Dottorato in TECNOLOGIE DELL'INFORMAZIONE E DELLE COMUNICAZIONI (ICT)

Titolo della tesi: Lab-On-Mask as a Telemedicine Device: implementation of commercial and innovative textile sensors for breath analysis

To date, both non-infectious and infectious diseases are leading causes of death worldwide. The technological complexity and the availability of medical infrastructures represent a significant burden on the healthcare systems, leading to delayed diagnoses. In this context, new approaches are needed for early-stage disease detection, monitoring of treatment effectiveness, higher curability and lower healthcare costs. From this standpoint, “volatolomics” offers a wide investigation over the volatile organic compounds (VOCs) emitted from the body, representing the heterogeneity of the disease. It represents a new frontier in medical research, giving preliminary information that can reduce unpleasant and costly tests to only those suspected cases. With 140.000 published research papers since 2000, the scientific community demonstrated huge interest in “breathatomics”. As saliva, faeces and urine, breath analysis is a non-invasive technique, but with patient-compliance and unlimited sample collection advantages. Thus, it results suitable for disease detection as therapeutic monitoring and treatment decision-making. Despite its potential, breath analysis has not yet been introduced into clinical practice due to technological gaps and absence of standardization for VOC testing. Addressing the challenges related to compact size, affordable and ease-of-use devices, the main objectives of this PhD thesis is the development of a prototype for breath analysis - Lab-on-Mask (LoM) - through the fabrication of innovative textile sensors and the implementation of commercial devices for breath monitoring into a face mask. Various types of sensors based on combination of gold-nanoparticles (AuNPs) and multiwalled carbon nanotubes (CNTs) are proposed as sensitive elements deposited on cotton substrates. Indeed, cotton enhances good absorption of functional materials and presents flexibility and breathability properties. On the other hand, it requires unconventional methods of patterning interdigitated electrodes. A morphological and structural characterization of the nanomaterial deposited on the cotton substrates was performed by means of SEM, EDX, Raman, FTIR, UV-vis analysis. The electrical properties of the sensors were studied firstly in AC mode to inquire on the physical meaning and equivalent circuit modelling. Subsequently, the DC-operation mode studied a chemiresistive response. Each sensor was tested with acetone, ethanol and ammonia as case examples of functional organic groups. The interacting mechanisms between the sensing layer and the analytes were examined in both gaseous and liquid states. Implementing patter recognition methods resulted in an overall accuracy of 95.2% proving a strong performance in classifying the sensor responses to various analytes concentrations. The safety issues related to the potential inhalation of nanostructures (AuNPs) were also investigated by exposing the sensor to simulated breath in a glove box equipped with standard instruments for particle counts. Furthermore, the thesis combines the powerful Internet of Things concept with 3D-printing capabilities to design and fabricate a smart face-mask for monitoring its breathing zone. The integration of (i) a printed circuit board containing commercial sensors of relative humidity (RH), temperature (T) and carbon dioxide (CO2) levels for data acquisition, (ii) the software for data collection and transmission, and (iii) the accurate design of the face-mask itself, form the foundation of the smart prototype architecture. Particularly, this thesis has developed a 3D-printed mask from a material perspective (with the related comfortable, flexible and biocompatible properties) and from a design point-of-view (efficient configuration optimizing the ratio of occupied spaces by electronic integration and air circulation). Monitoring T/RH helps the control of confounding factors during measurements, while knowing the CO2 levels allows for distinguishing alveolar air during the respiratory act. The whole system was tested to prove easy and comfortable wearing by different subjects and the correct and effective operation of the whole chain of measurement, transmission, and data storage.