RESEARCH

We develop novel technologies and methods to advance knowledge on respiratory physiology and pathophysiology and to improve diagnosis, monitoring and treatments of patients with respiratory diseases or who need respiratory support. We have ongoing research projects funded by public institutions and industries resulting in scientific publications, patents and medical devices.

We have an extensive worldwide network of collaborations with Universities, Hospitals and medical devices industries.

Our technologies are implemented in several diagnostics devices or invasive and non-invasive mechanical ventilators used by patients worldwide.

PEOPLE

We are a group of people passionate about electronic technologies for medical devices, respiratory medicine and respiratory physiology. We like to challenge ourselves addressing open issues in medicine and physiology in general, but especially when concerning diagnosis and management of respiratory disorders or technologies for respiratory support, from simple CPAP devices to the most complex systems for mechanical ventilation in ICU. 

NEWS

PUBLICATIONS

  1. Zannin, E, Stoecklin, B, Choi, JY, Simpson, SJ, Veneroni, C, Dellaca, RL et al.. Ventilatory response and stability of oxygen saturation during a hypoxic challenge in very preterm infants. Pediatr Pulmonol. 2023; :. doi: 10.1002/ppul.26343. PubMed PMID:36748837 .
  2. Pigmans, RRWP, van Leuteren, RW, Scholten, AWJ, Veneroni, C, van Kaam, AH, Hutten, J et al.. Influence of neonatal endotracheal tube dimensions on oscillometry-acquired reactance: a bench study. Physiol Meas. 2023;44 (1):. doi: 10.1088/1361-6579/acb03a. PubMed PMID:36599175 .
  3. Poletto, S, Trevisanuto, D, Ramaswamy, VV, Seni, AHA, Ouedraogo, P, Dellacà, RL et al.. Bubble CPAP respiratory support devices for infants in low-resource settings. Pediatr Pulmonol. 2023;58 (3):643-652. doi: 10.1002/ppul.26258. PubMed PMID:36484311 .
  4. Migliorelli, L, Cacciatore, A, Ottaviani, V, Berardini, D, Dellaca', RL, Frontoni, E et al.. TwinEDA: a sustainable deep-learning approach for limb-position estimation in preterm infants' depth images. Med Biol Eng Comput. 2023;61 (2):387-397. doi: 10.1007/s11517-022-02696-9. PubMed PMID:36441288 .
  5. Zannin, E, Rigotti, C, Neumann, RP, Dellacà, RL, Schulzke, S, Ventura, ML et al.. Oscillatory mechanics in very preterm infants on continuous positive airway pressure support: Reference values. Pediatr Pulmonol. 2023;58 (3):746-752. doi: 10.1002/ppul.26247. PubMed PMID:36416349 .
Search PubMed