Abstract
Health-care strategies are currently oriented towards non-invasive techniques for an early diagnosis. The chemical analysis seems to be a good answer to accomplish both prevention, a fundamental requirement for an efficient treatment of the disease, and non-invasivity. GC is very accurate but is expensive; its sampling and assaying processes are complicated and time consuming, while its results require expert interpretation. Over the last decade, "electronic sensing" or "e-sensing" technologies have undergone some important developments from both a technical and commercial point of view. Particularly, in recent years, the usefulness of the electronic nose has been clinically proved as an opportunity for the early detection of such diseases as lung cancer, diabetes, and tuberculosis. In this paper, a portable, versatile and inexpensive system for the measurement of gas concentration through a gas sensor array is described. The system uses low cost metal oxide gas transducers and can automatically compensate the values of gas concentration detected according to the current values of temperature and humidity. The device works in slave mode and its acquired and computed data are available by means of a host/slave ASCII serial communication protocol. A host device can periodically require the current values of gas concentration and apply the appropriate algorithms for the detection of the investigated substances.
Highlights
В настоящее время стратегии здравоохранения ориентированы на неинвазивные методы ранней диагностики
In the identification of gases acquired from the electronic nose, often are used analysis techniques based on Artificial Neural Networks [8], characterized by good noise immunity
E-noses have gradually been used in medicine for the diagnosis of lung cancer
Summary
В настоящее время стратегии здравоохранения ориентированы на неинвазивные методы ранней диагностики. Breath is fundamentally composed of nitrogen, oxygen, carbon dioxide, water, inert gases, and mixtures of numerous and different compounds in very low concentration. Some of these elements are specific markers of diseases [1]. The main advantages of MOS are the cheapness, the quick response and recovery times [7], but the measurement can be inaccurate and strongly influenced by temperature and humidity For this reason, in the identification of gases acquired from the electronic nose, often are used analysis techniques based on Artificial Neural Networks [8], characterized by good noise immunity. The system uses low cost transducers and can automatically compensate the values of gas concentrations detected, according to the current values of temperature and humidity measured
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