessary to determine the correlation between blood glucose concentrations and under different conditions, for example, insulin levels, as well as correlate the results with clinical tests, for example, Hb1Ac. Conclusions: It is well known that the concentration of acetone is strongly influenced by diet, insulin treatment, and so on. Therefore, much more complex analysis with long-term measurements are required. Thus, presented results should be regarded as tentative, and validation studies with the analysis of clinical test and in a large number of patients, including control groups, need to be carried out.

Exhaled breath analysis has become more and more popular as a supplementary tool for medical diagnosis. However, the number of variables that have to be taken into account forces researchers to develop novel algorithms for proper data interpretation. This paper presents a system for analyzing exhaled air with the use of various sensors. Breath simulations with acetone as a diabetes biomarker were performed using the proposed e-nose system. The XGBoost algorithm for diabetes detection based on artificial breath analysis is presented. The results have shown that the designed system based on the XGBoost algorithm is highly selective for acetone, even at low concentrations. Moreover, in comparison with other commonly used algorithms, it was shown that XGBoost exhibits the highest performance and recall.