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Vol. 215, Issue 8, August 2017, pp. 19-26




Cardio-metabolic Diseases Prevention by Self-monitoring the Breath

1 Danila GERMANESE, 2 Mario D’ACUNTO, 1 Massimo MAGRINI, 1 Marco RIGHI and 1 Ovidio SALVETTI

1 Institute of Science and Technology Information, ISTI-CNR, Via G. Moruzzi 1, 56127 Pisa, Italy
2 Institute of Biphysics, IBF-CNR, Via G. Moruzzi 1, 56127 Pisa, Italy
1 E-mail: danila.germanese@isti.cnr.it


Received: 1 June 2017 /Accepted: 7 August 2017 /Published: 31 August 2017

Digital Sensors and Sensor Sysstems


Abstract: As new as very promising technique, breath analysis allows for monitoring the biochemical processes that occur in human body in a non-invasive way. Nevertheless, the high costs for standard analytical instrumentation (i.e., gas chromatograph, mass spectrometer), the need for specialized personnel able to read the results and the lack of protocols to collect breath samples, set limit to the exploitation of breath analysis in clinical practice. Here, we describe the development of a device, named Wize Sniffer, which is portable and entirely based on low cost technology: it uses an array of commercial, semiconductor gas sensors and a widely employed open source controller, an Arduino Mega2560 with Ethernet module. In addition, it is very easy-to-use also for non-specialized personnel and able to analyze in real time the composition of the breath. The Wize Sniffer is composed of three modules: signal measurement module, signal conditioning module and signal processing module. The idea was born in the framework of European SEMEiotic Oriented Technology for Individual's CardiOmetabolic risk self-assessmeNt and Self-monitoring (SEMEOTICONS) Project, in order to monitor individual's lifestyle by detecting in the breath those molecules related to the noxious habits for cardio-metabolic risk (alcohol intake, smoking, wrong diet). Nonetheless, the modular configuration of the device allows for changing the sensors according to the molecules to be detected, thus fully exploiting the potential of breath analysis.


Keywords: Bio-signals, Signal processing, Breath analysis, E-nose, Semiconductor gas gensors.


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