Trabajamos con simulación avanzada para afianzar la seguridad nuclear.

La Cátedra UNESCO en Métodos Numéricos lidera la innovación de vanguardia en el Sur global.

Noticias

Atrás

CIMNE ICT participates in a joint research with UdL and IRBLleida to determine lung age with a mobile phone

Feb 17, 2022

With the goal of monitoring chronic diseases, CIMNE participates in an investigation that proposes using the mobile phone as a kind of spirometer. Alberto Tena, member of CIMNE ICT group, is the principal investigator of this project at the centre. Funded by the Spanish Ministry of Science and Innovation, it is carried out in partnership with researchers of the Higher Technical School of the UdL and the Biomedical Research Institute of Lleida (IRB Lleida). It is focused on the development of an mobile application which allows measuring lung capacity to evaluate chronic diseases such as asthma, chronic obstructive pulmonary disease (COPD) or pulmonary fibrosis.

This mobile application would offer a reliable alternative outside the hospital environment, without additional hardware or external devices.

By the moment, a machine learning model has been developed to obtain a person's lung age by analyzing the properties of their breathing out. The team has implemented a mobile application and a similar website to record exhalations of 188 people, 91 men (48.4%) and 97 women (51.6%), aged between 17 and 67 years. Sampling records consist of a distance of approximately 20 centimeters between the mouth and the phone. The user then breathes deeply and exhales as strongly as possible for as long as possible, like in a traditional spirometry. For each sound sample, researchers analyzed 42 features. In this phase, the CIMNE team has collaborated on the methodology to obtain the phonatory features and time-frequency features of the study.

espirometria

In line with this approach, they have tested different machine learning algorithms used in speech recognition. Thus they have found that using the quadratic linear discrimination algorithm and distributing people in age groups every 5 years, the accuracy of their model reaches 94.69%; sensitivity, 94.45%; and specificity, at 99.45%. «The good results obtained show that it is possible to obtain the lung age of the user by extracting the characteristics of an exhalation and that our methodology can become a reliable tool for use with mobile devices», said the doctoral student of the UdL Marc Pifarré.

«This research also opens the door to other interesting and necessary applications in health, with the diagnosis of serious tobacco use by measuring Carbon Monoxide (CO) levels in exhaled smoke», explains the IRB researcher Francesc Abella.

Noticias relacionadas

CIMNE lanza el proyecto DAMSHAI para mejorar la seguridad de las presas mediante inteligencia artificial
CIMNE lanza el proyecto DAMSHAI para mejorar la seguridad de las presas mediante inteligencia artificial

El Centro Internacional de Métodos Numéricos en Ingeniería (CIMNE) ha puesto en marcha DAMSHAI (Dam Structural Health Monitoring and Safety Assessment with an AI Agent), un proyecto de investigación de tres años que explorará la aplicación de la inteligencia...

La ciencia y los datos: perspectivas del Prof. Michael Ortiz en el seminario de la Cátedra UNESCO
La ciencia y los datos: perspectivas del Prof. Michael Ortiz en el seminario de la Cátedra UNESCO

  El profesor Michael Ortiz presentó el pasado 28 de octubre en el Palau Robert de Barcelona el seminario “Science Meets Data: Scientific Computing in the Age of Artificial Intelligence”, con motivo de su toma de posesión como titular de la Cátedra UNESCO en...

El CIMNE presenta avances en simulación sísmica e innovación en realidad virtual en el congreso anual de la Sociedad Nuclear Española
El CIMNE presenta avances en simulación sísmica e innovación en realidad virtual en el congreso anual de la Sociedad Nuclear Española

  La 51ª Reunión Anual de la Sociedad Nuclear Española (SNE), celebrada en Cáceres, volvió a consolidarse como el principal punto de encuentro del sector nuclear en España. Con 694 asistentes, 248 ponencias, 42 sesiones técnicas, 23 expositores y 31...

Etiquetas

Compartir: