Our colleagues worked as co-authors of the article "Monitoring Multi-respiratory Indices via a Smart Nanofibrous Mask Filter Based on a Triboelectric Nanogenerator". The research and development was a cooperation among several departments of BME.
The whole paper -illustrated with photos and videos- is available HERE
The new research is kind of a continuation of the previous successful cooperation: the development and characterization of a nanofiber mask filter layer.
The authors - Haijun He (Department of Polymer Engineering, PT), Jian Guo (Department of Control Engineering and Information Technology, IIT), Illés Balázs (Department of Electronics Technology, ETT), Géczy Attila (ETT), Istók Balázs (Department of Fluid Mechanics), Hliva Viktor (PT), Török Dániel (PT), Kovács József Gábor (PT), Harmati István (IIT) and Molnár Kolos (PT) - have presented a unique, complex measurement system and platform, based on a high filtering efficacy nanofibrous layer, which, besides the protection, is capable of measuring the respiratory parameters of the user; enhancing health monitoring and helping in diagnostics.
The journal "Nano Energy" has Impact Factor 17,881 and CiteScore 25,6. The study introduces a mask filter fabricated with a simple structure with both filtering and sensing capability, which has excellent potential for self-powered health diagnostics. The built-up of the sensoring layers and the whole measurement system, also the testing and the results are presented in detail.
Respiratory parameters, such as respiratory rate (RR), inhalation time (tin), exhalation time (tex), and their ratio (IER=tin/tex), are of great importance to indicate clinical differences between healthy people and those with respiratory diseases. Researchers report a respiration monitoring triboelectric nanogenerator (RM-TENG) with nanofibrous membranes, which can be used as a smart, changeable, self-powered mask filter with high filtration efficiency for monitoring multiple respiratory indices (e.g., RR, tin, tex, IER). BME scientists created a mathematical model to quantitatively analyze the effects of gap distance between two triboelectric layers on the contact area by recording the nanofiber layer‘s deformation profile with digital image correlation (DIC) tests. The RM-TENG is more sensitive to smaller gap distances between 1 mm - 5 mm because the high specific area of nanofibers can provide a more effective contact area. An RM-TENG built with optimized structure parameters can accurately and consistently detect the above-mentioned respiratory indices with excellent sensing stability for 40 hours. The monitored RR and IER have 100% and 93.53% agreement with the real-time RR and IER set on the ventilator, respectively. Furthermore, it has a filtration efficiency of 99wt% for particle sizes between 0.3 μm and 5μm.
